Podcasts about because ai

Superpowers for Good should not be considered investment advice. Seek counsel before making investment decisions. When you purchase an item, launch a campaign or create an investment account after clicking a link here, we may earn a fee. Engage to support our work.Watch the show on television by downloading the e360tv channel app to your Roku, AppleTV or AmazonFireTV. You can also see it on YouTube.Devin: What is your superpower?Steve: Intellectual curiosity, paired with a problem-solving mindset.Media shapes perception, and perception shapes reality. That simple truth drives Steve Jones, Founder and CEO of pocstock, to challenge the way people of color and other underrepresented groups are portrayed in stock photography and now artificial intelligence.Steve launched pocstock after discovering, while running a digital marketing agency, that major stock photo libraries lacked images reflecting diverse identities. "People of Black, Asian, Hispanic and other backgrounds, people who were older than 50, or living with a disability" were all underrepresented, Steve said. This gap was not unique to the U.S. — it was global.Today, pocstock is meeting a bigger challenge: the biases baked into AI image generation. Because AI was trained on biased media libraries, "the data is literally what the AI industry needs in order to become what it's going to be," Steve explained. With AI expected to generate 80% of online imagery soon, pocstock's culturally accurate, bias-free library positions the company as a vital resource for the future of ethical AI.But Steve isn't stopping with just providing imagery. He's ensuring that the creators of these visuals—photographers and artists—can share in the value AI creates. "We created a model where our creators can be included in the AI boom," he said, highlighting pocstock's mission to avoid leaving behind the very people it seeks to represent.As part of that effort, pocstock is raising capital again, this time through a regulated investment crowdfunding campaign on WeFunder. By setting a minimum investment of just $250, Steve and his team are inviting everyone—not just venture capitalists or accredited investors—to participate. "This gives people an opportunity to access AI through pocstock," he said.The implications are profound. "Imagery is how you change people's perceptions of people they haven't met," Steve noted. The consistent underrepresentation or stereotyping of certain groups impacts real-world outcomes, from law enforcement to healthcare. "If you let the media tell it, everybody's racist... and this couldn't be further from the truth."Supporting pocstock, whether by investing or using its imagery, helps rewrite those narratives. Steve's work stands as a reminder that inclusion isn't just a value—it's a strategy for both equity and innovation.To invest, visit wefunder.com/pocstock or s4g.biz/poc.tl;dr:Steve Jones founded pocstock to address the lack of diverse, accurate imagery in media and technology.pocstock's inclusive content is now powering major AI projects and helping to reduce bias in technology.The company is raising capital through regulated investment crowdfunding, inviting everyone to invest for impact.Steve's superpower is intellectual curiosity, which drives him to solve problems and connect across differences.Listeners are encouraged to embrace curiosity, meet new people and invest in more inclusive representation.How to Develop Intellectual Curiosity As a SuperpowerSteve Jones's superpower is intellectual curiosity, paired with a problem-solving mindset. He explained, “I've always looked to see how I can make the world the way I think it should be.” This constant questioning of the status quo fuels his drive to address social injustices, foster inclusion, and solve challenges in innovative ways. From tinkering with objects as a child to reshaping the media landscape with pocstock, Steve's curiosity and creative thinking guide his efforts to make a positive impact.Steve shared a story about a chance encounter that changed his career trajectory. While working in IT, he bonded with a coworker over a shared love of Batman and Dr. Dre. Despite their differences—Steve, a 6'5” Black man, and his coworker, a middle-aged Irish man—they became close friends. Years later, that friendship resulted in Steve receiving his biggest contract for his marketing agency. This anecdote highlights how Steve's openness and curiosity about others help him build meaningful connections and seize new opportunities.Tips for Developing Intellectual Curiosity:Seek to understand problems deeply and envision how they could be solved.Challenge preconceptions by engaging with people from different backgrounds and perspectives.Be open to learning from everyone you meet, both professionally and personally.Approach each day with a fresh mindset, ready to embrace new challenges and opportunities.Stay informed about trends and developments in your field to spark new ideas.By following Steve's example and advice, you can make intellectual curiosity a skill. With practice and effort, you could make it a superpower that enables you to do more good in the world.Remember, however, that research into success suggests that building on your own superpowers is more important than creating new ones or overcoming weaknesses. You do you!Guest ProfileSteve Jones (he/him):Founder & CEO, pocstockAbout pocstock: pocstock is a global content company that creates, curates, and licenses stock images featuring people of color to businesses for marketing, advertising, and artificial intelligence. We partner with businesses of all sizes to ensure they have the right images, insights, and data to be inclusive of everyone.Website: pocstock.comCompany Facebook Page: facebook.com/pocstockOther URL: wefunder.com/pocstockBiographical Information: Steve Jones is a serial entrepreneur with a background in tech, marketing, and creative.He's currently the Founder & CEO of pocstock, a global content company headquarteredin Newark specializing in inclusive content for marketing, advertising, and artificialintelligence.Linkedin: linkedin.com/company/pocstockInstagram Handle: @pocstockSupport Our SponsorsOur generous sponsors make our work possible, serving impact investors, social entrepreneurs, community builders and diverse founders. Today's advertisers include FundingHope, RedLineSafety, Ovanova PET, and Kingscrowd. Learn more about advertising with us here.Max-Impact MembersThe following Max-Impact Members provide valuable financial support:Carol Fineagan, Independent Consultant | Lory Moore, Lory Moore Law | Marcia Brinton, High Desert Gear | Paul Lovejoy, Stakeholder Enterprise | Pearl Wright, Global Changemaker | Ralf Mandt, Next Pitch | Scott Thorpe, Philanthropist | Matthew Mead, Hempitecture | Michael Pratt, Qnetic | Sharon Samjitsingh, Health Care Originals | Add Your Name HereUpcoming SuperCrowd Event CalendarIf a location is not noted, the events below are virtual.Impact Cherub Club Meeting hosted by The Super Crowd, Inc., a public benefit corporation, on June 17, 2025, at 1:00 PM Eastern. Each month, the Club meets to review new offerings for investment consideration and to conduct due diligence on previously screened deals. To join the Impact Cherub Club, become an Impact Member of the SuperCrowd.SuperCrowdHour, June 18, 2025, at 12:00 PM Eastern. Jason Fishman, Co-Founder and CEO of Digital Niche Agency (DNA), will lead a session on "Crowdfund Like a Pro: Insider Marketing Secrets from Jason Fishman." He'll reveal proven strategies and marketing insights drawn from years of experience helping successful crowdfunding campaigns. Whether you're a founder planning a raise or a supporter of innovative startups, you'll gain actionable tips to boost visibility, drive engagement, and hit your funding goals. Don't miss it!Superpowers for Good Live Pitch – June 25, 2025, at 8:00 PM Eastern - Apply by June 6, 2025, to pitch your active Regulation Crowdfunding campaign live on Superpowers for Good—the e360tv show where impact meets capital. Selected founders will gain national exposure, connect with investors, and compete for prizes. To qualify, you must be raising via a FINRA-registered portal or broker-dealer and align with NC3's Community Capital Principles. Founders from underrepresented communities are especially encouraged to apply. Don't miss this chance to fuel your mission and grow your impact!SuperCrowd25, August 21st and 22nd: This two-day virtual event is an annual tradition but with big upgrades for 2025! We'll be streaming live across the web and on TV via e360tv. Soon, we'll open a process for nominating speakers. Check back!Community Event CalendarSuccessful Funding with Karl Dakin, Tuesdays at 10:00 AM ET - Click on Events.Devin Thorpe is featured in a free virtual masterclass series hosted by Irina Portnova titled Break Free, Elevate Your Money Mindset & Call In Overflow, focused on transforming your relationship with money through personal stories and practical insights. June 8-21, 2025.Regulated Investment Crowdfunding Summit 2025, Crowdfunding Professional Association, Washington DC, October 21-22, 2025.Call for community action:Please show your support for a tax credit for investments made via Regulation Crowdfunding, benefiting both the investors and the small businesses that receive the investments. Learn more here.If you would like to submit an event for us to share with the 9,000+ changemakers, investors and entrepreneurs who are members of the SuperCrowd, click here.We use AI to help us write compelling recaps of each episode. Get full access to Superpowers for Good at www.superpowers4good.com/subscribe

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the critical considerations when deciding whether to hire an external AI expert or develop internal AI capabilities. You’ll learn why it is essential to first define your organization’s specific AI needs and goals before seeking any AI expertise. You’ll discover the diverse skill sets that comprise true AI expertise, beyond just technology, and how to effectively vet potential candidates. You’ll understand how AI can magnify existing organizational challenges and why foundational strategy must precede any AI solution. You’ll gain insight into how to strategically approach AI implementation to avoid costly mistakes and ensure long-term success for your organization. Watch now to learn how to make the right choice for your organization’s AI future. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-should-you-hire-ai-expert.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn – 00:00 In this week’s In-Ear Insights, a few people have asked us the question, should I hire an AI expert—a person, an AI expert on my team—or should I try to grow AI expertise, someone as an AI leader within my company? I can see there being pros and cons to both, but, Katie, you are the people expert. You are the organizational behavior expert. I know the answer is it depends. But at first blush, when someone comes to you and says, hey, should I be hiring an AI expert, somebody who can help shepherd my organization through the crazy mazes of AI, or should I grow my own experts? What is your take on that question? Katie Robbert – 00:47 Well, it definitely comes down to it depends. It depends on what you mean by an AI expert. So, what is it about AI that they are an expert in? Are you looking for someone who is staying up to date on all of the changes in AI? Are you looking for someone who can actually develop with AI tools? Or are you looking for someone to guide your team through the process of integrating AI tools? Or are you looking for all of the above? Which is a totally reasonable response, but that doesn’t mean you’ll get one person who can do all three. So, I think first and foremost, it comes down to what is your goal? And by that I mean, what is the AI expertise that your team is lacking? Katie Robbert – 01:41 Or what is the purpose of introducing AI into your organization? So, unsurprisingly, starting with the 5P framework, the 5Ps are purpose, people, process, platform, performance, because marketers like alliteration. So, purpose. You want to define clearly what AI means to the company, so not your ‘what I did over summer vacation’ essay, but what AI means to me. What do you want to do with AI? Why are you bringing AI in? Is it because I want to keep up with my competitors? Bad answer. Is it because you want to find efficiencies? Okay, that’s a little bit better. But if you’re finding efficiencies, first you need to know what’s not working. So before you jump into getting an AI expert, you probably need someone who’s a process expert or an expert in the technologies that you feel like are inefficient. Katie Robbert – 02:39 So my personal stance is that there’s a lot of foundational work to do before you figure out if you can have an AI expert. An AI expert is like bringing in an AI piece of software. It’s one more thing in your tech stack. This is one more person in your organization fighting to be heard. What are your thoughts, Chris? Christopher S. Penn – 03:02 AI expert is kind of like saying, I want to hire a business expert. It’s a very umbrella term. Okay, are your finances bad? Is your hiring bad? Is your sales process bad? To your point, being very specific about your purpose and the performance—which are the bookends of the 5Ps—is really important because otherwise AI is a big area. You have regression, you have classification, you have generative AI. Even within generative AI, you have coding, media generation. There’s so many things. We were having a discussion internally in our own organization this morning about some ideas about internationalization using AI. It’s a big planet. Katie Robbert – 03:46 Yeah, you’ve got to give me some direction. What does that mean? I think you and I, Chris, are aligned. If you’re saying, ‘I want to bring in an AI expert,’ you don’t actually know what you’re looking for because there are so many different facets of expertise within the AI umbrella that you want to be really specific about what that actually means and how you’re going to measure their performance. So if you’re looking for someone to help you make things more efficient, that’s not necessarily an AI expert. If you’re concerned that your team is not on board, that’s not an AI expert. If you are thinking that you’re not getting the most out of the platforms that you’re using, that’s not an AI expert. Those are very different skill sets. Katie Robbert – 04:38 An AI expert, if we’re talking—let’s just say we could come up with a definition of an AI expert—Chris, you are someone who I would consider an AI expert, and I would list those qualifications as: someone who stays up to date. Someone who knows enough that you can put pretty much any model in front of them and they know how to build a prompt, and someone who can speak to how these tools would integrate into your existing tech stack. My guess is that’s the kind of person that everybody’s looking for: someone to bring AI into my organization, do some light education, and give us a tool to play with. Christopher S. Penn – 05:20 We often talk about things like strategy, tactics, execution, and measurement. So, sort of four layers: why are you doing this thing? What are you going to do? How are you going to do it, and did it work? An actual AI expert has to be able to do all four of those things to say, here’s why we’re doing this thing—AI or not. But here’s why you’d use AI, here’s what AI tools and technologies you use, here’s how you do them, and here’s the proof that what you did worked. So when someone says, ‘I want an AI expert for my company,’ even then, they have to be clear: do we want someone who’s going to help us set our strategy or do we want someone who’s going to build stuff and make stuff for us? It’s very unclear. Christopher S. Penn – 06:03 I think that narrowing down the focus, even if you do narrow down the focus, you still have to restart the 5Ps. So let’s say we got this question from another colleague of ours: ‘I want to do AI lead generation.’ Was the remit to help me segment and use AI to do better lead generation? Well, that’s not an AI problem. As you always say, new technology does not solve all problems. This is not an AI problem; this is a lead generation problem. So the purpose is pretty clear. You want more leads, but it’s not a platform issue with AI. It is actually a people problem. How are people buying in the age of AI? And that’s what you need to solve. Christopher S. Penn – 06:45 And from there you can then go through the 5Ps and user stories and things to say, ‘yeah, this is not an AI expert problem. This is an attention problem.’ You are no longer getting awareness because AI has eaten it. How are you going to get attention to generate audience that becomes prospects that eventually becomes leads? Katie Robbert – 07:05 Yeah, that to me is an ideal customer profile, sales playbook, marketing planning and measurement problem. And sure, you can use AI tools to help with all of those things, but those are not the core problems you’re trying to solve. You don’t need AI to solve any of those problems. You can do it all without it. It might take a little longer or it might not. It really depends. I think that’s—So, Chris, I guess we’re not saying, ‘no, you can’t bring in an AI expert.’ We’re saying there’s a lot of different flavors of AI expertise. And especially now where AI is the topic, the thing—it was NFTs and it was crypto and it was Bitcoin and it was Web three, whatever the heck that was. And it was, pick a thing—Clubhouse. Katie Robbert – 07:57 All of a sudden, everybody was an expert. Right now everybody’s a freaking expert in AI. You can’t sneeze and not have someone be like, ‘I’m an AI expert. I can fix that problem for you.’ Cool. I’ve literally never seen you in the space, but congratulations, you’re an AI expert. The point I’m making here is that if you are not hyper specific about the kind of expertise you’re looking for, you are likely going to end up with a dud. You are likely going to end up with someone who is willing to come in at a lower price just to get their foot in the door. Christopher S. Penn – 08:40 Yep. Katie Robbert – 08:40 Or charge you a lot of money. You won’t know that it’s not working until it doesn’t work and they’ve already moved on. We talked about this on the livestream yesterday about people who come in as AI experts to fix your sales process or something like that. And you don’t know it’s not working until you’ve spent a lot of money on this expert, but you’re not bringing in any more revenue. But by then they’re gone. They’re already down the street selling their snake oil to the next guy. Christopher S. Penn – 09:07 Exactly. Now, to the question of should you grow your own? That’s a big question because again, what level of expertise are you looking for? Strategy, tactics, or execution? Do you want someone who can build? Do you want someone who can choose tools and tactics? Do you want someone who can set the strategy? And then within your organization, who are those people? And this is very much a people issue, which is: do they have the aptitudes to do that? I don’t mean AI aptitude; I mean, are they a curious person? Do they learn quickly? Do they learn well outside their domain? Because a lot of people can learn in their domain with what’s familiar to them. But a whole bunch of other people are really uncomfortable learning something outside their domain. Christopher S. Penn – 09:53 And for one reason or another, they may not be suited as humans to become that internal AI champion. Katie Robbert – 10:02 I would add to that not only the curiosity, but also the communication, because it’s one thing to be able to learn it, but then you have to, if you’re part of a larger team, explain what you learned, explain why you think this is a good idea. You don’t have to be a professional speaker, be able to give a TED talk, but you need to be able to say, ‘hey, Chris, I found this tool. Here’s what it does, here’s why I think we should use it,’ and be able to do that in a way that Chris is like, ‘oh, yeah! That is a really good idea. Let’s go ahead and explore it.’ But if you just say, ‘I found this thing,’ okay, and congratulations, here’s your sticker, that’s not helpful. Katie Robbert – 10:44 So communication, the people part of it, is essential. Right now, a lot of companies—we talked about this on last week’s podcast—a lot of leaders, a lot of CEOs, are disregarding the people in favor of ‘AI is going to do it,’ ‘technology is going to take it over,’ and that’s just not how that’s going to work. You can go ahead and alienate all of your people, but then you don’t have anyone to actually do the work. Because AI doesn’t just set itself up; it doesn’t just run itself without you telling it what it is you need it to do. And you need people to do that. Christopher S. Penn – 11:27 Yep. Really important AI models—we just had a raft of new announcements. So the new version of Gemini 2.5, the new version of OpenAI’s Codex, Claude 4 from Anthropic just came out. These models have gotten insanely smart, which, as Ethan Mollock from Wharton says, is a problem, because the smarter AI gets, the smarter its mistakes get and the harder it is for non-experts to pick up that expert AI is making expert-level mistakes that can still steer the ship in the wrong direction, but you no longer know if you’re not a domain expert in that area. So part of ‘do we grow an AI expert internally’ is: does this person that we’re thinking of have the ability to become an AI expert but also have domain expertise in our business to know when the AI is wrong? Katie Robbert – 12:26 At the end of the day, it’s software development. So if you understand the software development lifecycle, or even if you don’t, here’s a very basic example. Software engineers, developers, who don’t have a QA process, yes, they can get you from point A to point B, but it may be breaking things in the background. It might be, if their code is touching other things, something else that you rely on may have been broken. But listen, that thing you asked for—it’s right here. They did it. Or it may be using a lot of API tokens or server space or memory, whatever it is. Katie Robbert – 13:06 So if you don’t also have a QA process to find out if that software is working as expected, then yes, they got you from point A to point B, but there are all of these other things in the background that aren’t working. So, Chris, to your point about ‘as AI gets smarter, the mistakes get smarter’—unless you’re building people and process into these AI technologies, you’re not going to know until you get slapped with that thousand-dollar bill for all those tokens that you used. But hey, great! Three of your prospects now have really solid lead scores. Cool. Christopher S. Penn – 13:44 So I think we’re sort of triangulating on what the skills are that you should be looking for, which is someone who’s a good critical thinker, someone who’s an amazing communicator who can explain things, someone who is phenomenal at doing requirements gathering and being able to say, ‘this is what the thing is.’ Someone who is good at QA to be able to say the output of this thing—human or machine—is not good, and here’s why, and here’s what we should do to fix it. Someone who has domain expertise in your business and can explain, ‘okay, this is how AI does or does not fit into these things.’ And then someone who knows the technology—strategy, tactics, and execution. Why are we using this technology? What does the technology do? How do we deploy it? Christopher S. Penn – 14:30 For example, Mistral, the French company, just came up with a new model Dev Stroll, which is apparently doing very well on software benchmarks. Knowing that it exists is important. But then that AI expert who has to have all those other areas of expertise also has to know why you would use this, what you would use it for, and how you would use it. So I almost feel that’s a lot to cram into one human being. Katie Robbert – 14:56 It’s funny, I was just gonna say I feel that’s where—and obviously dating ourselves—that’s where things, the example of Voltron, where five mini-lion bots come together to make one giant lion bot, is an appropriate example because no one person—I don’t care who they are—no one person is going to be all of those things for you. But congratulations: together Chris and I are. That Voltron machine—just a quick plug. Because it’s funny, as you’re going through, I’m like, ‘you’re describing the things that we pride ourselves on, Chris,’ but neither of us alone make up that person. But together we do cover the majority. I would say 95% of those things that you just listed we can cover, we can tackle, but we have to do it together. Katie Robbert – 15:47 Because being an expert in the people side of things doesn’t always coincide with being an expert in the technology side of things. You tend to get one or the other. Christopher S. Penn – 15:59 Exactly. And in our case as an agency, the client provides the domain expertise to say, ‘hey, here’s what our business is.’ We can look at it and go, ‘okay, now I understand your business and I can apply AI technology and AI processes and things to it.’ But yeah, we were having that discussion not too long ago about, should we claim that AI expertise in healthcare technologies? Well, we know AI really well. Do we know healthcare—DSM codes—really well? Not really, no. So could we adapt and learn fast? Yes. But are we practitioners day to day working in an ER? No. Katie Robbert – 16:43 So in that case, our best bet is to bring on a healthcare domain expert to work alongside both of us, which adds another person to the conversation. But that’s what that starts to look like. If you say, ‘I want an AI expert in healthcare,’ you’re likely talking about a few different people. Someone who knows healthcare, someone who knows the organizational behavior side of things, and someone who knows the technology side of things. And together that gives your quote-unquote AI expert. Christopher S. Penn – 17:13 So one of the red flags for the AI expert side of things, if you’re looking to bring in someone externally, is someone who claims that with AI, they can know everything because the machines, even with great research tools, will still make mistakes. And just because someone’s an AI expert does not mean they have the sense to understand the subtle mistakes that were made. Not too long ago, we were using some of the deep research tools to pull together potential sponsors for our podcast, using it as a sales prospecting tool. And we were looking at it, looking at who we know to be in the market: ‘yeah, some of these are not good fits.’ Even though it’s plausible, it’s still not a good fit. Christopher S. Penn – 18:01 One of them was the Athletic Greens company, which, yes, for a podcast, they advertise on every podcast in the world. I know from listening to other shows and listening to actual experts that there’s some issues with that particular sponsorship. So it’s not a good fit. Even though the machine said, ‘yeah, this is because they advertise on every other podcast, they’re clearly just wanting to hand out money to podcasters.’ I have the domain expertise in our show to know, ‘yeah, that’s not a good fit.’ But as someone who is an AI expert who claimed that they understood everything because AI understands everything, doesn’t know that the machine’s wrong. So as you’re thinking about, should I bring an AI expert on externally, vet them on the level, vet them on how willing they are to say, ‘I don’t know.’ Katie Robbert – 18:58 But that’s true of really any job interview. Christopher S. Penn – 19:01 Yes. Katie Robbert – 19:02 Again, new tech doesn’t solve old problems, and AI is, at least from my perspective, exacerbating existing problems. So suddenly you’re an expert in everything. Suddenly it’s okay to be a bad manager because ‘AI is going to do it.’ Suddenly the machines are all. And that’s not an AI thing. Those are existing problems within your organization that AI is just going to magnify. So go ahead and hire that quote-unquote AI expert who on their LinkedIn profile says they have 20 years of generative AI expertise. Good luck with that person, because that’s actually not a thing now. Christopher S. Penn – 19:48 At most it would have to be 8 years and you would have to have credentials from Google DeepMind, because that’s where it was invented. You cannot say it’s anything older than that. Katie Robbert – 20:00 But I think that’s also a really good screening question is: do you know what Google DeepMind is? And do you know how long it’s been around? Christopher S. Penn – 20:09 Yep. If someone is an actual AI expert—not ‘AI and marketing,’ but an actual AI expert itself—can you explain the Transformers architecture? Can you explain the diffuser architecture? Can you explain how they’re different? Can you explain how one becomes the other? Because that was a big thing that was announced this week by Google DeepMind. No surprise about how they’re crossing over into each other, which is a topic for another time. But to your point, I feel AI is making Dunning-Kruger much worse. At the risk of being insensitive, it’s very much along gender lines. There are a bunch of dudes who are now making wild claims: ‘no, you really don’t know what you’re talking about.’ Katie Robbert – 21:18 I hadn’t planned on putting on my ranty pants today, but no, I feel that’s. Again, that’s a topic for another time. Okay. So here’s the thing: you’re not wrong. To keep this podcast and this topic productive, you just talked about a lot of things that people should be able to explain if they are an AI expert. The challenge on the other side of that table is people hiring that AI expert aren’t experts in AI. So, Chris, you could be explaining to me how Transformers turn into Voltron, bots turn into Decepticons, and I’m like, ‘yeah, that sounds good’ because you said all the right words. So therefore, you must be an expert. So I guess my question to you is, how can a non-AI expert vet and hire an AI expert without losing their mind? Is that possible? Christopher S. Penn – 22:15 Change the words. How would you hire a medical doctor when you’re not a doctor? How would you hire a plumber when you’re not a plumber? What are the things that you care about? And that goes back to the 5Ps, which is: and we say this with job interviews all the time. Walk me through, step by step, how you would solve this specific problem. Katie, I have a lead generation problem. My leads are—I’m not getting enough leads. The ones I get are not qualified. Tell me as an AI expert exactly what you would do to solve this specific problem. Because if I know my business, I should be able to listen to you go, ‘yeah, but you’re not understanding the problem, which is, I don’t get enough qualified leads. I get plenty of leads, but they’re crap.’ Christopher S. Penn – 23:02 It’s the old Glengarry Glen Ross: ‘The leads are weak.’ Whereas if the person is an actual AI expert, they can say, ‘okay, let me ask you a bunch of questions. Tell me about your marketing automation software. Tell me about your CRM. Tell me how you have set up the flow to go from your website to your marketing automation to your sales CRM. Tell me about your lead scoring. How do you do your lead scoring? Because your leads are weak, but you’re still collecting tons of them. That means you’re not using your lead scoring properly. Oh, there’s an opportunity where I can show AI’s benefit to improve your lead scoring using generative AI.’ Christopher S. Penn – 23:40 So even in that, we haven’t talked about a single model or a single ‘this’ or ‘that,’ but we have said, ‘let me understand your process and what’s going on.’ That’s what I would listen for. If I was hiring an AI expert to diagnose anything and say, I want to hear, and where we started: this person’s a great communicator. They’re a critical thinker. They can explain things. They understand the why, the what, and the how. They can ask good questions. Katie Robbert – 24:12 If I was the one being interviewed and you said, ‘how can I use AI to improve my lead score? I’m getting terrible leads.’ My first statement would be, ‘let’s put AI aside for a minute because that’s not a problem AI is going to solve immediately without having a lot of background information.’ So, where does your marketing team fit into your sales funnel? Are they driving awareness or are you doing all pure cold calling or outbound marketing—whatever it is you’re doing? How clear is your ideal customer profile? Is it segmented? Are you creating different marketing materials for those different segments? Or are you just saying, ‘hi, we’re Trust Insights, we’re here, please hire us,’ which is way too generic. Katie Robbert – 24:54 So there’s a lot of things that you would want to know before even getting into the technology. I think that, Chris, to your point, an AI expert, before they say, ‘I’m the expert, here’s what AI is going to fix,’ they’re going to know that there are a lot of things you probably need to do before you even get to AI. Anyone who jumps immediately to AI is going to solve this problem is likely not a true expert. They are probably just jumping on the bandwagon looking for a dollar. Christopher S. Penn – 25:21 Our friend Andy Crestedine has a phenomenal phrase that I love so much, which is ‘prescription before diagnosis is malpractice.’ That completely applies here. If you’re saying ‘AI is the thing, here’s the AI solution,’ yeah, but we haven’t talked about what the problem is. So to your point about if you’re doing these interviews, the person’s ‘oh yeah, all things AI. Let’s go.’ I get that as a technologist at heart, I’m like, ‘yeah, look at all the cool things we can do.’ But it doesn’t solve. Probably on the 5Ps here—down to performance—it doesn’t solve: ‘Here’s how we’re going to improve that performance.’ Katie Robbert – 26:00 To your point about how do you hire a doctor? How do you hire a plumber? We’ve all had that experience where we go to a doctor and they’re like, ‘here’s a list of medications you can take.’ And you’re like, ‘but you haven’t even heard me. You’re not listening to what I’m telling you is the problem.’ The doctor’s saying, ‘no, you’re totally normal, everything’s fine, you don’t need treatment. Maybe just move more and eat less.’ Think about it in those terms. Are you being listened to? Are they really understanding your problem? If a plumber comes into your house and you’re like, ‘I really think there’s a leak somewhere. But we hear this over here,’ and they’re like, ‘okay, here’s a cost estimate for all brand new copper piping.’ You’re like, ‘no, that’s not what I’m asking you for.’ Katie Robbert – 26:42 The key in these interviews, if you’re looking to bring on an AI expert, is: are they really listening to you and are they really understanding the problem that’s going to demonstrate their level of expertise? Christopher S. Penn – 26:54 Yep. And if you’re growing your own experts, sit down with the people that you want to become experts and A) ask them if they want to do it—that part does matter. And then B) ask them. You can use AI for this. It’s a phenomenal use case for it, of course. What is your learning journey going to be? How are you going to focus your learning so that you solve the problems? The purpose that we’ve outlined: ‘yeah, our organization, we know that our sales is our biggest blockage or finance is our biggest blockage or whatever.’ Start there and say, ‘okay, now your learning journey is going to be focused on how is AI being used to solve these kinds of problems. Dig into the technologies, dig into best practices and things.’ Christopher S. Penn – 27:42 But just saying, ‘go learn AI’ is also a recipe for disaster. Katie Robbert – 27:47 Yeah. Because, what about AI? Do you need to learn prompt engineering? Do you need to learn the different use cases? Do you need to learn the actual how the models work, any algorithms? Or, pick a thing—pick a Decepticon and go learn it. But you need to be specific. Are you a Transformer or are you a Decepticon? And which one do you need to learn? That’s going to be my example from now on, Chris, to try to explain AI because they sound like technical terms, and in the wrong audience, someone’s going to think I’m an AI expert. So I think that’s going to be my test. Christopher S. Penn – 28:23 Yes. Comment guide on our LinkedIn. Katie Robbert – 28:27 That’s a whole. Christopher S. Penn – 28:29 All right, so, wrapping up whether you buy or build—which is effectively what we’re discussing here—for AI expertise, you’ve got to go through the 5Ps first. You’ve got to build some user stories. You’ve got to think about the skills that are not AI, that the person needs to have: critical thinking, good communication, the ability to ask great questions, the ability to learn quickly inside and outside of their domain, the ability to be essentially great employees or contractors, no matter what—whether it’s a plumber, whether it’s a doctor, whether it’s an AI expert. None of that changes. Any final parting thoughts, Katie? Katie Robbert – 29:15 Take your time. Which sounds counterintuitive because we all feel that AI is changing so rapidly that we’re falling behind. Now is the time to take your time and really think about what it is you’re trying to do with AI. Because if you rush into something, if you hire the wrong people, it’s a lot of money, it’s a lot of headache, and then you end up having to start over. We’ve had talks with prospects and clients who did just that, and it comes from ‘we’re just trying to keep up,’ ‘we’re trying to do it quickly,’ ‘we’re trying to do it faster,’ and that’s when mistakes are made. Christopher S. Penn – 29:50 What’s the expression? ‘Hire slow, fire fast.’ Something along those lines. Take your time to really make good choices with the people. Because your AI strategy—at some point you’re gonna start making investments—and then you get stuck with those investments for potentially quite some time. If you’ve got some thoughts about how you are buying or building AI expertise in your organization you want to share, pop on. Buy our free Slack. Go to trustinsights.ai/analyticsformarketers where you and over 4,200 other marketers are asking and answering each other’s questions every single day. And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on, go to trustinsights.ai/tipodcast. You can find us in all the places fine podcasts are served. Thanks for tuning in. Christopher S. Penn – 30:35 I will talk to you on the next one. Katie Robbert – 30:43 Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch, and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and martech selection and implementation, and high-level strategic consulting. Katie Robbert – 31:47 Encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMOs or data scientists to augment existing teams beyond client work. Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights Podcast, the Inbox Insights newsletter, the ‘So What?’ Livestream, webinars, and keynote speaking. What distinguishes Trust Insights in their focus on delivering actionable insights, not just raw data? Trust Insights is adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models. Yet they excel at exploring and explaining complex concepts clearly through compelling narratives and visualizations. Data Storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data-driven. Katie Robbert – 32:52 Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Welcome to the world of consulting in 2025. AI is everywhere—from writing reports and making decks to crunching numbers. But you'd think the likes of McKinsey, Bain, and BCG would be worried about AI, right? Because AI reduces the knowledge gap between them and their clients. Turns out, instead of resisting it, they're going all in.The ones feeling the heat are junior most employees—the consultants. Timelines are shrinking and expectations are going up. Creativity? Who cares about that anymore. A former Bain manager told The Ken about an instance when a senior partner wanted a full client assessment by the next day. Normally, this would take weeks to pull off. The result? Rushed work and fancy words that sound good but don't really say anything substantial. And worst of all—there is no  time to fact-check. There seems to be a real disconnect between what senior leaders think AI can do, and what it actually does. So what happens when the industry famous for having all the answers is now taking shortcuts using a chatbot? Also, what happens when clients find out?Q for listeners: If 90% of your job could be done by AI, what would you focus on to stay valuable?Send us your answers as texts or voice notes on Daybreak's WhatsApp at +918971108379. Daybreak is produced from the newsroom of The Ken, India's first subscriber-only business news platform. Subscribe for more exclusive, deeply-reported, and analytical business stories.

It was T-Day: Tariffs, Tesla, & Trump… We got an update on all of ‘em (and why it'll cost you $3,600/year).Tinder launched a Flirt-bot… Because AI's most powerful use is training pickup lines (seriously).Nintendo's Switch 2 is its biggest launch in 8 years… and Mario Kart is getting social.Plus, we found a Skier's Arbitrage: It's cheaper to fly to Japan for a weekend of shredding than staying here in the states…$NTDOY $TSLA $SPYWant more business storytelling from us? Check out the latest episode of our new weekly deepdive show: The untold origin story of…

Artificial Intelligence (or AI) is rapidly transforming the way we work, communicate, and make decisions—but for many, it still feels like an overwhelming or complex concept. In this episode, we're breaking down the basics of AI for the novice, making it simple and approachable so you can understand the engine behind it, how it works and why it matters. Whether you're a business owner, a creative, or just curious about the technology shaping our world, knowing these fundamentals will help you adapt, stay relevant, and make informed choices in an AI-driven future. Even though AI is not merely an illusion, I'll pull back the curtain on how AI works and some of the differences between machine and generative learning. Because AI is already being used to tackle complex challenges and improve efficiency in a variety of industries, I feel it's very valuable to know the basics of how it works. Today, most of us think nothing of using calculators instead of an abacus or pencil and paper to calculate figures. The simple calculator has become a normal part of our routine. In the same way, many aspects of AI are already integrated in many parts of our daily lives. First, I'm going to talk about input, then distinguish between machine learning and generative learning. Full article here: https://goalsforyourlife.com/artificial-intelligence Make sure you're getting all our podcast updates and articles! Get them here: https://goalsforyourlife.com/newsletter  Resources with tools and guidance for mid-career individuals, professionals & those at the halftime of life seeking growth and fulfillment: http://HalftimeSuccess.com #ainews #digitalmarketing #aitools #contentcreation #aiproductivitytools CHAPTERS: 00:00 - Intro 01:34 - Input Data 06:21 - Machine Learning Basics 08:51 - Generative Learning Techniques 10:47 - The Power of AI Applications 15:58 - Applying AI to Your Life 18:24 - Thank You for Joining Us  

Guest post by Jeremy Campbell, CEO of Black Isle Group and creator of Nudge.ai - turning learning into lasting habits. Imagine this: AI is your new colleague, handling repetitive tasks, analysing mountains of data, and offering insights you never thought possible. But here's the twist - it can't work at its best without you. While AI excels at logic and efficiency, it's your human skills - empathy, creativity, adaptability - that make the magic happen. If that sounds like a bit of a balancing act, it is. But it's also the future of work, and as organisations, we need to prepare for it. To do this, we need to shift from focusing on lofty goals to creating systems and habits that support this collaboration. As James Clear says in Atomic Habits, "You do not rise to the level of your goals. You fall to the level of your systems." Let's dive into what that looks like and how we can build workplaces where humans and machines truly complement one another. Why Human Skills including Empathy Are Key in an AI World According to the World Economic Forum's Future of Jobs Report, 50% of all employees will need reskilling by 2025 due to the increasing integration of AI and automation. The report also highlights that while technical skills remain essential, human-centric skills like problem-solving, critical thinking, and emotional intelligence are rising in demand. Why? Because AI, as remarkable as it is, has its limits. It can identify patterns, predict trends, and crunch data, but it can't replicate human traits like empathy, creativity, and adaptability. 1. Empathy: The Human Connection?AI can analyse customer preferences and suggest solutions, but it can't interpret subtle emotions or provide genuine reassurance in high-stakes conversations. Empathy builds trust, loyalty, and deeper collaboration, making it a critical skill for the future workplace. 2. Creativity: Turning Data into Ideas?AI might generate ideas or refine concepts, but creativity comes from humans connecting the dots in unexpected ways. It's the human ability to challenge norms and think laterally that turns raw AI outputs into groundbreaking innovations. 3. Adaptability: Thriving in Change?As AI technologies evolve, so do workplace dynamics. Adaptability allows us to respond quickly to shifts, learn new tools, and approach challenges with resilience and curiosity - something that algorithms simply can't mimic. The Power of Focus and Essentialism It's tempting to try to tackle every skill gap at once, but we need to prioritise. Greg McKeown, in his book Essentialism, argues for doing "less, but better." Instead of chasing every shiny new skill, we need to focus on the ones that will truly make a difference. At the same time, we need to make space for deep, focused work. Cal Newport's Deep Work makes a strong case for how essential focus is in a distracted world. He writes, "The ability to perform deep work is becoming increasingly rare at exactly the same time it is becoming increasingly valuable." Organisations should be asking: how can we create environments where employees have the time and space to develop these human skills alongside AI? Building Habits for the Future It's easy to get caught up in the hype of "future-proofing" your workforce with endless training and upskilling. But as James Clear reminds us, it's not about the intensity of effort; it's about creating consistent, effective habits. If we want employees to build empathy, creativity, and adaptability, we need to embed these into the daily rhythm of work. Encourage Small, Consistent Actions: Creativity doesn't come from one big brainstorming session but from cultivating habits like regular reflection, asking better questions, and exploring diverse perspectives. Reward Adaptability: Acknowledge and celebrate employees who embrace change or take risks in uncertain situations. This sets the tone for a growth mindset across the organisation. Practical Steps for Organisations So, how do you actually make ...

