Podcasts about only humans need apply winners

Julia Kirby is the co-author of "Only Humans Need Apply: Winners and Losers in the Age of Smart Machines," which documents how nearly everyone is vulnerable to being replaced by artificial intelligence and machine learning, and was a Financial Times best book of 2016. Kirby talked to AFP Conversations host Ira Apfel about her book, co-authored with Thomas Davenport, and what treasury and finance professionals can do to prepare for the technological revolution.  Thanks for listening to AFP Conversations. Please give it a review on your podcast app of choice -- it will help other listeners find the show, and host Ira Apfel will read your review on air.  

The O'Reilly Radar Podcast: The value humans bring to AI, guaranteed job programs, and the lack of AI productivity.This week, I sit down with Tom Davenport. Davenport is a professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a fellow at the MIT Center for Digital Business, and a senior advisor for Deloitte Analytics. He also pioneered the concept of “competing on analytics.” We talk about how his ideas have evolved since writing the seminal work on that topic, Competing on Analytics: The New Science of Winning; his new book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, which looks at how AI is impacting businesses; and we talk more broadly about how AI is impacting society and what we need to do to keep ourselves on a utopian path.Here are some highlights: How AI will impact jobs In terms of AI impact, there are various schools of thought. Tim O'Reilly's in the very optimistic school. There are other people in the very pessimistic school, thinking that all jobs are going to go away, or 47% of jobs are going to go away, or we'll have rioting in the streets, or our robot overlords will kill us all. I'm kind of in the middle, in the sense that I do think it's not going to be an easy transition for individuals and businesses, and I think we should certainly not be complacent about it and assume the jobs will always be there. But I think it's going to take a lot longer than people usually think to create new business processes and new business models and so on, and that will mean that the jobs will largely continue for long periods. One of my favorite examples is bank tellers. We had about half a million bank tellers in the U.S. in 1980. Along come ATMs and online banking, and so on. You'd think a lot of those tasks would be replaced. We have about half a million bank tellers in the United States in 2016, so... Nobody would recommend it as a growth career, and it is slowly starting to decline, but I think we'll see that in a lot of different areas. And then I think there will be a lot of good jobs working alongside these machines, and that's really the primary focus of our book [Only