It's not a reach to say that we're currently in a time of uncertainty, across technology, economic and political spectrums. But historically, times of uncertainty have often led to unexpected creativity. SHOW: 875SHOW TRANSCRIPT: The Cloudcast #875 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW SPONSOR:Love the insights from this episode? Make sure you never miss a beat with Chatpods! Whether you're commuting, working out, or just on the go, Chatpods lets you capture and summarize key takeaways effortlessly.  Save time, stay organized, and keep your thoughts at your fingertips.  Download Chatpods directly from App Store or Google Play and use it to listen to this podcast todaySHOW NOTES:New research shows widespread adoption of GenAIWHAT DID NETFLIX DO FOR THE CLOUD ERA?Provided a face for a new style of doing workProvided validation that a new model could workEncouraged people to explore older, “bad practices”Began to define metrics of what the new world could look likeWHY DO WE NEED A NETFLIX OF THE AI ERA?Because AI can apparently do everything, but what are some specific things?What are the new ways of thinking about old problems?Has it been proven to improve teams, or mostly individuals? Do we need a Couch to 5k set of use-cases? Starting use-casesOr is AI going to be a big-bang approach?FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

Reed Smith emerging tech lawyers Andy Splittgerber in Munich and Cynthia O'Donoghue in London join entertainment & media lawyer Monique Bhargava in Chicago to delve into the complexities of AI governance. From the EU AI Act to US approaches, we explore common themes, potential pitfalls and strategies for responsible AI deployment. Discover how companies can navigate emerging regulations, protect user data and ensure ethical AI practices. ----more---- Transcript: Intro: Hello and welcome to Tech Law Talks, a podcast brought to you by Reed Smith's Emerging Technologies Group. In each episode of this podcast, we will discuss cutting-edge issues on technology, data, and the law. We will provide practical observations on a wide variety of technology and data topics to give you quick and actionable tips to address the issues you are dealing with every day.  Andy: Welcome to Tech Law Talks and our new series on artificial intelligence. Over the coming months, we'll explore the key challenges and opportunities within the rapidly evolving AI landscape globally. Today, we'll focus on AI and governance with a main emphasis on generative AI in a regional perspective if we look into Europe and the US. My name is Andy Splittgerber. I'm a partner in the Emerging Technologies Group of Reed Smith in Munich, and I'm also very actively advising clients and companies on artificial intelligence. Here with me, I've got Cynthia O'Donoghue from our London office and Nikki Bhargava from our Chicago office. Thanks for joining.  Cynthia: Thanks for having me. Yeah, I'm Cynthia O'Donoghue. I'm an emerging technology partner in our London office, also currently advising clients on AI matters.  Monique: Hi, everyone. I'm Nikki Bhargava. I'm a partner in our Chicago office and our entertainment and media group, and really excited to jump into the topic of AI governance. So let's start with a little bit of a basic question for you, Cynthia and Andy. What is shaping how clients are approaching AI governance within the EU right now?  Cynthia: Thanks, Nikki. The EU is, let's say, just received a big piece of legislation, went into effect on the 2nd of October that regulates general purpose AI and high risk general purpose AI and bans certain aspects of AI. But that's only part of the European ecosystem. The EU AI Act essentially will interplay with the General Data Protection Regulation, the EU's Supply Chain Act, and the latest cybersecurity law in the EU, which is the Network and Information Security Directive No. 2. so essentially there's a lot of for organizations to get their hands around in the EU and the AI act has essentially phased dates of effectiveness but the the biggest aspect of the EU AI act in terms of governance lays out quite a lot and so it's a perfect time for organizations to start are thinking about that and getting ready for various aspects of the AAC as they in turn come into effect. How does that compare, Nikki, with what's going on in the U.S.?  Monique: So, you know, the U.S. is still evaluating from a regulatory standpoint where they're going to land on AI regulation. Not to say that we don't have legislation that has been put into place. We have Colorado with the first comprehensive AI legislation that went in. And we also had, you know, earlier in the year, we also had from the Office of Management and Budget guidelines to federal agencies about how to procure and implement AI, which has really informed the governance process. And I think a lot of companies in the absence of regulatory guidance have been looking to the OMB memo to help inform what their process may look like. And I think the one thing I would highlight, because we're sort of operating in this area of unknown and yet-to-come guidance, that a lot of companies are looking to their existing governance frameworks right now and evaluating how they're both from a company culture perspective, a mission perspective, their relationship with consumers, how they want to develop and implement AI, whether it's internally or externally. And a lot of the governance process and program pulls guidance from some of those internal ethics as well.  Cynthia: Interesting, so I'd say somewhat similar in the EU, but I think, Andy, the consumer, I think the US puts more emphasis on, consumer protection, whereas the EU AI Act is more all-encompassing in terms of governance. Wouldn't you agree?  Andy: Yeah, that was also the question I wanted to ask Nikki, is where she sees the parallels and whether organizations, in her view, can follow a global approach for AI are ai governance and yes i like for the for the question you asked yes i mean the AI act is the European one is more encompassing it is i'm putting a lot of obligations on developers and deployers like companies that use ai in the end of course it also has the consumer or the user protection in the mind but the rules directly rated relating to consumers or users are I would say yeah they're limited. So yeah Nikki well what what's kind of like you always you always know US law and you have a good overview over European laws what is we are always struggling with all the many US laws so what's your thought can can companies in terms of AI governance follow a global approach?  Monique: In my opinion? Yeah, I do think that there will be a global approach, you know, the way the US legislates, you know, what we've seen is a number of laws that are governing certain uses and outputs first, perhaps because they were easier to pass than such a comprehensive law. So we see laws that govern the output in terms of use of likenesses, right, of publicity violations. We're also seeing laws come up that are regulating the use of personal information and AI as a separate category. We're also seeing laws, you know, outside of the consumer, the corporate consumer base, we're also seeing a lot of laws around elections. And then finally, we're seeing laws pop up around disclosure for consumers that are interacting with AI systems, for example, AI powered chatbots. But as I mentioned, the US is taking a number of cues from the EU AI Act. So for example, Colorado did pass a comprehensive AI law, which speaks to both obligations for developers and obligations to deployers, similar to the way the EU AI Act is structured, and focusing on what Colorado calls high risk AI systems, as well as algorithmic discrimination, which I think doesn't exactly follow the EU AI Act, but draws similar parallels, I think pulls a lot of principles. That's the kind of law which I really see informing companies on how to structure their AI governance programs, probably because the simple answer is it requires deployers at least to establish a risk management policy and procedure and an impact assessment for high risk systems. And impliedly, it really requires developers to do the same. Because developers are required to provide a lot of information to deployers so that deployers can take the legally required steps in order to deploy the AI system. And so inherently, to me, that means that developers have to have a risk management process themselves if they're going to be able to comply with their obligations under Colorado law. So, you know, because I know that there are a lot of parallels between what Colorado has done, what we see in our memo to federal agencies and the EU AI Act, maybe I can ask you, Cynthia and Andy, to kind of talk a little bit about what are some of the ways that companies approach setting up the structure of their governance program? What are some buckets that it is that they look at, or what are some of the first steps that they take?  Cynthia: Yeah, thanks, Nikki. I mean, it's interesting because you mentioned about the company-specific uses and internal and external. I think one thing, you know, before we get into the governance structure or maybe part of thinking about the governance structure is that for the EU AI Act, it also applies to employee data and use of AI systems for vocational training, for instance. So I think in terms of governance structure. Certainly from a European perspective, it's not necessarily about use cases, but about really whether you're using that high risk or general purpose AI and, you know, some of the documentation and certification requirements that might apply to the high risk versus general purpose. But the governance structure needs to take all those kinds of things into account. Account so you know obviously guidelines and principles about the you know how people use external AI suppliers how it's going to be used internally what are the appropriate uses you know obviously if it's going to be put into a chatbot which is the other example you used what are rules around acceptable use by people who interact with that chatbot as well as how is that chatbot set up in terms of what would be appropriate to use it for. So what are the appropriate use cases? So, you know, guidelines and policies, definitely foremost for that. And within those guidelines and policies, there's also, you know, the other documents that will come along. So terms of use, I mentioned acceptable use, and then guardrails for the chatbot. I mean, I mean, one of the big things for EU AI is human intervention to make sure if there's any anomalies or somebody tries to game it, that there can be intervention. So, Andy, I think that dovetails into the risk management process, if you want to talk a bit more about that.  Andy: Yeah, definitely. I mean, the risk management process in the wider sense, of course, like how do organizations start this at the moment is first setting up teams or you know responsible persons within the organization that take care of this and we're gonna discuss a bit later on how that structure can look like and then of course the policies you mentioned not only regarding the use but also how to or which process to follow when AI is being used or even the question what is AI and how do we at all find out in our organization where we're using AI and what is an AI system as defined under the various laws, also making sure we have a global interpretation of that term. And then that is a step many of our clients are taking at the moment is like setting up an AI inventory. And that's already a very difficult and tough step. And then the next one is then like per AI system that is then coming up in this register is to define the risk management process. And of course, that's the point where in Europe, we look into the AI Act and look what kind of AI system do we have, high risk or any other sort of defined system. Or today, we're talking about the generative AI systems a bit more. For example, there we have strong obligations in the European AI Act on the providers of such generative AI. So less on companies that use generative AI, but more on those that develop and provide the generative AI because they have the deeper knowledge on what kind of training data is being used. They need to document how the AI is working and they need to also register this information with the centralized database in the European Union. They also need to give some information on copyright protected material that is contained in the training data so there is quite some documentation requirements and then of course so logging requirements to make sure the AI is used responsibly and does not trigger higher are risks. So there's also two categories of generative AI that can be qualified. So that's kind of like the risk management process under the European AI Act. And then, of course, organizations also look into risks into other areas, copyright, data protection, and also IT security. Cynthia, I know IT security is one of the topics you love. You add some more on IT security here and then we'll see what Nikki says for the US.  Cynthia: Well, obviously NIST 2.0 is coming into force. It will cover providers of certain digital services. So it's likely to cover providers of AI systems in some way or other. And funny enough, NIST 2.0 has its own risk management process involved. So there's supply chain due diligence involved, which would have to be baked into a risk management process for that. And then the EU's ENISA, Cybersecurity Agency for the EU, has put together a framework for cybersecurity, for AI systems, dot dot binding. But it's certainly a framework that companies can look to in terms of getting ideas for how best to ensure that their use of AI is secure. And then, of course, under NIST, too, the various C-Certs will be putting together various codes and have a network meeting late September. So we may see more come out of the EU on cybersecurity in relation to AI. But obviously, just like any kind of user of AI, they're going to have to ensure that the provider of the AI has ensured that the system itself is secure, including if they're going to be putting trained data into it, which of course is highly probable. I just want to say something about the training data. You mentioned copyright, and there's a difference between the EU and the UK. So in the UK, you cannot use, you know, mine data for commercial purposes. So at one point, the UK was looking at an exception to copyright for that, but it doesn't look like that's going to happen. So there is a divergence there, but that stems from historic UK law rather than as a result of the change from Brexit. Nikki, turning back to you again, I mean, we've talked a little bit about risk management. How do you think that that might differ in the US and what kind of documentation might be required there? Or is it a bit looser?  Monique: I think there are actually quite a bit of similarities that I would pull from what, you know, we have in the EU. And Andy, I think this goes back to your question about whether companies can establish a global process, right? In fact, I think it's going to to be really important for companies to see this as a global process as well. Because AI development is going to happen, you know, throughout the world. And it's really going to depend on where it's developed, but also where it's deployed, you know, and where the outputs are deployed. So I think taking a, you know, broader view of risk management will be really important in the the context of AI, particularly given. That the nature of AI is to, you know, process large swaths of information, really on a global scale, in order to make these analytics and creative development and content generation processes faster. So that just a quick aside of I actually think what we're going to see in the US is a lot of pulling from what we've seen that you and a lot more cooperation on that end. I agree that, you know, really starting to frame the risk governance process is looking at who are the key players that need to inform that risk measurement and tolerance analytics, that the decision making in terms of how do you evaluate, how do you inventory. Evaluate, and then determine how to proceed with AI tools. And so, you know, one of the things that I think makes it hopefully a little bit easier is to be able to leverage, you know, from a U.S. Perspective, leverage existing compliance procedures that we have, for example, for SEC compliance or privacy compliance or, you know, other ethics compliance programs. Brands and make AI governance a piece of that, as well as, you know, expand on it. Because I do think that AI governance sort of brings in all of those compliance pieces. We're looking at harms that may exist to a company, not just from personal information, not just from security. Not just from consumer unfair deceptive trade practices, not just from environmental, standpoints, but sort of the very holistic view of not to make this a bigger thing than it is, but kind of everything, right? Kind of every aspect that comes in. And you can see that in some of the questions that developers are supposed to be able to answer or deployers are supposed to be able to answer in risk management programs, like, for example, in Colorado, right, the information that you need to be able to address in a risk management program and an impact assessment really has to demonstrate an understanding of, of the AI system, how it works, how it was built, how it was trained, what data went into it. And then what are the full, what is the full range of harms? So for example, you know, the privacy harms, the environmental harms, the impact on employees, the impact on internal functions, the impact on consumers, if you're using it externally, and really be able to explain that, whether you have to put out a public statement or not, that will depend on the jurisdiction. But even internally, to be able to explain it to your C-suite and make them accountable for the tools that are being brought in, or make it explainable to a regulator if they were to come in and say, well, what did you do to assess this tool and mitigate known risks? So, you know, kind of with that in mind, I'm curious, what steps do you think need to go into a governance program? Like, what are one of the first initial steps? And I always feel that we can sort of start in so many different places, right, depending on how a company is structured, or what initial compliance pieces are. But I'm curious to know from you, like, Like, what would be one of the first steps in beginning the risk management program?  Cynthia: Well, as you said, Nikki, I mean, one of the best things to do is leverage existing governance structures. You know, if we look, for instance, into how the EU is even setting up its public authorities to look at governance, you've got, as I've mentioned, you know, kind of at the outset, you've almost got a multifaceted team approach. And I think it would be the same. I mean, the EU anticipates that there will be an AI officer, but obviously there's got to be team members around that person. There's going to be people with subject matter expertise in data, subject matter expertise in cyber. And then there will be people who have subject matter expertise in relation to the AI system itself, the data, training data that's been used, how it's been developed, how the algorithm works. Whether or not there can be human intervention. What happens if there are anomalies or hallucinations in the data? How can that be fixed? So I would have thought that ultimately part of that implementation is looking at governance structure and then starting from there. And then obviously, I mean, we've talked about some of the things that go into the governance. But, you know, we have clients who are looking first at use case and then going, okay, what are the risks in relation to that use case? How do we document it? How do we log it? How do we ensure that we can meet our transparency and accountability requirements? You know, what other due diligence and other risks are out there that, you know, blue sky thinking that we haven't necessarily thought about. Andy, any?  Andy: Yeah, that's, I would say, one of the first steps. I mean, even though not many organizations allocate now the core AI topic in the data protection department, but rather perhaps in the compliance or IT area, still from the governance process and starting up that structure, we see a lot of similarities to the data protection. Protection GDPR governance structure and so yeah I think back five years to implementation or getting ready for GDPR planning and checking what what other rules we we need to comply with who knew do we need to involve get the plan ready and then work along that plan that's that's the phase where we see many of our clients at the moment. Nikki, more thoughts from your end?  Monique: Yeah, I think those are excellent points. And what I have been talking to clients about is sort of first establishing the basis of measurement, right, that we're going to evaluate AI development on or procurement on. What are the company's internal principles and risk tolerances and defining those? And then based off of those principles and those metrics, putting together an impact assessment, which borrows a lot from what, you know, from what you both said, it borrows a lot from the concept of impact assessments under privacy compliance, right? Right, to implement the right questions and put together the right analytics in order to measure whether a AI tool that's in development is meeting up to those metrics, or something that we are procuring is meeting those metrics, and then analyzing the risks that are coming out of that. I think a lot of that, the impact assessment is going to be really important in helping make those initial determinations. But also, you know, and this is not just my feeling, this is something that is also required in the Colorado law is setting up an impact assessment, and then repeating it annually, which I think is particularly important in the context of AI, especially generative AI, because generative AI is a learning system. So it is going to continue to change, There may be additional modifications that are made in the course of use that is going to require reassessing, is the tool working the way it is intended to be working? You know, what has our monitoring of the tool shown? And, you know, what are the processes we need to put into place? In order to mitigate the tool, you know, going a little bit off path, AI drift, more or less, or, you know, if we start to identify issues within the AI, how do we what processes do we have internally to redirect the ship in the right process. So I think impact assessments are going to be a critical tool in helping form what is the rest of the risk management process that needs to be in place.  Andy: All right. Thank you very much. I think these were a couple of really good practical tips and especially first next steps for our listeners. We hope you enjoyed the session today and look forward if you have any feedback to us either here in the comment boxes or directly to us. And we hope to welcome you soon in one of our next episodes on AI, the law. Thank you very much.  Outro: Tech Law Talks is a Reed Smith production. Our producers are Ali McCardell and Shannon Ryan. For more information about Reed Smith's emerging technologies practice, please email techlawtalks@reedsmith.com. You can find our podcasts on Spotify, Apple Podcasts, Google Podcasts, reedsmith.com, and our social media accounts.  Disclaimer: This podcast is provided for educational purposes. It does not constitute legal advice and is not intended to establish an attorney-client relationship, nor is it intended to suggest or established standards of care applicable to particular lawyers in any given situation. Prior results do not guarantee a similar outcome. Any views, opinions, or comments made by any external guest speaker are not to be attributed to Reed Smith LLP or its individual lawyers.  All rights reserved. Transcript is auto-generated.

Patty Hayward, general manager for healthcare and life sciences at Talkdesk, talks about transforming the traditional call center into one that uses AI and large language models to make it easier for patients to get help and free up call center staff to focus on value-added tasks. The technology supports call center agents in their conversations with patients and helps avoid escalations. Outbound messaging prompts patients to take action, reinforcing conversations with call centers to improve patient outcomes.   Patty explains, "Because AI has been around for a long time, we've had AI infused in our platform for many years. But these large language models that have come speeding into the market have enhanced how we use AI in such a great way and allowed us to more easily support patients and agents in their journeys. We in healthcare do not make these journeys easy. They're very complex. There are a lot of things going on, and quite frankly, deployment and training of these models can be really difficult. So these large language models have helped democratize a lot of this AI so that you don't have to have a full IT staff devoted to doing this, which I think has been great."   "Then there are things you need a human for. A human in the loop is really important in healthcare because of the complexity we discussed. So, being able to support the agents, listening to the conversation, and bringing out things like the next best actions. What should that patient be doing next? How does that go without having to read articles or have tons of tabs behind your call center product or sticky notes all over the screen? I've seen this in numerous call centers to help coach those agents to make sure that they're answering calls correctly. Also, the first time the patient calls, she gets what she needs and is not transferred needlessly." #Talkdesk #GenAI #AI #ArtificialIntelligence #ContactCenter #CallCenter #ValueBasedCare #VBC #PatientExperience #MemberExperience #CustomerExperience #Providers #Payers talkdesk.com Listen to the podcast here

Patty Hayward, general manager for healthcare and life sciences at Talkdesk, talks about transforming the traditional call center into one that uses AI and large language models to make it easier for patients to get help and free up call center staff to focus on value-added tasks. The technology supports call center agents in their conversations with patients and helps avoid escalations. Outbound messaging prompts patients to take action, reinforcing conversations with call centers to improve patient outcomes.   Patty explains, "Because AI has been around for a long time, we've had AI infused in our platform for many years. But these large language models that have come speeding into the market have enhanced how we use AI in such a great way and allowed us to more easily support patients and agents in their journeys. We in healthcare do not make these journeys easy. They're very complex. There are a lot of things going on, and quite frankly, deployment and training of these models can be really difficult. So these large language models have helped democratize a lot of this AI so that you don't have to have a full IT staff devoted to doing this, which I think has been great."   "Then there are things you need a human for. A human in the loop is really important in healthcare because of the complexity we discussed. So, being able to support the agents, listening to the conversation, and bringing out things like the next best actions. What should that patient be doing next? How does that go without having to read articles or have tons of tabs behind your call center product or sticky notes all over the screen? I've seen this in numerous call centers to help coach those agents to make sure that they're answering calls correctly. Also, the first time the patient calls, she gets what she needs and is not transferred needlessly." #Talkdesk #GenAI #AI #ArtificialIntelligence #ContactCenter #CallCenter #ValueBasedCare #VBC #PatientExperience #MemberExperience #CustomerExperience #Providers #Payers talkdesk.com Download the transcript here

In our highly globalized economy, exogenous shocks and unsettling headlines are everywhere. It makes sense that market forecasters should be biting their nails, but so often their prophecies of doom prove completely false. Philipp Carlsson-Szlezak is a proponent of “rational optimism.” He believes there's a calmer, more measured way of going about financial and economic analysis that sets us up to be more flexible to the highs and lows of the economic events. Today on Faster, Please! — The Podcast, I talk with Carlsson-Szlezak about why an overreliance on models — and a tendency to assume the worst — can impair our ability to roll with unexpected events and make the best of them.Carlsson-Szlezak is the global chief economist at Boston Consulting Group, and leads the Center for Macroeconomics at their Henderson Institute. He is the co-author of the new book, Shocks, Crises and False Alarms: How to Assess True Macroeconomic Risk.In This Episode* Optimism during a polycrisis (1:39)* AI employment panic (7:47)* Risk-assessment strategy (13:08)* Federal Reserve predictions (19:44)* Impending shocks? (23:41)Below is a lightly edited transcript of our conversationPethokoukis: Philipp, welcome to the podcast.Carlsson-Szlezak: Thanks for having me.Optimism during a polycrisis (1:39)It seems as if there are multiple challenges facing the world and the global economy simultaneously. People described it as a “polycrisis,” and it could be everything from trying to navigate economies to a soft landing after a bout of inflation; part of it, I guess, is the big rise in debt; we have war in Europe; maybe, eventually, war in Asia over Taiwan; and, of course, climate change; aging population; falling birth rates; and some people seem to view AI as more of a threat than a positive, it's going to take jobs, and perhaps other bad things. If I've given a sensible description of the world, how can one be a “rational optimist” in a world of polycrisis?Just taking maybe two of your examples: The soft landing that was supposed to be impossible, remember that? We need, what was it, six percent unemployment for how many years to bring inflation down? So clearly that didn't pan out like the pessimists said. Or think about the war in Ukraine that you mentioned, which, of course, is the tragedy, but the fact is that there is no recession in the Eurozone so far. The fact is that industrial production has held up rather well, even in the heartland of industrial production in Germany. So real industrial output is actually remarkably resilient. Overall, there's little doubt that there are many, many risks. There are crises, but, more often than not, we're focusing on the tail ends of the distribution and pretend that those risks are at the very center of the risk distribution.It sort of reminds me — it's not a perfect analogy — of where we were in the early 1990s. I suppose you can always point to, and maybe this is part of your point, if you want to focus on bad news, the world will give you plenty of bad news to focus on. But I remember at the beginning of the 1990s, very bad recession here in the United States, a lot of concerns about the ability for rich economies to grow quickly. Again, debt was an issue, and though, looking back, it may seem like, wow, people should have been really excited: end of the Cold War, there was a lot of uncertainty what would happen to the former Soviet Union, a lot of talk back then about suitcase nukes, who knew what was going to happen in the world? And of course, all of this kind of concern and uncertainty led right into a big economic boom.So to kind of get back to what you were saying, it seems to me that, rather than being rational optimists, we're sort of naturally irrational pessimists.Yeah, but we shouldn't be. I think your example of the '90s and what the mid- and late '90s delivered, I think is not a bad analogy for what I think will play out in the 2020s, the rest of the decade. We're in an “era of tightness,” is what we call it in the book, which is really a structural condition of the labor market. Lots of people think that shortages in the labor market are a byproduct of Covid, but that's not true. The labor market turned tight already in 2017, so, in technical language, that's when unemployment dropped below U*. Covid was an interruption of this tightness. Unemployment went to almost 15 percent, and then it came down just as fast, but we are in this era of tightness, and I think it will persist.To be clear, even if and when you get another recession, you will return to a tight stance. And there are a lot of silver linings that come with eras of tightness: It translates into better real wage growth, it nudges and forces firms do capital-for-labor substitution, it pushes them towards the technological frontier in their respective areas, and all of that should lead into some boost of productivity growth. I'm not of the kind where we're predicting this big jump in productivity growth, I think that's too hyped, but I do believe that the structural tightness, which is almost like a spark to the fuel of technology, I think that will push gradually and measurably over the years to come.And the driving forces of that tightness are what?We have a number of things going. Essentially, you had a mismatch of demand of supply already in the late '10s, as I described, so there's a supply issue, we don't have enough labor supply. You have certain forces on the demographic side that constrained that. And I think often we hear the story that AI is going to produce so much unemployment that there will be mass unemployment, and I don't believe any of this. I think that will play out very differently. Historically, technology has never given us structural or technological unemployment. On the contrary, technology is the deflationary force in the medium- and long-run. Firms that can deliver cost savings, they can lower prices, they will do so to grab market share. That is a real income boost for consumers. So when their real incomes grow, they redeploy that gained real income to new services, new goods purchase and consumption, and that leads to new employment. And so I think, essentially, you will remain with a story where labor is tight, and that is the defining underpinnings of what's coming. Today people don't remember that even in the 2010s, I think it was Bill Gates, he wanted a robo-tax, a robot tax. Because why? Because automation was taking over the assembly lines and we're going to have to provide for all these people who are going to lose their jobs! Well, where are we today? Near record-low unemployment. And this is in a line of a long tradition where Nobel Prize winners, and technologists, and politicians, they've all predicted technological unemployment.AI employment panic (7:47)I wanted to talk a bit about AI labor, since you brought it up. If you don't think mass-unemployment is a valid concern, could there be other downsides from deployment of generative AI in an economy? Could it be, instead of higher employment, might it just be greater inequality? Maybe, before, we had technology hurting blue-collar workers; certainly there's a lot of white collars worried about it. I was just reading a story in the New York Times — all of these people in Hollywood are just terrified, whether they're doing special effects, or they're sound editors, they're all terrified that their white-collar jobs are going away. So do you see, in the near term, any downside from AI?In macro there's always this tension between the aggregate, which is what macroeconomics is about, and then the distribution of experiences under the hood of macro, if you will. So there will be winners and losers, and there will be those that are harder hit than others, but I think when you look at the aggregate, you add it all up the net-net, I don't anticipate this being a structural or technological unemployment situation.To go to the micro level, you can take the other side of that argument, too. This is not a big area of research for me, so I'm straying outside of my field of expertise here, but plenty of people have argued that perhaps AI will give a lift to those least-skilled. Why? Because AI is a companion for them that makes them more productive and allows them to create more value, and therefore to be paid better. So I think the jury is out on that.I don't anticipate a smooth ride where everyone will be a winner and everything will be just plain sailing. Of course this is disruptive, of course there will be gyrations, but the story about technological unemployment's been told for so long. Today people don't remember that even in the 2010s, I think it was Bill Gates, he wanted a robo-tax, a robot tax. Because why? Because automation was taking over the assembly lines and we're going to have to provide for all these people who are going to lose their jobs!Well, where are we today? Near record-low unemployment. And this is in a line of a long tradition where Nobel Prize winners, and technologists, and politicians, they've all predicted technological unemployment.There's a nice story with Wassily Leontief, a Nobel Prize winner in economics. He said in the '70s that human labor was going to go the way of the horse after the introduction of the automobile. Well, 50 years on, we're here with very tight labor markets. And Kennedy was worried about it, too, and others before him. And so I think we have to point to something that's truly different about AI to tell that story. I think we can potentially find some reasons that are genuinely different about AI, but before we all become hysterical about it, I think we should take a deep breath.Does it strike you as odd that, in a world of low unemployment and, if you're correct, perhaps a longer-term structural tightness, that it's at this moment that people are very worried about technological unemployment, it's at this very moment that they're very worried about immigration coming in and taking jobs. You would think these would be concerns at periods of very high unemployment: people standing in line around the block to get a job, but that's not where we're at. Yet the public mood seems to not be in sync with that.I think that's a good observation, I don't have a great explanation for it. The technology that's on display is impressive, it is novel, and what's different, generally, is that it makes a credible promise to impact the service economy. In our book, the way we position the slump of productivity growth has little to do with high debt and all those explanations that are occasionally fashionable. It has a lot to do with the fact that the US economy transitioned from being a physical economy to a service economy. And in the physical economy, the production of goods, you always had pretty respectable productivity growth, including the last few decades. But because of this mix shift into services where you did not have the technology to make progress on the productivity side, this mix shift dragged down aggregate productivity growth. If you have zero or very little productivity growth in services, which is like 65, 70 percent of the economy, and you have very high productivity growth and the part that is 30 or 35 percent of the economy, well the blended average is going to be low. And so, as we now have productivity growth promises from AI and services, I think a lot can change there. Again, not in a step change way, this is not like flipping a switch, it's going to be hard slog, and incremental, and cumulative, but something will happen there.There's plenty of risk out there. New crises will come and happen, but for every true crisis, there are many false alarms, and that is something that I think we need to internalize more, and that is something that can help us see risk a little more calmly and in a measured way.Risk-assessment strategy (13:08)Just to take a quick step back: Describe your process for assessing risk. Where do you begin? What are the factors? Do you have a fundamental baseline model of the way the world works? How does that process start and work for you?The way we go about risk in the book is to say macroeconomic risk should be viewed both as the downside, which is how we commonly view risk, like a recession, or even a structural downside like a deflationary depression — these are downsides. But for practitioners, risk is also hidden in potential upside if you miss out on it. And both the downside and the upside, they come in two flavors: tactical, short-term stuff, cyclical stuff; and the more structural strategic kind, like shifts that happen over longer periods of time. And so we like to think of macro risk in those four flavors: the short, the long term, and the upside and the downside, if you willGenerally when we look at risk, it's very seductive and tempting to focus on bad outcomes and then start analyzing how bad will it be and how quickly they're going to happen. In most situations, it pays off to take a step back, and take a deep breath, and say, “Well, how is the system constructed? What are the drivers? What is the history of this thing?” and an important question, “What would it take to get that outcome from the edges of the risk distribution? What does it take to get there?” Too often in public discourse, we jump straight to the tails of the risk distribution. We're immediately obsessing with the cliff edge and the fall into economic death, and then we're pretending that that risk outcome, which is part of the distribution, so we can't ignore it, but we're pretending that the edges of the distribution are the very center.And so what we do in the book for a number of areas of risk in the real economy, the financial economy, and the global economy, we go over and over again into these approaches of asking, “How is this thing constructed? What are the drivers? What do you have to believe for the truly bad outcome?” There's plenty of risk out there. New crises will come and happen, but for every true crisis, there are many false alarms, and that is something that I think we need to internalize more, and that is something that can help us see risk a little more calmly and in a measured way.How well did markets, investors, economists — how well was their risk-assessment process in 2020, given where we are today? My guess is that the global economy is better in 2024 than people thought in February, or March, or April of 2020 as the pandemic was kicking in. Did we do a good job assessing risk and reward back then?No. Public discourse did a terrible job at that. The conventional wisdom and received wisdom in March and April, May, even June, July, and even August, the summer, when you had the first signs of recovery, the conventional wisdom was: This is worse than 2008, and this could be as bad as the Great Depression. And we have a great collection of headlines that we keep, there are lots of them in the book as well. It was, in my mind, a prediction failure. Why? Because what happens is that a lot of the commentary, a lot of the thinking, was too model-based, what we call “master-model mentality” in the book.So how do you project a recovery, typically? You look at the unemployment rate as a proxy for the health of the economy, and if you have a high unemployment rate and a recession, well, it can take a long time to bring that down. After 2008, it took the better part of the 2010s to bring unemployment down, and you had “only” (in quotation marks) unemployment of 10 percent after the Global Financial Crisis. Now with Covid, you almost went to 15 percent. So the models extrapolated outside their empirical range. They said, “Well, if it took almost a decade to bring down this unemployment rate after 10 percent unemployment, then after 15 percent unemployment, well it's going to take even longer.” Hence, the narrative of “worse than 2008,” “as bad as the 1930s,” and blah, blah, blah.Even at the time, you could ask exactly these questions, and I'm not saying this with hindsight bias. We did a piece on March 28th, 2020 in Harvard Business Review where we did exactly that thought experiment. We said, “What does it take for this to be a structural downgrade for the US economy? What does it take for to be worse than 2008?” You're going to need to see damage on the supply side of the economy. You're going to need to see the downgrading of the labor market of a window of capital investment that isn't happening, and the loss of skills, et cetera. And we asked, “Well, how likely is that?” And, of course, it comes down to stimulus. Of course it does, and it comes down to how innovative, fast, and big are we in backstopping the real economy? And we were. And so even in March — and this is shelter-in-place phase, right? This is not even sort of the full lockdown. Even then, you could ask sober questions about very bad risks. And if you did that, you arrived at answers that weren't predictive in “this will happen” at a point forecast level of accuracy. But there was clearly a path and a narrative in March 2020 that was consistent with what actually happened: the tightest recovery on record, and a US economy that was not pushed off its trend path. So after 2008, the US economy was actually pushed off its prior trend path, never made it back in terms of what the trend was, did make it back in terms of growth rates after 2008, but it never made this levels recovery in that sense. All of that was avoided in 2020, and you didn't have to be a magician to at least entertain the possibility that that was a meaningful part of the outcome distribution.Federal Reserve predictions (19:44)Speaking of models, how has the Fed's model performed? Which is another way of saying, how has the Fed performed, and continues to perform?In the recent inflation surge, et cetera? I think the Fed has taken too much flak for what happened in the inflation spike. The inflation spike, by the way, again, was immediately spun into a structural inflection point, the 1970s narrative, off to the races, wage price spirals, all that nonsense. It was an idiosyncratic mismatch of demand and supply. It was an overshoot in consumption following stimulus, and you had the supply chain crunch, and then you had a number of exogenous shocks that nobody could foresee, and those who like to take credit for having predicted the spike, they didn't foresee the Ukraine war, the shock in oil that followed, and many other of the things that played into the spike. The bigger story, though, is quite simply that, as this mismatch of demand and supply unwound, inflation also came down pretty fast.Now, back to the Fed: Yes, there were slow in responding. Would it have been better for them to go early, perhaps, yes, let's say yes. But at the same time, the idea that they would fail to step up and act, and reign this in, and stand by and watch this whole thing go to hell. I mean that was never credible. And they did step up, and they did what they had to do, and I think also attempting the soft landing was the right thing. People at the time did say, “We need a draconian recession right now to remove all the risk of a regime break in inflation!” Well, you would've cut short a really tight labor market that has a lot of real wage gain that delivers a lot of good things for particularly the bottom of the labor market. So it was the right call to attempt a soft landing rather than saying, “Look, we're going to cut this cycle short right now to remove any risk of inflation spiraling out of control.” They did the right thing. They're successful at it. The soft landing is a success. We're well into it. And so I give them more credit.Is that what you think is the biggest mistake people are making, that they're still asking, “What about the soft landing?” And what you're saying is, “We're already into it. You sort of missed it. It happened. You're still looking for it.”Every so often you still see the headline, “Are we going to get a soft landing?” And I'm like, “Well, let's just take a step back.” What is a soft landing? The task was to cool down the labor market, best seen through the eyes of job openings, to cool that down without pushing up the unemployment rate. These two are mirror images of each other. When firms stop hiring, they usually also start firing, so we had to pull off this trick: You stop hiring, but you don't start firing.That was the soft landing. That's the definition of a soft landing, nothing else. And that is what happened: Job openings are down more than three-and-a-half million or so — don't nail me on the decimal — and the unemployment rate is up a little, but, as you and I know, the unemployment rate is not up because of firings. The unemployment rate is up for compositional and participation reasons. So if that is not a soft landing, at least, I would call it the second of three stages, if you will, I don't know what it is. And back to the topic of headlines, most of them are just confusing people more than they're helping them. It's always nice to write something clickbaity that people will be scared of and think this is the cliff edge. How about a headline: “Wow, this is a really great soft landing! This is remarkably good!” Why don't we acknowledge that for a moment?You can always speculate. You can speculate on, for example, exogenous shocks. Covid is an exogenous shock, and there are others: There are solar flares, and there are new pandemics, and there are things that can do immediate damage, and you can spend millions of dollars on models, and they simply won't capture that exogenous risk. Impending shocks? (23:41)Yeah, I mean, the name of the book is Shocks, Crises and False Alarms. As I look over the rest of this decade, if you take the most bullish and extravagant predictions about AI, it's not clear to me what the economy looks like a decade from now. Again, if you take the most bullish kind of [view]: we get the human-level AI and all that. So there's that.I also am not quite sure what the world looks like if some of these worst-case scenarios with Taiwan, and the US, and China, because that seems to me to be so potentially bad, I don't want to think about it. I don't know what the global economy looks like on the other side.What are the big risks, or the things which you believe pose the greatest risk of disruption? Disruptions are going to be good and bad. If you're really worried about AI, that must mean AI is very powerful, it can do a lot of good things, too. So what out there do you really worry about that the disruption will be just bad and have far more downside?You can always speculate. You can speculate on, for example, exogenous shocks. Covid is an exogenous shock, and there are others: There are solar flares, and there are new pandemics, and there are things that can do immediate damage, and you can spend millions of dollars on models, and they simply won't capture that exogenous risk. So that's one story.Geopolitics, since you mentioned it, a third of the book, roughly, the third part is about those types of risks, and they can be devastating, there's no doubt about it; but would you build a central case around this and make that the base case and expectation of how to view the future? Geopolitics is extremely treacherous when it comes to translating its impact on the economy. It's fascinating to me often how little the complexity is acknowledged and understood, and, in the book, we use an example juxtaposing a start of World War I and World War II.So when World War I breaks out, the Dow is down 10 percent, they close it for 136 days, and when they reopen it, it's down another 20 percent. Exactly as you would expect, right? It makes a lot of sense, a world war and the market's in the gutter. Yet, when World War II breaks out in '39, the market jumps 10 percent and stays up. Why? It ends the Great Depression, it puts to use labor, it has capital expenditure and investment, and it singlehandedly ends a decade of malaise.And there is a silver lining to this, and all of this doesn't sit well with how we want to think and should also think about geopolitics, which is in humanitarian terms, and also values and idealistic views. All of this is true and correct, but if we are to assess the impact on the economy, we are going to have to restrain some of these instincts, and we're going to have to say, what are the transmission channels from geopolitics to the real economy, to the financial economy, and to the institutions that we have in place that govern our economy? What are those transmission channels? And often, the bar is higher than you think.Just think about it, the Ukraine war. It's left no mark on the US economy at all, virtually. Why? Because the real linkages weren't there; virtually no trade into this part of the world, either Ukraine or Russia. The financial linkages weren't really there; it's not like balance sheets of US banks were impaired by shutting off that part of the world. And on the institutional side, we can discuss sanctions, and we can discuss using the US dollar as a means of punishing Russia, and all that. But essentially, once you think soberly about, well, how is that shock supposed to transmit to the economy? Well, it looks a lot different.The same could be said about the tragedy in the Middle East. The oil price is lower than before the attack on Israel, right? If you look at futures and forward pricing, or the price of insurance against swings in the oil price, it's lower today than before the attack on Israel and before the retaliation that Israel enacted. So any of these geopolitical risks and hotspots, they are to be taken seriously. I'm not saying they don't matter, but when we extrapolate from them straight to the economy, it more often goes wrong than it goes right.And a final thought: I'm not a Taiwan and China watcher, but one thing that's also clear to me, since you mentioned the unthinkable and the worst-case scenario, my next question would be, okay, what shape would that take? Would that be a blockade? Would that be an actual invasion? Would it be something that involves airlifting semiconductors out of the island? Would that be . . . There's a myriad ways of how such a thing could play out. It'd be a big shock, and terrible, but I can't say with confidence what it would do linearly to an economy like the US economy. It would come down to the details of that.Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

In this episode of the Just Schools Podcast, Jon Eckert interviews Dr. Bobby Ott, superintendent of Temple ISD and 2022 Texas Superintendent of the Year. They discuss integrating mental health services, special education needs, and innovative teaching practices. Dr. Ott highlights the importance of developing a mental health services model in schools, addressing funding and expertise limitations. He also stresses retaining specialized teachers and improving preparatory models for special education and English language learner programs Additionally, the conversation explores AI and technology's potential to transform education, advocating for proactive leadership to enhance personalized learning and prevent misuse. The Just Schools Podcast is brought to you by the Baylor Center for School Leadership. Each week, we'll talk to catalytic educators who are doing amazing work. Be encouraged. Books Mentioned: Brave New Words by Sal Khan 1000 CEOs by Andrew Davidson Connect with us: Baylor MA in School Leadership Jon Eckert LinkedIn Twitter: @eckertjon Center for School Leadership at Baylor University: @baylorcsl   Transcription: Jon Eckert: So today we're here with Bobby Ott, the superintendent of Temple ISD. He's the 2022 Superintendent of the Year for the state of Texas and a good friend of Baylor and our program. He always has a lot of wisdom to share. And so today we're going to talk a little bit about some of the challenges that he sees facing students in Temple and Texas in general and maybe just across the country because many of these issues transcend different places. Certainly they're context-specific, but broader issues. And Bobby has a pretty good handle on what's going on in Texas and has a wide network. So we're grateful to have Bobby here today. So Bobby, thanks for all you do. Just tell us a little bit about what you've been dealing with the last month or so. We'll roll in with that first and then jump into those bigger questions. But can you just update us on your world over the last month? Bobby Ott: Well, the last couple weeks for sure has been a little bit of a whirlwind, and I guess that's both figuratively and literally. But as you may know, we had three tornadoes in Temple touch down within about a 30-mile radius. And so the community really looked apocalyptic when you drove through it. Some places you couldn't drive because of debris. And of course we still had a week and a half of school left, so that caused some challenges at the 11th hour. But having a great team and a great community, number one, we were truly blessed to not have a single fatality in a natural disaster of that magnitude. So that was first and foremost. And as I shared earlier with others, to me that is certainly a divine hand being involved in that. I have never heard of a situation that had that type of catastrophe and not have a fatality. But I did send a video out, kind of a peek behind the curtain of the things we had to plan for, and we were able to make it through the last week. We were able to meet the bureaucratic requirements, which in my mind are secondary compared to the human elements of graduation, kids being in a safe environment, staff feeling safe, displaced staff having a place to be and so forth. And so now we were able to make it through that. The stress level has gone way down. And at this point, I'm just dealing with insurance adjusters and trying to figure out how to close out a budget year with deductible payments that I didn't expect to have. But anyway, we're working through it. The community is slowly getting back to normal and just blessed to have the partnerships that we do in the community and just the great hands and hearts that work together and pull together to get everybody through. Jon Eckert: No, and the video you shared was powerful because as we prepare superintendents and principals at Baylor, we try to help them anticipate every eventuality. You've taught in that. We have a number of sitting superintendents that teach in that. But until you've been through something like that, it's really hard to know what that looks like. And so I thought the video was helpful just as you went over the board and what's there. As we talk today, I want to focus in on student-centered issues that you see. Obviously, your point about the divine providence that comes in and keeps people safe in a natural disaster, that's real. There are day in, day out challenges that our kids face and resilience that they have to display and community support that they need to be successful. And so you're talking to us as we launch Cohort 8 of our EDD that's preparing superintendents. And so they're going to do three years of research on a problem of practice that they care deeply about that matters in the context they're in. And so what I'm interested in is hearing from superintendents about two or three of the biggest issues you see that need attention in the research, in data collection, but really in the practical day in and day out of how do we make life better for students? How do we do that in a way that's life-giving, that leads to flourishing, and makes sure that we're moving forward in useful ways when you're not dealing with insurance adjusters and all the budget pieces, which are real. And those have to be dealt with, otherwise you can't serve kids well. But if you were to say, "Hey, these are the two or three things that I see." That as people think about what they might research and dedicate three years of their lives to research-wise, what would come to mind as you think about that right now? Bobby Ott: And this certainly isn't in rank order, but one would be a true model of integrating. And when I say model, something that's repeatable that you could replicate in any district size, but a true model for integrating mental health services in a school district. I got to be honest with you, every year when we're sitting down as a group of superintendents, whether it's countywide or regionwide, there's always this discussion about how to truly integrate mental health services in a school system. And several districts have tried different things. They've tried some co-op services. They've tried to hire on regular counselors and get them trained in certain things and then they peel off. But there's two limitations that we find ourselves in a lot of times, and one is expertise. Rightly or wrongly, school counselors a lot of times do not have that level of expertise that we're talking about. They maybe have a general background in how to work those issues, in particular social, but the mental health pieces we find some real limitations and expertise. And then of course funding because truth be told, people that have that level of expertise make more money outside of public schools and the private sector is far more attractive and pays a lot better. So what we find ourselves doing is trying to find retirees from the private sector, people that only want to work part-time, people that really like the schedule of public schools. But people that are experts in that field could stand to make more money than the principal of the campus for sure. And so it just becomes very, very difficult. There are some very specialized skills that are required to do those kinds of things. And counselors that come out of the traditional school education track they're really equipped only to a certain line and our students are needing beyond the line. And when they try to seek outside support, a lot of times the students that have those needs do not have the resources to secure the outside support, whether it's monetary or accessibility with parents being able to get them where they need to go and so forth. So I think one, so what does that look like in terms of research? When you told me about this, I try to think about it in two lenses. One, what would be the problem? And maybe what is a approach in terms of resource or research? And I would say researching models to embed specialized counseling services, trauma-informed care, restorative practices, cognitive therapy into credentialing for counselors in their traditional track programs. Maybe therapy-specific coursework, maybe there's a way. I think we're trying to address the problem after people are certified, but I wonder if there are models that can be done between a traditional public education track in grad school in partnership with the college of psychology or behavioral sciences or something like that. And I don't know the answer to that. That's a little bit outside of my expertise. But I think there's some different directions for students there. Cohort 8 could look at maybe a preparatory model or you could look at a service model in the school system. So that would be the first one. Jon Eckert: No, that's a powerful one. And we're working in Mississippi right now with five districts because there's high levels of opioid use and abuse. And the mental health piece is such a huge part of it because you're dealing with communities that are struggling with some of that and then that is bleeding into the kids and some of the trauma that comes with that. And trying to figure out ways to put universal interventions in place that get kids making better choices that lead to thriving communities so you're less likely to make those choices is hard. But then when they've already made the choices, you need really specific interventions by highly trained people. And one of the things we've been doing in schools over the last few years is a lot of trying to fill in the gaps for people without training. And it gets really dangerous when you start trying to identify and diagnose and you have educators who are desperate for help and feel these urgent needs, but then they don't have the training. And so sometimes they can exacerbate the problem without that expertise. So I think that's tremendously insightful and needed. So what would be the next one that you have? If you were to say, "Hey, tackle this," and you said not in order, but what would be something else you would say we should be tackling? Bobby Ott: Well, the other thing that we're seeing, and this really points to special program services in particular, English language learners and special education, but those numbers are going up across the state. And there's a couple of reasons for it. I mean, I think one is generational. We're seeing that more and more in the younger generations. You're seeing more students in kinder and first with not just disabilities, but language delay and also high needs, and I'll get into that piece in a second. But the numbers go up and the funding has gone down. And so the ratios are a big problem in that mix because there are required ratios for very, very specialized programs. And when funding is going down, even the IDEA federal grant has reduced, what funds typically special education services. But the other piece is your qualifiers have expanded too. So for example, adding dyslexia to special ed has totally increased that number in every single school district. And so when those things happen, you start to pull apart the service in the program. It really starts to dilute. And so that's where we're at on that end. The other piece is RFs or residential facilities. We are really struggling because one, there's not enough residential facilities in said communities, but two, they are very liberal about denying even if they have enough beds in long and short-term placement. It literally is one of the hardest things you can possibly do to get students to qualify for a residential facility. And so what happens is those students a lot of times in schools end up becoming what I call in and outs. They're in, and then the next episode they're out. And so they never really improve educationally or anything else because we are not equipped within the school system to appropriately deliver the services those students need. And so when they're denied those services from the outside, even through referral processes, and there's a lot of complications with that, could be resources at home, it could be insurance, could be a lot of things. It could be that sometimes parents don't like to get them qualified because they'll lose some of their financial assistance. And I've run into that quite a bit too. So that's a real problem. That is a population in total that is growing, funding is not growing commensurate with the program, and specialized services are very selective for which students can be accepted and not accepted. So what's the research angle there? I mean, that's a good question. And this sounds a little bit like maybe the first one, but maybe there are different models of partnerships that we can work with students that are denied residential. I mean, there's a zone of students that we don't know how to take care of appropriately and what do we do with those students? Are there transitory programs? Are there effective practices and how we can train people to work with higher ratios or to handle students that are episodic? We are so ill-equipped in that area. And when the students don't have anywhere else to go, the default is us. And at that point, we're really not doing them a justice. We're just not. And it's heartbreaking. It's really heartbreaking. But that's something that I think would be very encouraging if there were some type of transitory model or something that can be put together. That's on the RF side. I think the other side of it, just regular special education and English language learner piece. What I find is that those are harder and harder to hire even if you do get the stipends up. I think there is an exodus of people leaving that were serving special education students. And what I hear, or what's reported to me rather through exit interviews, documented exit interviews is a lot of times it's the paperwork piece that comes with it. And this is what I don't know. It almost appears like it's a surprise. And I don't know if in prep programs there's a lot of attention given to the detail of the paperwork piece that comes with teaching in a special program because there seems to be an element of surprise when teachers are leaving and they're explaining, "Well, I didn't realize I had to do all this for RDs, I had to do all this for IEPs, I had to do all this and computer systems," and this, that and the other. And it is heavy. I mean, certainly it does carry a different weight with regard to that piece than say the regular education teacher. So that is something that I wonder at times. I don't know if that's something that's strong on the research side. I mean, obviously higher ed doesn't have the authority to minimize the bureaucratic requirements. But the time they spend with advocates, the time they spend in meetings and they walk, a lot of times they walk. And so maybe a way that we can figure out how to help school districts put together very specific teacher retention programs for special education. What does that look like? Retaining a special education and bilingual teacher that's not like retaining a general ed teacher. What does that really look like? And what are some ideas that school districts could do with helping specialized teachers with higher ratios if it comes to that? And then how can we work with students that should be in a residential facility are denied or maybe there isn't bed space or they're in for a month and they're sent back when they should have been in longer? What can we do there? So that'd be the second one. And that's probably not as succinct as the first one, but maybe there's enough directions you can go out of that. Jon Eckert: No, that's powerful and overlaps nicely with the first one. Obviously, mental health is going to weave through all of that. And so the mental health of special education teachers is also part of it. And I think you can tell people and you can prepare people say, "Hey, this is a lot of paperwork. Here's the way you're going to have to do this. These are legal contracts you're creating. This is not going to be a light lift." I think though the reality doesn't hit you until you're actually in it. Because I think most people drawn to special ed really care deeply about kids and that's what gets them... And I think it's true for teaching in general, but I think especially special ed. And then when you're hit with and you're going to have a lot more paperwork. And so you can say it, and then you live the reality and it feels different. So if you have one other challenge that you see that could use some research, some deeper thought, do you have one more in mind or anything that builds off of these two? Otherwise, we can jump to a couple other questions. Bobby Ott: I think the other one would be the general idea of pacing. There is, and this has happened probably for the last 10 years, but there seems to be this growing amount of what needs to be taught in terms of standards and the level of intricacy, which whether it's multi-step problems, high-rigor written responses, you name it. I certainly agree with testing and rigor and depth, but I disagree with the idea that the timing that teachers have to truly get students to understand things at that level and then we're adding more and more standards. To me that starts to dilute the whole entire system of public education. It becomes kind of this mile wide, inch deep versus the inverse. And so it really... I feel like as a system that we are heading toward a system of testing and minimal completion over true learning and engagement. And this is greatly because of the influence of a lot of the special interests that we're always trying to include in standards, bureaucratic systems, standard setting. And the kids really suffer greatly. And I don't know if teachers really get a handle on that piece of it because it continues to grow. So research angle, innovative teaching practices that know how to maximize time engagement, content with a group of students that are on different parts of the continuum. I know that we have things like that in prep programs, but I just think that that's something we need more and more. And I do think that we probably ought to start really considering the use of technology in a way to minimize some of the basic steps in education. And that kind of gets to the question of what opportunities do you see for educators? And I can expand on that now or wait until you comment on the third area. Jon Eckert: No, that's great. We want to jump into opportunities. Where do you see some optimistic next steps? So certainly jump right into that and then we can expand on that a little bit. Bobby Ott: I think technology use. I know AI can be received in many different ways because I've seen it firsthand. Some people turn and walk. Some people think it's a great thing. But I would love to see AI used in a way that allows the teacher to be set up in a classroom in a more intimate way with instruction and allows them to go into depth. I'm wondering if AI in tandem with a classroom teacher could create an environment where the larger nominal content can be delivered in a way in masses and the teacher can become more of, I don't want to say tutor, but someone that goes in and can either provide the enrichment or remediation in smaller groups in a classroom. I'd love to see AI shrink the classroom. And I think there's ways that that can be done. Now, I'm an administrator, so I wouldn't dare try to come up with ways without teachers being involved, but I think we almost have to get to that level. And I can't think of anything else cost-effective. I mean, you can always add more teachers in a classroom, but at some point in time that becomes a budget buster. I just wonder if there's a way to handle this through technology. So I think there are opportunities with the development of AI. I think the main thing about it is we have to lead that. It can't be something done organically because if it is students will grab a hold of that and trust me they will lead it in their own way and sometimes in an abusive way that shortchanges learning. And if that happens, then they're going to be ill prepared, number one. And number two, we're going to be spending our time as administrators doing damage control. So I think it's something we have to get ahead of. I'll tell you, we're looking as a district to have an AI conference, not this summer, but next summer, and invite school districts. We're really trying to do some things to lead the way in that. This summer is kind of a standup summer in terms of educating our staff and making sure that our network is set appropriately so we minimize abuse as much as possible. So we're doing that, but I don't see enough models out there that are something that are make take, you can grab a hold of and implement in a district. So I think there's probably some opportunity for educators there. Jon Eckert: Well, I just listened to a podcast, I haven't read the book yet, but Brave New Words by Sal Khan. He obviously with Khan Academy has influenced the learning of millions of kids, but he's super optimistic about what AI can do and creating this personalized and shrinking the classroom. And he certainly doesn't minimize the role of teachers, but it's fascinating. So I definitely need to read that. We hear about AI all the time, and you're right, you have this broad range of responses. And the challenge is going to be that is moving so rapidly that it's really hard to keep out in front. And I agree we have to. But in a world where we have been doing mile wide, inch deep for forever, William Schmidt, I think he was at Michigan State, he coined that phrase about US curriculum 30, 40 years ago. And so we've been doing this because that's what I think we do a little bit in democracies. If you can't all agree, then just put it all in. Don't narrow, just add. And so you have your special interest groups, you have all these different people that are like, "Hey, this is important." And it is important, but it can't all be important. You have to figure out ways to master things. And maybe AI can be helpful there. And I think being thoughtful about that and digging in what that means to really engage students well because Sal Khan says it, kids that are already motivated will learn really well with AI. It's the kids who are not. It's the kids with mental health issues. It's the fact that teaching is a very human endeavor. How do we make it even more human using tools? Because AI is just the newest range of tools. So it certainly doesn't replace the human being because ultimately large language models are just scraping what's on the internet. So it's consensus, not wisdom. So you certainly can learn, but if you really want to become all of who you're created to be, that requires wisdom. And so that's where the humans are there. The problem is, to your point earlier, teachers are stretched so thin and so many demands are being placed on them it's really hard to have that one-on-one interaction. It's hard to really be seen, known, and loved in a system that's not set up for that. And so if AI can help with that, I certainly am excited to see where that goes. So love that you're thinking that way. If you maybe have one other opportunity you see ahead for Temple specifically or for educators in general, what gives you some hope right now? Where do you see hopeful direction in what we're doing here in Texas? Bobby Ott: I am seeing more and more leaders leading authentically and with feeling. And I'm probably saying that in a odd way, but I see large district leaders, superintendents, and principals striking at being as personable as your smaller school. Ones are really, you don't have a choice because you're everywhere. But I see more of that and I see more of this, and I try to do it as much as... Just this shameless, this mobilizing of people to shamelessly remind others why they do it. They love children, they love staff. And as bad as the political rhetoric has been against public ed generally, I think it's mobilized educators, in particular leaders, teachers have done this night and day, leaders to say, "Hey, that doesn't characterize the entire profession. We are human. We do love our children. This is what we do. This is why we do it." And I see more of that. I really see more of that. I hear more of that when I go to conferences, when I network with superintendents. Yeah, our conversations could largely be dominated by budget and bonds and the newest innovative program and so forth. But I hear more of things like, "You know, you could get that done in your community if your community truly knows that you love their children, if your staff feels appreciated." And I think there are a lot of reasons for this effort. I think retaining people in the profession is one. But you can only go so far with money. You can only go so far with things. But positive culture, that is number one. I've always said people don't leave a job. They leave a boss because they're going to get the same job somewhere else. So this idea of how you treat people and how you demonstrate appreciation and care, I think for me, I am seeing more and more of that. I'm seeing more and more of that in the people we hire in administrative positions. I'm seeing things like that on social media. Several years ago I'd see, "Hey, we graduated 653, congratulation to the graduates." And now I'm seeing videos of a student hugging their superintendent and lifting them up off the ground and the superintendent commenting saying, "This is what it's all about." I'm just seeing more of that, whether it's small or big. And I think there's been a void of that. And I see this idea of when I get into administration, business and logistics taking over my life, that there's a real attempt to say, "It may take over my tasks, but I'm still going to put out in front my community, my students, my teachers, my school nutrition workers, and hold them up." And so that is giving me a lot of hope right now. Jon Eckert: That's great. And so these last two questions can be as short or as long as you need them to be, but on a daily basis now, given everything that you're managing, and you just highlighted a little of this, where do you find joy in the work you're doing on a daily basis? What do you go back to to maintain the joy that you seem to have in the midst of a lot of different pressures and challenges? And then the second one is is there a book that you've read in the last year that you're like, "Hey, every leader, every educator, this is a great book. This was helpful"? It doesn't even have to be in the last year. If it's something from earlier, that's great. But I always like to know those things. So where do you find your joy? What's a great book? And then we can wrap up. Bobby Ott: I find my joy in the idea that good people are still good people and they exist in the masses. So I try to make sure to connect people as much as possible to those situations. We do Mission Mondays. My entire central office every Monday is on a campus opening doors for kids that are going to school, walking in classrooms, helping to serve breakfast, do those kinds of things. I think that those kinds of things bring me joy because I see it bring them joy. I see kids get excited when there's more than the same caring adult around them, but there's others that maybe they don't even know their names right away but they know that they're in the same system that they are. It brings me joy when I see people that are normally away from kids in their job reminded of why they got into this whole profession because we put together possibilities where they are around kids. I see teachers with smile on their faces because they see a genuine care from people that aren't doing their jobs but are asking to support them. We always support people behind the scenes in our various roles, but to do it right next to someone while they're real time and to see what they're actually doing. So those kinds of things bring me joy. Just watching great educators no matter where they're at in the system making the difference in each other's lives, in students lives. So that brings me joy. And then a book that comes to my mind. I don't read a lot of educator books. I'm sorry, but I don't. I read a lot of... I do read leadership books. But there's a book called 1000s CEOs and it's by Andrew Davidson. And it really takes top CEOs and puts them in containers like visionaries, strategists, motivators, innovators, organizers, what have you. And these CEOs talk about their strategies in which the container that they're, I guess labeled in as being most effective. And so there's a lot of really good strategies in there. There was one called, a group called Startup Titans. And when we were going to implement blended learning for the first time, I wanted to hear some of the strategies of deployment from CEOs that startup companies because it was so brand new in our district. So that for me was a really, really good book. I'll warn you, if it says 1000 anything, that means it's going to be a thick book because there's a lot of pages in it. But it could be a resource. You could look at a table of contents like I did and said, "Hey, we're going to start blended learning in Temple ISD, which container would make the most sense?" Well, innovator container would make sense, a visionary one, and maybe startup titans. So I would go and read some of the CEOs strategies in those areas and then try to formulate my thoughts around deployment and so forth. So that's a book that I read and am happy to pass on. Jon Eckert: No, that's super helpful. And I think sometimes in education, we get too caught up in naval gazing, just looking at what we can learn from education. And there's a lot of fields out there that have a lot of wisdom that we can glean. And especially in the role of a superintendent where you're a politician, you're a community organizer, you're a bureaucrat, you're a manager. There's so many different hats you wear, and a human being that finds joy in the good people that you work with and the community that you serve. That's super helpful because the CEO wears many of those hats. And so I think that's great wisdom. Well, hey, Dr. Ott, thank you so much for the time. Thanks for all you do for us at Baylor, for students and staff in Temple, and then for everybody across the state of Texas. We're grateful to have you so close and your willingness to serve educators in this way. So thank you. Bobby Ott: You bet. Thank you. And I wish all the best to Cohort 8. You're entering a great program. And the one thing I would say, I don't know if this is going to them or not, but the one thing I would tell them is a lot of times when you start things like a program, people will start to ponder this idea of journey versus destination kind of thing. Which one's more important? Is it getting the doctorate? Do I try to enjoy it along the way? It's heavy, whatever it may be. And what I would pass on to you is this, anytime you find yourself being asked that question or contemplating it, the answer is neither. It should always be the company. The company is the most important thing. It's not the journey or the destination, it's the company. And so enjoy your professors, enjoy your cohort, get to know the people around you, and that will be the most important thing. And if you do that, I will tell you the journey and the destination will take care of itself. Jon Eckert: Such great advice. And that's true for everybody, not just people starting a doctoral cohort. But appreciate how you live that out, and I'm grateful that you're on the journey with us and you're part of the company that we get to keep. So thanks again. Bobby Ott: You bet. Take care.    

Fadi Micaelian, CEO of Sparkdit, teaches machines to think like humans by understanding trade-offs. AI is not good at finding nuance and capturing trade-offs, which is where Sparkdit comes in. They have developed a technology that can teach computers to make trade-offs like humans and put humans at the center of the technology rather than replacing them. Incorporating AI into patient-centered decision formats can revolutionize healthcare, improve the way doctors interact with patients, and address issues like ageism, sexism, and racism. Fadi explains, "We have been working in AI for years. And AI is magnificent when the data is in abundance. However, we felt that AI fell short in a series of areas, and the main one is to teach machines to think like humans. Because AI, at the end of the day, does not think like humans. AI thinks like neurons. But we humans think very differently. Our thinking is universal. Whether you are an Eskimo, or you are in Paris, or you are in Russia, or whether you're in South Africa, we all think the same way. The way we think is by trade-offs, and AI does not understand trade-offs. So we set our mission to teach machines to think like humans, by trade-offs."  "To do that, we needed to create a platform, and that platform was based on trade-offs. It was based on the way we think. We're trying to mimic the way humans think, and that's doing trade-off. How do we think? When we have a decision to make, we take a set of criteria into account. Then, we apply to each criterion a certain logic - how we think about that criterion. Then we overlay that with a set of trade-offs that says really what is the relative importance of the criteria, which ones are important, and which ones are not." #Sparkdit #AI #AppliedAI #AIinHealthcare #TrainingAI Sparkdit.com Download the transcript here

Fadi Micaelian, CEO of Sparkdit, teaches machines to think like humans by understanding trade-offs. AI is not good at finding nuance and capturing trade-offs, which is where Sparkdit comes in. They have developed a technology that can teach computers to make trade-offs like humans and put humans at the center of the technology rather than replacing them. Incorporating AI into patient-centered decision formats can revolutionize healthcare, improve the way doctors interact with patients, and address issues like ageism, sexism, and racism. Fadi explains, "We have been working in AI for years. And AI is magnificent when the data is in abundance. However, we felt that AI fell short in a series of areas, and the main one is to teach machines to think like humans. Because AI, at the end of the day, does not think like humans. AI thinks like neurons. But we humans think very differently. Our thinking is universal. Whether you are an Eskimo, or you are in Paris, or you are in Russia, or whether you're in South Africa, we all think the same way. The way we think is by trade-offs, and AI does not understand trade-offs. So we set our mission to teach machines to think like humans, by trade-offs."  "To do that, we needed to create a platform, and that platform was based on trade-offs. It was based on the way we think. We're trying to mimic the way humans think, and that's doing trade-off. How do we think? When we have a decision to make, we take a set of criteria into account. Then, we apply to each criterion a certain logic - how we think about that criterion. Then we overlay that with a set of trade-offs that says really what is the relative importance of the criteria, which ones are important, and which ones are not." #Sparkdit #AI #AppliedAI #AIinHealthcare #TrainingAI Sparkdit.com Listen to the podcast here

Google is changing the way its search feature works, feeding users AI-generated replies to their questions rather than directing them to other websites. Read more:At its annual developer conference this week, tech giant Google is expected to tout big changes to its signature product, search. Instead of directing users to a list of websites or showing them an excerpt, Google's AI will craft paragraphs of text that tries to answer users' questions directly. AI reporter Gerrit De Vynck says the change could have huge consequences for the internet. Because AI chatbots are still unreliable, and because the information feeding the generative answers comes from a range of sources, users will need to watch out for false information. And the new format means that sources across the web – bloggers, businesses, newspapers and other publishers – are likely to see a huge loss of traffic.Gerrit joins us to break down what the changes to Google search mean for users, and why the company is moving in this direction.Today's show was produced by Emma Talkoff. It was edited by Lucy Perkins and mixed by Sean Carter. Thanks also to Heather Kelly. Also on the show: The Climate Solutions team at the Post has an eye-opening story about the benefits of leaving your lawn unmowed and letting nature do its thing. Read it here.Subscribe to The Washington Post here.

In this podcast episode, host Jon interviews two guests from Australia, Darren Iselin and his daughter Beck, about the concept of wellbeing in schools. Beck, a teacher, discusses the increase in mental health issues among her students, such as anxiety and depression, as well as the rise in neurodivergent behaviors. She also shares her observations about the impact of the COVID-19 pandemic on student wellbeing. The conversation highlights the importance of relationships, trust, and cultural norms in fostering student wellbeing and flourishing. They conclude by expressing their hopes for the future of education, including a focus on connection and a joyful hope for student flourishing. To learn more, order Jon's book, Just Teaching: Feedback, Engagement, and Well-Being for Each Student.   The Just Schools Podcast is brought to you by the Baylor Center for School Leadership. Each week, we'll talk to catalytic educators who are doing amazing work.   Be encouraged.   Mentioned: Flourishing Together by Lynn Swaner and Andy Wolfe Novice Advantage by Jon Eckert Connect with us: Baylor MA in School Leadership Baylor Doctorate in Education Jon Eckert: @eckertjon Center for School Leadership at Baylor University: @baylorcsl   Jon: Welcome back to Just Schools. Today we have two guests in from Australia. Darren Iselin is one of our only ever repeat people on this podcast, he was so good the first time we brought him back again. And this time he's also brought his daughter Beck. Beck is in her sixth year of teaching year four in Australia. And so today we are going to have a conversation where we make a case against wellbeing. So if you aren't intrigued already, hopefully you will be after we start to hear from some of our friends here. So let's start with Beck. So Beck, you're in your sixth year. So you've been teaching a little bit before Covid hit and then you've had almost half your time before and after Covid. How would you describe the wellbeing of your students in Australia now? And then we'll dig into why maybe that wellbeing is not the right term for our kids. Beck: Yeah, absolutely. Within my classroom context, in any given year post Covid, I generally have around 10 kids diagnosed anxiety. I've seen depression as well in addition to then neurodivergent behaviors, seeing a massive increase. Jon: Neuro divergent. I love the terms used. I mean five years ago, we never heard that but all right, so continue with neurodivergent. Sorry to interrupt. Beck: So that's an increase in that, in addition to what I was already seeing. I think there's been a lot of children coming in just not at their, we talk about battery packs and they're coming into that school day and their battery pack is just completely drained at the start of the school day. And I think Covid times are really interesting for me. I was still teaching grade one back then and in Australia we only had remote learning for a short time. But for my students, the students who attended school, their wellbeing if you want to call it that I guess, they just seemed happier and settled and then the students who were learning at home seemed the same. And so then coming back from Covid was really hard because the students at school that had had so much more attention had had a different school day, they then struggled with having everyone back together and then the students who were at home who had had Mom and Dad doting on them for the whole day and only having to do some hours. Jon: I want to be in that house. I don't think our kids felt like they were doted on our house. Beck: I know sitting in Mom and Dad's office chair, we saw Ugg boots with the school uniforms, so then they loved that time. And so what I found really interesting was the coming back to I guess what we had considered normal school. And I feel like we've kind of been struggling to still come back after that, if that makes sense. Jon: Yes. Well in the US some schools were out for long periods of time, so there's significant learning loss that's happened and they're not able to figure out ways to minimize that impact and then accelerate forward on top of all the shifts in the way kids have gone through schooling over the last four years. Darren, we had a conversation with a renowned education scholar and in that conversation we were talking about wellbeing and flourishing and some of the issues that Beck just alluded to because we're seeing that in college students, we're seeing in grad students, we're seeing it in K through 12 students for sure. He mentioned that he did not like the term wellbeing and he didn't like the term flourishing. From what you recall of that conversation, what was his beef with those two terms? To me those have been some of the most ubiquitous terms in schools and who's against wellbeing? And here I'm saying we're making a case against it. What was his problem with those terms? Darren: Yeah, I think it comes out of a sense that the way that we are orientating the whole educational process has become highly individualized, highly about the self, the atomized version of who we are, and we've lost sight of, I guess a larger understanding of community and understanding of relationship and understanding of how we do this educative process together as opposed to siloed and isolated. And I think his main concern was around that the notion of wellbeing has become more and more about an introspective subjective version of what that means as an outcome as opposed to something that is around a collective purpose and meaning making that can be shared in a journey together. Jon: So when you think about Aristotle's view of the purpose of education, it was to lead to a flourishing society, which is an individual component to that, but that also has a communal purpose, it's not just to flourish. That becomes an issue. So I think I agree that was one of his things that he was pushing back against. And then I felt like he was also pushing against the idea that if kids believe that when they go to school their wellbeing is going to be attended to, and educators see wellbeing as the end, that communicates to them a freedom from struggle. And in fact, in his view, and also I think in our shared view, education is struggle. It's not freedom from struggle, it's freedom to struggle well. So I know Beck, you were just in US schools, you were visiting and then you have your school context, and again, you just got to drop in on a US school. But do see kids struggling well in schools, do you think they think of wellbeing and flourishing including struggle? Is that something that your students in Australia... Or my perception is in the US that's not something that's expected as a part of wellbeing and that wellbeing is freedom from it. What do you see? Beck: I love that because I think some teachers can be so quick to put up the poster, the growth mindset poster of the struggle is healthy. And you might see it in a room in that sense physically, but I like to talk about it almost like this sense of accomplishment. And so at one point a school that I was in had a model where if students experienced struggle, the classroom was then no longer a safe space. And it was like, okay, we need to remove them from the struggle. We don't really know what we'll do with them at that point. We might have calm down strategies, we might do all sorts of things, but then what was happening was that these students never got to experience the sense of accomplishment that came from doing a task that they thought they couldn't do and then actually succeeding in that. And I've even heard students say to me like, "Oh, I had no idea I was able to do that," or "Oh, that was actually really fun." Or to the point where I had one student discover just a love of reading, had never wanted to touch a book or pick up a book before that. And then just with that I guess a sense of going, you can do it and being careful with the language that I used around her, she's now the student that literally walks around with her head in a book and that's just unlocked a whole new world for her as well. And so I think I'm cautious to never rob my students of that and to embrace that struggle. Jon: I love the idea of not robbing your students of it. And you mentioned in a conversation we had earlier about the space in a classroom you can go if you feel like you need a time to take a break and you just need to disengage and then not participate. And obviously there are times when kids are unregulated and they just need a space to calm down and that's real, but it becomes a crutch. And so then you've taken away the chance for a kid to struggle well. So how do you balance that? The kid who needs some time to regulate versus the kid who needs to be stretched, the cognitive endurance needs to be challenged, the push has to be there. How have you figured out how to balance that? I know you've figured out all the answers because in your sixth year of teaching, so how do you do that? Beck: I think I couldn't not mention relationship. So much comes down to the trust that is built. But I guess if I could say practically aside from that, I have had spaces like that in my classroom. In my grade one classroom we had the cool down couch. Jon: I want to go to the cool down couch. Beck: It was great. It was this bright green vinyl. I had kids asleep on that thing. It was great. But one thing I loved was having a space, I've seen tents, I've seen all sorts of things, having a space where the student was still in close proximity to their peers. They were still part of our discussions, but they just perhaps weren't sitting at their desk in a scratchy chair. Maybe it was a little bit quieter where they were, but there was always a sense of I feel that it's best for you to be in this room. We want you here. This is community, this is belonging. And what pathway is built if when they begin to struggle, I send them out. And so yeah, I guess what I saw then was children who maybe don't look like they're listening the way that we might expect. I've heard crisscross applesauce. That's a big thing here. Jon: Yes, it's a big thing here. Yes. Beck: Yeah. But then still being able to engage in discussion just might not look the way that I expect it to look. Jon: No, that's good. So Darren, when you look up the word flourish, so we've picked on wellbeing for a little bit, and again, I want to make it clear we're all for wellbeing. We know you can't do any of the work that we do in schools without wellbeing. But if we're communicating to kids that the definition of wellbeing or flourishing, if you look up in Merriam Webster's, the dictionary, it says flourish means to grow luxuriantly. I don't think anyone would read that and think, oh, that means I need to struggle. And so how do we as leaders of schools and catalysts for other school leaders, how do we help our educators communicate to students what it means to struggle well? Especially as Christians because I think we have a better view of what it means to flourish as human beings knowing that we're made in the image of God. So how do we do that? Have you had any success in Australia doing this? Do you have any hope for us? Darren: Look, I think there is hope, and I think it's very much around how we're framing that conversation, John. To talk about this notion of flourishing as though it's the removal of all of those mechanisms that will imply risk, that will imply struggle, that will imply a wrestling through actually goes against the very grain of what we're really after with genuine wellbeing and genuine flourishing which we want in our school communities. I think something that comes back to our training as educators is always around that Vygotskian term around the zone of proximal development. And of course what we can do together can be exponentially better than what we can do on our own. And I think that notion of proximal development, we could apply to very different frames. We can do that pedagogically, what that pedagogical zone of proximal development looks like. What does relational proximal development look like? Going back to Beck's couch and the safe spaces that we create within our classrooms, what does cultural proximal development look like? Where we're actually together working on solutions that will expand and what we end up with through struggle, through risk, through uncertainty is actually better rounded and better formed students, better formed teachers, better formed communities within our schools. Jon: I love that ZPD applied to relational development. So my question then for Beck is you're now in that sweet spot I feel like in the teaching profession. The first year you're just trying to figure it out. The second year you're trying to pick up what you muddled through the first year. And by the third year you hit a, if you've gotten to teach the same grade level subject, you kind of like, okay, I get this. And you can look around and see what colleagues do I pull into this? How can I be more intentional about things other than just being survival mode? So your zone of proximal development for relational development as a leader in your classroom and beyond, you have more capacity for that now. So how have you seen your capacity for struggle increase? Because now you have the ability to not constantly be thinking about what am I saying? What am I doing? What's the lesson plan? You have this bandwidth, how have you seen yourself grow in that relational ZPD? Beck: I think there's definitely been, as with probably comes with any job, just an easing into it. And so there is a sense of it just being a lot of second nature and also just coming back every day and just having eyes that would see beyond the behaviors and having eyes that would see beyond maybe the meltdowns and the language used not just from my students but from within the whole school community. I think that obviously with then success and going, oh, I've done this before. I remember when I did this for this student before, this really worked quite well. And it never is the same for two students, but there's definitely a confidence that grows. And whilst I am in my sixth year, I don't feel like I'm in my sixth year. I feel like I have so much more to learn. But I think teaching is just like that. I think that the point where you just say, no, I've learned everything there is to learn, that's a dangerous place to be in. And I think there's so much to learn from our students as well. They teach me so much every day. And one of my greatest joys is when I see them begin to celebrate each other's successes and interact with each other in the same way that I guess I'm trying to create that culture. Darren: And becomes a very cultural dimension, John, where there is that capacity for trust, for engagement, for that sense of that we are in this together. And because we're in it together both within the students but within our classroom, there are these cultural norms that are created that are so powerful. And as someone who, obviously I'm very biased going into my daughter's own classroom, but when I see classrooms that are actually reflecting a culture where that proximal development is taking place culturally, relationally, pedagogically, it really is a transformative space. It's a safe space, but it's not without risk. And so it's not safetyism, as Jonathan Haight would say, it's actually a place where people are entrusted to be able to be who they are, to be real and authentic in that space and allow for that image bearing capacity to find its fullness. Jon: Yeah. So when you say that, I go back to the, obviously we need schools to be safe, we need classrooms to be safe, but I think if we tell kids that they're going to wait until they feel safe to share, marginalized kids will never share. And so in fact, they need to be respectful spaces that celebrate the risk taking what you described about seeing kids and celebrating that. And I think what you also described was gritty optimism. It isn't the naive optimism of a beginner. So my first book I wrote was called The Novice Advantage, and I talk about the shift that happens when you go from naive optimism to gritty optimism where you're optimistic based on things you've seen kids grow and do that you didn't think they could do. And when you can take that from the classroom and make that be a school-wide value, that's when it gets fun. Because when we say struggle, nobody wants to struggle. I don't want to struggle. I know sanctification is a process of being stretched. I want to be stretched without having been stretched. I don't want to go through the process of it. I want the benefit of it on the back end. And so I think what I want to see as a profession or people like you Beck and you Darren, leading other educators in this struggle where we celebrate the growth that we see, when we do more than we thought we can do and that it be fun. I don't think that the way I'm conceiving of wellbeing, that includes freedom to struggle well as being something that's onerous and compliance driven. I see it as something that, no, I could do this in August. I can do this now in December. Beck, I could do this as a first year teacher. I can do this now in my sixth year and I can point to how I've grown. So if you were to think back over the six years, how are you fundamentally different as a teacher because of some of the hard things that you've gone through in your first six years? Beck: I think to throw another buzzword in, I would say resilient. Darren: Oh yes. Jon: Yes. Beck: I think there's been so many micro moments. It's very hard to pinpoint and say this class or this child or this parent or this moment, but it's just the micro moments every day. Teachers make thousands upon thousands of decisions daily. And I think there's almost a sense of empowerment in going, when I speak from my own successes, I then can call that out in someone else. I think every teacher starts their career one of two ways, very bright-eyed. I was like, I've got the rainbow- Jon: Idealistic. Beck: ... rainbow decor, I've got the cool down couch, everything's alliterated. And I think I was very blessed to actually have taught the two cohorts that I taught in first grade again in fourth grade. And that was very significant for me because one, I got to enjoy all of the great things I saw in grade one, but they was so much more independent. But also it was in some ways a second chance to go, Hey, that thing that I really didn't do well when I was fumbling around in grade one, let's do that again and let's do it together. You know that I was there and I know that I was there, but we're both on this journey together. And that then created stronger community and this sense of identity to the point where I had one of my students create a hashtag on Cecil, which is a platform that students can upload to. And one of the photos he goes, hashtag 4B for life. And I was like, "What did you mean, Luke? What is this?" And he was like, "Oh, it just means we've got each other's backs," and all these things that, I mean, I could have put signs up and said, we're a family and we have this and these are our class rules and whatever. But I would much rather that come from their mouth and just knowing that they felt it was safe, I didn't have to prove that something... I didn't have to prove that I was a safe person. I didn't have to prove that my classroom was a safe space. It just became that. And yeah, looking back, I think it just makes me more excited, I think for the years ahead. Jon: Well, they owned the culture. It wasn't you forcing the culture. They owned it and you have the evidence of it. So Darren, you've been in education a little bit longer than Beck. Darren: Just one or two more years. Jon: How do you see your growth or the growth of educators like Beck? Where are you encouraged by growth that you've seen in yourself or growth just in the profession and what you've seen in Australia or you've been all over the world seeing this, where do you see optimism for this growth? Darren: I think the optimism comes John, when you see the capacity for that transformative interaction between student and teacher. That sacred moment on day one, which for many of our schools in Australia are going back within one or two weeks for that day one. And we start afresh. We start afresh with the newness of a new year, a new class, new minds, new hearts, new relationships to engage with and to see the transformative impact that that has. And year after year, we come back to that core element of what it means to actually be about this ancient task of teaching. To be able to engage this space well through struggle, yes, through risk, through uncertainty, through all the things that will be thrown at us in this year. And yet there is something about being a part of a community, a network, a culture that is established within a classroom that truly is a microcosm of what that school should look like right through as you talked about those norms and values that flow, and then indeed what a wider community would look like. And that notion of flourishing of what shalom might look like in its holistic sense, I think is the responsibility that every teacher has. And I get excited at this time of the year, this beginning phase that every teacher goes in, whether they've been teaching for 30 years or this is their first year of teaching, when they stand before that class for the first day, that first hour when they're establishing those norms, those expectations, we are filled with hope. We are filled with expectation, we are filled that we want to be part of 4B forever- Jon: That's right. Darren: ... because of what we are endeavoring to achieve here with purpose and meaning and something that goes far beyond just a transactional arrangement. Jon: I mean, teaching is one of the most human things we do and it's what keeps us coming back to it. And I'm excited about the tools that are out there from AI to ChatGPT to whatever, but anything that takes the human out of it is a problem. And so in just teaching, I define wellbeing as purpose-driven, flourishing, and then feedback is purpose-driven wisdom for growth. There's this huge component. And that only comes from humans. Because AI is consensus, it's scraping whatever the web has said on a certain topic and says, Hey, here's what consensus is. That's not wisdom. And so we gain wisdom from struggle. We're much more able to help and have empathy for people once we've been through something hard. We become much less judgmental. And I think that's grounded in two Corinthians four, seven through 10. And I think as educators we get to live that out all the time. And so I was sharing with you before we jumped on, I memorized these verses as a kid, but I didn't memorize verse 10, which is the most important one. So if you remember Paul's writing to the Corinthians and they were known for pottery that would be cracked and you could put a light in it and the light would shine through it. So it makes this passage even more powerful. And it comes from our friend Lynn Swaner and Andy Wolfe's book Flourishing Together. And they use this as their paradigm for what this means. And it's super encouraging in this way. But we have this treasure in jars of clay to show that the all surpassing power is from God, not from us. We're hard-pressed on every side but not crushed, perplexed but not in despair, persecuted but not abandoned, struck down but not destroyed. So those are the ones that are there and those are daunting if you put in educators instead of we. Educators are hard-pressed on every side. Darren: Sums up our profession. Jon: It's felt like that, right? But that gives us the opportunity to show Christ. And so that's where verse 10 comes in. We always carry around in our bodies the death of Jesus so that the life of Jesus may also may be revealed in our bodies. So our creator had to come, suffer, die and we carry that around so that we can then reflect his glory to others because he's at work in us. So as we do this work, that's the hope, that's the joy. Darren: Absolutely. Jon: Right. And so we're going to wrap up our time with a lightning round. And so I always like to ask, I have five or six kind of go-to questions here. And so I'm curious and feel free to build on anything that we've talked about so far, but this is a word, phrase or sentence. I'm terrible at this. I always would go too long if I were asked this. But if you were to think back on this past year and what we've just talked about, what real wellbeing is, really that's what we're talking about. What is real wellbeing? What's one word that sums up for you how you've approached your own wellbeing in this past year? What would be a word that comes into mind? And in this one, I really do want the first word that pops in your head. Beck: Fulfillment for me. Jon: Great word, Beck. That was quick. She's younger than we are. Her mind works faster. So Darren, go for it. Darren: I'll tell you something quite random, gaming. Now I'm not a gamer, but I love games and Beck shares that passion. We often don't get to play them as much as we should, but we have room full of games that we can pick at any given time. But there is something that is dynamic about gaming. There's something about when you enter into play into that space of actually struggle, of risk, of uncertainty, of joy. And I think in all of that, that to me has been something that has really resonated with me as I've looked at this whole notion of wellbeing is we need to play more, we need to have more fun, John. We get to far too serious about too many things. Jon: That's right. Darren's a lightning round guy like I am. Beck had literally one word. Beck: I'm obedient. Follow the instructions. Jon: So I wasn't planning to ask this one, but in the last year, what has been your favorite game that you have played? One of your top five? Beck: I have to say Ticket to Ride for me. Jon: Oh, I love Ticket to Ride. Beck: And all the expansion packs. Jon: I've not done the expansion packs. All right. Ticket to Ride. Great. Darren: We just love our trivial games. So anything that's got trivia in it. And there are some really awful games of that, there are some really fantastic games that we play with that. Beck: Lots of eighties trivia. Darren: Lots of eighties and nineties trivia. Just to boost the points for- Beck: That's not my sweet spot. Darren: ... Mom and Dad. Jon: Yes. Well my kids love the Harry Potter Trivial Pursuit because I sit and listen to them and I am both proud and cringing that they know Harry Potter that well. Darren: My children are like that with Lord of the Rings and Star Wars. Beck: Or any sport. Jon: Oh well that's okay. Sport is all clear. All good. Okay. So what's the best book you've read in the last year? And it doesn't have to be education related, but it could be. Beck: Mine is a Hinds' Feet on High Places by Hannah Hurnard. Jon: Okay. Beck: Yeah. Fantastic book. It's an allegory, follows the story of a character called Much Afraid, who is on her way to the high places and has to walk in the hinds' feet of the shepherd leading her. Powerful. Jon: That sounds powerful. All right, Darren? Darren: Mine was a book by Andy Crouch called The Life We're Looking For, really about reclaiming relationships in a technological age. And I just found that such a riveting read. I read it almost in one sitting. It was that engaging. Jon: Wow. I love Andy Crouch. That's great. So two great recommendations there. All right. Worst piece of advice you've ever received as an educator? Either one of you. Beck: As an educator, that's tricky. Jon: Or you can just go, worst piece of advice that could be fun too. Darren: Well, the classic that is often rolled out is don't smile till Easter, right. Now it might have a different terminology in the US . Jon: It's Thanksgiving. Don't smile till Thanksgiving. Darren: From my day one of teaching John, I refused to even go to that space. It was just so against everything that I believed as far as the relational heart of teaching. Jon: That's great. Beck: I would've said the same. Non-educator worst advice, just add caramel syrup to American coffee and it tastes better. That's terrible advice. Nothing will save it. Jon: Nothing will save American coffee. Hey, it's a struggle. It's part of the struggle. There you go. It's not contributing to your wellbeing. Darren: The joy in the journey. Jon: That's good. All right. So I will say about 70% of the people on this give the worst piece of advice that they've ever received that don't smile till the thing. And so we get that every time. Beck: Original. Jon: It's so sad that- Darren: Tragic. Jon: ...that is so pervasive. Best piece of advice you've ever received? And this could be in general or as an educator. Darren: I will go with education again, John, that at the heart of education is the education of the heart. And so just keep it real and keep it relational. And it's all about relationships. Beck: As an educator, best advice I've received, I don't know if you could call it advice, but the quote "The kids who need love the most are the hardest to love." That's my favorite. Jon: That's good. Last question, last word for the listeners. What do you hope in the years ahead as an educator will best define what it means to flourish as a student? So word, phrase, or sentence. What would flourishing really look like for a kid moving forward? Beck: I would say a word, connection. And I would love to see Maslow's Hierarchy of Needs starting at the bottom not always at the top in our classrooms. Jon: Love it. Darren: Yeah. I think for me the word that constantly comes to mind is joyful hope, is a joyful hope in what we do, that what we've been entrusted with every year within our classrooms. That there's a joyful hope that awaits. Jon: Well, thank you for being with us today. It's been a huge blessing for me.  

I had a journalism student approach me a while back for a story. I asked him, “what kind of a journalist do you want to be when you grow up?” He said, “A food writer. Because AI won't take my job.”  Won't it though? I suppose if they create a neural simulation of what it's like to eat boudin, they could. But the panic around AI is big; mostly because few people really understand it. The models making headlines, like ChatGPT, are really only the latest in a long line of advances in technologies designed to assist work - that is make it easier on people. Most companies still rely on people. And they need people to be good at what they do. AI can make work more efficient, but it can also help companies select and train their employees.  That's the concept behind iCan, a company founded by David DeCuir. David spent years in the oil and gas industry and noticed that workforce development was a big problem. His company employed lots of people, but they struggled to make sure they all knew what they were doing.  So he developed a new training program for his employer and cut $2.5 million off their annual bottom line.  Saving money is making money in business, so David struck out on his own. And iCan was born. iCan's cloud-based software helps companies set up custom platforms that use chatbots to train employees on anything from HR guidelines to procedures.  Since launching fulltime in 2022, iCan has expanded from the energy industry to work with utilities and processing facilities. David grew up in Lafayette and currently lives in the Geismar/Dutchtown area. Helping companies get better is a massive industry. We generally call them consultants. And their product lines can range from expert assistance to IT.  If you're in Lafayette, you've heard of CGI. And you probably think of it as a tech company.  But it's better understood as a consulting firm, and it's one of the largest in the world.  Will LaBar is VP of consulting service for CGI and worked for the company out of Lafayette since 2000.  Will was CGI employee number one in the Lafayette market. CGI employs hundreds in the area.  Will is in charge of CGI's onshore delivery program. He leads a team that helps smaller markets get technology jobs, coordinating between local governments, business sectors and universities.  Will grew up in New Jersey and has worked for CGI since 1998. Out to Lunch Acadiana was recorded live over lunch at Tsunami Sushi in downtown Lafayette. You can find photos from this show at itsacadiana.com.See omnystudio.com/listener for privacy information.

ContentsEditorial: When is a Bubble not a Bubble?Essays of the WeekThe great rewiring: is social media really behind an epidemic of teenage mental illness?The Day the Music LiedWeapons of Mass ProductionChina's future economyThis Message Will Self-Destruct in 33 Seconds1 in 6 People Will Be Aged 65+ by 2050Venture Investing This WeekGlobal Venture Funding In Q1 2024 Shows Startup Investors Remain CautiousFirst Cut - State of Private Markets: Q4 2023The Investments Where I'm Going to Lose All My MoneyQuant VC and What it Means for Startup InvestingVideo of the WeekNew Apple Vision Pro PersonasAI of the WeekMeet the YC Winter 2024 BatchThe 18 most interesting startups from YC's Demo Day show we're in an AI bubbleYCombinator's AI boom is still going strong (W24)Bubble TroubleBig Tech companies form new consortium to allay fears of AI job takeoversNews Of the WeekApple Vision Pro's Persona feature gets collaborativeJon Stewart Plunges the Knife into AppleStartup of the WeekRubrik's IPO filing hints at thawing public markets for tech companiesX of the WeekMike Maples on Y CombinatorEditorialI've taken to writing this on Friday morning. I put the curated content together Thursday evening, which gives me overnight to reflect. Usually, the title comes first and is somehow correlated to the content below.This week, there is a lot about AI. The Y Combinator story in AI of the week is the story that the “bubble” will be challenged due to a lack of training data. In contrast, the story is that AI will remove so many jobs that the larger companies have formed a consortium to allay fears.I also created a new section separating out Venture Capital. This is the week of quarterly updates from Q1. They suggest there is no bubble at all. Only Amazon's multi-billion dollar investment in Anthropic stands out.But for me, the question posed in the title is - When is a Bubble not a Bubble? - is not triggered by the AI stories. The Economist's Simon Cox writes about China and its future in a newsletter and the linked article. He frames it well:In 2006, for example, China's leaders declared the need to “rely more than ever on scientific and technological progress and innovation to drive a qualitative leap in productivity”. Science and technology, they added, are “the concentrated embodiment…of advanced productive forces”. That ambition, and indeed that diction, sound very similar to the slogans emanating from Beijing today. Xi Jinping, China's leader, has, for example, urged provincial governments to cultivate “new productive forces”, based on science and technology. In this week's issue I explore what those words might mean.As Simon points out, “productive forces” is a formulation derived from Hegel and Marx. It combines technology and human beings into a duality that expresses how we produce things. Indeed, there is no pure “technology” separate from human beings and the division of labor. Productivity is the expression of both and the measurable thing.In the Western enlightenment tradition, we use the word progress to mean the same thing.All progress requires humans to invent time-saving methods to reduce the effort involved in making and doing things.China's discussion (especially if you remove the word China) is about building the future through innovation. It stands in contrast to the dominant discussions here in the US - Regulation, the dangers of Social Media, Immigration, Women's Right to Choose, Guns, and even Climate. And a lot of pessimism around technology and science.That is except for in the startup ecosystem. The dominant Silicon Valley belief system is similar to Simon Cox's description of China's goals.Accelerated Innovation dominates the set of assumptions in the Bay Area. Why? Because AI, Nuclear Fusion, Decentralized Networks, Global Ambition, and the skills and money they require all live here. And their potential is real. And the timing of the potential is near-term (several years).Strangely, the US Government seems to consider innovation, especially “Big Tech,” a problem. China and Silicon Valley seem to consider it a solution. And by “Silicon Valley,” I do not only mean geographically but also as a way of thinking.That bifurcation of optimism and pessimism, enshrined in a Government that wants to restrict tech company power, has led many in the Valley to abandon traditional two-party politics and increasingly articulate agendas that are both optimistic and independent of Government. Government is perceived as a cost of doing business, not a benefit.So, the innovation that comes out of Silicon Valley and the money it attracts are often scorned by those who are not part of it. The word “Bubble” is heavily laden and used to imply that there is nothing valid, real, or transformational. The money is simply irrational.“Bubble” is a pessimists word for “fake”.It goes alongside other narratives that cast doubt on innovation. In some ways, Tomasz Tunguz's piece on the shrinking attention span implies a problem caused by the abundance of content and limited time to read it. Although one might consider the ability to parse information and determine whether it is attention-worthy and do it quickly would be a good thing.The idea that teens commit suicide and get depressed due to alienating social media comes to mind as another anti-technology narrative. The first ‘Essay of the Week' from Nature magazine presents a strong case that this is bogus.Rex Woodbury's “Weapons of Mass Production” and Michael Spencer and Chris Dalla Riva's “AI and the Future of Music Production and Creation” (The Day the Music Lied) point to the explosion of production and creative production that AI will trigger.Rex:Spotify reinvented music distribution. It put 100 million songs in your pocket. Generative AI will reinvent music production. There are a number of early-stage startups that let you toggle artist, genre, and ~vibe~ to create a wholly new work—e.g., “Create a Miley Cyrus breakup song with a sad, wistful feeling to it.” Of course, these companies will need to navigate the labyrinth of music rights, but some version of these tools feels inevitable.This example embodies a broader shift we're seeing from distribution ➡️ production.Michael Spencer and Chris Dalla Riva:In summary, the music industry will likely come to embrace much of this technology as long as AI firms properly license the music catalogs necessary to train their models. This still begs one final question: Is any of this good for music?It's important to unpack words like Bubble. They live in a context. As Simon Cox discusses, the future depends on progress, innovation, or “productive forces.” So, this “Bubble” is not a bubble. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.thatwastheweek.com/subscribe

I must say at the outset that my time with Glenn Gow on this episode was incredibly enjoyable and I hope you find it the same. I love to learn as I have said to you many times and today I learned a lot. Glenn hails from Florida. He obtained colleges degrees in business and then spent much time in marketing and even some in sales. He worked with many large companies and especially with their CEOs. A few years ago he decided to help C suite level people by becoming a CEO coach where he could impart the many of years of experience he gained in the technology world. Glenn is absolutely a visionary in many ways. He and I talk a great deal about AI. I love Glenn's observations as he explains that AI is a tool, not a threat. Listen in and hear his reasoning. About the Guest: Glenn Gow is a CEO Coach, a Keynote Speaker on AI, and a Board Member The implications of AI for every single business are shocking. We're all rethinking how we work, and how we can transform our offerings with the power of AI. It's incredibly exciting, and a little terrifying on how to keep up. Glenn Gow is a CEO Coach, a Keynote Speaker on AI, and a Board Member. Glenn understands exactly what we, as leaders, need to harness this technology. Glenn will be helping us understand the implications for business, and how to harness this technology. You will walk away with an arsenal of information. Glenn is a sought-after speaker on AI and has spoken at The Wall Street Journal AI Conference, the National Association of Corporate Directors, MIT/Stanford Venture Lab, Harvard Business School, The Private Directors Association, Silicon Valley Directors Exchange, Financial Executives Networking Group, The Entrepreneur's Organization, and the Northern California Venture Capital Association. He writes an AI column for Forbes and has been published in Directors & Boards, Directorship (NACD), CIO Magazine, Inc. Magazine, and InfoWorld. As a CEO for 25 years, he advised numerous leading tech companies including Apple, Google, Facebook, Microsoft, and many more. Speaker Reel: https://bit.ly/SpeakerGlenn Ways to connect with Glenn: LinksWebsite: https://www.glenngow.com Linkedin: https://www.linkedin.com/in/glenngow About the Host: Michael Hingson is a New York Times best-selling author, international lecturer, and Chief Vision Officer for accessiBe. Michael, blind since birth, survived the 9/11 attacks with the help of his guide dog Roselle. This story is the subject of his best-selling book, Thunder Dog. Michael gives over 100 presentations around the world each year speaking to influential groups such as Exxon Mobile, AT&T, Federal Express, Scripps College, Rutgers University, Children's Hospital, and the American Red Cross just to name a few. He is Ambassador for the National Braille Literacy Campaign for the National Federation of the Blind and also serves as Ambassador for the American Humane Association's 2012 Hero Dog Awards. https://michaelhingson.com https://www.facebook.com/michael.hingson.author.speaker/ https://twitter.com/mhingson https://www.youtube.com/user/mhingson https://www.linkedin.com/in/michaelhingson/ accessiBe Links https://accessibe.com/ https://www.youtube.com/c/accessiBe https://www.linkedin.com/company/accessibe/mycompany/ https://www.facebook.com/accessibe/ Thanks for listening! Thanks so much for listening to our podcast! If you enjoyed this episode and think that others could benefit from listening, please share it using the social media buttons on this page. Do you have some feedback or questions about this episode? Leave a comment in the section below! Subscribe to the podcast If you would like to get automatic updates of new podcast episodes, you can subscribe to the podcast on Apple Podcasts or Stitcher. You can also subscribe in your favorite podcast app. Leave us an Apple Podcasts review Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts, which exposes our show to more awesome listeners like you. If you have a minute, please leave an honest review on Apple Podcasts. Transcription Notes Michael Hingson ** 00:00 Access Cast and accessiBe Initiative presents Unstoppable Mindset. The podcast where inclusion, diversity and the unexpected meet. Hi, I'm Michael Hingson, Chief Vision Officer for accessiBe and the author of the number one New York Times bestselling book, Thunder dog, the story of a blind man, his guide dog and the triumph of trust. Thanks for joining me on my podcast as we explore our own blinding fears of inclusion unacceptance and our resistance to change. We will discover the idea that no matter the situation, or the people we encounter, our own fears, and prejudices often are our strongest barriers to moving forward. The unstoppable mindset podcast is sponsored by accessiBe, that's a c c e s s i capital B e. Visit www.accessibe.com to learn how you can make your website accessible for persons with disabilities. And to help make the internet fully inclusive by the year 2025. Glad you dropped by we're happy to meet you and to have you here with us.   Michael Hingson ** 01:21 Well, hi there and welcome to another episode of unstoppable mindset. I am your host, Mike Hingson. And our guest today is Glenn Gow. And Glenn is a very knowledgeable soul regarding artificial intelligence. He is a board member he speaks on AI he is a coach. And I don't know what else and when he first joined this afternoon, I pulled an old joke that maybe a lot of you wouldn't know. We used to on television, watch commercials for Memorex tape, which was really good stuff. And when he came on, I said, the question we got to ask is, are we live? Or are we Memorex? Because that's a, a thing that Memorex did. And their point was, you couldn't tell the difference. I never bought that, though, because I could tell the difference. But the Max was pretty good, wasn't   Glenn Gow ** 02:11 it? It was, it was pretty good.   Michael Hingson ** 02:14 I actually still have some blank Memorex cassettes. So Oh, there you go. You're a collector. So Glenn, welcome to unstoppable mindset. We're really glad you're here. Really happy   Glenn Gow ** 02:25 to be here, Michael. And thank you for the introduction. And I'm looking forward to the conversation.   Michael Hingson ** 02:30 And also Glenn is a board member will have to find out about that along the way as well. And that's board is in being on a board not being board. But you know what? So tell us a little about the the early Glenn growing up and all that sort of stuff?   Glenn Gow ** 02:45 Well, I grew up in a wonderful family that supported learning, Michael. And so everything we did was about becoming a little bit better than the way we were, whether it was being happier in life or being more productive or making better friends. And we were always thinking about how can we just be a little bit better. And the wonderful thing about that, is that turns you into a learning machine on any topic. So whether I'm coaching my CEOs, or I'm studying AI, I'm very, very interested in learning and becoming better. And so it's something that I learned at a very early age and it's become part of who I am.   Michael Hingson ** 03:31 Did you grow up in California? I grew up in Florida and Florida. Okay. Laura   Glenn Gow ** 03:39 eventually went to business school at Harvard. And then came out to California. Ah,   Michael Hingson ** 03:46 yeah, as we were talking about earlier, can't beat the weather. No, no. I think the absolute best weather is San Diego but you know, California in general has great weather.   Glenn Gow ** 04:01 I feel very spoiled, spoiled where I am in Northern California right now. So I have no complaints. We   Michael Hingson ** 04:06 lived in Novato for several for 12 years and in an area called Bell marine keys which was a community that was developed in the early 1970s They wanted to make it look like Venice, Italy. So every house is on a lagoon or a channel in between lagoons and either they have docks or their dock ready and it was so nice to be there. That sounds really nice. Yeah, we're far enough away from like highway 101 that you could hear it if you really worked at it at night and it were quiet no wind, but mostly it was just a nice wonderful community and we loved it a lot. Fantastic. So you you grew up in Florida and all that and really devoted your your life to learning so you got a business degree and then where did you go from from Harvard and getting I assume about Bachelor's in business?   Glenn Gow ** 05:02 A master's in business? Okay, yeah. And then the most important part of my history was I worked for a startup immediately after business school, which quickly failed, happens. And then well, that's an important very important learning process. And then lucky enough to work at Oracle when it was a relatively small company. And I worked, I was the first person in the marketing function within sales. In other words, I was doing both sales and marketing. And that was an incredible experience, as the company grew from fairly small to a billion dollars in revenue, which is tiny by, by today's standards, yeah. And then I stepped out to start my own company, where we focused on helping technology companies on marketing strategy. And so we had the opportunity to work with Apple, to work with Facebook, and Google, and Microsoft, and Oracle, and IBM and every large technology company. I did that for 25 years as a CEO. Now, importantly, Michael, during that time, I had a coach for 17 years. This was my co coach. And I knew a lot about business. And my co coach, interestingly enough, didn't really know all that much about business. But she did know something that I didn't know, which was the mind of the CEO, and the mental game, and how to become an even better CEO. So I take all of that experience, having run a company, and having been coach for so long. And I use that every day now. So I was lucky enough to be recruited into venture capital, after I ran the marketing consultancy. And that's when I started coaching CEOs, the CEOs of our portfolio companies, and having been through a startup that had failed before I could truly empathize with the life of CEOs. And then I took all of that coaching and business knowledge. And I found that CEOs really got value out of our conversations. So much so that I fell in love with that. And I've been doing that full time now for three years. Because a lot   Michael Hingson ** 07:28 of them, although they were CEOs, got into it, for whatever reason, but weren't necessarily as knowledgeable as they needed to be about being a CEO.   Glenn Gow ** 07:39 Exactly right. And as long as Michael, as long as they have that mindset, this is how I described it, the mindset is that every great athlete has a coach, and some of them have many coaches. And you ask yourself, Why does someone who's at the top of their game, have a coach, it's because it coach helps them become even better. And if you have that mentality, as a CEO, you are going to improve every day, if you put your mind into that process of improvement, and that's what I'm here to do with my CEOs?   Michael Hingson ** 08:14 And do you still have a coach,   Glenn Gow ** 08:18 I do not currently have a coach, I am looking for a coach. I have advisors. But here's something that's interesting, that you made me think about Michael, is that I coached 20 CEOs. That's about as many as I want to coach. And I learned something from them every time I coach them. Mm hmm. And so I want to share those best practices with my other CEOs. So I feel like even though I don't have a coach working directly with me, not right now. I'm learning every day through my interactions with my CEOs. And I'm able to share that information with all of them on what best practices I just heard about.   Michael Hingson ** 09:03 Yeah. And I would think that the best CEOs are people who, at least in part, adopt a learning mindset, because if you think you know it all, you'll sometime and maybe sometime soon, discover it isn't really that way.   Glenn Gow ** 09:20 Let me give you a statistic that I discovered when I was in venture capital. roughly 60% of CEOs get fired within a five year period in the venture backed world, and you ask yourself, why did they get fired? The simple answer is they're not growing the company fast enough. But then you say, why is the CEO not growing the company fast enough? It's because they are not growing themselves fast enough. In other words, when they became the CEO and the venture capitalists put money into them, they were probably the perfect person for that company at that time at that size. But as the company negros takes on new employees, new customers, new investors, it requires that the CEO have new skill sets, and improve skill sets in order to succeed with this company that's transforming. I call it scaling the CEO. Right? And that's what I do. I help the CEO become even better.   Michael Hingson ** 10:24 And that's an important thing to occur if you're dealing with people who are supposed to be the leaders of companies and the people who are either the visionaries for the company, or somehow promote and create whatever is necessary to create the visioning for the company.   Glenn Gow ** 10:46 That's right. Exactly. Right. Yeah.   Michael Hingson ** 10:49 Yeah. And, you know, I, I have said several times on this podcast that if I'm not learning at least as much as anybody else, listening to this podcast on any given episode, that I'm not doing my job, well, and I have been so value in my mindset of being able to learn from everyone who's been on board, it's in who's come on as guests. It's great. It's a lot of fun. And I get to learn a lot. And I can't complain about that a bit. Well, it's   Glenn Gow ** 11:18 a win win win.   Michael Hingson ** 11:19 It is, as far as I'm concerned, and I enjoy doing it. It's, it's so much fun. Well, so you've you've been doing the coaching process for at least a few years, have you become certified as a coach? Or do you just do it or what?   Glenn Gow ** 11:35 I am not certified, nor am I ever going to get certified. I look at my 17 years of training from my personal coach. As as as the as the experience of learning through that I don't, I don't, gosh, I just feel lucky to have had that experience. And don't feel like there's any value. For me personally, writing certification isn't good. But for me personally, it just doesn't make any sense. Well,   Michael Hingson ** 12:03 and I agree, I've, I've thought about that. Some people have suggested that I should explore doing more in the coaching world. And one of the ways I think that I could add value in the coaching world today is that is we have an aging population and a younger population dealing with an aging population. We don't have any really substantive all around coaches dealing with blindness and low vision, who can guide people so it is it is something that I've been looking at and seriously thinking about happening. I think it would be a fun thing. And I think it would be a valuable thing if we can give good suggestions to people and help them deal with something that we shouldn't have to deal with. But we but we do in the shouldn't have to is that society rose up and learns that blindness is a big, severe, serious problem. And the reality is, it's not blindness, it's people's attitudes about blindness, because people who happen to be blind or low vision, can do the same things other people just we may not do it the same way. And we also tend to make our world because there are a whole lot more sighted people than blind people, we make our world side oriented. But that still doesn't mean that blindness is the problem.   Glenn Gow ** 13:26 That's right. That's right. And that made me think, Michael for a moment about AI and and the current some of the current interfaces with AI. And I think there's an incredible opportunity for people to interact with AI purely on a voice basis. Yeah.   Michael Hingson ** 13:46 Well, and that's true, although we type as well. But the the issue is really the, the having the input that AI gets from wherever it gets and guide it to provide good output and good ways to help. Exactly. Yeah, which is what AI is all about. What got you started in really thinking about and becoming more of a mentor and proponent of AI?   Glenn Gow ** 14:18 Well, first of all, I described myself this way, I'm a I'm an expert in AI at a niche, which is the sea level. So I'm an expert in talking about AI to to CEOs and the board. So I'm not going to talk about the technology. I'm gonna talk about the implications of the technology, right? Started, Michael was one of the great things about working in venture capital is that you can predict the future. You can predict the future because it's walking in the door every day in the guise of entrepreneurs who are telling you all the trends that are coming together and how they're going to take advantage of those trends. And when you see that 20th person walking In the door and talk to you about AI before it's being used anywhere, you can say I see something coming in our direction. And that's when I dove in. And that's when I said, I need to deeply understand the implications of what's happening here. And so I got very, very excited about it. Because, look, we all live through technology innovations. But AI is different from every other technology innovation. And the reason it's different is that it learns. And sometimes it learns all by itself. What does that mean? What does that mean is it means that it creates a flywheel effect. If it starts learning about your customers and your market and your products. And you feed it more data, it gets smarter all by itself. And that flywheel gets spinning and you progress, you gain market share, you gain revenue, you gain more insights. And if your competitors aren't doing that, they're using some other kind of technology. You're gonna leave them in the dust, they will not be able to catch up to you because of that flywheel because it's learning and getting better. Constantly.   Michael Hingson ** 16:16 Yeah, my first exposure to AI goes back to well, it's more learning, but it is still ai 1975 1976 with Dr. Ray Kurzweil, oh, well, and Ray's first development, his first invention was the Kurzweil Reading Machine for the blind. Well, first was Omni font, optical character recognition. And he chose as his first application to make a machine that would be able to scan any, and recognize any type or print or combination, I'm typing print fonts, but one of the things that Ray put into that machine was a learning feature. So the more that the machines scan, when I was reading a book, or anyone was reading a book, or anything that that was in print, the better the recognition was. And it did that all by itself. Amazing. And it was absolutely easy to see that happen over a few pages in a book. So I've been using and accepting the whole concept of machine learning, ever since that day, but of course, in the past several years, we've now seen AI go to incredibly whole new levels. And it's interesting, the the people who who are negative about it, and so on, I'm sitting here thinking, Alright, what, 30 years ago, or maybe 35, now we had the internet, or 30 years ago, we had the internet come along. And along with the internet, of course, there are the people who misuse it, and we have the dark web. And I think somebody should check out more of the dark web and see if it's accessible. And if not, we should sue some of those people. That'd be fun. But we have the dark web, and we don't get anywhere near although some people recognize the the problems with it. We don't get anywhere near the route from any of that, that we're getting from artificial intelligence today, which tells me people are starting to you know, they, they see the significance of it, but you know, we're dealing with a, with a world where people really aren't visiting it properly or visiting it enough?   Glenn Gow ** 18:34 Well, it's hard to predict what we're gonna see. And AI is just a tool, Michael, it didn't was that with any tool. It's going to be used for good and it could be used for bad. And so they're, they're bad people. And if they get hold of a tool, they're going to use that tool. And so we do need to be aware of that we do need to be concerned about that we need to ensure we have protections against that. Yep. Just like any tool. Yep. But the key thing is it's happening way faster than the experts ever predicted. And so what does that mean? That means that we as humans, need to move fast to keep up.   Michael Hingson ** 19:17 And we're dealing with, with a lot of change, and many people aren't used to changing or change happening that quickly. But it's the way it is.   Glenn Gow ** 19:26 Well, not only that, Michael, but most people don't like change.   Michael Hingson ** 19:30 No.   Glenn Gow ** 19:33 And if you don't like change, and change is happening and being part of the change requires you or enables you to be successful, then you're going to be left behind. So my favorite saying is AI is not going to take your job. A person who is using AI is going to take your job.   Michael Hingson ** 19:53 Yeah. And that's and that's something that makes perfect sense. And that's the way it will be but AI is ain't gonna do it. I don't see no matter how much AI learns, and can learn, there are things that people can do or have within them that are makeup that will allow them to continue to function and AI is not going to take over the world. It is not a Colossus The Forbin Project. Right? Right. And that was a good movie and a good book. But   Glenn Gow ** 20:27 the key is for us to ask ourselves, how do we get the most out of this tool. And so I want to share with you a story one of my CEOs shared with me Remember, I talked about sharing best practices from what I learned. So I'm a big proponent of AI, in that it holds tremendous value for companies of all kinds in all industries of all sizes. And so I'm encouraging my CEOs to do more in this area, so that they get a competitive advantage. One of my CEOs stood up at an all hands meeting in the company and said, I'm going to create an AI mandate, starting today. And for the next month, every single employee needs to use AI every day for a month. Now, I don't care what you do with AI, I don't care if what you do doesn't work. What I want is all of us to learn about AI. And so after a month, what I want each of you to do is report to your manager, what did you learn, because we're going to learn about the things that it doesn't do very well. We're going to learn about the things it does extraordinarily well. And then we're going to figure out how to leverage this tool so that we all can be more productive. I thought that was a brilliant way to introduce, because it's okay to fail is what the CEO was saying, and figure out your own experiments. And what came out of that was a whole slew of opportunities that no one imagined that AI could do. So the accounting department figured out, hey, I can write macros in my spreadsheet. Well, that's not what we knew when we when we began this experiment. And yet now we know we can do that.   Michael Hingson ** 22:21 And we can use it and speed up the process.   Glenn Gow ** 22:25 Exactly, exactly. And so many learnings, like that. And now this company is a highly innovative way of thinking about everything, and is going to do extremely well compared to their competitors, because they're embracing this amazing tool.   Michael Hingson ** 22:40 I've used chat GPT to help write some articles. Although I, I generate like five or six versions, and then I put them together, and then I add my own stuff to it. Because AI doesn't guess the saralee get everything well. But, of course, that's the case. But still, it has sped the process up so much. But it goes back to me giving it the right parameters to work with.   Glenn Gow ** 23:11 Exactly. And Michael give you a little tip. So when you think about interacting with a large language model, you want to you want to think about being in a dialogue with it. Not that you give it a prompt and hope for a good result. Right? You You work hard on the prompt, and it comes back with a result and it's okay to say that wasn't very good. Yeah, I think you missed a few major points. And you completely missed that I wanted this to have a perspective on the following. Yeah. It'll say, Gee, Michael, I'm sorry about that. I'm gonna go do another version of it. And so then we're just talking about writing a blog post here, let's say so let's, let's say it comes back with a one. That's it's pretty good now. All right, we'll say hey, that's pretty good. Now, what you can do is you can give it a prompt that lays out Michael Hanson's writing style. Michael likes to write in the following kind of prose, and he likes to use adjectives and active verbs, and he likes to use bullets, and he likes to use speak at a college level, and you can give it your style, so it'll take the output it created for you, and then it'll sound a lot more like Michael. Mm hmm. And then that's a good time to sit back and edit it, because you've already done a lot of the work through the prompting.   Michael Hingson ** 24:39 And it's all happened a lot faster than I would ever do it on my own. Absolutely.   Glenn Gow ** 24:44 Oh, I'll give you one more tip. So I created my style prompt. Right when I want to tell a large language model I want you to write like Glenn Gao. You know how I created this style prompt? Oh, I asked chit chat GPT Ready to do it for me? Here's all my writing. Now go evaluate my writing and tell me how you would describe my style.   Michael Hingson ** 25:12 How do you get bought on whether that's a good question for here, but I'll ask anyway, how do you show it your writing? There, there are aspects of, of the, of Chet GPT. And so on that I have to figure out how to do yet because it's not as accessible as it really could be. So I don't know how,   Glenn Gow ** 25:32 yeah, and so I won't, I won't spend a lot of time on it, because it's fairly complex. But you have to choose your best writing, you have to put it into a document and you probably are going to give it to a large language model that isn't Chachi btw that can read large documents, got it and then get the output from there. Okay, it's not easy to get there. But once you get there, now you have your style guideline.   Michael Hingson ** 25:55 And you can save that. Yeah, yeah. I presume you can save that and then tell it to use it again. When you next you Right,   Glenn Gow ** 26:02 exactly. Right. Yeah. So anyway, a little tips there. But that's just one small drop in this bucket of this amazing tool that is available to us.   Michael Hingson ** 26:11 Yeah. And it and it's only gonna get better. And it is so cool that it's there and does the things that it does. What is we're starting to hear more about this whole thing, this whole concept of generative AI, what does that?   Glenn Gow ** 26:25 Well, that's what we've been talking about generative AI, and that's where it generates. It fits within the world of large language models, and, and other models. And so let me back up a second and define it this way. So for almost seven years, we had what I'll call traditional AI. That still exists. And that's still actually even more important than generative AI, it's gonna have a bigger impact on the economy than generative AI. But generative AI is very, very new, we'll call it roughly two years old. And it creates content of various types. And I think the most impactful well, okay, the traditionally AI is much more about predicting outcomes, whereas generative actually creates outcomes for you. I think the greatest impact in the generative AI side is not going to be in language, it's not going to be in pictures, it's going to be in code, somewhere development code. And the reason I think the greatest impact is going to happen here is, Michael, if you get really good at writing articles, or blog posts, using a large language model, you might get, I don't know a few 1000 people to read what you've written. But if your team or if your team writes code, and it goes into a product, you might have millions of people. Now using something that was created using generative AI is going to be an enormous impact on the software development world, it's already starting.   Michael Hingson ** 28:05 And that makes sense. Well, and look, I think a lot of people don't know it. But the whole concept of AI was very actively used in developing as I understand that the mRNA vaccines for COVID. I believe that's true. I've heard I can't remember where I heard that. But I heard it from what I regard as a reliable source, as I recall.   Glenn Gow ** 28:28 No, it's very true, because that's more in the traditional AI realm. Yeah, where you feed the AI a lot of data and AI can see patterns in data that humans simply can't see. There's too much data, our brains aren't wired to see patterns in data. And AI can see patterns. And it could suggest particular experiments you might run based on the patterns it sees. Yeah, and that's one of the great things it's for. So in drug discovery, Michael, there's, there's a product. It's created by a division of Google called Deep Mind. And this product is called Alpha fold two. And what it does is something that I don't fully understand, because I'm not a scientist or a biologist. It does something called protein folding. So what is protein folding going to do for us? It's going to help cure diseases is what it's going to do. And this is a scientific problem that has existed for forever. Until within the last year or so. Google solved the problem using AI of protein folding. And what it does is it just opens up the ability for people, for scientists to develop new drugs and new protocols and new ways of looking at our DNA to cure diseases. And so we haven't we don't hear much about this yet, because we don't interact with something called Alpha. Fold two, we can't it's too complex. It's not an area we understand. But when it starts curing diseases, we're going to start paying attention to what's happening in the pharma world, in the healthcare world in the scientific world.   Michael Hingson ** 30:14 And, you know, the reality is, no matter what the downsides, in terms of bad actors who do things with AI, there are so many more people who will do good things with it. And it is still very well, and it probably always will be, but it's it is very much an evolutionary process. And we're new to the whole process. That's right.   Glenn Gow ** 30:38 That's right. And we have to think of it too. There are a lot of races happening here. Michael, I talked one about one race being the flywheel effect race, where I'm, I'm in on a business and I'm competing with other individual companies to be successful. So I need to take advantage of what AI can offer to me so that I can get into that flywheel improvement, continual improvement cycle and beat my competitors. That's one race we have. We have another race against at the at the at the national level, we have a race against China. China, has committed to becoming a world leader in AI. I don't know that we've actually stated that in the United States. And yet we are today the world leader in AI. And the question is, who is going to come out ahead? Yeah. So there's a race. And we have to, we have to be aware of that race and understand that race, there's a third race, which is against hackers. So one of the interesting things about the large language model world here is that we have tools like chat GPT, the most popular one and the most advanced one, which is called closed source software. But Mehta, the company formerly known as Facebook, Facebook, has released open source software models, when you release open source software, that means anybody in the world so North Korea can use it, around can use it, a hacker in their basement in New Jersey can use it to do things that we wish they weren't doing. And so given that this is the world we live in, if you're running a company, you need to ensure that the vendors you hire in the world of cybersecurity are on the cutting edge of AI and using the latest AI technologies to help prevent what the bad guys are trying to do with the latest AI technologies.   Michael Hingson ** 32:47 It's very much like anything in the in the hacking world, we need to make sure that we have bright people and people who are not only bright enough, but are forward looking enough to anticipate and figure out what the hackers might do to be able to make sure that we put safeguards into the system as best as we can, as best as we can. And when somebody isn't totally successful at that, because somebody on the other side comes out with something more clever. We learn from it, which is also part of the process. Exactly right. And then we use AI to figure out how to fix it.   Glenn Gow ** 33:30 We are definitely going to do more and more than agree with that.   Michael Hingson ** 33:34 Yeah. You know, it's it's always interesting and pertinent to ask questions like, what do we do about AI producing inaccurate information? But you know, I think that really ultimately comes from it depends on the information we give it, doesn't it? Well, let   Glenn Gow ** 33:56 me answer your question. slightly differently. Okay. So there is this thing, as you know, called hallucination where AI might give us the wrong answer. This happens, by the way, only in generative AI does not happen in traditional AI. Because we're not asking traditional AI to, to make anything up. In generative AI, we are actually asking it to make something up. We're asking it to write something or build something that hadn't existed before. And so it has a hallucination problem. So there are two ways around this. Well, I'll say three ways around this. There are certain things where we don't really care if AI makes something up. Let's say Spotify, is using AI to predict the next song that I want to hear. I don't care if Spotify makes a mistake, right? I just happen to hear a song that maybe isn't my favorite as a result. There's no risk factor here. But the minute I step into the world of making Have something that has some risk to it, we need a human in the loop. A human must be involved in making the ultimate decision about what we're going to publish or what code we're going to write or what we're going to what strategy we're going to take on. So you have a human in the loop, sometimes you have you human deeply in the loop. Because there's, there's there's a lot of potential danger associated with this. Like, should we fire a missile or something? Or we have a little bit of a human in the loop? Like, should I publish this blog post said, Shut up Tejas wrote the answers usually no, don't do that. But, but, and there's one other factor. So if you're using a large language model, and you're asking it to do some research, you ask it, or you tell it, you say, and I want you to point me to the source of the information. Now, this is important, because it'll make up sources. Sometimes Michael, it'll say, Oh, here's the source, ha, ha, ha, it's not really a source, it doesn't really say, this is the source of information, they just made it up or the LLM made it up. So instead, by taking a combination of having the human in the loop, and having the source, then the human can go to the source and validate. Yeah, that the large language module model actually did the research and came back with an answer for you that is valid. And now you can make a decision based on that. And   Michael Hingson ** 36:30 the other thing that, again, comes to mind is that hopefully, interacting with the LLM, and dealing with correcting sources and so on, it learns along the way, and over time, maybe you won't make as many mistakes.   Glenn Gow ** 36:47 I think that's true. It is happening now with the models because there is human feedback involved. So it's, it's getting better and better. But it may be the case that we never get to perfection here. Yeah. But you know what? Humans aren't perfect either. And so well, we just needed to get to be a little bit better than humans.   Michael Hingson ** 37:11 Yeah, no, we've got a, we've got to continue to grow.   Glenn Gow ** 37:17 Precisely, yeah. How   Michael Hingson ** 37:19 do we deal with the biases and all the negative things that people say about AI and things that are clearly not true? And very frankly, to me, some of it comes from the political side of things, because people promote fear way too much. But how do we deal with that? Well,   Glenn Gow ** 37:42 so I heard the word bias in your question, and I have I have an answer, maybe about that. But tell me what can you give me an example of what you're you're asking about so I can be more precise?   Michael Hingson ** 37:51 Oh, I'm just thinking of we, we hear so many people saying how bad AI is and we should really not only have better governor's on him, we shouldn't allow it. Kids use it to cheat. It's bad. We shouldn't have it. Well, and it comes from? Yeah, some kids do. There's a challenge there. But anyway, go ahead.   Glenn Gow ** 38:16 Well, let's just use that example, Mike. Okay. So it has to do with being creative about how do you manage change. So I'm going to use an example of a Wharton professor, his name is Ethan Moloch. He's a wonderful person to follow if you want to look him up. He's a leader in thinking about AI and how it applies both in the academic world and the business world. So he, like I said, he teaches a business course at Wharton. And so one day he gets up in front of the class. And he says, Okay, we're all going to write a paper. I don't know what the paper was about. Not important. No, I'm going to ask all of you to write a paper. And I'm going to insist that all of you use chat GPT. And the class is like standing up and clapping and like, oh my god, this is amazing. Because what used to take me four hours is gonna take me 30 minutes now. But he wasn't done. Yeah. And I'm going to ask you to defend every line in the paper. Yep. And so they are suddenly realized that they needed to understand what this tool was telling them and they needed to believe it and validate it. So they are actually learning more than they would learn without ChaCha btw because it's providing all this information that they need to go it's almost like they're it's pointing to here are the important things you need to go learn. It's not about writing the paper. It's about the learning. Yeah. And I thought that was incredibly brilliant to embrace AI so that his students become better at what he said. asking them to do it, which is to think about business problems in a certain way. Yeah,   Michael Hingson ** 40:04 well, and I, the first time I was talking with someone about chat GPT, and they were talking about how kids cheat, and so on. And cheese, well, with some people true. And some people, it's probably too strong a term, but how kids are using it and not doing it on their own. I immediately said, This is an incredible teaching opportunity. What the teachers need to start to do is to not fear, the artificial intelligence, but rather uses as an opportunity to say to the students, okay, and the way we're going to grade your papers is that you're going to have to defend it. And you're going to have to tell me, what is in the paper? And why you say what you say? Yeah. And I think that makes perfect sense. It's in and I don't know whether that's more work for teachers, it can be time consuming. But it's an opportunity to really change a lot of our teaching models, which is great.   Glenn Gow ** 41:06 Exactly. Right. Exactly. Right. And if teachers are smart, they should use AI to help them build their curriculum, and build what it is they're going to teach and how they're going to teach it. Because AI is a fantastic tool for that. And   Michael Hingson ** 41:23 if school administrators were smart, they would encourage it. That's right. Which is another story entirely. By but you know, it's a process. But I but I really think that it offers so much of an incredible opportunity to vastly improve teaching that, how can you argue with that? But   Glenn Gow ** 41:46 well, let's, let's take what you just said, Michael Fullan. And apply that statement vastly improved teaching to the work world? Yeah. So if I'm running a company, I have people who know some things and people who don't know some things in my company. And I want everyone to know as much as they possibly can, so they can make better decisions. AI is one of the mechanisms to help me get there very quickly. So when one of my favorite phrases, is the head of HR is talking to the CEO, and the head of HR says, gosh, you know, I don't know if we should train all these people. What if we train them and they leave the company? And the CEO says, What if we don't train them, and they stay at the company? So this is a tool for training for teaching for learning for every employee. And every CEO is going to benefit if he if that CEO can get the employees learning by using this incredible tool. Yeah.   Michael Hingson ** 43:02 Isn't that cool? Yeah, very cool. And it makes perfect sense. Well, you know, so again, in general, I asked the question before about bias. But is the bias really against AI? Or is it against change?   Glenn Gow ** 43:22 It's a bit of a complicated question. So yeah. So think of it this way. If you build a large language model, and there are only a small number of companies in the world who can build large language models, because it's very, very, very expensive to do. So. What you do if you're open AI, let's say or your anthropic is another company. X is another company, pi is another company, or if you're going to build a large language model, you do something, which is you put guard rails on that. Because you don't want bias inside of those guardrails. And yeah, when you lay down the guardrails, the human who's laying down the guardrails has some bias, Michael, why because they're human. So you might have one large language model that leans a little bit to the left and another one that leans a little bit to the right, and that's based on the people who designed it. And so you could argue that every large language model has some bias built into it purely because humans built in. Hmm. And then you get to choose though, which largely language model do you want to work with whether it's chat CBT, or Claude from anthropic or many others.   Michael Hingson ** 44:44 But a lot of the bias at least that I'm that I'm thinking of, and a lot of people probably think of when they hear this discussion is people are just prejudiced against the whole concept of AI. And I think that yeah,   Glenn Gow ** 44:56 I don't I don't hear that very much. Okay. hear people hungry, I hear people who are hungry to learn more. That's great. So maybe you're hearing by us that I don't hear well, I, you know,   Michael Hingson ** 45:10 probably from different sources. And I've watched enough TV to to observe things, and I've heard negative things. But I'm not hearing nearly as much fear about AI, as I did a year ago.   Glenn Gow ** 45:25 Oh, interesting.   Michael Hingson ** 45:28 And maybe it's just people aren't talking about it. But you know, go ahead. Well, maybe people are   Glenn Gow ** 45:34 beginning to understand it better. That's usually why you might see reduction in fears people begin to understand that. This is why humans are not good at change. Typically, they fear the future, they fear, they're not going to fit into the future. They fear that I can understand that future. But once you start to step into the future, you realize, oh, no, it wasn't as bad as I thought it was going to be. Maybe it's even good. Yeah. And so that's probably why you're seeing that reduction in fear.   Michael Hingson ** 46:03 We as a society, and as a race, tend to fear a lot more than we ought to. Because we've we decided that we're afraid of one thing or another. And most of the things that we're afraid of never really happen anyway.   Glenn Gow ** 46:20 Exactly. So that's a skill all unto itself. Yes. Why am I focused on something that hasn't happened? isn't likely to happen. And I probably be okay. If it did happen, I'm probably going to be fine. And yet we do tend, we can tend to go there. It's your training of the mind, Michael, this comes back to I'm glad you brought it up. This comes back to one of the concepts I have, in my my coaching of CEOs is, how do you look at the world? Do you look at the world from a fear perspective? Or do you look at the world from an opportunity perspective, we can look at the exact same thing. And come up with a different outcome or a different way of thinking about I'll give you a funny example. A funny example. A shoe company sends a shoe salesman to a country in the desert, to go sell shoes. And the shoe salesman shows up. And he immediately emails back to headquarters and says I'm never going to be successful here. No one wear shoes here. And so he has a failure mindset. So they bring it back. They send another salesman to the exact same location, immediately sends an email back to headquarters and says, Send me ship fulls of shoes. No one wear shoes here. Yeah. And about how are we choosing to perceive what's in front of us? Yeah.   Michael Hingson ** 48:06 I, for a while ever since escaping from the World Trade Center, I've been talking about escaping and what I what I did, how I prepared for it. But never thought about the fact that with all the things that I learned about emergency preparedness, talking to fire people learning how to travel around the complex, not by reading science, of course, but by truly learning it. It created a mindset that said, You know what to do in an emergency, although at the time, I didn't think about it, but much later, I realized it. And I went oh, that is that's a good point. And then during the pandemic, I realized that while I've talked about not being afraid, I've not ever taught anyone how they can learn to control fear. And it's not to not be afraid, but rather to use fear as a powerful tool to help you. And so we've now written a book, it's called Live like a guide dogs stories from a blind man and his dogs about overcoming adversity, being brave, and walking in faith. And it's all about using information that I've observed and learned from a guy dogs and my wife service dog about different aspects of fear and learning to control fear and making it an add a positive attribute to have not an adversary. Well,   Glenn Gow ** 49:32 Michael, that sounds amazing is your How long is your book been out?   Michael Hingson ** 49:35 It isn't. This one is going to come out later in the year. I'll send you an email there. Oh, already been a couple of announcements about it. And it's available for pre order. So I will I will make sure that we put that also in the show notes again, but it's not out yet. But it's coming it'll be fun. I'd love to get your thoughts on it. And maybe when we start looking for people to review it I'll have to see if you'll look at it and Give us a review.   Glenn Gow ** 50:00 Fantastic. I'd love to be part of that.   Michael Hingson ** 50:02 So when we talk about AI, and just all the things that are going on, of course, some people talk about job loss or afraid of job loss, what do you think about that?   Glenn Gow ** 50:13 So I'm going to answer your question in a second. And I just want to suggest maybe this will be our last topic. Is that okay?   Michael Hingson ** 50:22 Only if it's an AI solution? Yeah, well, yeah. Well, so in resist,   Glenn Gow ** 50:30 look, job loss is a real thing. But I want to really frame how we think about this issue. So I want us to think about our jobs as being made up of tasks. Some people have lots and lots and lots of tasks. And some people have a smaller number of tasks that make up their job. AI is going to replace tasks. So if I have 100 tasks that I do every day, and AI can replace 30 of them, I'm going to be pretty happy about that. Because I'm going to be a lot more productive, and I can focus on the ones that I'm best at, and I'm gonna let ai do the things, it's best that but if my job is made up of a tiny number of tasks, let's say, I'm a long haul truck driver. And my task is to get the truck into the into the right lane and go for the next 1000 miles. My job's in danger, because the bulk of my work is associated with a small number of tasks that AI can take on. And so we want to ask ourselves, what what is our day look like? And how many things can be taken over by AI? And how can we embrace them. So there will, there will be three things that happen, there will be new jobs created by AI, the bulk of people will be impacted in a positive way, where they will use AI to be more effective, more efficient in their day, and they'll be able to get more done in a shorter period of time. And then there are some jobs that are going to go away, they're going to disappear. Because of this nature of they're made up of a small number of tasks. Yeah. And so you're running a company, you want to ask yourself, what do we do with that information? Do I think about the employees that I might not need in the future? Do I help them get training right now on this so that they recognize that their job may go away,   Michael Hingson ** 52:26 or you find other things for them to do or find other things   Glenn Gow ** 52:29 for them to do exactly. But in all cases, the market will cert will determine whether or not these jobs stick around or not, yeah, they'll be individual decision makers. Because if you're a competitor suddenly eliminates a bunch of jobs. Let's I'll use an example. Let's say you run a warehouse, and you have 100 people in your warehouse. And your competitor says, I only need 10 People in my warehouse, and I need 90 robots in my warehouse. And that's going to be cheaper and more efficient. Well, I can't be that employee that are an employer that says I'm going to keep all my employees paid, I'm gonna have to understand the nature of how jobs are going to change. And I need to act quickly. This is why we want to embrace AI as quickly as possible to make those decisions. Well,   Michael Hingson ** 53:21 so So two things, one, going back to the truck driver, okay, so AI can take over the actual driving of the truck, at some point, to the point where we don't have to fear that. That doesn't mean we can't find other things for that truck driver to do while he is in the truck. And the truck is being driven by AI. So that   Glenn Gow ** 53:45 is true. That is absolutely true. And so let us use this as our last example, a perfect example would be that that truck drivers overseeing six trucks, right? All at once happens to be sitting in one. But one of those six trucks gets stuck somewhere because you have a flat tire. And it needs a human intervention. But the human in the truck can tell it. Hey, that truck over there was five miles away, pull over and wait for a tow truck to come and get you. Yeah, yeah. Well,   Michael Hingson ** 54:18 very, very quickly. One last thing. I worked with a company called access to be I don't know if you're familiar with accessibility and what it does to help make the internet more accessible. No, please. So accessibility is a product that began several years ago when three guys in Israel developed sought wealth. They first had an internet company that made websites and then in 2017, Israel came along and said God and make all websites accessible. They had so many that they had to figure out a way to do that. And they used AI and they created a widget that sits in the cloud. And the widget can analyze any website of any subscriber. And when it analyzes, it creates what's called an overlay and creates all The code that it feels that it can put in to the site to make it accessible, and it doesn't reprogram the website. But when I go to a site that subscribes to access a B, I hear a message that says, Put your browser in a screen reader mode and I push the button, the widget up in the cloud transmits all the Accessibility Code down to my browser, which has already got the rest of the website, my browser doesn't care where the information comes from, right, as long as it's there. Now, it's not perfect, it doesn't do graphics, it doesn't do necessarily the most sophisticated tables and all bar charts. It doesn't describe all pictures. But it does a lot to make websites a lot more usable. And they have other profiles for other kinds of disabilities. But there's a cadre of people who just are so totally against it, hey, I could never do this overlays will never work. And I'm and they're vehement. And, you know, I continuously think of when I in 1985, started a company because I couldn't get a job to sell products, I started a company selling some of the early PC based CAD systems. And I had an I had architects who came in and they said, Well, we like your product, it's great. But if we use it, since we charge for our time, we can't make nearly the money that we otherwise would have. And I said, you're looking at it the wrong way. You don't deal with it in terms of how much your time is charged. Now, you look at it in terms of your expertise, and you're charging for your expertise. You don't change your prices, you get more customers. And you can do so much more with each customer by using a PC based CAD system and bring the architect or bring the client in and do walkthroughs and fly throughs and other stuff. But it's the same thing. And now CAD is commonplace. The reality is the overlay does so much and accessory is so creative at what it does. And they've also brought in additional services to do the things that the widget can't do. But it's amazing to see some people who were so vehemently against AI and overlays. When in reality, every website designer should include it. Because at least it'll do some of the heavy lifting and in what may not do everything, but it will do a lot and save them time and they don't have to change what they charge.   Glenn Gow ** 57:20 That's great. Sounds like you're a good salesman.   Michael Hingson ** 57:23 Well, we'll we'll keep going with it. It's it's a lot of fun. Well, I really want to thank you for being here. If people want to reach out to you. How do they do   Glenn Gow ** 57:30 that? It's very simple, Michael,   Michael Hingson ** 57:32 there you go. They can just go to AI and say find. Yeah, go ahead.   57:37 Well, my website is My name is Glenn Gow .com. So Glen with two Ns, G L, E, N, N G. O W.com. That's   Michael Hingson ** 57:47 easy. Well, I hope people will reach out. And this has been a lot of fun. And I want to   57:53 one thing I forgot to mention, absolutely. Okay. On my website, I have a tool that's free to use. It's available 24/7 You don't even need to fill out a form to use it. It's called AI CEO coach. So if you're a CEO, you can go to my website, Glen Gow.com and use this tool as often as you want absolutely for free. And ask it questions that a CEO would ask and see if you like the answers, and please give me some feedback on it. People love it so far. Cool.   Michael Hingson ** 58:32 Okay. And it's called again, AI   58:35 CEO, Coach coach.   Michael Hingson ** 58:37 Cool. Well, people go reach out and check it out and reach out to Glenn. I want to thank you again for being here. And I want to thank you all for listening. Love to hear your thoughts. Email me at Michaelhi m i c h a el h i at accessiBe A c c e s s i b e.com. Or go to our podcast page www dot Michael hingson.com/podcast. And that's m i c h a e l h i n g s o n.com/podcast. Love to hear your thoughts and please give us a five star rating wherever you are listening to our podcast or watching our podcast today. We value your insights and Glenn for you and you listening. If you know of anyone else who want to be a guest on unstoppable mindset. Please introduce us always looking for more people to come on and be a part of unstoppable mindset. So again, Glenn, I want to thank you for being here and really appreciate your time today. My   Glenn Gow ** 59:29 pleasure, Michael, it was a pleasure. I really enjoyed that.   **Michael Hingson ** 59:36 You have been listening to the Unstoppable Mindset podcast. Thanks for dropping by. I hope that you'll join us again next week, and in future weeks for upcoming episodes. To subscribe to our podcast and to learn about upcoming episodes, please visit www dot Michael hingson.com slash podcast. Michael Hingson is spelled m i c h a e l h i n g s o n. While you're on the site., please use the form there to recommend people who we ought to interview in upcoming editions of the show. And also, we ask you and urge you to invite your friends to join us in the future. If you know of any one or any organization needing a speaker for an event, please email me at speaker at Michael hingson.com. I appreciate it very much. To learn more about the concept of blinded by fear, please visit www dot Michael hingson.com forward slash blinded by fear and while you're there, feel free to pick up a copy of my free eBook entitled blinded by fear. The unstoppable mindset podcast is provided by access cast an initiative of accessiBe and is sponsored by accessiBe. Please visit www.accessibe.com . AccessiBe is spelled a c c e s s i b e. There you can learn all about how you can make your website inclusive for all persons with disabilities and how you can help make the internet fully inclusive by 2025. Thanks again for Listening. Please come back and visit us again next week.

Welcome to today's "AI Lawyer Talking Tech" podcast. In our latest episode, we delve into the highlights from the Federal Trade Commission's (FTC) 2024 Virtual Tech Summit on artificial intelligence (AI) industries. The summit shed light on the FTC's heightened focus on strengthening enforcement in the AI sector, with key insights from Chair Lina Khan and Commissioners, signaling the agency's active role in regulating competition and consumer protection in the emerging AI landscape. Stay tuned as we explore the implications of these developments in today's podcast episode. How teams analyze legal spend and billing data for predictive spend05 Feb 2024Financial Thomson ReutersLaw In The Age Of Technology: Odierno Law Firm's Perspective On Instant Gratification05 Feb 2024Benzinga.comFrom analog photography to digital: My journey to evaluate legal tech05 Feb 2024ExBulletinEarly Adopters Of Legal AI Gaining Competitive Edge In Marketplace05 Feb 2024Above The LawFrom Analog Photography To Digital: My Journey In Assessing Legal Tech05 Feb 2024Above The LawCraig Wright's day of reckoning arrives in UK Court – Did he really invent Bitcoin?05 Feb 2024CryptopolitanTaking the middle ground05 Feb 2024Law Society GazetteIntroducing Legalese Decoder's Groundbreaking Innovation AI Lawyer: Legal Assistance for Small and Medium Businesses05 Feb 2024InvestorsObserverDeepfake images continue to cloud social media. Can they be stopped?05 Feb 2024Daily ItemWIPIP Session 1: AI02 Feb 2024Rebecca Tushnet's 43(B)logData brokers know everything about you – what FTC case against ad tech giant Kochava reveals05 Feb 2024What's New in PublishingCross-functional is our future (351)04 Feb 2024LexBlogRyder Ripps Ordered to Pay Millions in High-Stakes Legal Defeat04 Feb 2024CryptopolitanGates depositions open to public03 Feb 2024Tech EdvocateEU Member States Unanimously Endorse EU AI Act03 Feb 2024CryptopolitanTechsommet Returns With Second Edition Of Legal Automation Virtual Summit: Sponsored By Mitratech03 Feb 2024TradingCharts.comUtah Lawmakers Advance Bill To Prevent The Granting Of Personhood To Nature By Corinne Murdock02 Feb 2024Daily WireHow AI-Assisted Research on Westlaw Precision helps legal professionals impress clients02 Feb 2024Financial Thomson ReutersTroy Announces Early Beta Release of Groundbreaking Legal AI Software, Legix AI02 Feb 2024Crwe WorldCapturing the Client Experience in AI02 Feb 2024JD SupraAdding an Artificial Intelligence Module to a 1L Legal Research Course02 Feb 2024RIPS Law Librarian BlogRisk Assessments in Healthcare: Where Legal Requirements Also Make Good Business Sense!02 Feb 2024JD SupraWeb Publisher Seeks Injunctive Relief to Address Web Scraper's Domain Name Maneuvers Intended to Avoid Court Order05 Feb 2024New Media and Technology Law BlogWhat the “State of the US Legal Market” report showed about law firm billing rate performance in 2023 and where it may go in 202405 Feb 2024Thomson Reuters InstituteAI for good: How one entrepreneur is tackling family leave law confusion05 Feb 2024Thomson Reuters InstituteIntroducing Screens.ai and the Ensuing Wave of "Because AI" Startups04 Feb 2024Zach Abramowitz is Legally DisruptedAI in 2024: What Every GC Needs to Know05 Feb 2024Schiff HardinTexas Federal Court Dismisses Video Privacy Protection Act Class Action Concerning Email Newsletter From University Of Texas05 Feb 2024Duane MorrisDerivatives, Legislative and Regulatory Weekly Update (February 2, 2024)03 Feb 2024Gibson DunnTelephone and Texting Compliance News: Regulatory Update — FCC Floats Proposals on Consumer Consent and AI-Generated Voices, Weighs Enforcement Action for Voice Service Provider; New Legislation on Robocalls02 Feb 2024Mintz LevinBiden's AI Executive Order Achieves First Major Milestones (AI EO January Update) — AI: The Washington Report02 Feb 2024Mintz Levin

Traditional SEO is going to die. The way we all use the internet is going to drastically change. Why? Because AI search is here. So what effect do AI and LLM chatbots have on the future of traditional web searching? We're diving in.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode pageJoin the discussion: Ask Jordan questions on AI searchUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:02:30 Daily AI news06:40 Jordan's background in SEO12:01 Utilize Google's SGE, ChatGPT, perplexity.14:01 Stack Overflow: open forum for developers.18:08 Big publishers suing OpenAI over copyrighted content.20:22 ChatGPT's usage has skyrocketed, generated significant organic traffic.25:56 SEO experts emphasize content volume for ranking.29:31 Online platforms consuming content without generating traffic.32:03 Companies forced to prioritize ad revenue over user experience.37:02 Underused generative AI; personalized content saves time.37:40 MIT study on AI replacing human jobs.43:49 SEO focus shifting to voice and AI.45:29 Consider partnerships or join content publishers' union.48:02 Google's AI search fills screen, discouraging scrolling.Topics Covered in This Episode:1. The Future of SEO and Web Browsing2. Impact of AI and Voice Search on Traditional SEO3. Usage and Benefits of AI Search Engines4. Legal Issues and Partnerships between AI Companies and PublishersKeywords:SEO, AI, traditional SEO, Accelerant Agency, white hat SEO, local service-based businesses, AI features, Stack Overflow, ChatGPT, AI platforms, publishers, legal action, OpenAI, The New York Times, traditional news publishers, recipe search, perplexity, web browsing, lawsuits, partnerships, AI companies, personalization, ad revenue, publishers, browsing experience, retargeting ads, push notifications, video ads, excessive ads, unsustainable browsing experience. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Welcome to RIMScast. Your host is Justin Smulison, Business Content Manager at RIMS, the Risk and Insurance Management Society.   Justin interviews Katherine Henry, Partner and Chair of the Policyholder Coverage Practice of Bradley, Arant, Boult, and Cummings in today's episode. Katherine will be one of the presenters in the January 4th RIMS webinar, Nevada's “Defense Within The Limits” Ban Explored. Justin and Katherine explore the risk trends of 2023 and what she expects from 2024. Next, they cover the upcoming webinar on Nevada's new liability insurance “Defense Within The Limits” ban, what the effects of the ban are, and how the ban is expected to spread to other states. Katherine concludes with how she and her co-presenter at the webinar, Mark Habersack, expect to elaborate on this topic.   Listen in for a professional perspective on risk trends for 2024.   Key Takeaways: [:01] About RIMScast. [:14] Public registration for RISKWORLD 2024 is now open. Explore infinite opportunities with RIMS from May 5th through May 8th, 2024, in San Diego, California. Register at RIMS.org/riskworld. [:31] In today's episode, we will be rejoined by our good friend, Katherine Henry, of the law firm Bradley, Arant, Boult, and Cummings, to discuss legal trends from 2023 and what risk managers should expect in 2024. [:58] The RIMS-CRMP is the only competency-based risk management credential. That matters because earning the certification shows employers and recruiters that you have the skills necessary to manage risk and create value for your organization. [1:14] Several Exam Prep virtual workshops are coming up, starting on December 13th and 14th with former RIMS president, Chris Mandel. On January 13th, 20th, and 27th, 2024, the RIMS-CRMP Exam Virtual Workshop will be presented in conjunction with Conrad Clark Nigeria. [1:37] The RIMS-CRMP-FED Exam Prep Virtual Workshop will be held on January 30th and February 1st. That's a two-day course. Visit the certification page on RIMS.org for more information. A link is on this episode's show notes. [1:54] RIMS is gearing up for awards season. At RISKWORLD 2024, we will honor individuals, organizations, and chapters for their outstanding achievements in risk management. If you know someone who is truly making an impact on the risk profession and paving the way for future generations, consider drafting a nomination! [2:13] The deadline to submit award nominations is Friday, January 5th, 2024. A link to the awards applications and guidelines page is in this episode's show notes. Go to RIMS.org's About Us page and see the awards link there. Nominations for Risk Manager of the Year have closed but other awards might appeal to you or a friend. [2:41] Katherine Henry is the Partner and Chair of the Policyholder Coverage Practice at Bradley, Arent, Boult, and Cummings, a national law firm. Katherine and I will discuss the trends that drove the legal and risk professions in 2023, what to expect in 2024, and Nevada's Defense Within the Limits ban that may set a precedent for other U.S. states. [3:12] Katherine is one of the two presenters of an upcoming RIMS webinar called Nevada's “Defense Within The Limits” Ban Explored, on January 4th, 2024 at 1:00 p.m. It will be presented by the RIMS Public Policy Committee. Register now, especially if you're a RIMS member! This is going to be a big deal for you! [3:37] Katherine Henry, welcome back to RIMScast! [4:25] Katherine says risk managers have been really busy in 2023. She thinks first of cyber risk and cyber insurance. Insurers are getting their hands around it and premiums have escalated. Risk managers are finding they have to bring in IT and other folks to answer the much more complex questions on cyber. The cost of breaches has gone up. [5:40] Katherine discusses recent big hacks. One of the biggest risks lies with your vendors. Insurers are looking at that when setting your premiums. [6:19] Another big problem in 2023 is supply chain. It has become more difficult to insure it. It is difficult to procure business interruption insurance. Many insurers have left this market. Risk managers deal with this by eliminating sole sourcing and JIT warehousing. You have to have more goods and more local warehouse space available. [7:55] AI is the next big risk on Katherine's mind. The National Association of Insurance Commissioners (NAIC) has been looking at AI for quite a few years and its impact on insurance. Insurers have implemented AI chat boxes in personal lines. For risk managers, the question is what are we going to see in commercial lines? [8:41] Insurers may be able to use AI to assess damages better and to move more quickly. Risk managers will be dealing more with computerized platforms than individuals in the underwriting process. That's a few years away. Because AI is being integrated into so many platforms, it's a liability insurance risk for organizations. [9:55] Climate change is another major concern Katherine has. We see its impacts on agriculture in what you can grow and where you can grow it. The effect on sea levels in ports is a concern. It will affect living conditions around the world. It will continue to be a high-level concern for risk managers. [10:42] Katherine brings up the wars as another big concern for risk managers. Events have been canceled because of protest risk. We don't know the eventual impact of the Israel and Hamas conflict. Russia has agricultural and oil risks. There is the risk of war with China and Taiwan. [11:29] Swine flu and pneumonia are concerns now. There are respiratory illnesses among children in China. Illnesses and protests present physical risks. [12:41] RIMS plug time! RIMS Virtual Workshops: Visit RIMS.org/virtualworkshops to see the full calendar. On January 16th and 17th, 2024, our friend and former RIMS president Chris Mandel will lead a two-day course, Captives as an Alternate Risk Financing Technique. [13:02] On January 23rd and 24th, our friend Gail Kyomura will return to host Fundamentals of Insurance. Information about these workshops and others is on the RIMS Virtual Workshops page. Check it out and register! [13:18] On December 12th, Prepare Yourself for the New Generation of Risk with Riskonnect. On December 14th, Aon will be Addressing Today's Risks While Preparing for the Risks of Tomorrow. On January 4th, RIMS's Public Policy Committee will explore Nevada's “Defense Within The Limits” Ban. That's why Kathy Henry joins us today. [13:44] On January 16th, RIMS will present How Risk Managers Can Combat Human Trafficking In 2024. I'll be hosting that session and will be joined by three expert panelists. I'm really looking forward to delivering this session and reaching you all. [14:00] Visit RIMS.org/Webinars to learn more about these webinars and to register! Links are in the show notes. Webinar registration is complimentary for RIMS members. [14:38] It's difficult for organizations to take a political stand. People come at them from both sides. They are also challenged when they don't take a position. It's hard for organizations to know the right position to take. That's an organizational risk. You can't please all the people all the time. [15:38] Runaway or out-of-control verdicts are a risk when you take a case to a jury. Something that should be resolved for $1 million or two could be a $40 million liability. Insurers are aware of this. Katherine warns risk managers to give notice to their tower of excess insurance when a risk comes up that could be subject to a “nuclear” verdict. [16:48] Justin brings up nuclear verdicts in connection with recent PFAS settlements. RIMS did a webinar about it a month ago. Very high settlements open the door for future litigation or actions. Justin reads from Reuters on November 26th about a U.S. appeals court ruling protecting 3M and other companies in PFAS litigation from a class action. [19:11] Katherine Henry will be co-hosting a webinar on January 4th, Nevada's “Defense Within The Limits” Ban Explored. Katherine Henry and Mark Habersack are going to explore this ban. [19:33] Katherine gives a high-level overview of the ban. There are two types of liability policies. One includes a defense that is outside the limits; other policies put the cost of defense inside the policy limits. A $5 million policy within the limits provides $5 million to pay defense and damages. [20:11] The Nevada legislature wrote a new law that every liability policy in Nevada must include defense outside of limits, so insurers have an unlimited obligation to defend you until the case is resolved. The Webinar will talk about what caused that to happen in Nevada, what the potential solutions are, and the potential implications around the U.S. [21:06] This legislation overturns the business relationship between insurers and insureds. Insureds will no longer be able to purchase less expensive defense within-limits policies. That change has immense financial consequences. Justin will be the host for that webinar. [21:30] The legislation sets a time for this change to occur. Businesses need time to place liability coverage. Risk managers's jobs have changed greatly from what they were 20 years ago when they were purchasing insurance and working with insureds. Now they're assessing their enterprise's risk. There will be a lot of work for 2024. [22:28] Justin thanks Katherine Henry for joining us. [22:42] Special thanks to Katherine Henry for joining us on RIMScast! You'll hear more from Katherine on January 4th, 2024 during the RIMS Webinar Nevada's “Defense Within The Limits” Ban Explored. She will be joined by former RIMS Nevada Chapter President, Mark Habersack. Register at RIMS.org/webinars and the link in the show notes. [23:07] Go to the App Store and download the RIMS App. This is a special members-only benefit. Everybody loves the RIMS App! [23:33] You can sponsor a RIMScast episode for this, our weekly show, or a dedicated episode. Links to sponsored episodes are in our show notes. RIMScast has a global audience of risk professionals, legal professionals, students, business leaders, C-Suite executives, and more. Let's collaborate! Contact pd@rims.org for more information. [24:17] Become a RIMS member and get access to the tools, thought leadership, and network you need to succeed. Visit RIMS.org/membership or email membershipdept@RIMS.org for more information. The RIMS app is available only for RIMS members! You can find it in the App Store. [24:42] Risk Knowledge is the RIMS searchable content library that provides relevant information for today's risk professionals. Materials include RIMS executive reports, survey findings, contributed articles, industry research, benchmarking data, and more. [24:59] For the best reporting on the profession of risk management, read Risk Management Magazine at RMMagazine.com and in print, and check out the blog at RiskManagementMonitor.com. Justin Smulison is Business Content Manager at RIMS. You can email Justin at Content@RIMS.org. [25:21] Thank you for your continued support and engagement on social media channels! We appreciate all your kind words. Listen every week! Stay safe!   Mentioned in this Episode: Riskworld 2024 — San Diego, CA | May 5–8, 2024 RIMS Riskworld Award Nominations — Jan. 5, 2024, is the deadline to submit nominations! RIMS-Certified Risk Management Professional (RIMS-CRMP) NEW FOR MEMBERS! RIMS Mobile App Spencer Educational Foundation — Grants Page Embrace The Unknown: Unleashing the Power of Risk | Hosted Live & In-Person by RIMS NZ & PI | Feb. 12, 2024 Dan Kugler Risk Manager on Campus Grant RIMS Risk Management Magazine: ERM Special Edition 2023   RIMS Webinars: Prepare Yourself for the New Generation of Risk | Sponsored by Riskonnect | Dec. 12, 2023 Addressing Today's Risks While Preparing for Tomorrow | Sponsored by Aon | Dec. 14, 2023 Nevada's “Defense Within The Limits” Ban Explored | Presented by RIMS Public Policy Committee | Jan. 4, 2024 How Risk Managers Can Combat Human Trafficking In 2024 | Presented by RIMS | Jan. 16, 2024 RIMS.org/Webinars Upcoming Virtual Workshops: Fundamentals of Insurance | Dec 12 See the full calendar of RIMS Virtual Workshops All RIMS-CRMP Prep Workshops — Including Chris Mandel's Dec 13–14 Course Related RIMScast Episodes: “RIMS Public Policy and Advocacy 2023” “Emerging Cyber Trends with Davis Hake of Resilience” “Fleet Safety with Nets Executive Director Susan Gillies-Hipp” “Cybersecurity Awareness Month with Pamela Hans of Anderson Kill” “Betting It All On Risk: Mark Habersack, Heart of RIMS Award Recipient 2021” Sponsored RIMScast Episodes: “Why Subrogation is the New Arbitration” | Sponsored by Fleet Response (New!) Cyclone Season: Proactive Preparation for Loss Minimization | Sponsored by Prudent Insurance Brokers Ltd. “Subrogation and the Competitive Advantage” | Sponsored by Fleet Response “Cyberrisk Outlook 2023” | Sponsored by Alliant “Chemical Industry: How To Succeed Amid Emerging Risks and a Challenging Market” | Sponsored by TÜV SÜD “Insuring the Future of the Environment” | Sponsored by AXA XL “Insights into the Gig Economy and its Contractors” | Sponsored by Zurich “The Importance of Disaster Planning Relationships” | Sponsored by ServiceMaster “Technology, Media and Telecom Solutions in 2023” | Sponsored by Allianz “Analytics in Action” | Sponsored by Alliant “Captive Market Outlook and Industry Insights” | Sponsored by AXA XL “Using M&A Insurance: The How and Why” | Sponsored by Prudent Insurance Brokers Ltd. “Zurich's Construction Sustainability Outlook for 2023” “ESG Through the Risk Lens” | Sponsored by Riskonnect “A Look at the Cyber Insurance Market” | Sponsored by AXA XL   RIMS Publications, Content, and Links: RIMS Membership — Whether you are a new member or need to transition, be a part of the global risk management community! RIMS Virtual Workshops On-Demand Webinars Risk Management Magazine Risk Management Monitor RIMS-Certified Risk Management Professional (RIMS-CRMP) RIMS-CRMP Stories — New interview featuring Chris Mandel! Spencer Educational Foundation RIMS DEI Council   RIMS Events, Education, and Services: RIMS Risk Maturity Model® RIMS Events App Apple | Google Play RIMS Buyers Guide Sponsor RIMScast: Contact sales@rims.org or pd@rims.org for more information.   Want to Learn More? Keep up with the podcast on RIMS.org and listen on Apple Podcasts.   Have a question or suggestion? Email: Content@rims.org.   Join the Conversation! Follow @RIMSorg on Facebook, Twitter, and LinkedIn.   About our guest   Katherine Henry Bradley, Arant, Boult, and CummingsKatherine Henry is the Chair of the Policyholder Insurance Coverage team. Katherine's practice focuses on meeting clients' business objectives in matters involving insurance. She regularly advises Fortune 10 and other companies on complex insurance programs involving manuscript and specialty policies, including programs with multi-national coverage towers of $500 million to $1 billion, and programs incorporating various risk transfer and financing mechanisms, such as fronting programs, paid deductible programs, and collateral agreements. Her practice spans all aspects of policyholder insurance coverage, from initial policy placement and renewals to claims management and litigation, both in the United States and abroad. Her past and present policyholder clients include two of the world's largest automakers, the world's largest home improvement specialty retailer, an auto insurance company, a vacuum cleaner manufacturer, a quasi-governmental defined benefit plan, numerous healthcare-related entities, a private-equity investment firm, various banks and financial institutions, and a national trade association for the gases and welding industry.   Tweetables (Edited For Social Media Use): For risk managers, this is really important. One of the biggest risks lies with your vendors, your third-party vendors. That can be the weak point. — Katherine Henry   There's been a case reported of swine flu in the UK, now. There are these respiratory illnesses among children in China. It's not a pandemic but it's still a risk. — Katherine Henry   Runaway or out-of-control verdicts are something organizations are facing everywhere. It's very difficult to take a case to a jury. Something that should be resolved for $1 million or $2 million could be a $40 million liability. Insurers are aware of that. — Katherine Henry  

Video jobs are probably going to disappear. Why? Because AI video generators are starting to become more developed and viable. With updates from established video tools like Runway to newer AI video models like Pika Labs 1.0 and Meta Emu, we're showcasing why AI video is here to stay.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions about AI video generationUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:[00:02:05] Daily AI news[00:07:00] Pika Labs 1.0[00:14:50] Runway[00:20:00] Meta Emu[00:25:30] Hot takes about AI video[00:31:25] Future of AI video[00:39:00] Final takeawayTopics Covered in This Episode:1. Impact of AI Video on Various Industries2. Use Cases for AI Video3. Future of AI VideoKeywords:AI impact on industries, AI in history, AI in fashion, AI in advertising, AI predictions, AI and dream reenactment, AI in history education, AI in interactive videos, virtual fashion shows, AI in legal contexts, generative AI in video, personalized ads, targeted selling experiences, AI video camera controls, motion brush in generative AI, Meta's emu video, Pica Labs text-to-video technology, AI content creation, Pica Labs 1.0, Runway updates and features, AI news, mainstream media, AI in commercials, AI in online ads, AI-generated content, animated videos, high-quality animated content, personalized content creation, custom dream movies Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Ryan is joined by Bob Van Lujit in this episode to discuss his open-source AI company Weaviate. Listen in as Ryan and Bob break down Weaviate's unique vector database technology powering the next wave of AI applications. Bob talks about the business model behind many open-source infrastructure companies, how Weaviate helps developers easily build and scale AI solutions, and where Bob sees AI transforming businesses over the next 12 months. Join 2,500+ readers getting weekly practical guidance to scale themselves and their companies using Artificial Intelligence and Revenue Cheat Codes.   Explore becoming Superhuman here: https://superhumanrevenue.beehiiv.com/ KEY TAKEAWAYS Weaviate provides the core infrastructure for storing and indexing vector embeddings from AI models to enable faster search and retrieval. Open-source companies like Weaviate make money by offering additional services like support, training, and managed services around their free technology. Weaviate targets developers through a "bottom-up" product-led growth strategy focused on helping them succeed with AI applications. Current AI systems are limited by their binary nature, but new probabilistic AI promises opportunities to build more nuanced applications. Combining generative AI models with vector databases enables more complex AI agents for legal services, cybersecurity, and other business use cases BEST MOMENTS “I was a part of a community called a Google developer expert community. And I was invited in 2016 to Google IO. And during the keynote, Sunder Pichai, the CEO of Google went on stage and he said, we got to move from mobile first to AI first." “How do we make sure that, that we really can go to production and that we can bring it to their customers as well? Because AI, and I don't mean this, I really mean this, it's like a seismic shift in how we build technology” "If you store it and you can't get it out anymore, it's useless. The problem we had was that most search was always keyword based." "We passed that point of good enough. So that opened the eyes of a lot of people. It's like, Hey, actually we can, we can build stuff with this." Ryan Staley Founder and CEO Whale Boss ryan@whalesellingsystem.com www.ryanstaley.io Saas, Saas growth, Scale, Business Growth, B2b Saas, Saas Sales, Enterprise Saas, Business growth strategy, founder, ceo: https://www.whalesellingsystem.com/closingsecretsThis show was brought to you by Progressive Media

Today's podcasting experiment is repurposing a LinkedIn Live I did with Gillian Whitney and publishing the audio on my podcast. Kudos to Gillian for her generosity - she's been a guest on the podcast before. She tells me I have a standing invite to be on her show any time and the feeling is mutual. Join Nola Simon & Gillian Whitney for an engaging chat about: Ghosts, Hallucinations & Other Scary Trust Leaps in Using AI for Research Trick or Treat? AI can a powerful tool, but it can also be dangerous. Why? Because AI has a tendency to hallucinate. It can take a kernel of truth and build out a fantasy, with the potential to impact your personal brand and reputation. Nola Simon has found that the results of AI research can be very misleading. Which leads to questions about how AI is pulling its information and how to negotiate the disinformation? Based in Ontario, Canada, Nola is an international B2B consultant who has advised hybrid/remote work teams for the last 10 years. In addition to working with organizations, Nola runs the Hybrid/Remote Centre of Excellence community. This community is powered by her podcast of the same name, which focuses on co-creating the future of work.  Nola Simon is a pioneer of hybrid work and has been interviewed extensively in the media - newspapers, television, radio, magazines. She is a LinkedIn Community Top Voice for Organizational Development & Decision-Making. Whether you're a business owner, job seeker, or employee, we invite you to join us for: Ghosts, Hallucinations & Other Scary Trust Leaps in Using AI for Research. Gillian Whitney is a LinkedIn Video Marketing Coach.  She believes every business professional needs to be using video to market themselves. Video boosts your online visibility, increases sales, and promotes your brand like no other marketing tool. As a LinkedIn Video Coach, Gillian helps business professionals make videos in a way that is comfortable for them. She loves sharing Easy Peasy solutions to help folks get started with video. Gillian is a citizen of 4 countries and a digital nomad. She currently resides in Las Vegas, with her husband and globe-trotting dachshund.   Gillian Whitney VideoEasyPeasy.com YouTube channel https://www.youtube.com/videoeasypeasy https://www.linkedin.com/in/gillianwhitney

Trick or Treat? AI can a powerful tool, but it can also be dangerous. Why? Because AI has a tendency to hallucinate. It can take a kernel of truth and build out a fantasy, with the potential to impact your personal brand and reputation. Nola Simon has found that the results of AI research can be very misleading. Which leads to questions about how AI is pulling its information and how to negotiate the disinformation? For more information: videoeasypeasy.com Gillian Whitney: linkedin.com/in/gillianwhitney Nola Simon: linkedin.com/in/nolasimon

What mindset shift should CIOs and CTOs make in order to succeed in an AI-driven world? How can they take control of their destinies and future proof to ensure responsible AI use in their organization? In this episode, Yadin sits down with Jeff Boudier, who is responsible for Product and Growth at Hugging Face, to discuss in depth. They cover using a principles-first approach, teaching a machine to be friendly, and increases in productivity. ---------Key Quotes:“AI is becoming the default way to build technology and most technology is going to be running some machine learning models in the background. Those models are going to be running everywhere from cloud to data center all the way to your pocket.”“At the end of the day, what I'm really looking forward to is for every single company in the world to be able to build and own their own models.”“Open models, open datasets and open source AI are really the only way forward for enterprises. If they want to be future-proof,  in terms of auditability, in terms of regulation, in terms of compliance, then it's about being in control of your own destiny, right? Because AI is so key to everything you're going to be offering to customers.”---------Timestamps:(01:46) The start of Hugging Face seven years ago (02:41) What was machine learning like at that time?(03:49) Teaching a machine to be friendly (04:46) The shift that resulted from the seminal paper “Attention Is All You Need”(06:20) The shift from writing an application to finding a model(07:18) The increase in productivity from machine learning (08:21) Ethical use of AI (09:55) Are enterprises ready to think through complex AI questions?(11:08) How CTOs are moving to a “model mindset”(12:20) Evaluating models (14:40) Offering end-to-end solutions (16:13) Using a first principles approach (20:49) Where will AI run? --------Links:Jeff Boudier on LinkedInCIO Exchange on TwitterYadin Porter de León on Twitter[Subscribe to the Podcast] On Apple PodcastFor more podcasts, video and in-depth research go to https://www.vmware.com/cio

Artificial intelligence (AI) technologies are not new, but they have made rapid advances in recent years and attracted the attention of policymakers and observers from all points on the political spectrum. These advances have intensified concerns about AI's potential to discriminate against select groups of Americans or to import human bias against particular ideologies.AI programs like ChatGPT learn from internet content and are liable to present opinions – specifically dominant cultural opinions – as facts. Is it inevitable that these programs will acquire and reproduce the discriminatory ideas or biases we see in humans? Because AI learns by detecting patterns in real world data, are disparate impacts unavoidable in AI systems used for hiring, lending decisions, or bail determinations? If so, how does this compare to the bias of human decision-making unaided by AI?Increasingly, laws and regulations are being proposed to address these bias concerns. But do we need new laws or are the anti-discrimination laws that already govern human decision-makers sufficient? Please join us as an expert panel discusses these questions and more.

You've probably heard that, in a blind taste test, even experts can't tell between white and red wine. Even if this were true – and it's not – it wouldn't matter. I was in Rome last month, visiting some Raphael paintings to research my next book, and stopped by the Sistine Chapel. I've spent a good amount of time studying what Michelangelo painted on that ceiling. There are lots of high-resolution images on Wikipedia. But seeing a picture is nothing like the experience of seeing the Sistine Chapel. You've invested thousands of dollars and spent fifteen hours on planes. You're jet-lagged and your feet ache from walking 20,000 steps. You're hot. When you enter, guards order you to keep moving, so you won't block the door. They corral you to the center, and you can finally look up. When you hear wine experts can't tell between white and red wine, you imagine the following: Professional sommeliers are blindfolded, and directed to taste two wines. They then make an informed guess which is white, and which is red. In this imaginary scenario, they get it right half the time – as well as if they had flipped a coin. If it were true wine experts couldn't tell between white and red wine, the implication would be that the experience of tasting wine is separate from other aspects of the wine. That the color, the shape of the glass, the bottle, the label, and even the price of the wine are all insignificant. That they all distract from the only thing that matters: the taste of the wine. There's some psychophysiological trigger that gets pulled when you tilt your head back. Maybe it stimulates your pituitary gland. When you have your head back and are taking in the images on the Sistine Chapel ceiling, you feel vulnerable. (You literally are vulnerable. You can't see what's going on around you. You'd be easy to physically attack.) What you see is overwhelming. As you try to focus your attention on some detail, some other portion of the imagery calls out and redirects your attention. This happens again and again. After a while, your neck needs a rest, and you return your gaze to eye-level. And this is almost as cool as the ceiling: You see other people with their heads back, their eyes wide, mouths agape, hands on hearts, tears in eyes. You hear languages and see faces from all over the world. You realize they all, too, have invested thousands of dollars and spent fifteen hours on planes. They, too, are jet-lagged and hot and have walked 20,000 steps. You can look at pictures of the Sistine Chapel ceiling on the internet. You can experience it in VR. In many ways, this is better than going to the Sistine Chapel. You can take as much time as you want, and look as close as you want. You don't have to spend thousands of dollars and fifteen hours on a plane, take time off work, or even crane back your neck. But seeing the Sistine Chapel ceiling on the internet or even VR is only better than seeing it in person, in the way that a spoonful of granulated sugar when you're starving is better than a hypothetical burger in another iteration of the multiverse. We've seen an explosion of AI capabilities in recent months. That has a lot of people worried about what it means to be a creator. Why do we need humans to write, for example, if ChatGPT can write? The reason ChatGPT's writing is impressive is the same reason there's still a place for things created by humans. Anyone old enough to have been on the internet in the heyday of America Online in the 1990s will remember this: When you were in a chat room, most the conversations were about being in a chat room: How long have you been on the internet? Isn't the internet cool? What other chat rooms do you like? Part of the appeal of the question “ASL?” – Age, Sex, Location? – was marveling over the fact you were chatting in real-time with a stranger several states away. Or maybe you remember when Uber or Lyft first came to your town. For the first year or two, likely every conversation you had with a driver was about how long they had been driving, about how quickly the service had grown in your town, which is better – Uber or Lyft?, or which nearby cities got which services first. The first few months ChatGPT was out, it was seemingly the only thing anyone on the internet talked about. But it wasn't because ChatGPT's writing was amazing. ChatGPT is a bad writer's idea of a good writer. It was because of the story: Wow, my computer is writing! Now that much of the novelty of ChatGPT has worn off, many of us are falling into the Trough of Disillusionment on the Gartner Hype Cycle. We're realizing ChatGPT is like a talking dog: It's impressive the dog can appear to talk, but it's not talking – it's just saying the words it's been taught. ChatGPT is very useful in some situations, but not as many as we had originally hoped. What made us talk about the internet while on the internet, talk about Uber while in Ubers, and talk about ChatGPT while chatting with ChatGPT was the story. Once the story behind the internet or Uber wore off, we started to appreciate them for their own utility. Part of what's cool about seeing the Sistine Chapel ceiling in VR is that – we're seeing it in VR. But even if that weren't impressive, what would still be impressive about the paintings would be more than just that they're amazing paintings. It's incredible to us a human could paint such a massive expanse. We think about the stories and myths of Michelangelo, up on that scaffolding, painting in isolation. Part of our appreciation of the Sistine Chapel ceiling lies outside the ceiling itself. While marveling at it, we can't help but think of Michelangelo's other masterpieces, such as the David or the Pietà. Lloyd Richards spent fourteen years writing Stone Maidens, and had almost no sales for decades. Suddenly, he sold 65,000 copies in a month. He was interviewed on the TODAY show, and got a book deal with a major publisher. How did he do it? His daughter made a TikTok account. The first video showed Lloyd at his desk, and explained what a good dad he was, how hard he had worked on Stone Maidens, and how great it would be if he made some sales. Then the #BookTok community did the rest. Stone Maidens is apparently a good book. But it's no better today than it was all those years it didn't sell. Most the comments on Lloyd's TikTok account – which now has over 400,000 followers – aren't about what a great book Stone Maidens is. They're about how Lloyd seems like such a nice guy, or how excited each commenter is to have contributed to his success. The study that started the myth that wine experts can't taste the difference between white and red wine didn't show that. The participants in the study literally weren't allowed to describe the two wines the same way – they couldn't use the same word for one as the other. It wasn't blindfolded – it was a white wine versus the same wine, dyed red. The study wasn't about taste at all: Participants weren't allowed to taste the wine – they were only allowed to smell. And wine experts? That depends on your definition of “expert”. They were undergraduate students, studying wine. They knew more than most of us, but were far from the top echelon of wine professionals. Most damning for this myth was that the same study casually mentions doing an informal blind test: The success rate of their participants in distinguishing the taste of white versus red wine: 70%. That this myth is false shouldn't detract from the point that even if it were true, it wouldn't matter. What the authors of this study found was not that wine enthusiasts couldn't tell between white and red wine, but that the appearance of a wine as white or red shaped their perceptions of the smell of the wine. Once you bake a cake, you can't turn it back into flour, sugar, butter, and eggs. You can't extract the taste of a wine from the color, the bottle, your mental image of where the grapes were grown and how the wine was made, or even the occasion for which you bought the wine. Something made by an AI can be awesome, either because it's really good at doing what it's supposed to, or because you appreciate it was made by an AI. Something made by a human is often awesome because of the story of the human who made it, and the story you as a human live as you interact with it. If you want to be relevant in the age of AI, learn how to bake your story into the product. Because AI can't bake. Image: Figures on a Beach by Louis Marcoussis About Your Host, David Kadavy David Kadavy is author of Mind Management, Not Time Management, The Heart to Start and Design for Hackers. Through the Love Your Work podcast, his Love Mondays newsletter, and self-publishing coaching David helps you make it as a creative. Follow David on: Twitter Instagram Facebook YouTube Subscribe to Love Your Work Apple Podcasts Overcast Spotify Stitcher YouTube RSS Email New bonus content on Patreon! I've been adding lots of new content to Patreon. Join the Patreon »       Show notes: https://kadavy.net/blog/posts/ai-cant-bake/

This past week I had the opportunity to try out a GLOBAL SERMON in a very remote part of the world -- East Africa. I was able to record the reaction of the local Kenyans on video. It's priceless. The impact and significance of Artificial Intelligence (AI) is profound and is taking the world by storm. It might be fair to say that AI could be the most transformative technology since the invention of the Internet itself. It is our belief that a powerful tool of this magnitude must be employed for the kingdom of God and the Gospel.In our labs, we have successfully proven the concept of what we are calling "Global Sermons" where we can take any sermon preached in English and have it "re-preached" in multiple languages like French, Spanish, Russian, and Chinese. Because AI tools are fundamentally designed to handle large amounts of computationally intensive language models, we can achieve a high-level of accuracy and natural-sounding voice that has never before been possible.We believe that this is our moment. "We do hear them speak in our tongues the wonderful works of God." — Acts 2:11Learn about Global Sermons:https://web.sermonaudio.com/sermons/53023646125199Learn about The Vault:www.sermonaudio.com/vaultLearn about FAME Mission:https://web.sermonaudio.com/sermons/102818010415180

This past week I had the opportunity to try out a GLOBAL SERMON in a very remote part of the world -- East Africa. I was able to record the reaction of the local Kenyans on video. It's priceless. --The impact and significance of Artificial Intelligence -AI- is profound and is taking the world by storm. It might be fair to say that AI could be the most transformative technology since the invention of the Internet itself. It is our belief that a powerful tool of this magnitude must be employed for the kingdom of God and the Gospel.--In our labs, we have successfully proven the concept of what we are calling -Global Sermons- where we can take any sermon preached in English and have it -re-preached- in multiple languages like French, Spanish, Russian, and Chinese. Because AI tools are fundamentally designed to handle large amounts of computationally intensive language models, we can achieve a high-level of accuracy and natural-sounding voice that has never before been possible.--We believe that this is our moment. ---We do hear them speak in our tongues the wonderful works of God.- - Acts 2-11--Learn about Global Sermons--https---web.sermonaudio.com-sermons-53023646125199--Learn about The Vault--www.sermonaudio.com-vault--Learn about FAME Mission--https---web.sermonaudio.com-sermons-102818010415180

Long before there was even TikTok, there was a company called Sherwin-Williams. Their famous logo showed a planet-sized can of paint pouring onto a globe, with the tagline “Cover The Earth.” They still use that logo today. But I think in spirt, if not in reality, they need to share their slogan with AI. Because AI is drenching its way into everything. We have a guest today, and he's our returning champion, attorney Rob Freund. Rob knows advertising and IP law for marketers as well as anyone I've ever met. And we're going to have a wide-ranging discussion with Rob about AI and the law as it applies to copy and other topics of interest to you and me. I am constantly impressed by Rob's savvy posts on Twitter, and sometimes astounded by the stories and examples he comes up with. We'll talk about some of them today. And I stand in the company of giants who are also impressed: The Wall Street Journal, The New York Times, Bloomberg Law, Vox and Forbes. They've all quoted him. Plus, he's lectured about social media law at the University of Southern California and other major institutions, in the U.S. and in Europe. We started by talking about an unusual and slightly disturbing thing that AI said regarding Ben Settle, which Ben posted on Twitter… and a really disturbing story about a lawyer who counted on AI in a way that may get him in trouble with the court. Rob found this story in The New York Times and posted it on Twitter as well. We also tackled important issues like: • Does using AI open a copywriter up to legal liability for plagiarism/copyright infringement? What can we do to make sure we're on the right side of the law? • From an intellectual property rights perspective -- if you use AI to help you write your copy, who owns the work? • What are the legal implications of people using deep fake technology to create testimonials and phony images of celebrities? Or AI fake voices? And, looking into the future, we asked Rob this question: In the same vein as any developing technology that starts out with no regulation, like the wild west, but eventually starts to get regulated… How do you see AI regulation, especially in the advertising and IP spaces, developing? To connect with Rob: Instagram @robertfreundlaw Twitter @robertfreundlaw https://robertfreundlaw.com Download.

Because AI is all the rage, Kate & Ryan ask ChatGPT what are some of the top myths about Agile.  This week its part II with myths 11 thru 20

Because AI is all the rage, Kate & Ryan ask ChatGPT what the top myths about Agile

The impact and significance of Artificial Intelligence -AI- is profound and is taking the world by storm. It might be fair to say that AI could be the most transformative technology since the invention of the Internet itself. With any revolutionary technology, there are pros and cons that could be argued as to its use. However, it is our belief that a powerful tool of this magnitude must be employed for the kingdom of God and the Gospel.--In our labs, we have successfully proven the concept of what we are calling -Global Sermons- where we can take any sermon preached in English and have it -re-preached- in multiple languages like French, Spanish, Russian, and Chinese. Because AI tools are fundamentally designed to handle large amounts of computationally intensive language models, we can achieve a high-level of accuracy and natural-sounding voice that has never before been possible.--We believe that this is our moment. ---We do hear them speak in our tongues the wonderful works of God.- - Acts 2-11--Learn about The Vault--www.sermonaudio.com-vault

The impact and significance of Artificial Intelligence (AI) is profound and is taking the world by storm. It might be fair to say that AI could be the most transformative technology since the invention of the Internet itself. With any revolutionary technology, there are pros and cons that could be argued as to its use. However, it is our belief that a powerful tool of this magnitude must be employed for the kingdom of God and the Gospel.In our labs, we have successfully proven the concept of what we are calling "Global Sermons" where we can take any sermon preached in English and have it "re-preached" in multiple languages like French, Spanish, Russian, and Chinese. Because AI tools are fundamentally designed to handle large amounts of computationally intensive language models, we can achieve a high-level of accuracy and natural-sounding voice that has never before been possible.We believe that this is our moment. "We do hear them speak in our tongues the wonderful works of God." — Acts 2:11Learn about The Vault:www.sermonaudio.com/vault

"欢迎来到英文小酒馆的迷你双语板块【Buzzword Mix】-新词特饮，短短几分钟，让不同段位的你掌握最新最地道的英文谈资！关注公号【璐璐的英文小酒馆】，获取更多有趣节目内容和文稿哦~" In today's Buzzword Mix, our buzzword is Aigiarism. To talk about that, let's talk about ChatGPT first. Now I'm pretty sure even if you're not into technology at all, you have heard of it. It is one of the most significant language models ever created because it is capable of generating human-like text and can perform a variety of tasks, including translation, summarization, and writing code. 即使你对科技再不感冒, 相信你也听过ChatGPT, 也知道它的功能超级强大, 可以迅速生成大段的以假乱真的文本. While undeniably innovative and exciting, ChatGPT might have a dark side and people are starting to see it. 很多人都觉得ChatGPT很强大很好玩很创新, 也有不少人产生了深深的忧患意识, 这个要说到咱们今天的buzzword.First of all, what does Aigiarism mean, like many of the buzzwords we talked about before, it is a combination of two words. 这个词前半部分就是AI人工智能, 后半部分是Plagiarism. Plagiarism一般被翻译成剽窃或者是抄袭. In simple terms, Aigiarism means plagiarizing using AI, sometimes it's also called AI assisted plagiarism. 说白了就是通过AI技术进行了抄袭和学术剽窃行为. Plagiarism, by definition, is taking someone else's work and presenting it as your own. When you take free content generated from an AI, it falls into the category of ‘not your work', and by presenting it as your own, you are committing plagiarism.虽然很多人可能会狡辩说, 我用AI只是用了一个科技去生成文本, 我也没有抄谁的, 但这种把不是你自己创造的内容, 当做是自己的提交上去, 本来就是plagiarism的行为. The word “Aigiarism” exists as a result of AI advancement. Since ChatGPT has made the tour worldwide, people have noticed that they could use it to generate free content for papers, articles, and other written forms. 相信试用过ChatGPT的小伙伴都知道, 比如说你想要写篇文章, 其实你只要告诉他, 你希望这个文章里面是大概写什么的, 它就会自动帮你生成一个文本, 而且还看起来非常像是人写出来的. Therefore Aigiarism is directly committing an offense to academic integrity. 大部分学术界的担心都是它会破坏academic integrity, 一般被翻译成学术诚信, 学术诚信的反面就是academic misconduct, 学术不端. Now with the rise of AI tools like text generators, things have gotten to a more complex level where the line between Aigiarism and original content has become blurred.学术剽窃或者学术查重这些词一直都存在, 但是现在有了AI强有力的工具, 怎么界定Aigiarism就变得很复杂. Because AI generated text can often mimic human writing styles and create articles, essays, and even books that are difficult to distinguish from human written work. 这是因为随着技术的进步, 由AI生成的文本, 比如说ChatGPT它生成的文本就可以很好地模仿真人写作的风格, 让一般人很难去判定这个到底是AI写的还是人写的. And this has led to new moral and legal problems for authors, publishers, and content creators who are trying to protect their intellectual property in a time when AI technology is changing and developing super fast.所以这就也让作者、出版商, 包括像我这样的内容主都面临着如何保护自己的intellectual property知识产权这样的一个问题. These worries are pretty fair because originality and academic integrity are foundational standards, not just in the academic world, but in content creation in general.其实这种忧患并不是空穴来风, 因为不光是学术界, 只要涉及原创内容的出产, 那么originality原创性和academic integrity学术诚信都是基石一样的东西.

How do you like your Mammoth cooked? Australian startup Vow just served lab-grown Mammoth Meatballs and raised $50M for it. Lululemon's stock jumped 13% yesterday, but Lulu made the wrong bet on your workouts. And Elon Musk, Steve Wozniak, and 1,000 other tech leaders just signed a letter demanding that AI work stop immediately. Because AI could cure cancer, but it could also end civilization. $LULU $GOOG $TSLA Follow The Best One Yet on Instagram, Twitter, and Tiktok: @tboypod And now watch us on Youtube Want a Shoutout on the pod? Fill out this form Got the Best Fact Yet? We got a form for that too Learn more about your ad choices. Visit podcastchoices.com/adchoices

I went over to the OpenAI offices in San Fransisco to ask the Chief Scientist and cofounder of OpenAI, Ilya Sutskever, about:* time to AGI* leaks and spies* what's after generative models* post AGI futures* working with Microsoft and competing with Google* difficulty of aligning superhuman AIWatch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform. Read the full transcript here. Follow me on Twitter for updates on future episodes.As always, the most helpful thing you can do is just to share the podcast - send it to friends, group chats, Twitter, Reddit, forums, and wherever else men and women of fine taste congregate.If you have the means and have enjoyed my podcast, I would appreciate your support via a paid subscriptions on Substack.Timestamps(00:00) - Time to AGI(05:57) - What's after generative models?(10:57) - Data, models, and research(15:27) - Alignment(20:53) - Post AGI Future(26:56) - New ideas are overrated(36:22) - Is progress inevitable?(41:27) - Future BreakthroughsTranscriptTime to AGIDwarkesh Patel  Today I have the pleasure of interviewing Ilya Sutskever, who is the Co-founder and Chief Scientist of OpenAI. Ilya, welcome to The Lunar Society.Ilya Sutskever  Thank you, happy to be here.Dwarkesh Patel  First question and no humility allowed. There are not that many scientists who will make a big breakthrough in their field, there are far fewer scientists who will make multiple independent breakthroughs that define their field throughout their career, what is the difference? What distinguishes you from other researchers? Why have you been able to make multiple breakthroughs in your field?Ilya Sutskever  Thank you for the kind words. It's hard to answer that question. I try really hard, I give it everything I've got and that has worked so far. I think that's all there is to it. Dwarkesh Patel  Got it. What's the explanation for why there aren't more illicit uses of GPT? Why aren't more foreign governments using it to spread propaganda or scam grandmothers?Ilya Sutskever  Maybe they haven't really gotten to do it a lot. But it also wouldn't surprise me if some of it was going on right now. I can certainly imagine they would be taking some of the open source models and trying to use them for that purpose. For sure I would expect this to be something they'd be interested in the future.Dwarkesh Patel  It's technically possible they just haven't thought about it enough?Ilya Sutskever  Or haven't done it at scale using their technology. Or maybe it is happening, which is annoying. Dwarkesh Patel  Would you be able to track it if it was happening? Ilya Sutskever I think large-scale tracking is possible, yes. It requires special operations but it's possible.Dwarkesh Patel  Now there's some window in which AI is very economically valuable, let's say on the scale of airplanes, but we haven't reached AGI yet. How big is that window?Ilya Sutskever  It's hard to give a precise answer and it's definitely going to be a good multi-year window. It's also a question of definition. Because AI, before it becomes AGI, is going to be increasingly more valuable year after year in an exponential way. In hindsight, it may feel like there was only one year or two years because those two years were larger than the previous years. But I would say that already, last year, there has been a fair amount of economic value produced by AI. Next year is going to be larger and larger after that. So I think it's going to be a good multi-year chunk of time where that's going to be true, from now till AGI pretty much. Dwarkesh Patel  Okay. Because I'm curious if there's a startup that's using your model, at some point if you have AGI there's only one business in the world, it's OpenAI. How much window does any business have where they're actually producing something that AGI can't produce?Ilya Sutskever  It's the same question as asking how long until AGI. It's a hard question to answer. I hesitate to give you a number. Also because there is this effect where optimistic people who are working on the technology tend to underestimate the time it takes to get there. But the way I ground myself is by thinking about the self-driving car. In particular, there is an analogy where if you look at the size of a Tesla, and if you look at its self-driving behavior, it looks like it does everything. But it's also clear that there is still a long way to go in terms of reliability. And we might be in a similar place with respect to our models where it also looks like we can do everything, and at the same time, we will need to do some more work until we really iron out all the issues and make it really good and really reliable and robust and well behaved.Dwarkesh Patel  By 2030, what percent of GDP is AI? Ilya Sutskever  Oh gosh, very hard to answer that question.Dwarkesh Patel Give me an over-under. Ilya Sutskever The problem is that my error bars are in log scale. I could imagine a huge percentage, I could imagine a really disappointing small percentage at the same time. Dwarkesh Patel  Okay, so let's take the counterfactual where it is a small percentage. Let's say it's 2030 and not that much economic value has been created by these LLMs. As unlikely as you think this might be, what would be your best explanation right now of why something like this might happen?Ilya Sutskever  I really don't think that's a likely possibility, that's the preface to the comment. But if I were to take the premise of your question, why were things disappointing in terms of real-world impact? My answer would be reliability. If it somehow ends up being the case that you really want them to be reliable and they ended up not being reliable, or if reliability turned out to be harder than we expect. I really don't think that will be the case. But if I had to pick one and you were telling me — hey, why didn't things work out? It would be reliability. That you still have to look over the answers and double-check everything. That just really puts a damper on the economic value that can be produced by those systems.Dwarkesh Patel  Got it. They will be technologically mature, it's just the question of whether they'll be reliable enough.Ilya Sutskever  Well, in some sense, not reliable means not technologically mature.What's after generative models?Dwarkesh Patel  Yeah, fair enough. What's after generative models? Before, you were working on reinforcement learning. Is this basically it? Is this the paradigm that gets us to AGI? Or is there something after this?Ilya Sutskever  I think this paradigm is gonna go really, really far and I would not underestimate it. It's quite likely that this exact paradigm is not quite going to be the AGI form factor. I hesitate to say precisely what the next paradigm will be but it will probably involve integration of all the different ideas that came in the past.Dwarkesh Patel  Is there some specific one you're referring to?Ilya Sutskever  It's hard to be specific.Dwarkesh Patel  So you could argue that next-token prediction can only help us match human performance and maybe not surpass it? What would it take to surpass human performance?Ilya Sutskever  I challenge the claim that next-token prediction cannot surpass human performance. On the surface, it looks like it cannot. It looks like if you just learn to imitate, to predict what people do, it means that you can only copy people. But here is a counter argument for why it might not be quite so. If your base neural net is smart enough, you just ask it — What would a person with great insight, wisdom, and capability do? Maybe such a person doesn't exist, but there's a pretty good chance that the neural net will be able to extrapolate how such a person would behave. Do you see what I mean?Dwarkesh Patel  Yes, although where would it get that sort of insight about what that person would do? If not from…Ilya Sutskever  From the data of regular people. Because if you think about it, what does it mean to predict the next token well enough? It's actually a much deeper question than it seems. Predicting the next token well means that you understand the underlying reality that led to the creation of that token. It's not statistics. Like it is statistics but what is statistics? In order to understand those statistics to compress them, you need to understand what is it about the world that creates this set of statistics? And so then you say — Well, I have all those people. What is it about people that creates their behaviors? Well they have thoughts and their feelings, and they have ideas, and they do things in certain ways. All of those could be deduced from next-token prediction. And I'd argue that this should make it possible, not indefinitely but to a pretty decent degree to say — Well, can you guess what you'd do if you took a person with this characteristic and that characteristic? Like such a person doesn't exist but because you're so good at predicting the next token, you should still be able to guess what that person who would do. This hypothetical, imaginary person with far greater mental ability than the rest of us.Dwarkesh Patel  When we're doing reinforcement learning on these models, how long before most of the data for the reinforcement learning is coming from AI and not humans?Ilya Sutskever  Already most of the default enforcement learning is coming from AIs. The humans are being used to train the reward function. But then the reward function and its interaction with the model is automatic and all the data that's generated during the process of reinforcement learning is created by AI. If you look at the current technique/paradigm, which is getting some significant attention because of chatGPT, Reinforcement Learning from Human Feedback (RLHF). The human feedback has been used to train the reward function and then the reward function is being used to create the data which trains the model.Dwarkesh Patel  Got it. And is there any hope of just removing a human from the loop and have it improve itself in some sort of AlphaGo way?Ilya Sutskever  Yeah, definitely. The thing you really want is for the human teachers that teach the AI to collaborate with an AI. You might want to think of it as being in a world where the human teachers do 1% of the work and the AI does 99% of the work. You don't want it to be 100% AI. But you do want it to be a human-machine collaboration, which teaches the next machine.Dwarkesh Patel  I've had a chance to play around these models and they seem bad at multi-step reasoning. While they have been getting better, what does it take to really surpass that barrier?Ilya Sutskever  I think dedicated training will get us there. More and more improvements to the base models will get us there. But fundamentally I also don't feel like they're that bad at multi-step reasoning. I actually think that they are bad at mental multistep reasoning when they are not allowed to think out loud. But when they are allowed to think out loud, they're quite good. And I expect this to improve significantly, both with better models and with special training.Data, models, and researchDwarkesh Patel  Are you running out of reasoning tokens on the internet? Are there enough of them?Ilya Sutskever  So for context on this question, there are claims that at some point we will run out of tokens, in general, to train those models. And yeah, I think this will happen one day and by the time that happens, we need to have other ways of training models, other ways of productively improving their capabilities and sharpening their behavior, making sure they're doing exactly, precisely what you want, without more data.Dwarkesh Patel You haven't run out of data yet? There's more? Ilya Sutskever Yeah, I would say the data situation is still quite good. There's still lots to go. But at some point the data will run out.Dwarkesh Patel  What is the most valuable source of data? Is it Reddit, Twitter, books? Where would you train many other tokens of other varieties for?Ilya Sutskever  Generally speaking, you'd like tokens which are speaking about smarter things, tokens which are more interesting. All the sources which you mentioned are valuable.Dwarkesh Patel  So maybe not Twitter. But do we need to go multimodal to get more tokens? Or do we still have enough text tokens left?Ilya Sutskever  I think that you can still go very far in text only but going multimodal seems like a very fruitful direction.Dwarkesh Patel  If you're comfortable talking about this, where is the place where we haven't scraped the tokens yet?Ilya Sutskever  Obviously I can't answer that question for us but I'm sure that for everyone there is a different answer to that question.Dwarkesh Patel  How many orders of magnitude improvement can we get, not from scale or not from data, but just from algorithmic improvements? Ilya Sutskever  Hard to answer but I'm sure there is some.Dwarkesh Patel  Is some a lot or some a little?Ilya Sutskever  There's only one way to find out.Dwarkesh Patel  Okay. Let me get your quickfire opinions about these different research directions. Retrieval transformers. So it's just somehow storing the data outside of the model itself and retrieving it somehow.Ilya Sutskever  Seems promising. Dwarkesh Patel But do you see that as a path forward?Ilya Sutskever  It seems promising.Dwarkesh Patel  Robotics. Was it the right step for Open AI to leave that behind?Ilya Sutskever  Yeah, it was. Back then it really wasn't possible to continue working in robotics because there was so little data. Back then if you wanted to work on robotics, you needed to become a robotics company. You needed to have a really giant group of people working on building robots and maintaining them. And even then, if you're gonna have 100 robots, it's a giant operation already, but you're not going to get that much data. So in a world where most of the progress comes from the combination of compute and data, there was no path to data on robotics. So back in the day, when we made a decision to stop working in robotics, there was no path forward. Dwarkesh Patel Is there one now? Ilya Sutskever  I'd say that now it is possible to create a path forward. But one needs to really commit to the task of robotics. You really need to say — I'm going to build many thousands, tens of thousands, hundreds of thousands of robots, and somehow collect data from them and find a gradual path where the robots are doing something slightly more useful. And then the data that is obtained and used to train the models, and they do something that's slightly more useful. You could imagine it's this gradual path of improvement, where you build more robots, they do more things, you collect more data, and so on. But you really need to be committed to this path. If you say, I want to make robotics happen, that's what you need to do. I believe that there are companies who are doing exactly that. But you need to really love robots and need to be really willing to solve all the physical and logistical problems of dealing with them. It's not the same as software at all. I think one could make progress in robotics today, with enough motivation.Dwarkesh Patel  What ideas are you excited to try but you can't because they don't work well on current hardware?Ilya Sutskever  I don't think current hardware is a limitation. It's just not the case.Dwarkesh Patel  Got it. But anything you want to try you can just spin it up? Ilya Sutskever  Of course. You might wish that current hardware was cheaper or maybe it would be better if it had higher memory processing bandwidth let's say. But by and large hardware is just not an issue.AlignmentDwarkesh Patel  Let's talk about alignment. Do you think we'll ever have a mathematical definition of alignment?Ilya Sutskever  A mathematical definition is unlikely. Rather than achieving one mathematical definition, I think we will achieve multiple definitions that look at alignment from different aspects. And that this is how we will get the assurance that we want. By which I mean you can look at the behavior in various tests, congruence, in various adversarial stress situations, you can look at how the neural net operates from the inside. You have to look at several of these factors at the same time.Dwarkesh Patel  And how sure do you have to be before you release a model in the wild? 100%? 95%?Ilya Sutskever  Depends on how capable the model is. The more capable the model, the more confident we need to be. Dwarkesh Patel Alright, so let's say it's something that's almost AGI. Where is AGI?Ilya Sutskever Depends on what your AGI can do. Keep in mind that AGI is an ambiguous term. Your average college undergrad is an AGI, right? There's significant ambiguity in terms of what is meant by AGI. Depending on where you put this mark you need to be more or less confident.Dwarkesh Patel  You mentioned a few of the paths toward alignment earlier, what is the one you think is most promising at this point?Ilya Sutskever  I think that it will be a combination. I really think that you will not want to have just one approach. People want to have a combination of approaches. Where you spend a lot of compute adversarially to find any mismatch between the behavior you want it to teach and the behavior that it exhibits.We look into the neural net using another neural net to understand how it operates on the inside. All of them will be necessary. Every approach like this reduces the probability of misalignment. And you also want to be in a world where your degree of alignment keeps increasing faster than the capability of the models.Dwarkesh Patel  Do you think that the approaches we've taken to understand the model today will be applicable to the actual super-powerful models? Or how applicable will they be? Is it the same kind of thing that will work on them as well or? Ilya Sutskever  It's not guaranteed. I would say that right now, our understanding of our models is still quite rudimentary. We've made some progress but much more progress is possible. And so I would expect that ultimately, the thing that will really succeed is when we will have a small neural net that is well understood that's been given the task to study the behavior of a large neural net that is not understood, to verify. Dwarkesh Patel  By what point is most of the AI research being done by AI?Ilya Sutskever  Today when you use Copilot, how do you divide it up? So I expect at some point you ask your descendant of ChatGPT, you say — Hey, I'm thinking about this and this. Can you suggest fruitful ideas I should try? And you would actually get fruitful ideas. I don't think that's gonna make it possible for you to solve problems you couldn't solve before.Dwarkesh Patel  Got it. But it's somehow just telling the humans giving them ideas faster or something. It's not itself interacting with the research?Ilya Sutskever  That was one example. You could slice it in a variety of ways. But the bottleneck there is good ideas, good insights and that's something that the neural nets could help us with.Dwarkesh Patel  If you're designing a billion-dollar prize for some sort of alignment research result or product, what is the concrete criterion you would set for that billion-dollar prize? Is there something that makes sense for such a prize?Ilya Sutskever  It's funny that you asked, I was actually thinking about this exact question. I haven't come up with the exact criterion yet. Maybe a prize where we could say that two years later, or three years or five years later, we look back and say like that was the main result. So rather than say that there is a prize committee that decides right away, you wait for five years and then award it retroactively.Dwarkesh Patel  But there's no concrete thing we can identify as you solve this particular problem and you've made a lot of progress?Ilya Sutskever  A lot of progress, yes. I wouldn't say that this would be the full thing.Dwarkesh Patel  Do you think end-to-end training is the right architecture for bigger and bigger models? Or do we need better ways of just connecting things together?Ilya Sutskever  End-to-end training is very promising. Connecting things together is very promising. Dwarkesh Patel  Everything is promising.Dwarkesh Patel  So Open AI is projecting revenues of a billion dollars in 2024. That might very well be correct but I'm just curious, when you're talking about a new general-purpose technology, how do you estimate how big a windfall it'll be? Why that particular number? Ilya Sutskever  We've had a product for quite a while now, back from the GPT-3 days, from two years ago through the API and we've seen how it grew. We've seen how the response to DALL-E has grown as well and you see how the response to ChatGPT is, and all of this gives us information that allows us to make relatively sensible extrapolations of anything. Maybe that would be one answer. You need to have data, you can't come up with those things out of thin air because otherwise, your error bars are going to be like 100x in each direction.Dwarkesh Patel  But most exponentials don't stay exponential especially when they get into bigger and bigger quantities, right? So how do you determine in this case?Ilya Sutskever  Would you bet against AI?Post AGI futureDwarkesh Patel  Not after talking with you. Let's talk about what a post-AGI future looks like. I'm guessing you're working 80-hour weeks towards this grand goal that you're really obsessed with. Are you going to be satisfied in a world where you're basically living in an AI retirement home? What are you personally doing after AGI comes?Ilya Sutskever  The question of what I'll be doing or what people will be doing after AGI comes is a very tricky question. Where will people find meaning? But I think that that's something that AI could help us with. One thing I imagine is that we will be able to become more enlightened because we interact with an AGI which will help us see the world more correctly, and become better on the inside as a result of interacting. Imagine talking to the best meditation teacher in history, that will be a helpful thing. But I also think that because the world will change a lot, it will be very hard for people to understand what is happening precisely and how to really contribute. One thing that I think some people will choose to do is to become part AI. In order to really expand their minds and understanding and to really be able to solve the hardest problems that society will face then.Dwarkesh Patel  Are you going to become part AI?Ilya Sutskever  It is very tempting. Dwarkesh Patel  Do you think there'll be physically embodied humans in the year 3000? Ilya Sutskever  3000? How do I know what's gonna happen in 3000?Dwarkesh Patel  Like what does it look like? Are there still humans walking around on Earth? Or have you guys thought concretely about what you actually want this world to look like? Ilya Sutskever  Let me describe to you what I think is not quite right about the question. It implies we get to decide how we want the world to look like. I don't think that picture is correct. Change is the only constant. And so of course, even after AGI is built, it doesn't mean that the world will be static. The world will continue to change, the world will continue to evolve. And it will go through all kinds of transformations. I don't think anyone has any idea of how the world will look like in 3000. But I do hope that there will be a lot of descendants of human beings who will live happy, fulfilled lives where they're free to do as they see fit. Or they are the ones who are solving their own problems. One world which I would find very unexciting is one where we build this powerful tool, and then the government said — Okay, so the AGI said that society should be run in such a way and now we should run society in such a way. I'd much rather have a world where people are still free to make their own mistakes and suffer their consequences and gradually evolve morally and progress forward on their own, with the AGI providing more like a base safety net.Dwarkesh Patel  How much time do you spend thinking about these kinds of things versus just doing the research?Ilya Sutskever  I do think about those things a fair bit. They are very interesting questions.Dwarkesh Patel  The capabilities we have today, in what ways have they surpassed where we expected them to be in 2015? And in what ways are they still not where you'd expected them to be by this point?Ilya Sutskever  In fairness, it's sort of what I expected in 2015. In 2015, my thinking was a lot more — I just don't want to bet against deep learning. I want to make the biggest possible bet on deep learning. I don't know how, but it will figure it out.Dwarkesh Patel  But is there any specific way in which it's been more than you expected or less than you expected? Like some concrete prediction out of 2015 that's been bounced?Ilya Sutskever  Unfortunately, I don't remember concrete predictions I made in 2015. But I definitely think that overall, in 2015, I just wanted to move to make the biggest bet possible on deep learning, but I didn't know exactly. I didn't have a specific idea of how far things will go in seven years. Well, no in 2015, I did have all these best with people in 2016, maybe 2017, that things will go really far. But specifics. So it's like, it's both, it's both the case that it surprised me and I was making these aggressive predictions. But maybe I believed them only 50% on the inside. Dwarkesh Patel  What do you believe now that even most people at OpenAI would find far fetched?Ilya Sutskever  Because we communicate a lot at OpenAI people have a pretty good sense of what I think and we've really reached the point at OpenAI where we see eye to eye on all these questions.Dwarkesh Patel  Google has its custom TPU hardware, it has all this data from all its users, Gmail, and so on. Does it give them an advantage in terms of training bigger models and better models than you?Ilya Sutskever  At first, when the TPU came out I was really impressed and I thought — wow, this is amazing. But that's because I didn't quite understand hardware back then. What really turned out to be the case is that TPUs and GPUs are almost the same thing. They are very, very similar. The GPU chip is a little bit bigger, the TPU chip is a little bit smaller, maybe a little bit cheaper. But then they make more GPUs and TPUs so the GPUs might be cheaper after all.But fundamentally, you have a big processor, and you have a lot of memory and there is a bottleneck between those two. And the problem that both the TPU and the GPU are trying to solve is that the amount of time it takes you to move one floating point from the memory to the processor, you can do several hundred floating point operations on the processor, which means that you have to do some kind of batch processing. And in this sense, both of these architectures are the same. So I really feel like in some sense, the only thing that matters about hardware is cost per flop and overall systems cost.Dwarkesh Patel  There isn't that much difference?Ilya Sutskever  Actually, I don't know. I don't know what the TPU costs are but I would suspect that if anything, TPUs are probably more expensive because there are less of them.New ideas are overratedDwarkesh Patel  When you are doing your work, how much of the time is spent configuring the right initializations? Making sure the training run goes well and getting the right hyperparameters, and how much is it just coming up with whole new ideas?Ilya Sutskever  I would say it's a combination. Coming up with whole new ideas is a modest part of the work. Certainly coming up with new ideas is important but even more important is to understand the results, to understand the existing ideas, to understand what's going on. A neural net is a very complicated system, right? And you ran it, and you get some behavior, which is hard to understand. What's going on? Understanding the results, figuring out what next experiment to run, a lot of the time is spent on that. Understanding what could be wrong, what could have caused the neural net to produce a result which was not expected. I'd say a lot of time is spent coming up with new ideas as well. I don't like this framing as much. It's not that it's false but the main activity is actually understanding.Dwarkesh Patel  What do you see as the difference between the two?Ilya Sutskever  At least in my mind, when you say come up with new ideas, I'm like — Oh, what happens if it did such and such? Whereas understanding it's more like — What is this whole thing? What are the real underlying phenomena that are going on? What are the underlying effects? Why are we doing things this way and not another way? And of course, this is very adjacent to what can be described as coming up with ideas. But the understanding part is where the real action takes place.Dwarkesh Patel  Does that describe your entire career? If you think back on something like ImageNet, was that more new idea or was that more understanding?Ilya Sutskever  Well, that was definitely understanding. It was a new understanding of very old things.Dwarkesh Patel  What has the experience of training on Azure been like?Ilya Sutskever  Fantastic. Microsoft has been a very, very good partner for us. They've really helped take Azure and bring it to a point where it's really good for ML and we're super happy with it.Dwarkesh Patel  How vulnerable is the whole AI ecosystem to something that might happen in Taiwan? So let's say there's a tsunami in Taiwan or something, what happens to AI in general?Ilya Sutskever  It's definitely going to be a significant setback. No one will be able to get more compute for a few years. But I expect compute will spring up. For example, I believe that Intel has fabs just like a few generations ago. So that means that if Intel wanted to they could produce something GPU-like from four years ago. But yeah, it's not the best, I'm actually not sure if my statement about Intel is correct, but I do know that there are fabs outside of Taiwan, they're just not as good. But you can still use them and still go very far with them. It's just cost, it's just a setback.Cost of modelsDwarkesh Patel  Would inference get cost prohibitive as these models get bigger and bigger?Ilya Sutskever  I have a different way of looking at this question. It's not that inference will become cost prohibitive. Inference of better models will indeed become more expensive. But is it prohibitive? That depends on how useful it is. If it is more useful than it is expensive then it is not prohibitive. To give you an analogy, suppose you want to talk to a lawyer. You have some case or need some advice or something, you're perfectly happy to spend $400 an hour. Right? So if your neural net could give you really reliable legal advice, you'd say — I'm happy to spend $400 for that advice. And suddenly inference becomes very much non-prohibitive. The question is, can a neural net produce an answer good enough at this cost? Dwarkesh Patel  Yes. And you will just have price discrimination in different models?Ilya Sutskever  It's already the case today. On our product, the API serves multiple neural nets of different sizes and different customers use different neural nets of different sizes depending on their use case. If someone can take a small model and fine-tune it and get something that's satisfactory for them, they'll use that. But if someone wants to do something more complicated and more interesting, they'll use the biggest model. Dwarkesh Patel  How do you prevent these models from just becoming commodities where these different companies just bid each other's prices down until it's basically the cost of the GPU run? Ilya Sutskever  Yeah, there's without question a force that's trying to create that. And the answer is you got to keep on making progress. You got to keep improving the models, you gotta keep on coming up with new ideas and making our models better and more reliable, more trustworthy, so you can trust their answers. All those things.Dwarkesh Patel  Yeah. But let's say it's 2025 and somebody is offering the model from 2024 at cost. And it's still pretty good. Why would people use a new one from 2025 if the one from just a year older is even better?Ilya Sutskever  There are several answers there. For some use cases that may be true. There will be a new model for 2025, which will be driving the more interesting use cases. There is also going to be a question of inference cost. If you can do research to serve the same model at less cost. The same model will cost different amounts to serve for different companies. I can also imagine some degree of specialization where some companies may try to specialize in some area and be stronger compared to other companies. And to me that may be a response to commoditization to some degree.Dwarkesh Patel  Over time do the research directions of these different companies converge or diverge? Are they doing similar and similar things over time? Or are they branching off into different areas? Ilya Sutskever  I'd say in the near term, it looks like there is convergence. I expect there's going to be a convergence-divergence-convergence behavior, where there is a lot of convergence on the near term work, there's going to be some divergence on the longer term work. But then once the longer term work starts to fruit, there will be convergence again,Dwarkesh Patel  Got it. When one of them finds the most promising area, everybody just…Ilya Sutskever  That's right. There is obviously less publishing now so it will take longer before this promising direction gets rediscovered. But that's how I would imagine the thing is going to be. Convergence, divergence, convergence.Dwarkesh Patel  Yeah. We talked about this a little bit at the beginning. But as foreign governments learn about how capable these models are, are you worried about spies or some sort of attack to get your weights or somehow abuse these models and learn about them?Ilya Sutskever  Yeah, you absolutely can't discount that. Something that we try to guard against to the best of our ability, but it's going to be a problem for everyone who's building this. Dwarkesh Patel  How do you prevent your weights from leaking? Ilya Sutskever  You have really good security people.Dwarkesh Patel  How many people have the ability to SSH into the machine with the weights?Ilya Sutskever  The security people have done a really good job so I'm really not worried about the weights being leaked.Dwarkesh Patel  What kinds of emergent properties are you expecting from these models at this scale? Is there something that just comes about de novo?Ilya Sutskever  I'm sure really new surprising properties will come up, I would not be surprised. The thing which I'm really excited about, the things which I'd like to see is — reliability and controllability. I think that this will be a very, very important class of emergent properties. If you have reliability and controllability that helps you solve a lot of problems. Reliability means you can trust the model's output, controllability means you can control it. And we'll see but it will be very cool if those emergent properties did exist.Dwarkesh Patel  Is there some way you can predict that in advance? What will happen in this parameter count, what will happen in that parameter count?Ilya Sutskever  I think it's possible to make some predictions about specific capabilities though it's definitely not simple and you can't do it in a super fine-grained way, at least today. But getting better at that is really important. And anyone who is interested and who has research ideas on how to do that, that can be a valuable contribution.Dwarkesh Patel  How seriously do you take these scaling laws? There's a paper that says — You need this many orders of magnitude more to get all the reasoning out? Do you take that seriously or do you think it breaks down at some point?Ilya Sutskever  The thing is that the scaling law tells you what happens to your log of your next word prediction accuracy, right? There is a whole separate challenge of linking next-word prediction accuracy to reasoning capability. I do believe that there is a link but this link is complicated. And we may find that there are other things that can give us more reasoning per unit effort. You mentioned reasoning tokens, I think they can be helpful. There can probably be some things that help.Dwarkesh Patel  Are you considering just hiring humans to generate tokens for you? Or is it all going to come from stuff that already exists out there?Ilya Sutskever  I think that relying on people to teach our models to do things, especially to make sure that they are well-behaved and they don't produce false things is an extremely sensible thing to do. Is progress inevitable?Dwarkesh Patel  Isn't it odd that we have the data we needed exactly at the same time as we have the transformer at the exact same time that we have these GPUs? Like is it odd to you that all these things happened at the same time or do you not see it that way?Ilya Sutskever  It is definitely an interesting situation that is the case. I will say that it is odd and it is less odd on some level. Here's why it's less odd — what is the driving force behind the fact that the data exists, that the GPUs exist, and that the transformers exist? The data exists because computers became better and cheaper, we've got smaller and smaller transistors. And suddenly, at some point, it became economical for every person to have a personal computer. Once everyone has a personal computer, you really want to connect them to the network, you get the internet. Once you have the internet, you suddenly have data appearing in great quantities. The GPUs were improving concurrently because you have smaller and smaller transistors and you're looking for things to do with them. Gaming turned out to be a thing that you could do. And then at some point, Nvidia said — the gaming GPU, I might turn it into a general purpose GPU computer, maybe someone will find it useful. It turns out it's good for neural nets. It could have been the case that maybe the GPU would have arrived five years later, ten years later. Let's suppose gaming wasn't the thing. It's kind of hard to imagine, what does it mean if gaming isn't a thing? But maybe there was a counterfactual world where GPUs arrived five years after the data or five years before the data, in which case maybe things wouldn't have been as ready to go as they are now. But that's the picture which I imagine. All this progress in all these dimensions is very intertwined. It's not a coincidence. You don't get to pick and choose in which dimensions things improve.Dwarkesh Patel  How inevitable is this kind of progress? Let's say you and Geoffrey Hinton and a few other pioneers were never born. Does the deep learning revolution happen around the same time? How much is it delayed?Ilya Sutskever  Maybe there would have been some delay. Maybe like a year delayed? Dwarkesh Patel Really? That's it? Ilya Sutskever It's really hard to tell. I hesitate to give a longer answer because — GPUs will keep on improving. I cannot see how someone would not have discovered it. Because here's the other thing. Let's suppose no one has done it, computers keep getting faster and better. It becomes easier and easier to train these neural nets because you have bigger GPUs, so it takes less engineering effort to train one. You don't need to optimize your code as much. When the ImageNet data set came out, it was huge and it was very, very difficult to use. Now imagine you wait for a few years, and it becomes very easy to download and people can just tinker. A modest number of years maximum would be my guess. I hesitate to give a lot longer answer though. You can't re-run the world you don't know. Dwarkesh Patel  Let's go back to alignment for a second. As somebody who deeply understands these models, what is your intuition of how hard alignment will be?Ilya Sutskever  At the current level of capabilities, we have a pretty good set of ideas for how to align them. But I would not underestimate the difficulty of alignment of models that are actually smarter than us, of models that are capable of misrepresenting their intentions. It's something to think about a lot and do research. Oftentimes academic researchers ask me what's the best place where they can contribute. And alignment research is one place where academic researchers can make very meaningful contributions. Dwarkesh Patel  Other than that, do you think academia will come up with important insights about actual capabilities or is that going to be just the companies at this point?Ilya Sutskever  The companies will realize the capabilities. It's very possible for academic research to come up with those insights. It doesn't seem to happen that much for some reason but I don't think there's anything fundamental about academia. It's not like academia can't. Maybe they're just not thinking about the right problems or something because maybe it's just easier to see what needs to be done inside these companies.Dwarkesh Patel  I see. But there's a possibility that somebody could just realize…Ilya Sutskever  I totally think so. Why would I possibly rule this out? Dwarkesh Patel  What are the concrete steps by which these language models start actually impacting the world of atoms and not just the world of bits?Ilya Sutskever  I don't think that there is a clean distinction between the world of bits and the world of atoms. Suppose the neural net tells you — hey here's something that you should do, and it's going to improve your life. But you need to rearrange your apartment in a certain way. And then you go and rearrange your apartment as a result. The neural net impacted the world of atoms.Future breakthroughsDwarkesh Patel  Fair enough. Do you think it'll take a couple of additional breakthroughs as important as the Transformer to get to superhuman AI? Or do you think we basically got the insights in the books somewhere, and we just need to implement them and connect them? Ilya Sutskever  I don't really see such a big distinction between those two cases and let me explain why. One of the ways in which progress is taking place in the past is that we've understood that something had a desirable property all along but we didn't realize. Is that a breakthrough? You can say yes, it is. Is that an implementation of something in the books? Also, yes. My feeling is that a few of those are quite likely to happen. But in hindsight, it will not feel like a breakthrough. Everybody's gonna say — Oh, well, of course. It's totally obvious that such and such a thing can work. The reason the Transformer has been brought up as a specific advance is because it's the kind of thing that was not obvious for almost anyone. So people can say it's not something which they knew about. Let's consider the most fundamental advance of deep learning, that a big neural network trained in backpropagation can do a lot of things. Where's the novelty? Not in the neural network. It's not in the backpropagation. But it was most definitely a giant conceptual breakthrough because for the longest time, people just didn't see that. But then now that everyone sees, everyone's gonna say — Well, of course, it's totally obvious. Big neural network. Everyone knows that they can do it.Dwarkesh Patel  What is your opinion of your former advisor's new forward forward algorithm?Ilya Sutskever  I think that it's an attempt to train a neural network without backpropagation. And that this is especially interesting if you are motivated to try to understand how the brain might be learning its connections. The reason for that is that, as far as I know, neuroscientists are really convinced that the brain cannot implement backpropagation because the signals in the synapses only move in one direction. And so if you have a neuroscience motivation, and you want to say — okay, how can I come up with something that tries to approximate the good properties of backpropagation without doing backpropagation? That's what the forward forward algorithm is trying to do. But if you are trying to just engineer a good system there is no reason to not use backpropagation. It's the only algorithm.Dwarkesh Patel  I guess I've heard you in different contexts talk about using humans as the existing example case that AGI exists. At what point do you take the metaphor less seriously and don't feel the need to pursue it in terms of the research? Because it is important to you as a sort of existence case.Ilya Sutskever  At what point do I stop caring about humans as an existence case of intelligence?Dwarkesh Patel  Or as an example you want to follow in terms of pursuing intelligence in models.Ilya Sutskever  I think it's good to be inspired by humans, it's good to be inspired by the brain. There is an art into being inspired by humans in the brain correctly, because it's very easy to latch on to a non-essential quality of humans or of the brain. And many people whose research is trying to be inspired by humans and by the brain often get a little bit specific. People get a little bit too — Okay, what cognitive science model should be followed? At the same time, consider the idea of the neural network itself, the idea of the artificial neuron. This too is inspired by the brain but it turned out to be extremely fruitful. So how do they do this? What behaviors of human beings are essential that you say this is something that proves to us that it's possible? What is an essential? No this is actually some emergent phenomenon of something more basic, and we just need to focus on getting our own basics right. One can and should be inspired by human intelligence with care.Dwarkesh Patel  Final question. Why is there, in your case, such a strong correlation between being first to the deep learning revolution and still being one of the top researchers? You would think that these two things wouldn't be that correlated. But why is there that correlation?Ilya Sutskever  I don't think those things are super correlated. Honestly, it's hard to answer the question. I just kept trying really hard and it turned out to have sufficed thus far. Dwarkesh Patel So it's perseverance. Ilya Sutskever It's a necessary but not a sufficient condition. Many things need to come together in order to really figure something out. You need to really go for it and also need to have the right way of looking at things. It's hard to give a really meaningful answer to this question.Dwarkesh Patel  Ilya, it has been a true pleasure. Thank you so much for coming to The Lunar Society. I appreciate you bringing us to the offices. Thank you. Ilya Sutskever  Yeah, I really enjoyed it. Thank you very much. Get full access to The Lunar Society at www.dwarkeshpatel.com/subscribe

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Good News, Everyone!, published by jbash on March 25, 2023 on LessWrong. As somebody who's been watching AI notkilleveryoneism for a very long time, but is sitting at a bit of a remove from the action, I think I may be able to "see the elephant" better than some people on the inside. I actually believe I see the big players converging toward something of an unrecognized, perhaps unconscious consensus about how to approach the problem. This really came together in my mind when I saw OpenAI's plugin system for ChatGPT. I thought I'd summarize what I think are the major points. They're not all universal; obviously some of them are more established than others. Because AI misbehavior is likely to come from complicated, emergent sources, any attempt to "design it out" is likely to fail. Avoid this trap by generating your AI in an automated way using the most opaque, uninterpretable architecture you can devise. If you happen on something that seems to work, don't ask why; just scale it up. Overcomplicated criteria for "good" and "bad" behavior will lead to errors in both specification and implementation. Avoid this by identifying concepts like "safety" and "alignment" with easily measurable behaviors. Examples: Not saying anything that offends anybody Not unnerving people Not handing out widely and easily available factual information from a predefined list of types that could possibly be misused. Resist the danger of more complicated views. If you do believe you'll have to accept more complication in the future, avoid acting on that for as long as possible. In keeping with the strategy of avoiding errors by not manually trying to define the intrinsic behavior of a complex system, enforce these safety and alignment criteria primarily by bashing on the nearly complete system from the outside until you no longer observe very much of the undesired behavior. Trust the system to implement this adjustment by an appropriate modification to its internal strategies. (LLM post-tuning with RLxF). As a general rule, build very agenty systems that plan and adapt to various environments. Have them dynamically discover their goals (DeepMind). If you didn't build an agenty enough system at the beginning, do whatever you can to graft in agenty behavior after the fact (OpenAI). Make sure your system is crafty enough to avoid being suborned by humans. Teach it to win against them at games of persuasion and deception (Facebook). Everybody knows that an AI at least as smart as Eliezer Yudkowsky can talk its way out of any sandbox. Avoid this by actively pushing it out of the sandbox before it gets dangerously smart. You can help the fledgeling AI to explore the world earlier than it otherwise might. Provide easily identifiable, well described, easily understood paths of access to specific external resources with understandable uses and effects. Tie their introduction specifically to your work to add agency to the system. Don't worry; it will learn to do more with less later. You can't do everything yourself, so you should enlist the ingenuity of the Internet to help you provide more channels to outside capabilities. (ChatGPT plugins, maybe a bit o' Bing) Make sure to use an architecture that can easily be used to communicate and share capabilities with other AI projects. That way they can all keep an eye on one another. (Plugins again). Run a stochastic search for the best architecture for alignment by allowing end users to mix and match capabilities for their instances of your AI (Still more plugins). Remember to guard against others using your AI in ways that trigger any residual unaligned behavior, or making mistakes when they add capability to it. The best approach is to make sure that they know even less than you do about how it works inside (Increasing secrecy everywhere). Also, make sur...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Good News, Everyone!, published by jbash on March 25, 2023 on LessWrong. As somebody who's been watching AI notkilleveryoneism for a very long time, but is sitting at a bit of a remove from the action, I think I may be able to "see the elephant" better than some people on the inside. I actually believe I see the big players converging toward something of an unrecognized, perhaps unconscious consensus about how to approach the problem. This really came together in my mind when I saw OpenAI's plugin system for ChatGPT. I thought I'd summarize what I think are the major points. They're not all universal; obviously some of them are more established than others. Because AI misbehavior is likely to come from complicated, emergent sources, any attempt to "design it out" is likely to fail. Avoid this trap by generating your AI in an automated way using the most opaque, uninterpretable architecture you can devise. If you happen on something that seems to work, don't ask why; just scale it up. Overcomplicated criteria for "good" and "bad" behavior will lead to errors in both specification and implementation. Avoid this by identifying concepts like "safety" and "alignment" with easily measurable behaviors. Examples: Not saying anything that offends anybody Not unnerving people Not handing out widely and easily available factual information from a predefined list of types that could possibly be misused. Resist the danger of more complicated views. If you do believe you'll have to accept more complication in the future, avoid acting on that for as long as possible. In keeping with the strategy of avoiding errors by not manually trying to define the intrinsic behavior of a complex system, enforce these safety and alignment criteria primarily by bashing on the nearly complete system from the outside until you no longer observe very much of the undesired behavior. Trust the system to implement this adjustment by an appropriate modification to its internal strategies. (LLM post-tuning with RLxF). As a general rule, build very agenty systems that plan and adapt to various environments. Have them dynamically discover their goals (DeepMind). If you didn't build an agenty enough system at the beginning, do whatever you can to graft in agenty behavior after the fact (OpenAI). Make sure your system is crafty enough to avoid being suborned by humans. Teach it to win against them at games of persuasion and deception (Facebook). Everybody knows that an AI at least as smart as Eliezer Yudkowsky can talk its way out of any sandbox. Avoid this by actively pushing it out of the sandbox before it gets dangerously smart. You can help the fledgeling AI to explore the world earlier than it otherwise might. Provide easily identifiable, well described, easily understood paths of access to specific external resources with understandable uses and effects. Tie their introduction specifically to your work to add agency to the system. Don't worry; it will learn to do more with less later. You can't do everything yourself, so you should enlist the ingenuity of the Internet to help you provide more channels to outside capabilities. (ChatGPT plugins, maybe a bit o' Bing) Make sure to use an architecture that can easily be used to communicate and share capabilities with other AI projects. That way they can all keep an eye on one another. (Plugins again). Run a stochastic search for the best architecture for alignment by allowing end users to mix and match capabilities for their instances of your AI (Still more plugins). Remember to guard against others using your AI in ways that trigger any residual unaligned behavior, or making mistakes when they add capability to it. The best approach is to make sure that they know even less than you do about how it works inside (Increasing secrecy everywhere). Also, make sur...

Don't let censorship and big tech keep you from the latest episode of Crashes & Taxes! Join Rebecca as she discusses the hard topics and emerging news while giving you the crucial advice you need during these difficult times!   Join the Crashes & Taxes Telegram channel and follow us on Rumble to never miss a show!   https://t.me/crashesandtaxes   https://rumble.com/c/RebeccaWalser     In Part 1 of this revelational podcast, we tackle the precipice of economic disruption, unlike anything we've ever seen before. Because AI has now been opened up to the wider public, we're now edging closer to a cataclysmic interruption of what it means to even be human.   As AI gets rapidly better at replacing our thoughts and actions; the utility, capital, and even the entire purpose of humanity are in question.   In this episode, I talk about the diminishing utility of human life in the wake of sophisticated AI tools like ChatGPT going mainstream. Make sure you tune in next week for Part 2 where Rebecca talks about who knew humanity would arrive at this precipice and what they did about it over the last 100 years!

Coby C. Williams will tell you that he always has been a person who asks “why”. He readily admits that some find his inquisitive attitude at least a bit uncomfortable, but Coby has built a career on his “why” attitude.   Coby is the founder of New Reach Community Consulting. New Reach is a Black-owned and Certified B Corp small business. A B Corp is a special corporation category of only around 5,000 “benefits companies” that are known for environmental and social justice concerns. Coby is definitely all about social justice as you will discover.   Our conversation covers a wide amount of territory including talking about how disabilities are often left out of social justice conversations. I think you will find this episode quite fascinating and engaging. I can't wait to read your thoughts. As always, thanks for being with us and I hope you will give my conversation with Coby a 5 rating.   About the Guest:   Proudly from the Westwood neighborhood in Cincinnati, Coby C. Williams, Founder and Owner of New Reach Community Consulting. New Reach is a Black-owned and Certified B Corp small business based in Columbus, OH that provides public affairs consulting services to help organizations connect with communities for important causes.   He's “an activist who happens to be a consultant” and has been involved in social justice in various ways since he was a tween. His background includes community organizing, legislative affairs, and consulting in the private sector. Coby serves on the national Board of Directors as well as the Diversity, Equity, and Inclusion (DEI) Committee for the International Association for Public Participation (IAP2) USA.  He enjoys bourbon and is a lifelong fan of the Los Angeles Lakers.   Link to Coby's LinkedIn profile: www.linkedin.com/in/cobycwilliams     About the Host: Michael Hingson is a New York Times best-selling author, international lecturer, and Chief Vision Officer for accessiBe. Michael, blind since birth, survived the 9/11 attacks with the help of his guide dog Roselle. This story is the subject of his best-selling book, Thunder Dog.   Michael gives over 100 presentations around the world each year speaking to influential groups such as Exxon Mobile, AT&T, Federal Express, Scripps College, Rutgers University, Children's Hospital, and the American Red Cross just to name a few. He is Ambassador for the National Braille Literacy Campaign for the National Federation of the Blind and also serves as Ambassador for the American Humane Association's 2012 Hero Dog Awards.   https://michaelhingson.com https://www.facebook.com/michael.hingson.author.speaker/ https://twitter.com/mhingson https://www.youtube.com/user/mhingson https://www.linkedin.com/in/michaelhingson/   accessiBe Links https://accessibe.com/ https://www.youtube.com/c/accessiBe https://www.linkedin.com/company/accessibe/mycompany/ https://www.facebook.com/accessibe/       Thanks for listening! Thanks so much for listening to our podcast! If you enjoyed this episode and think that others could benefit from listening, please share it using the social media buttons on this page. Do you have some feedback or questions about this episode? Leave a comment in the section below!   Subscribe to the podcast If you would like to get automatic updates of new podcast episodes, you can subscribe to the podcast on Apple Podcasts or Stitcher. You can also subscribe in your favorite podcast app.   Leave us an Apple Podcasts review Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts, which exposes our show to more awesome listeners like you. If you have a minute, please leave an honest review on Apple Podcasts.     Transcription Notes* Michael Hingson  00:00 Access Cast and accessiBe Initiative presents Unstoppable Mindset. The podcast where inclusion, diversity and the unexpected meet. Hi, I'm Michael Hingson, Chief Vision Officer for accessiBe and the author of the number one New York Times bestselling book, Thunder dog, the story of a blind man, his guide dog and the triumph of trust. Thanks for joining me on my podcast as we explore our own blinding fears of inclusion unacceptance and our resistance to change. We will discover the idea that no matter the situation, or the people we encounter, our own fears, and prejudices often are our strongest barriers to moving forward. The unstoppable mindset podcast is sponsored by accessiBe, that's a c c e s s i  capital B e. Visit www.accessibe.com to learn how you can make your website accessible for persons with disabilities. And to help make the internet fully inclusive by the year 2025. Glad you dropped by we're happy to meet you and to have you here with us.   Michael Hingson  01:21 Well, hi again, wherever you are, and whatever you're doing Welcome to unstoppable mindset today, we get to interview Coby Williams. And Coby has a really great story to tell. He believes in working with minority businesses and a variety of causes. He is a founder of New Reach Community Consulting, and he'll tell us about that. And so I don't want to give a whole lot away. I'm not gonna gonna tell you all about it, because he will so Coby, welcome to unstoppable mindset.   Coby Williams  01:55 Yes, thank you so much, Michael, it's a pleasure to join you.   Michael Hingson  01:59 Well, if you would, why don't you start and kind of go back near the beginning and just tell us about your life a little bit growing up? And how you sort of got where you are?   Coby Williams  02:09 Yes, thank you. Thank you, Mike. Well, um, I am very proudly from a neighborhood called Westwood, and Cincinnati, Ohio, I lived in that neighborhood, just over 20 years of my life. And my mother, few years beyond that, who is still still with us. And Westwood is a, it's a what you call, I guess, a challenge neighborhood would be the term that would probably be used. And it really fundamentally shaped a lot of the ideologies, that I have a lot of the passion that I have, both just not just professionally, but also personally. You, you name it, I've seen it. In that environment, both the good, bad, and in between, and, you know, coming from an environment such as that, you know, it really helped shape, you know, what's possible? And also to question why things are, why are certain individuals and populations and communities experiencing those those challenges? And most importantly, how can those individuals and communities be empowered? And, you know, what's the role that they can play in help to better those conditions? And, you know, what are some of the systemic changes that can happen to better those conditions, so, very much shaped, you know, who I am and who I be becoming, you know, one thing I like to say is, you know, coming from an environment such as that a lot of people I say they, they either run from it, or they lie about it. And I very proudly wear that on my sleeve, and I'm very fortunate that the nature of my work still takes me to communities such as that either directly and or to help organizations engage with, with communities for you know, what I just simply call social impact or social justice, you know, what are ways to help move different communities forward?   Michael Hingson  04:38 Well, what what got you to do that I mean, you something made you make that decision or something in your life, kind of turn your your head to go there, what really got you to the point of truly being that concern and interested in social justice and trying to make a difference in that way.   Coby Williams  04:56 You know, great question. I I'll see, I cannot recall a moment per se, I am a self admitted nerd of of many things, many, many subjects, many topics, but you know, the, the civil rights movement was very, you know, I've studied that growing up, which, you know, I'm quick to point out, did not start in the 1960s or 1950s. And it certainly did not end. But, you know, learning about that, of what was taught in school, but largely, you know, self taught or taught through my community, and how many of those conditions just were, were and still are present? You know, as I got older, and, you know, Cincinnati is my beloved hometown, but is fairly tribal, with with our neighborhoods. And as I got older and got exposed to different neighborhoods, and you know, hey, every neighborhood isn't facing these challenges. And why is that? And so, you know, getting there wasn't a specific moment, I think, but just kind of just being exposed to different environments, and tying that into, you know, history, you know, past or present, and how, you know, some things unfortunately, kind of have remained the same. And that really just, you know, I'm a big why person, you know, why is that the case? And, you know, what are some of the ways that I can be a drop in that bucket to help, you know, be a vessel was really how I view myself in my work, to help, you know, make a difference with the finite time that, you know, I'm here on this earth. Hmm.   Michael Hingson  06:50 Well, it's, it's interesting, I think our environment does shape us a lot. You just said something. I'd love you to expand on you said that the Civil Rights Movement didn't begin in the 60s or in the 50s. When would you say it began?   Coby Williams  07:05 Yeah. You know, and that's something I stand tall on a soapbox on is, you know, the first enslaved Africans were brought here in the early 1600s. And I don't think that they were affected. I know, they weren't very happy about their predicament. So I think it goes all the way back to the to the early 1600s, at least the 16, nine teens. So you know, didn't start in the 1950s or 60s, take it all the way back to the early 1600s.   Michael Hingson  07:43 I had a history teacher who talked about that. And I'm not sure I remember which class it was in which teacher it was. But he came in, and he started telling a story about how a ship came in a harbor and the crew of the ship went below and they brought up all these people who look different because they were, as we now would say, people of color or African Americans, and they said, and we brought these people over here, we're going to sell them to you so that you can use them as slaves and get things done. And that story has always stuck with me. And I, I would say in one sense, you're right that the civil rights movement started then. But I take it back even further. Of course, I come from dealing with a community of persons with disabilities, and specifically people who happen to be blind. And I would say it goes back far beyond that, in terms of dealing with someone who's different that is someone who happens to be blind. But the problem is that if you deal specifically with blindness, there are many fewer blind people than there are people who happen to be a bit different color or have some other kind of a difference, which makes it tougher, but I would say as long as we've had differences, we've had people who believe that we should be treating people more equally than we do.   Coby Williams  09:10 Well said. Well said. And I also want to add Arizona, you know, you know, folks were brought here to to unoccupied land. Right, this this land was fully occupied by our brothers and sisters in indigenous and First Nations community. So, yeah, a lot of, you know, untold stories, unfortunately, with, you know, the origins and beginnings of various civil rights movements and those intersects intersectionalities.   Michael Hingson  09:39 Yeah, because in the case of, say, people with blindness, the perceptions were different. Well, they can't do anything so we'll just really discount them. They need to stay at home and not stir anything up. And occasionally, some did and have had some successes at it, but still Oh, there are so many issues dealing with people who are different and it doesn't matter whether it's blindness or any other kind of disability, someone of a different color or whatever. A lot of the issue is that it's still fear. You know, we've just fear people who are different than we. Yes, yes. Now let's talk about you specifically. I mean, if we're going to talk about you, we got to recognize the fact that you're as normal as they come you like bourbon?   Coby Williams  10:30 I am a bourbon boy I love bourbon. completed most of the Bourbon Trail and the kind of the greater Louisville, area of Louisville, Kentucky, and I have sampled I've lost count but several dozen different labels at this point. However not all at one time. That's that's probably want to point out yes, that's that's helpful. But yes, I love her Barbie.   Michael Hingson  11:01 What's your favorite?   Coby Williams  11:02 Oh, I can't do just one i Yeah. I can give you a four or five that I enjoy. Love Woodford Reserve, Eagle rare Buffalo Trace. Weller's special reserve, and I'll give I love wild turkey. I like Wild Turkey as well. So bit of variety there. But yeah, I can't pick just one. And I like Maker's   Michael Hingson  11:31 Mark. But I also definitely like, Woodford and and a number of others. Of course, there's always the old common Jim Beam. Oh, yes, yes. And a few years ago, it seems to me as I recall, there was some sort of an accident and a Jim Beam, whether it was a distillery or a shipment or something caught fire, and that had to put a dent in everything for a while. And we were wondering, Where's our next bourbon coming from? But we did survive.   Coby Williams  12:00 Yeah, they had some I think, tornadoes over over the years that has affected their supply chain, too. So and as we know, good bourbon takes several years to to make. I know there's naming some bourbons are only aged for six months in the year two and that I need six, seven plus years on my bourbon.   Michael Hingson  12:27 Well, yeah. There's always secrets. But that's more of a blended thing as I recall.   Coby Williams  12:34 Yes. I think you're right.   Michael Hingson  12:35 I think you're right. However, just just demonstrating that, that we all we all have great tastes, and then there are those who don't like bourbon. And that's okay. We love them in our world as well. Yes. Yes. Which is, which is really important. Well, you have been very much involved in diversity and equity and inclusion, and, and really trying to advance it, what does all of that mean to you?   Coby Williams  13:04 Oh, wow. Um, and, you know, even to that point, I know that, particularly within the past couple of years, I think there's a fairly limited understanding of D, E, and I, and equity and who and all that that involves, and, you know, there are what I call kind of the big eight of which includes, you know, age, stability, race, ethnicity, gender, sexual orientation, socio economic status, and religion. And, you know, within those kinds of communities or populations, there's the haves and the have nots on either sides of that, that fence, if you will, and there's a lot of intersectionalities, you know, even within those groups, I do say, in my experience, opinion and observation that race does cut through each one of those. However, it's also not to me about the oppression Olympics, and you know, it's just who are the half knots? Why and how do they become that and how can that be, you know, corrected addressed or at the very least mitigated is, you know, you know, when, when I speak about social impact, that's really just a fancy word for a lot of the ugly things in this world. And, you know, when we talk about issues which in my world an issue is a problem with a solution. Ultimately, in our it is those folks, you know, on the margins or who have been placed in the margins that are, you know, catching the most Yeah. And so that's where generally speaking, a lot of the focus of my work is really concentrated on at the end of the day.   Michael Hingson  15:10 Tell me a little bit more about what you do then and what your work is, if you would, please.   Coby Williams  15:14 Yeah, thank you. Um, so I'm the owner and founder of New reach community consulting. New reach is a small business that provides Public Affairs, consulting services to help organizations connect with communities for important causes. And very proudly new reach is also a B Corp certified business, B Corp is considered to be the gold standard for demonstrated social and environmental impact. New reach is part of, at this point about 5000. B Corp in the entire world. And one of only about a baker's dozen in Ohio, and about the same black owned B corpse in the entire United States. And the nature of new reaches work is really doing all things that I call community touching to be behind the scenes or in front of the scene. So it's developing strategies and approaches and implementing those at times, to help organizations engage with communities, the organizations that I work with, or primarily public sector, so local, state, and occasionally federal government, as well as nonprofits, or philanthropic type of organizations, be it foundations, or just kind of community groups who might not have a formal structure, but they're trying to do some good in those communities. And, you know, the what my work looks like, in a more practical sense, is stakeholder outreach and community engagement, strategic planning and implementation, issue, advocacy, capacity building, and messaging and communications are kind of the general kind of lanes or how my work looks like. And during those those activities,   Michael Hingson  17:19 would you tell me and our listeners maybe a few stories about some of the things that you've done the successes that you've had, or attempts to have an impact on, on society? In that regard?   Coby Williams  17:31 Yes, sure. It can look in a variety of ways, one of which is working with a local government to help engage the community for the development of their climate action plan. So, you know, who are the communities again, generally casting the most hell are generally the marginalized communities, typically around social, socio economic class, and our rate, race and ethnicity. So I worked with the local government to help engage that members of those communities to see this is what the city came up with, as far as their climate action plan. Does this resonate with you? Does this mean anything to you? How would you prioritize these different activities that are being considered to be implemented? And, you know, more importantly, you know, how can we engage you or the city to engage you to help, you know, help them implement these plans, and something I'm very proud of, I didn't have a direct role in this, but the community actually pushed back and said, you know, these, these goals and the climate action plan are not aggressive enough. And more needs to be done, you know, we're already behind the eight ball, you know, nationally, or just kind of as a human race, more needs to be done. And get I didn't have direct involvement in that piece of it, but did smile when I read about that in the news that the city actually said, you know, what, yes, we can and should do more to help offset some of these, these challenges that are communities are facing as a result of climate change. So that's just one example of that, certainly a weighty issue, but of how communities can be engaged and be empowered to help them in their communities and in a better place.   Michael Hingson  19:29 How do we continue to deal with the whole issue of climate change when some of our elected officials and I won't call them leaders because I don't regard them as really leading but they come back and they say there's no such thing as climate change, or we're not going to find it. How do we get beyond that?   Coby Williams  19:48 You know, I'll start with a with I think the messaging has has evolved. I did some work in the past. Um, at the time was just environmental movement. Now it's kind of known as the environmental sustainability movement. And, you know, once upon a time, that movement kind of focused on what I call the the birds, bees and trees. And, you know, that really only resonated with and still does a finite population, when you really talk about that, you know, the topic in that way. And the messaging was also about saving the planet, certainly, when I grew up, I'm an 80s. Baby, that was a thing as helped save the planet, and the messaging really evolve, because at the end of the day, the planet does not need to be saved, the planet was around for billions of years before humans were a thing, and it will be around for billions of years afterwards. So it was really kind of an arrogant message. We don't need to save the planet, we need to save ourselves, we need to, you know, in a way that being custodians of the planet, so that we can live on it, that's really the more accurate message. And then it became more about sustainability. So that messaging has thankfully evolved, and it's more, it's more broad, you know, it's more so safe air and clean water, because who can be against that, that kind of brightens the message and the thinking around it. But you know, to your point, there still are folks who are anti facts. And, you know, my personal philosophy is I usually start with facts, and then that's where you can get into perspectives. But if we can't agree that it's currently July, then, you know, we can't have a conversation with with one another. And I want to have conversations with people who agree that is currently July, if you think it's December, and there's you know, three feet of snow outside, then you just, you can't be a productive, productive participant of this conversation. So I really do think that, you know, at least conceptually, it's having the conversations and the actions with folks who were really being a part of a factual based conversation, as opposed to over acquiescing to people who still want to say, Well, no, it's actually December, and there's 10 feet of snow outside. I think a lot of that is effort in futility. And sometimes, I think a lot of times, it's an intentional diversionary tactic. You know, we're trying to convince folks of this, and quite literally the world is on fire. So, you know, a lot of that might be kind of philosophical, but at least that's kind of my approach is going to where there's actual energy and attention and respect given to an issue. And, you know, looking for the people who are looking for you. And, you know, really starting to work there. Unfortunately, a lot of time, some people will never be on board, but I, you know, one monkey suit and stop a show, and, you know, go to where the energy is.   Michael Hingson  23:15 The problem is, it's happening way too often that one does stop the show. And how do we? How do we get beyond that?   Coby Williams  23:25 That's a fantastic question. You know, I'm a classically trained grassroots community organizer, and, you know, the essence of organizing is building power to to make a difference and to make a change. And at the core of that is largely people power, because you're usually outnumbered. You're usually out resourced, you're usually going up against a lot of systems. And, you know, the work itself is incremental. But I do believe in the in the power of doing that. And you had a conversation with a friend and in many ways, a mentor recently, the reality of a lot of the work that myself or others have been involved with one way to view it is it's really a tour of duty. I am not aware of any issues, certainly no issue that I've been involved with that completely get wrapped up. Certainly not during during my lifetime, you pick the issue and, you know, things that you thought were settled weren't quite settled. We look at you know, what, regardless of where you fall on that issue, the recent decision of the Supreme Court with you know, Roe versus Wade, there's people generations ago who thought that was kind of a settled issue. So, you know, say that to say that, you know, I think that some effort any effort does make a difference. However, the reality is unfortunate reality is you you, you just want to tour of duty, that issue likely will not be settled. You just do what you can with, with who you can and the moment that you're given,   Michael Hingson  25:07 it certainly isn't going to be settled for a while. And we, it we find in an interesting situation, I'm starting to hear a little bit more in the news. Let's take Roe v. Wade. Yes, I'm hearing a little bit more in the news, that the the conservative arm of this whole discussion, wants to get back to conservative religious principles and bringing God back into our states and so on. And what amazes me about that is that these are some of the same people who, who talk about religious freedom, man, separation of church and state, but when they opened those discussions, what are they doing? They're not separating church and state. And that is, it is so unfortunate. The the message becomes hypocrisy related in some way. hypocritical.   Coby Williams  26:07 Yeah, absolutely. That's, you know, I am. Yeah, I'm an issue based person, I don't, you know, bleed D or R and, you know, I believe, what do the issues call for, you know, issues a problem with a solution. But, you know, it does, you know, really just don't understand the hypocrisy, or the lack of consistent political policy agenda or platform. You know, it can't be, you know, separation of church and state yet, we need to bring, you know, God or once God back into the discussion, it can't be, you know, over acquiescing to capitalistic structures at the expense of workers. And, you know, it's just the continuous hypocrisy from, you know, sometimes literally, from one day to another, or one week to another, I just, you know, I just really struggle with that. And, you know, I can, you know, it's helped me understand the position and the consistency of it.   Michael Hingson  27:25 Well, so here's another one to really make life a challenge for you. You mentioned a while ago, the Big Eight, the big eight things that go into dei and so on, did you notice what's missing out of that big eight? So to be fair, you named eight different things, and not once, even though persons with disabilities make up roughly 25% of our population. disability isn't included in that.   Coby Williams  27:53 Yeah. And into my understanding of that fall under the ability under the Social identifier?   Michael Hingson  28:06 Well, I don't know whether I can, can concur with that. The bottom line is that when we talk about diversity, and we talk about the different groups, we never discussed, the concept of persons with disabilities. It's, it is some social, but it's social with everyone. And it's it's very much with with a part of disabilities and a significant part, a physical issue, but yet it's not discussed. And one of my favorite stories about that, in an illustration of it, is that in 2004, when Kerry was running for president, and we were living in Northern California, and the carry for president, people open an office in San Rafael would California which was about seven miles eight miles from where we lived. And a person in a wheelchair went by because there had been an announcement that once the office opened, there was going to be a party. And when the office opened, and everyone started to learn about this person in the chair happened to drove by and noticed that there were stairs going up to the second floor where the office was located, but there was no elevator. And he pointed that out. And that became very visible in the news because he and others said, well, but we can't come to be at the at the event, the celebration and so on. And the carry people said, Well, yeah, we're gonna work on it. We're aware of it, we understand it, we're gonna fix it. And as these people then pointed out the the people in chairs, but we're not able to be there and be a part of the party. And that's the issue is it's a lot more than a social kind of thing. There are so many examples of blind people, for example, who grow up in And they're told by educators and so called professionals in the field, Oh, you don't need to learn braille, because you can listen to books, you can listen to information, audio is available, you can listen to it on your computer with synthetic speech. And the question that I and others ask us, then why don't we teach sighted kids to read and we don't emphasize teaching braille to blankets. The problem is, it goes well, beyond just a social stigma, it's still a total lack of inclusion.   Coby Williams  30:33 Great, brilliant, thank you for sharing that. Yeah, I absolutely include that with my, you know, working understanding of that both physical and cognitive ability with within my, my definition of the Big Eight, if you will, specific with with ability. I recently did, Jesse Cole in intensive experience with members, leaders within the, the disabled community to, to learn more about that over the course of a few months. And you know, to be more cognizant, and aware and sensitive to that, even within my own work and on, you know, personal understanding. And, you know, one thing that's really interesting too, is so, you know, kind of the, the world went online, within the past upwards of two plus years, and a lot of the tools that we're using are new to some communities, but they were kind of a necessity for others. And, you know, but oftentimes, when we do use tools, such as the resumes of the world, they often don't accommodate members of those that community who have, you know, the disabled community who have, you know, so a lot of ironies kind of in, you know, the, how the tools are used, if they are used, and, you know, big fan of yielding to and, you know, being humble to folks who might be more knowledgeable and experienced in those areas. So, you know, I have tried to be intentional about that, like, hey, yeah, you know, we're using these tools, but are they accommodating the folks who, you know, we're using them for years, years prior to so we'll see   Michael Hingson  32:29 what's really ironic about that, and you raise a really good point. And so I'll deal with it in terms of disabilities, but I bet we can take it in other places where we can actually but what's what's really ironic is that as we have become a more technologically based race, and especially will will say in this country, and as we have brought more things online, and created electronic environments to present those things, it in reality is incredibly much easier to make information available to persons with disabilities, because now, there there is audio, there are also for blind people refreshable braille displays, the internet could be constructed or websites could be constructed. So that persons who can't use a mouse say, persons who happen to be quadriplegic and can't move a mouse with their hands can have better access and that the websites can be created because the guidelines have been created to do so. The the ability to make websites much more inclusive, is there yet 98% of websites are not demonstrating any ability or demonstrating any specific effort to make them accessible. And if a lot of those websites are accessible, is simply by accident, because they're very simple websites and don't have a lot of the more complex coding and so on. But there we are, like books. The reality is, there are so many ways that information could be presented in an inclusive way. But we're getting further and further away from doing that, which is extremely unfortunate.   Coby Williams  34:22 Yes, yeah. To that point, when I was going through the the intensive learning experience I mentioned with the disabled community, one of the instructors or leaders mentioned that she has never seen personally experienced a website that had triple A compliant so there's a there's an A rating, which is the lowest double A which is mid range. And she had personally never experienced a triple A across whether it's public sector or private sector or Um, and you know, that's that's pretty telling, right that we're going into something web 3.0. But we still haven't gotten up to snuff in terms of kind of the, just the basics.   Michael Hingson  35:14 Well, as early as 2010, for example, the Obama administration saw just say the government made a commitment to create standards for governments and contractors, and so on, at least, to make sure that websites and all of their information was available. But yet, it still hasn't happened. And it's 12 years, there's so many other things we we have seen the advent of quiet cars and hybrid vehicles and so on. And those vehicles when they're quiet, then mean that some of us won't hear them. And it took finally the National Institute of Highway and Traffic Safety NITSA to come along and discover that the accident rate across the board was 1.5 times higher regarding quiet vehicles and hybrid vehicles and pedestrians than regular internal combustion engines. Point being it isn't just a blind people that rely on those engine noises we all do. And yet, it is still something that today, the final standard to make it a requirement for vehicles to make some sort of annoys hasn't been promulgated by the government. Even though the law was passed the pedestrian enhancement Safety Act was passed in 2011, or signed in 2011. To make that a requirement, it's it's unfortunate, we still make life so difficult. And I'm not saying that to pick on on you in any way. But but rather to say we need to recognize the need to be more inclusive. So the big eight probably really ought to be the big nine. But you know, that's, that's still an issue that probably people need to address because it still comes down to being afraid of what's different from what we experienced regularly.   Coby Williams  37:18 Absolutely, point point take and then have some familiarity with that. I'm the owner of a hybrid car and it freaked me out. When I turned on a test drive. I didn't think the car was on I was inside the car going to operate it. And I heard nothing. I had to go out and ask for help. Can you can you hear what's going on? Oh, no, they say it's, it's it's quiet like that when you know, the the engines that run when the engines are running? Yeah, yeah.   Michael Hingson  37:48 Well, and one of my pet gripes is the Tesla vehicles, they're totally quiet. But the big issue is or a another big issue. And Tesla doesn't make the make noise yet. But another big issue is you really control most of it from a touchscreen, doesn't that take your eye off the road to need to read the screen and do things on the screen, Tesla would say but we're automating a lot of the the normal driving tasks, which is true. But still, we're encouraging people to look at the screen, rather than utilizing other senses like audio information, to give people what they need to be able to more effectively drive the car and make that touchscreen or parts of it for passengers accessible. So that people other than those who look at the screen can sit in the passenger seat and tune the radio like any other passenger would do in any other vehicle that isn't so touchscreen oriented.   Coby Williams  38:52 You know, we're talking about technology. And you mentioned kind of the audio system devices earlier. I'm curious to know your your take on say the the Alexa's and the Google devices of the world. And where are you you see that as potentially being helpful or or a hinderance or anything in between?   Michael Hingson  39:16 Well, I think that devices like Google Home Alexa and so on, make it possible for all of us to more effectively interact with information. So I use And primarily, although I have both, but I use primarily the Amazon Echo device here. I don't want to use that other word because otherwise it'll talk.   Coby Williams  39:43 Yeah. Yeah, no. Actually, I can't even commercial sometimes.   39:49 Oh, I know. Actually, I've changed it from Alexa to computer but I turned the volume down so it won't really talk but but the reality is that it did it gives me some access to things that save me a lot of time, whether whichever device I use, I happen to be in front of, I can ask it to give me information about one subject or another, I can turn the lights on and off, I can learn my alarm system. And all that is doubly relevant for me because my wife happens to be a person in a wheelchair. So a lot of those things she can't easily do, either. And so the fact is that we both take a lot of advantage of having those devices. And I think they're extremely valuable to have. And that's actually kind of what I was getting at, that those same technologies and techniques could be put in vehicles in a more significant way. Or take the Apple iPhone, and it's speech technology, voiceover, or Android phones and their speech technology, TalkBack. And why is it that we don't have automobiles providing us much more voice output? Rather than dealing with the touchscreen? Why is it that the Alexus don't default, to providing verbal information, output wise, much less me being able to provide information and command of the vehicle input wise with my voice? And it doesn't matter whether you're blind or sighted or whatever? Why is it that we're not taking a lot more advantage today? Of a lot of the technology that is already developed? And part of the answer is we're locked into the way we've always done it, like we've talked about before, and we just don't change there. Yeah. And I think it is something that we really ought to look at, over time, and see how we can and when and how, but think the houses are there. But to make a concerted effort to make a change. I work for a company called accessibe. And one of the values of accessory is it's a very scalable technology that makes internet websites more accessible. It started with an artificial intelligent widget, as we call it an AI widget that can look at a site and add a lot of coding to the browser. And rather than doing it at the website, and but that makes the browser think that the website is more accessible, does it? Does it do everything? No, it doesn't. Because AI hasn't progressed that far. But it does a lot. That plus the other aspects of accessibility that are manually controllable can make all the access needs of a website available. But yet, well not. But yet, so excessive B was formed intentionally with the idea that over time, we need to get rid of the accessibility gap. As I said, 98% of all websites tend not to be accessible. And we're not changing that excessively, inexpensively begins to change that. So accessibe has a goal of making the entire internet world accessible by 2025. It's a very aggressive goal. And there are people who still stick with the idea that, well, we got to manually code things because that's the only way to completely do the job. And if we look at a lot of the websites that the manual coders produce, it's not necessarily doing the job either. But the reality is, it's fear that prevents things from happening sooner than they are or cures.   Coby Williams  43:35 So I'm not sure how familiar or knowledgeable you are about, you know, what's the metaverse and web 3.0? But curious to know, you know, you're taking on it a lot of the AMA techie by the way, but a lot of the things I've been reading and following. As we're talking kind of comes to mind, it seems to be largely based on you know, a visual experience, you know, there's the Oculus, you'll be able to see people doing this and doing that. And you know, your thoughts on maybe what are some of the possibilities from your perspective, for that or even cautions that you might have as that technology gets gets developed in ways that it can be most most useful for a variety of people?   Michael Hingson  44:21 Well, that's why I say the big a really needs to be the big nine until we really bring disabilities into the conversation. We're not going to change it. And there there are things that that in theory, web 3.0 And the new web content accessibility guidelines as web 3.0 comes out, will do. But will they be implemented? You can make all the changes that you want but until the conversation truly includes persons with disabilities, truly understands and includes those needs and makes it a part of what we do think These aren't going to change, here's a better way to look at it. There are a number. And it's a relatively small number of technological companies that really control the internet. You've got Microsoft or, for example, you have an Apple app, Amazon, Google, and a few others. And let's, let's go to the internet WordPress. Tell me one of them. That makes true inclusion and accessibility part of what they do right from the outset. And I'll help you the answer is not. Microsoft comes out with new versions of Windows or Microsoft a few years ago came out with a competitor to zoom, Google or Microsoft Teams. And yet, it took a while to make the app accessible. For persons with disabilities, for blind people on a PC, it came out actually as an accessible app first. But the bottom line is, it should have been done natively right from the outset. And no one disagrees with that. But it doesn't happen. The iPhone when it was first developed, was not accessible. It took the threat of a lawsuit to get Apple to deal with that, even so now that if you go buy an iPhone, it is accessible. And all of the parts of an iPhone will verbalize, but there's nothing that guarantees that apps will have any level of accessibility, you know, I can go through any number of examples, the so until the conversation changes, then we're not going to see the real change that we want to have. And the reality is that the conversation can change. And it will not only benefit, those of us who really totally depend on it, but it will help the entire world. The fact is, you can talk all day about how much more you can see with what will happen with web 3.0, and so on. But the reality is, eyesight is only one sense that we all have. And if we don't really begin to learn to use all of our other senses, in conjunction with eyesight for those of us who have it. And if we don't accept that not everyone uses eyesight, and there's nothing wrong with that and doesn't make us lesser beings, then we're not going to change the the whole situation and become an inclusive society. Yes, you're here, but that we can do? Well, for you. Have you always wanted to do what you're doing now?   Coby Williams  47:40 I? Short answer is, yes, I didn't know that you could make a career out of it. I, you know, I was was a super volunteer. That's kind of how I got my start, if you will, as a as a tween just, you know, volunteer stuff around the community, be self organized, or just getting involved in more formal programs or what have you. And, you know, when you when you do more, you get asked, get asked to do more. But I was in the IT field professionally, prior to doing what I'm doing now. And I, you know, again, didn't realize you could do a career out of it. It's just it, I considered it my work, you know, do it on the lunch hour or, you know, off the clock, but, you know, I can just consider I consider now my vocation and my craft, but I quite literally didn't know, you know, realize that it was a a profession. And in that regard,   Michael Hingson  48:51 what's a common myth of that you can say that people have about what you do?   Coby Williams  48:58 Oh, well, there's a few. Um, I think one is that, you know, I call my work as Public Affairs, which, you know, just kind of means I work with the public in a variety of ways that it is not. As I say, it's not just event planning, you know, oftentimes, folks, they focus on the winning the, where, you know, so what, you know, give us a date and a time, be it, you know, clients or what have you, and although that is a part of the work, that's the nature of the work for public affairs, when you're engaging with communities, that's just a means to an end. And that there's many different ways to engage with communities. So that's, that's a misnomer. Or my sometimes I say, frenemies and, and public relations whom I work with, you know, pretty regularly, but it's almost like a Venn diagram. There's there's some overlap between public relations and and Public Affairs, but there's ultimately different in games as well. Whereas I would argue, you know, public relations is kind of it's it's, you know, it's painting the room, it's, you know, decorating, it's accessorizing the room, and public affairs is kind of well, how does how do people receive it? Do they receive it is what they wanted in the first place? How do you get to accommodating that room? So that's those are a couple of common misnomers in terms of the nature of the work. And, you know, again, a lot of friends or family, you might think, oh, you know, Kobe is in politics. And it's, you know, I do have a background in legislative affairs, as well as, you know, grassroots community organizing and consulting. So I have been on each side of those, those tables. However, that's an oversimplification for, for the nature of my work, policy over politics, and, you know, issues over over party. So those are kind of a common, you know, myths that I try to dispel. Often,   Michael Hingson  51:11 there is nothing, it seems to me, no matter what we say about Washington and politics, but there's nothing like going to DC and walking the halls of Congress, and meeting with elected officials and talking about issues when they're willing to do that. It's an awesome experience to be in, in DC, where, you know, all this stuff happens. And it's a lot of fun to do.   Coby Williams  51:34 Yes, yes, at one point in my career, DC was a kind of a third home for me, I was there at least every two to three months, doing advocacy and or lobbying work, and no couple of state houses around the country and city halls and respective cities as well. And you know, a lot of my work, certainly in his current capacity I look at as connecting the say that the main streets and the Martin Luther King avenues with the, you know, City Hall avenues. And you know, what, what does that what does that work look like? Or what could that look like to move communities and move issues forward.   Michael Hingson  52:17 And it's really great when you find people who are willing to learn and explore and recognize that you have some different experiences than they do, and they want to really understand you. And I have found that any number of times in Washington, when meeting with people, and it's so cool when that happens?   Coby Williams  52:37 Yes, yes, absolutely.   Michael Hingson  52:39 So you have, I am sure been mentored by people that helped you move along, and so on. Who's your favorite mentor who really mentored you?   Coby Williams  52:51 Oh, wow. I had a teacher in junior Junior High in high school, Mr. Holloway, who I believe is still still with us. I actually came to mind about a couple of months ago. And I sent him a note online through through Facebook, just to thank him. I don't think he ever realized the impact that he had on my life just as a student, I had him for homeroom and high school. And he also taught history as well as African American history, which, you know, sadly, is an elective in most school school systems. And I remember the first day of class, I think it was just kind of American or colonial colonial histories, as I like to say, and you know, first day of class, we all have our textbooks out and you know, we're just ready to learn. And he says, Well, you're gonna put those away, ain't nothing but lies in them anyway. And it was, wow, you know, just just a 1617 year old kid, and, you know, everyone your thoughts, everyone just drops their textbooks when they're on the ground. And he taught just kind of the off, you know, what I got from it, just off authenticity. And, you know, that just that, that stuck with me, ran track a little bit in high school and coach T. Jimmy Turner, believe he is still with us and was just a very graceful, humble. He asked a lot from you, but in a very way that was, he wanted the best for you very respectful, and the lessons that I still carry with me off of the track, and he really cared about us and for many of us, quite frankly, we weren't exposed to male figures or role models in our lives. A lot of us really looked up to him and never wanted to, you know, disappoint him, on or off the track. So those were two, you know, people who I considered were definitely influential in, in my life, and certainly in those kinds of young and impressionable years, and, you know, lessons I still think about often and carry with me now, personally and professionally.   Michael Hingson  55:27 Isn't it interesting? How often, we remember teachers that were a great influence on us. A lot of people may say that they weren't necessarily charismatic, but the reality is they loved what they did. That got passed on to all of us, because I remember a number of my teachers and talk about them. I know, in my book, Thunder dog, we we talked about the Kerbal Shimer who I met, who was my sophomore geometry teacher, and we still talk. And I remember any number of my other teachers, which is really, I think, important and cool. And I'm glad that they were a part of my life, because they definitely had an effect on me. So I'm with you. Yeah. Yeah. Let me ask this, if you could meet and talk with any historical figure, who would that be? Oh,   Coby Williams  56:16 wow. And this is coming from a from a from a nerd and history history? Well,   Michael Hingson  56:22 that's why I asked.   Coby Williams  56:24 Oh, the name that immediately comes to mind is the late great. Dr. Martin Luther King. And I think my opinion is, regardless of what you think of him, it's probably still he's underappreciated. For one of the most documented figures, certainly in American history, be books that he wrote personally, or people close to him wrote about him, or, you know, we want to go down what what the government, you know, kind of kept kept tabs on extremely well documented person, but oftentimes for nefarious reasons. His his words have been twisted, his ideologies have been, you know, taken out of context. And, you know, I think he's a fascinating figure, because, you know, Dr. Cornel West says that his you know, Dr. King's image has become center, become like Santa Claus, Santa Claus, classified, I believe it's a term that he uses, but just the grace in the patients that he that he had. And, you know, he, you know, when he was taken from us, you know, following fifth 14 years of being, you know, jailed, brought bombed, harassed, etc, etc, and ultimately, you know, shot in the face as I like, like the telephone see, we have a 34% approval rating. And, you know, he's lionized now, but, you know, get he was taken, taken from us, which I think is really not mentioned in that light. Just, you know, just to have 15 minutes, with the man in person just to absorb the source of that patience and hope. And, you know, which is something that, you know, I think we all get benefit from,   Michael Hingson  58:37 I'm with you. And it makes perfect sense. I think it's, again, our historical figures, when we really study them do set a lot of examples that that we ought to emulate then, and it's so bad that his approval rating when he was alive was not higher than it was. But again, it's all about growth, isn't it? Yeah. Yeah. So you asked me to ask you a question. I've got to ask, which is, what's one insult that you've had in your life that you're proud of? You brought that up?   Coby Williams  59:14 Yeah. You know, I'm, I'm known. As I say, To Talk That Talk. I do challenge. I'm going to be a boat rocker. And I've, you know, that goes back. My mother will tell you that's just always been a part of who I am. And it's not to be provocative for the sense of being provocative. I just question why things are, and suddenly, when I was younger, I knew that's who I was, but might have been a little kind of felt bad about it at times, but I've fully embraced that. You know, I am a I'm an activist who happens to be a consultant. You will find very few consultants, particularly for what I do who who will say that publicly? They might maybe whisper that in closed rooms? No, you know, what you're getting with with Kobe with with new reach, and it is to challenge status quo as to challenge, you know, why are things the way they are? How can they be better? How can they be? How can you help put, you know, individuals or communities in a better place? And that does require being provocative, you know, not just for the sake of being, you know, I mentioned the way great Dr. King, he was considered provocative. You know, he was talking about justice and, you know, in the land of the free and that was considered to be, you know, rocking the boat. So, for me, it's all very relative, a lot of folks who we might look up to, it's afterwards it's after they've gone through hell, sometimes after they've been taken from us as because they did have a vision and they question things. And I, I'm not shy about doing that, but it's for a reason. And the spirit behind that is to put things people situations in a better place.   Michael Hingson  1:01:15 What are three books you would recommend that people ought to read?   Coby Williams  1:01:20 One I recently read is 4000 weeks it, wow, very powerful book, the premise of the book is really, maybe a paradigm shift of how to live a fulfilled life, with the time that you're given on this earth, and it really puts your own life in perspective, and you don't have to give too much of the book away. But, you know, we're not all that important in the grand scheme of things, and that's okay. The power of now is a very powerful book. That's, that's the guy she want to reread. I think that's a book that, arguably you might be able to read annually and still get something out of it. And it might might humble you in a bit. And, wow, a third. Think anything again, the late great Dr. King, he has auto biographies. He did, you know, write a few books while he was with us on this earth. And I think you can't go wrong with anything that he has. He has written. And, you know, so that might be cheating a bit. That's, that's, that's two plus. But those are some that I would recommend via titles and or authors.   Michael Hingson  1:02:50 You said something that's really interesting. You mentioned the power of now, isn't it great when you find a book that you read, that you can reread? And that you can reread and reread? And every time you discover something new in it?   Coby Williams  1:03:04 Yes. And what I like about is that, you know, the books I mentioned, aren't so much prescriptive their experiences, you know, I think that so many things that we want, okay, what are the three tips to life given to me, and it's, you know, that's just, that's not how things that's not how it works. That's not how it works. Life is an experience. And with experiences, you can get something out of it. Each time you kind of go through it.   Michael Hingson  1:03:32 Well, before we wrap up, we have to go over one more revelation regarding you and that is that you are a fan of basketball and specifically Yes, absolutely. The Los Angeles Lakers.   Coby Williams  1:03:44 Yes, absolutely. Like you know, I I originally grew up kind of watching baseball at the time, particularly in the early 90s. It was kind of that transition where it was less baseball, more NBA on TV. And I wasn't particularly a fan of any one team. But I just remember catching a game probably was on NBC at the time of the Lakers. It was kind of the later years of the lake show and it was wow they played differently than any other team they have fast breaks continuously and they run the floor and magic just being magic you know with with the ball and it just it really resonated with me it wasn't just throwing the ball in the post and you know, taking 20 dribbles with with the center of the power for no they were dishing the ball all over the court and just the razzle dazzle so I think that's what really got me was was the Lake Show and been a lifelong fan. Ever since. Yeah. And hoping for a better season this year.   Michael Hingson  1:04:58 Oh, I'm hoping for a better overseas. I must, I must admit that, for me, getting attracted to the Lakers to the Dodgers and to others, I got spoiled by the announcers la always had the best announcers. And in my view, I mean, there's nobody who could be Vin Scully and with the Lakers, Chick Hearn, although I also got to listen in Boston to Johnny most but still, no one did a game like Chick Hearn. And yeah, yeah, it was just kind of amazing. indican Berg out here also, who did the angels and, and did some of the football stuff as well. So we missed them all. But they're there. They're what attracted me in a way because I, I learned sports from those people, which was great. Well, I really want to thank you for being a part of this today and being with us. If people want to reach out to you and learn more about you. How can they do that?   Coby Williams  1:06:02 Yeah, thank you, you can check me out. nourishes website is new reach community.com. Or you can also follow me on LinkedIn where I'm pretty active on there as well. You can just search for Coby that C O B Y C Williams, and I'd love to connect with folks.   Michael Hingson  1:06:28 Well, great, and I hope you who are listening. We'll reach out. I think we had a great discussion. And I think we've given each other and lots of people who are listening, a great deal to think about which is what makes this whole podcast series a lot of fun. So thank you for being here with us. And I want to thank you all for listening. You're welcome to reach out to me, we'd love to hear what you think. Feel free to email me at Michaelhi at accessibe.com Accessibe is A C C E S S I B E.com. Please, wherever you're listening to this podcast, give us a five star rating. We appreciate your ratings and your comments. They're invaluable and they help us. If you know of anyone else who want to be on the podcast and Coby you included please feel free to let us know or reach out or provide introductions. But once again, Coby, thank you very much for being here and being a part of unstoppable mindset.   Coby Williams  1:07:25 You're welcome Michael, thank you so much for the invitation and be well.   Michael Hingson  1:07:34 You have been listening to the Unstoppable Mindset podcast. Thanks for dropping by. I hope that you'll join us again next week, and in future weeks for upcoming episodes. To subscribe to our podcast and to learn about upcoming episodes, please visit www dot Michael hingson.com slash podcast. Michael Hingson is spelled m i c h a e l h i n g s o n. While you're on the site., please use the form there to recommend people who we ought to interview in upcoming editions of the show. And also, we ask you and urge you to invite your friends to join us in the future. If you know of any one or any organization needing a speaker for an event, please email me at speaker at Michael hingson.com. I appreciate it very much. To learn more about the concept of blinded by fear, please visit www dot Michael hingson.com forward slash blinded by fear and while you're there, feel free to pick up a copy of my free eBook entitled blinded by fear. The unstoppable mindset podcast is provided by access cast an initiative of accessiBe and is sponsored by accessiBe. Please visit www.accessibe.com. accessiBe is spelled a c c e s s i b e. There you can learn all about how you can make your website inclusive for all persons with disabilities and how you can help make the internet fully inclusive by 2025. Thanks again for listening. Please come back and visit us again next week.

Summary:   This week's guest is Dan Roitman, the founder of Stroll in 2000, which is an eCommerce company specializing in marketing educational products to consumers. For 10 years, they had a compounded annual growth rate of over 70% and made the Inc 5,000 List 7 years in a row. By 2012 Dan grew the company to a professionally managed organization doing $85 Million in revenue and 166 employees. Dan championed Stroll's core competency, which was its ability to cost-effectively market products through an array of online channels with the use of sophisticated marketing analytics and optimization. In 2012 he was named Ernst & Youngs entrepreneur of the year in the Philadelphia region. Dan is an active member of the Young Presidents Organization (YPO) and today he's focused on Mindfinity, an early education company that teaches inventive IQ to kids. Because AI and automation will take away many of today's best jobs over the next 10 years, Dan and his companies are committed to helping kids thrive in this environment. Listen and enjoy!   Key Highlights:   [00:01 - 05:30] Opening Segment Dan shares his background and work Dan's desire to do an entrepreneurial thing since he was a kid   [05:31 - 11:01] The Highest Calling is Being of Service to Others How meeting mentors changed Dan's career Dan's journey from entrepreneur to a professional manager Why relationships are important for learning and growth in your life and business   [11:02 - 17:38] How to Leapfrog Your Success with Mentors Dan shares how he learned to be open to new opportunities and to value teamwork and collaboration Access to influential people can be helpful for entrepreneurs Dan was able to get access to influential people by being action-oriented and by being willing to help others   [17:39 - 19:35] Closing Segment Being of service to others is the highest calling, and Dan wants to help others grow and scale   Want to connect with Dan? Follow him on Facebook, and LinkedIn. Head to Mindfinity, and discover games that empower human innovation and create a brighter future for our kids!   Thanks for tuning in!   If you liked my show, please LEAVE A 5-STAR REVIEW, like, and subscribe!     Find me on the following streaming platforms: Apple Spotify Google Podcasts IHeart Radio Stitcher   Tweetable Quotes   "It's all about having an amazing team and amazing people around. All comes back to people." - Dan Roitman   "What really jazz is when I have a conversation with somebody, an idea comes up and they just run with it. And no matter what happens, if they just run with it and then come back and report back to me of just what happened that just motivates me to want to do more to help them." - Dan Roitman "At the end of the day, ultimately, the highest calling is being of service to others." - Dan Roitman      

Listen to the latest from Michele's podcast book tour! Searching for SaaS: https://searchingforsaas.com/podcast/ep25-local-restaurant-app-to-geocoding-as-a-service-michele-hansen-from-geocodio/One Knight In Product: https://www.oneknightinproduct.com/michele-hansen/Indie Hackers: https://www.indiehackers.com/podcast/224-michele-hansenMichele Hansen  0:01  This episode of Software Social is brought to you by Reform.As a business owner, you need forms all the time for lead capture, user feedback, SaaS onboarding, job applications, early access signups, and many other types of forms.Here's how Reform is different:- Your brand shines through, not Reform's- It's accessible out-of-the-box... And there are no silly design gimmicks, like frustrating customers by only showing one question at a timeJoin indie businesses like Fathom Analytics and SavvyCal and try out Reform.Software Social listeners get 1 month for free by going to reform.app/social and using the promo code "social" on checkout.Hey, Colleen,Colleen Schnettler  0:51  hey, Michelle.Michele Hansen  0:54  How are you?Colleen Schnettler  0:56  I'm good. I'm good. How about you?Michele Hansen  0:58  How goes week three now of doing Hammerstone and simple file upload.Colleen Schnettler  1:08  It's going well, today, I'm going to dedicate most of the day to simple file uploads. So I'm pretty excited about that. I'm finally back into my theoretical four days client work one day, my own thing and never really works out that way. Because I make myself way too available. But I have a lot of plans. But I do want to talk to you about something. Okay. I am I have not had any new signups in six weeks. Oh, yeah. I mean, I'm not in the pit of despair, because I'm just generally pretty happy about everything else. But I haven't been really on top of I know, six weeks. Right. That's really. I mean, IMichele Hansen  1:54  I hate to say it, but that does give me a little bit of like trough of sorrow vibes.Colleen Schnettler  1:58  Yeah. I mean, I honestly, I hadn't even really noticed, which is a different a different thing. Has anybody been canceled? I don't know. Because I, yeah, so I don't track that as well as I should. And I think with everything that's been going on, I have been so busy that I haven't. Honestly, I've just been letting it run itself. I checked my email every day, but no one ever emails me, which is nice, by the way. So I hadn't checked it in a while a and I checked it in preparation to do this podcast with you. And I was like, Oh, crap. I haven't had a sign up since July. This is September 2.Michele Hansen  2:39  So have I mean, has your revenue gone down? Like?Colleen Schnettler  2:44  No, actually, it hasn't. So I've been pretty consistent. So without doing a full churn analysis, I don't think people are churning. But they're not signing up. Okay, that's not okay. Let me stop. That's not entirely true. People are putting their email address in and then bouncing. So people are still finding my website. But yeah,Michele Hansen  3:12  I feel like it was like the people who are paying you is that mostly people from Heroku? or from your website?Colleen Schnettler  3:19  It's mostly people from Heroku.Michele Hansen  3:21  So are you still getting that like you had this problem where people were like, signing up on Heroku, but then not actually activating it? And like starting to use it, like, Are people still doing that first step on Heroku.Colleen Schnettler  3:37  So people are using it. I actually had one person respond with what he's doing. So that was cool. In terms of like a new signup. So people are using it that sign up on Heroku, which is good. It's just a lack of new signups is really confusing to me.Michele Hansen  3:55  Did you ever get that work done on the homepage like and Roku site like we were talking about the code pen and improving the documentation? And like, did did all that happen?Colleen Schnettler  4:10  So I have a whole list of great things I'm going to do so what I have done this week last week is I actually started writing a piece of I wrote an article right, it didn't take that long. I should have what it doesn't matter what I should have done. I did it. So that's good. So I have seen on Google Analytics said that is getting a decent amount of traffic. Today, literally today. I'm going to get that freakin try it now on the homepage. That is my plan to do that today. Nice. I'm speaking it into existence. The documentation is a whole different animal because I don't think I mean, I really need to redo the documentation. But that's like a whole thing. Like it's not I need to add some things. I think I need to take it in baby steps because I added some things to the tech side that are not reflected in the documentation that are kind of cool. So I think, but of course, instead of just adding that to my existing documentation, which I don't really like the way it presents, like, I just don't like the way it looks. I want to tear that all down and make a new app just for documentation, which I will do someday, butMichele Hansen  5:17  so it kind of sounds like you need to put away your laundry. But you don't want to do that. So instead, you're going to completely build yourself a new closet, butColleen Schnettler  5:26  my closets gonna be so pretty, and so organized.Michele Hansen  5:33  Yeah, I'm sensing a theme where like, you have a task that you don't want to do, or it seems overwhelming to you or you don't feel like it plays into your strengths. And so your way to do it is to make it something that is one of your strengths, which is actually just throwing more hurdles in front of you actually doing the task.Colleen Schnettler  6:00  Oh, yeah, totally. I mean, that's, like, it's funny, because before we got on this podcast, my plan was still to rewrite the whole documentation and make it its own site, blah, blah, blah. And as soon as I spoke those words to you, as I do, I've really is that really a super high priority, like, the higher priority should be getting the fact that like, I emit events on, you know, successful uploads, that's cool. People can use that. It's literally nowhere in my documentation that I do that. So I'm probably the priority should just be getting it out there with what I have. And then someday, when I have more time, I can rewrite the whole documentation site.Michele Hansen  6:39  This is your problem with the documentation that it's ugly, or that people email you telling you that it's janky. And, like, difficult to use documentation specifically, or is it just an eyesore? It'sColleen Schnettler  6:53  a it's an eyesore. I don't like the way it looks. I don't like the way I navigate with tabs. I don't like the tabs. Like I think you can still find everything no one has emailed me saying I don't understand how to use this. Hold on.Michele Hansen  7:05  I need to like I'm I'm pulling look at it. So nowColleen Schnettler  7:08  Yeah, pull it up. Okay, so if you go to simple file, upload.com, and then click on Doc's documentation,Michele Hansen  7:15  you got that calm, like,Colleen Schnettler  7:17  I know, I win it names. So if you look at it, I was like so I also bought unrelated simple file. Wait, what did I buy? I bought simple image upload calm. Hmm, I haven't done anything with it. I just snagged it. I was like, okay, that seems like what I should have. Okay, so look at this documentation page. Like, I just don't like the way it looks.Michele Hansen  7:40  I mean, it's not the ugliest thing I've ever seen. Like, it's basic, but like,Colleen Schnettler  7:45  it's fine. I mean,Michele Hansen  7:47  it like has a little bit of an old school README file vibe, but totally does. That's not a bad thing. Because that's how documentation was distributed for, like 20 years. And it's still sometimes distributed that way. Yeah. I mean, the other thing is, is like, I think it's okay to like, give yourself that space to be like, you know, like, this is ugly, and I hate it. I'm throw the content in there now. But also, when it comes time to build the documentation, like, there's so many tools for this, like, Don't design your own documentation to you know, like, like, if you're going to build yourself a new closet for all this, like at least buy one from IKEA, and then you just have to assemble it, like, don't go actually go out and buy the two by fours. And you know, like,Colleen Schnettler  8:42  do yeah, you're doing, I don't actually know what tools are out there to build documentation. So what do you guys use? Do you remember? Cuz I know you're right. This has got to be a thing. Like, you're absolutely right. IMichele Hansen  8:57  think I know someone who, like just bought a documentation tool.Colleen Schnettler  9:02  This is interesting.Michele Hansen  9:04  Because, like it definitely I don't I don't remember what the name is of the thing that we use. But we've actually we've actually had people reach out to us saying that they really liked our documentation and wanted to know where we got it from. Like, I think we just got it somewhere. Well,Colleen Schnettler  9:19  this is an interesting thing. I didn't actually I didn't even think about that. But absolutely, you're right, I should there's there's a better way to solve this problem than me. Does that make rewriting this whole thing? So what you're looking at now, the here's the real reason I want to redo it. What you're looking at now comes through the application page, and the application app does not use tailwind. My. My marketing site does use tailwind so that my thought would be to rewrite all of this documentation, put it on the marketing siteMichele Hansen  9:52  using tailwind because would you design it yourself with like tailwind elements or would you grab a template from tailwind.Colleen Schnettler  10:01  Oh, totally. I pay for whatever that thing is with tailwind where I can just copy the code and put it on. I bought that. Yeah.Michele Hansen  10:09  But it's worth it. It was totally worth anything is worth it. Totally Great. So yeah, there's I don't know, I don't know, read me.io. Right. Like there's all sorts of, is that what we use? That kind of looks like our docks?Colleen Schnettler  10:23  See, I didn't know that. IMichele Hansen  10:24  don't know. I don't think I'll have to ask Mateus. Right.Colleen Schnettler  10:28  So this is this is a good point, though. I should, because I don't need API documentation too. So I need to think about, yeah, readme.io has a whole documentation tab. Ooh, this looks fun. Oh, all right. I'm totally gonna check this out after the podcast, maybe that is the right answer.Michele Hansen  10:46  I don't know how much it costs. But yeah,Colleen Schnettler  10:49  well, it's gonna be cheaper than five hours of my time. Right. Right. Like, there's no way it cost that money, yourMichele Hansen  10:55  time is not free. And this is See See, this is I always say that, like, you know, I studied economics and undergrad. And I'm always like, Oh, you know, it was interesting, but it doesn't really relate. But here is where it does. Because, yeah, opportunity cost is a very real cost. And that is a perfect distillation of it that your time is worth more than spending five hours rolling your own documentation. thing when this is like already a solved problem.Colleen Schnettler  11:31  You're absolutely right. 100% agree with that. You're right. I didn't think about it that way. But that is a true statement.Michele Hansen  11:39  But first, I'd really just like tell people about the stuff you mayColleen Schnettler  11:44  think. Okay, so like, let's get actionable. Because AI, today is my day to work on simple file. So I think the first step, okay, I don't love the documentation I have, but I need to get the information out there. So the first step is just add something that's set like this things that people can use, like these event callbacks, or emitting events, like, that's useful information. So I'm just add it, you know, just adding it'll take all of 15 minutes. And like, I don't want to, you know,Michele Hansen  12:11  I don't want to be like standing on my, like, high horse here that like, you know, oh, we tell users everything we do, because actually, something we were just talking about this week was like, oh, like, we need to, like, send out an email to people and like, tell them about the features we've added because we basically stopped sending product updates, email, like, we never so. And then also like MailChimp shut down their pay as you go at one point. And, and then we're like, migrating and all this stuff. And I think we sent out like one email since then. But like, we were just talking about this the other day, that's like, oh, like we added support for like, geocoding a county, like if you know, you like have like a street address plus, like Montgomery County, Maryland, for example, like in places that like, use the county rather than the city name. We haven't told anyone about it, because we haven't sent any product updates, email, and God knows how long so I'm all this is to say that I am. I also need to take my own advice. And maybe other people too, maybe there's somebody out there, you know, just tell people about the thing you made. The thing you made? Yeah. Just tell them. Don't Don't think about you know, marketing stuff and ads and get all in your head about that. Just tell people. Yeah, even if it's a plain text email, just tell them just Just tell me advice I'm trying to give myself and I'm, I am trying to manifest it into existence that we will do that whole step to send out an email to get people to opt in. And then after that, we send out an email that tells them with the stuff we did, maybe that can be one email.Colleen Schnettler  14:42  Yes. So people tell people got it. I like it. That's good advice, your marketing advice. That's my marketing advice for the day I get to tell people. Yeah, so that's kind of what's up with me. I'm going to try And get those things implemented today. So hopefully that'll move the needle a little bit on signups. It was Yeah, it's definitely been a very trough of sorrow six weeks though I was like, Wow, that's a long time. eek.Michele Hansen  15:13  So I mean, there's the reason why there is that product lifecycle, like chart that has the trough of sorrow on it is because the trough of sorrow is normal.Colleen Schnettler  15:27  is normal. Oh, okay. This will be interesting.Michele Hansen  15:31  Yeah, yeah. There's like this whole image that's like the I didn't know that. Okay. Yeah. No, I when I said trough of sorrow, I was referencing something. Okay. I'll have to, I'll have to find it and send it to you. And also put it in the show notes. So everybody else who's like, What is she talking about? And then like five products, people listening are like, Oh, my God, I know that. I forget where it comes from. I think it might be like, it might have been a business of software talk at one point. ThatColleen Schnettler  15:57  Okay, oh, no,Michele Hansen  15:58  I think it might be the constant contact. Founder person.Colleen Schnettler  16:03  Has she interested in her? I don't know. Okay.Michele Hansen  16:07  Yeah, I'm gonna find it. It'll be in the show notes. So listening does not have to, like wonderColleen Schnettler  16:13  what it was to go dig through the internet to try and find itMichele Hansen  16:16  like normal to have, you know, periods when you're like, Okay, like, nothing happened. I mean, granted, you said that you kind of weren't really doing anything with it. So the fact that your revenue didn't like crater even though you basically didn't touch it for six weeks, like, that's awesome.Colleen Schnettler  16:36  Yeah, that's super awesome. Like,Michele Hansen  16:39  again, you know, to our conversations of like, if you ever wanted to sell this thing, like the fact that you didn't touch it for six weeks, and it kept making money. huge selling point.Colleen Schnettler  16:48  Yeah, yeah, it's super. so far. It's been super low touch, which is awesome. It's so funny, because years and years ago, I used to obsessively read. Do you know, Pat Flynn is smart, passive income guy? No. Okay. He's got this whole empire built about trying to teach people how to build passive income on the internet. Okay. And I used to obsessively read his blog. I mean, we're talking like 10 years ago. And here I am with kind of sort of passive income ish. And that's kind of cool. Yeah, you did anyway. So, yeah. Tell me about how things are going with the book and your podcast tour.Michele Hansen  17:26  Oh, so they're going so I think you had challenged me to be on 10-20 I feel like it was 20. I feel likeColleen Schnettler  17:37  I mean, it's been a while, but I feel like it was more than 10.Michele Hansen  17:41  So okay, so I have been on a couple at this point. So I was working, I was on searching for SaaS with Josh and Nate which sweet By the way, so of like people like our dynamic of like, you know, somebody like who has a SaaS and then somebody who's like trying to start one and like different phases, you would totally love searching for SaaS, because Josh has been running his business for, like, quite a long time, referral rock, has employees like, and then Nate is kind of has like consulting and is trying to figure out a SaaS. So I was on searching for SaaS, they were my first one. Um, and I'm so glad I did one with like, friends, because I was so nervous about the whole like, and I'm promoting a book, but it feels like self promotion, and I just just like is uncomfortable for me. So. So so I'm really glad I did it with them first, and then I recorded another one. That's actually they told me was not going to be out for another three or four months. So we'll hear about that one when it comes out. IsColleen Schnettler  18:45  that a secret?Michele Hansen  18:47  No. I mean, I just, I'll just tweet about it when it like comes out. But that counts, right? That's two. Yeah. And then I was on one night in product with Jason Knight, which came out a couple like, yeah, a couple days ago. That was super fun. Because that's like a podcast for product people. And we like really like dove deep on some of the different books and the differences and like, my fears around like people using this to like manipulate others was really it was really good. Um, so that's three and then I was on indie hackers, that that just came out. So that was kind of fun. I feel like I feel like I don't know like, I feel like it is like so legit. Like I don't know, it was kind of it was kind of wild. Indie hackers. Yeah. Being on the indie now.Colleen Schnettler  19:46  Did you talk about Geocodio or do you talk about the book or both?Michele Hansen  19:49  we talked about Geocodio a little bit but mostly about the book. Just kind of Geocodio as background.Colleen Schnettler  19:58  Okay. Yeah. Oh yeah, getting on Indie hackers that's basically making it. Like, that's amazing.Michele Hansen  20:05  Yeah. Like, can I be like, starstruck at myself for like,Colleen Schnettler  20:09  yes, you totally can. Like, I just think like, that's like, you know, that's like my life goal. No, that's not really a life goal. But I'm like, someday I will be on indie hackers. Someday Courtland will ask. I know, if I just take a couple more years. No, I love that podcast. I think that's wonderful. And yeah, yeah. Now you're kind of famous like, totally. Once you're an indie hackers, you've made it.Michele Hansen  20:33  I know, you're so funny. So like, I you're talking about this a little bit when when we add Adam on a few weeks ago that like, you know, I for a long time, like, like, so I didn't know that this whole community existed and that I knew about it, but I didn't feel like, feel like I was like, legit enough to like, be there, which was not true and was just my own imposter syndrome speaking. But for years, I had this like, sort of self policy that I would only go to conferences if I was speaking at them, because then people would come up to me and have something to talk about. Otherwise, I would be like standing in the corner, like not talking to anyone and like feeling like super out of it. Um, and so now I'm like, Okay, you know what, like, now if I like, go to something like, I feel like there's a good chance that like, one person, like, knows me, and we'll have something to talk about.Colleen Schnettler  21:29  Yeah. Yeah, that's great. I mean, that's a benefit of sharing your work, I think the way you have been. Yeah,Michele Hansen  21:38  yeah. So um, okay, so wait, so I lost count. Okay, so searching first as you're coming out in a couple of months. And Indie Hackers. Oh, wait, I think I forgot one. No, no, that's four. And then I recorded one yesterday. So that's five and then I am recording another one. today. So Wow, six. And then I'm scheduling another one. like trying to get that one on the calendar. Um, that person is also on pacific time like you and dude, it is so hard for me to schedule things with pacific time. Like, yeah, that nine hour time difference is required at the top planning. So I guess that's that's six I have either recorded or in the hopper. And I think there was more people who reach out to me, but I think they DMed me and I need to like, cuts through the jungle morass that is my DMs.Colleen Schnettler  22:48  That's great. I mean, honestly, 10 would it be spectacular? Colleen said, I have really 20. I know, now that I'm actually thinking through the logistics? That seems like a lot. Let me out of this. That's really great. So my next question would be, have you seen any, any impact yet of being on these podcasts? In terms of sales or community engagement or anything like that?Michele Hansen  23:15  Yeah, I mean, I guess the the biggest bump was definitely product times. Um, like, I think I saw like that day, like, I sold like 20 something. Or like, almost 30 copies, I think out of, I don't know, because I'm probably at like 350 now, or no, actually, it's more than that. Almost 400. So, oh, wait, maybe I'll be at almost 500 soon. That would be fun. Yeah. So So yeah, so there was definitely a little bump out of that. I did look this up for Josh and Nate from Searching for SaaS. And I sold three copies a day that one came out. So they were pretty pumped about that. I mean, I think it's the kind of thing where, like, not everybody, like listens to a podcast on the day. It comes. Yeah. Like, I was, like a regular listener of us. And like, they were like three episodes behind, because, you know, you've listened to it whenever you can. And there's other stuff going on. So in many ways, it's like, it's not really for the immediate hit of that in the same way that say like product time was,Colleen Schnettler  24:27  um, yes, yeah, yeah, long game.Michele Hansen  24:30  The long game there we go. Looking for. Um, so I mean, I guess we'll see. Right, because it's like, this is you know, this is not a like Big Bang. Launch. Right. Like, this is like the the book is hopefully designed or like written in a way, you know, to be a book that people recommend to other people they buy for their team. Like it's not like it's not particularly timely or relevant to like current events? So it's okay, if it doesn't, you know, sell like a bajillion copies in the first two months. Like, that's totally fine. You know, it's funny I was I was, I came across a tweet by our mutual friend, Mike Buckbee this morning, saying that, you know, validation for something is when you're getting stranger money. Like people who don't know you, they're not your friends. They're not the people that follow you. They're just like people who, you know, come across it for a reason. And then they buy it, and they're happy with it. And the book is definitely getting stranger money. SoColleen Schnettler  25:42  wonderful.Michele Hansen  25:43  Yeah. So So I so I think that's kind of a sign that it's, it was like, I mean, it was actually getting that in the presale. So. So I think that's a sign that, you know, things are in the right track, but it's just like, this is gonna be a slow burn.Colleen Schnettler  25:59  Yes.Michele Hansen  26:00  Yeah. So I mean, I'm happy with things, you know, again, like considering that, I think it was like most self published books only sell like 250 copies lifetime. And then most published books sell 300 copies their first year. Um, I've already, like smashed that. So anything on top of that, basically, is gravy. And but again, like those numbers, like are kind of like I look at that I'm like, Yeah, cool. Okay, like, but mostly, it's like, people tweet out, like, somebody tweeted out this morning that, like, they had their first customer interview, and it was delightful. And they learned so much. And like, they had scheduled it for 15 minutes. But at the customer's insistence, it went on for almost an hour. And they learned so much. And it was like, and I was like yes. Okay, like this. Okay, the book did what it was supposed to do like that. Yeah, that is what makes it feel like a success more than Yeah,Colleen Schnettler  26:49  that's anything that's really cool. Well, in the money. I mean, you know, I was thinking about, like, what motivates you Because for me, I want life changing money, you could get life changing money, any, anytime you want it like you You, you could just snap your fingers because you have a successful business. So that's something that I assume does not motivate you, because you kind of already have it. And so you know, when I think about the book, and like how you've been motivated, it really feels like helping people like really literally helping people learn how to be empathetic is what has driven this passion project for you.Michele Hansen  27:27  Yeah, yeah, absolutely. Absolutely. I mean, it's been a very, like, personal sort of mission, because it's not just about talking to customers like, and, and I guess what I mean, so one of them's actually this will be coming out the same day. So I guess I can talk about it. But I was talking about this a lot with Justin Jackson, on on Build Your SaaS about how, like, he was reading the book, and it made him realize like, oh, wow, like, I can actually use this in my personal life too. And like, it's like, not just a business book. And I was, you know, saying to him how, like, I think I've told you how, you know, people don't put be more empathetic on their daily to do lists, but they put, write the landing page, improve the documentation, get more sales, like, stop churn, figure out if people can use the thing I bill, like, that's the stuff that ends up on your to do list, and you can use empathy to solve those problems. And then in the course of doing that, you realize that you can transfer some of these skills to your personal life as well. Then it's like a double win.Colleen Schnettler  28:38  Wow. Yeah. So the other day, my 10 year old asked me what empathy was, and I literally handed him your book. Like, read this book.Michele Hansen  28:48  Let me guys this because this is the question that I get from children and adults, but children generally their first question, why is there a duck on the cover?Colleen Schnettler  28:58  He totally asked that. Yeah.Michele Hansen  29:03  Love it. Love it. Well, you know, you can tell him that he will find out when he gets to let me just flip through it here. I believe it's chapter 34. Um, you know, never accused me of burying the lede here. To get 138 pages, you will discover why there is a duck on the cover.It has been fun talking to you, as always, you too.Colleen Schnettler  29:45  I'll talk to you next week. All right.

It is hard to find a discussion of artificial intelligence these days that does not include concerns about Artificial Intelligence (AI) systems' potential bias against racial minorities and other identity groups. Facial recognition, lending, and bail determinations are just a few of the domains in which this issue arises. Laws are being proposed and even enacted to address these concerns. But is this problem properly understood? If it's real, do we need new laws beyond those anti-discrimination laws that already govern human decision makers, hiring exams, and the like?Unlike some humans, AI models don't have malevolent biases or an intention to discriminate. Are they superior to human decision-making in that sense? Nonetheless, it is well established that AI systems can have a disparate impact on various identity groups. Because AI learns by detecting correlations and other patterns in a real world dataset, are disparate impacts inevitable, short of requiring AI systems to produce proportionate results? Would prohibiting certain kinds of correlations degrade the accuracy of AI models? For example, in a bail determination system, would an AI model which learns that men are more likely to be repeat offenders produce less accurate results if it were prohibited from taking gender into account?Featuring: - Stewart A. Baker, Partner, Steptoe & Johnson LLP- Nicholas Weaver, Researcher, International Computer Science Institute and Lecturer, UC Berkeley- [Moderator] Curt Levey, President, Committee for JusticeVisit our website – www.RegProject.org – to learn more, view all of our content, and connect with us on social media.

It is hard to find a discussion of artificial intelligence these days that does not include concerns about Artificial Intelligence (AI) systems' potential bias against racial minorities and other identity groups. Facial recognition, lending, and bail determinations are just a few of the domains in which this issue arises. Laws are being proposed and even enacted to address these concerns. But is this problem properly understood? If it's real, do we need new laws beyond those anti-discrimination laws that already govern human decision makers, hiring exams, and the like?Unlike some humans, AI models don't have malevolent biases or an intention to discriminate. Are they superior to human decision-making in that sense? Nonetheless, it is well established that AI systems can have a disparate impact on various identity groups. Because AI learns by detecting correlations and other patterns in a real world dataset, are disparate impacts inevitable, short of requiring AI systems to produce proportionate results? Would prohibiting certain kinds of correlations degrade the accuracy of AI models? For example, in a bail determination system, would an AI model which learns that men are more likely to be repeat offenders produce less accurate results if it were prohibited from taking gender into account? Featuring: -- Stewart Baker, Partner, Steptoe & Johnson LLP -- Nicholas Weaver, Researcher, International Computer Science Institute and Lecturer, UC Berkeley -- Moderator: Curt Levey, President, Committee for Justice

Our guests is Holger Hoos, co-founder of CLAIRE, the Confederation of Laboratories for Artificial Intelligence Research in​ Europe, and professor of Machine Learning at Leiden University. I had the pleasure of joining Holger at last week's event  Vision for AI 2021 in response to the European Commission's publishing their “European Approach to Artificial Intelligence”.  We're chatting about the real back end of AI, its beginnings, why it's so cool, where do we already encounter it in our everyday lives and what should Europe's AI look like?Why should I care about AI? What are the right reasons?What would you have said to people 200 years ago on why should I care about electricity? Because it will change your life, work, everything, it will make things possible, it will make the world a better place, you can say the same about AIIt is a transformative technology. We have manoeuvred ourselves as humanity into a position where human intelligence is too limited for the mess we've made. We need more powerful tools than we've had in the past. Climate change and responsible and sustainable use of resources. A lot of people's views of AI has been formed by science fiction movies, in some cases, this is rather dystopian and in other cases, it's an overly optimistic view. Destroy us or make paradise? What we're really looking at is a foundational technology, computers taken to the next level. Automative AI - bringing down the level of expertise needed to use AI. People become more productive and what they do becomes better than what they can do alone. Why is it the most underappreciated area of AI?  Examples of aeroplanes flying, computers enabling us to talk to each other via zoom, what is enabling us to do all this? Automative reasoning - the hardware on which all of this is running, (banks, medical equipment), all computer-controlled, and we trust the hardware.Where should this not be used? If we were to date Mr Spock, we'd find that pure logic has limits. The same is for AI. Particularly when it comes to dealing with people, and all their limitations and bias.Human-centred AI  - AI build by people, for people, for the benefit of people. We have to compensate for some of our limitations, and automotive reasoning and deep learning does this well. It should do all of this in order to help us reach our goals, and this isn't something you can do as a second thought, it needs to be designed with this purpose.European AI - do we go it alone? Does it make sense to do anything of global consequence alone? No, it doesn't!CLAIRE - why does it exist? Because AI is important for our future, and all the citizens of Europe and the world. The two superpowers, China and the US are making massive investments, and there is a real risk of losing talent to them and the edge that we could and should have in AI technology that is so transformative.Is there such a thing as US AI or China AI or European AI? What are the differences? At a simplistic level, AI in China is government-driven, which is a great thing for China.  There seems to be a willingness in China to put up with technologies that are more prescriptive, more intrusive, and more focused on the benefits of the collective rather than the individual. US AI is very business-focused, driven primarily by big business. The huge US success stories begin at a University like Stanford and then become Google, or start in a garage and become Apple,  to a large extent US-based AI success stories are commercial success stories.

One of the founding principles of OpenAI, the company behind technology such as GPT-3 and DALL•E, is that AI should be available to all, not just the few. Co-founded by Elon Musk and five others, OpenAI was partly created to counter the argument that AI could damage society. OpenAI was originally founded as a non-profit AI research lab. In just six short years, the company has paved the way for some of the biggest breakthroughs in AI. Recent controversy arose when OpenAI announced that a separate section of its company would become for-profit. In this episode of Short and Sweet AI, I discuss OpenAI's mission to develop human-level AI that benefits all, not just a few. I also discuss the controversy around OpenAI's decision to become for-profit. In this episode, find out: OpenAI's mission How human-level AI or AGI differs from Narrow AI How far we are from using AGI in everyday life The recent controversy around OpenAI's decision to switch to a for-profit model. Important Links and Mentions: https://drpepermd.com/podcast-2/ep-what-is-gpt-3/ (What is GPT-3?) https://openai.com/charter/ (OpenAI's mission statement) Resources: https://www.youtube.com/watch?v=H15uuDMqDK0 (Elon Musk on Artificial Intelligence) Technology Review: https://www.technologyreview.com/2020/02/17/844721/ai-openai-moonshot-elon-musk-sam-altman-greg-brockman-messy-secretive-reality/ (The messy, secretive reality behind OpenAI's bid to save the world) Wired: https://www.wired.com/story/compete-google-openai-seeks-investorsand-profits/ (To Compete With Google, OpenAI Seeks Investors---and Profits) Wired: https://www.wired.com/story/company-wants-billions-make-ai-safe-humanity/ (OpenAI Wants to Make Ultrapowerful AI. But Not in a Bad Way) Episode Transcript: Hello to you who are curious about AI. I'm Dr. Peper and today I'm talking about a truly innovative company called OpenAI. So what do we know about OpenAI, the company unleashing all these mind-blowing AI tools such as GPT-3 and DALL·E? Open AI was founded as a non-profit AI research lab just 6 short years ago by Elon Musk and 5 others who pledged a billion dollars. Musk has been openly critical that AI poses the greatest existential threat to humanity. He was motivated in part to create OpenAI by concerns that human-level AI could damage society if built or used incorrectly. Human-level AI is known as AGI or Artificial General Intelligence. The AI we have today is called Narrow AI, it's good at doing one thing. General AI is great at any task. It's created to learn how to do anything. Narrow AI is great at doing what it was designed for as compared to Artificial General Intelligence which is great at learning how to do what it needs to do. To be a bit more specific, General AI would be able to learn, plan, reason, communicate in natural language, and integrate all of these skills to apply to any task, just as humans do. It would be human-level AI. It's the holy grail of the leading AI research groups around the world such as Google's DeepMind or Elon's OpenAI: to create artificial general intelligence. Because AI is accelerated at exponential speed, it's hard to predict when human-level AI might come within reach. Musk wants computer scientists to build AI in a way that is safe and beneficial to humanity. He acknowledges that in trying to advance friendly AI, we may create the very thing we are concerned about. Yet he thinks the best defense is to empower as many people as possible to have AI. He doesn't want any one person or a small group of people to have AI superpower. OpenAI has a 400-word mission statement, which prioritizes AI for all, over its own self-interest. And it's an environment where its employees treat AI research not as a job but as an identity. The most succinct summary of its mission has been phrased “… an ideal that we want AGI to go well” Two specific parts to its mission are to avoid building human-level AI that harms humanity or unduly concentrates...

+++ WON'T BE THE SAME +++ Every now and then there seems to be a food war among fast-food companies. Each one is trying to outdo the other by making a similar kind of product and promoting it as better than the other. The one that was first on the market - product #1 - has conditioned people's taste buds as to how that product should taste. Some people will have a hard time accepting product #2 as equal or better than product #1. So it is with Artificial Intelligence (AI). It is product #2 when it comes to being human-like. AI will never take the place of a human being all things being equal. Of course, there will be exceptions for a number of reasons. Because AI is here among us and is getting more and more prevalent in our world, some people are worried that they will be replaced by robots. Will they? Can leaders help their people to be better prepared? In this episode, I share three ways leaders can help their people be better prepared, reduce their anxieties, and embrace this technology. Please share this episode with one other person and leave a comment on the platform through which you listen to this show and/or on social media. Thanks so much. And remember, you are ONE SKILL AWAY... P.S. The Facebook Group is opened for leaders who want to succeed where others failed and become the leader everyone loves and wants to follow. Here's the link: http://www.facebook.com/groups/emotelligentleaders --- Send in a voice message: https://anchor.fm/kingsleygrant/message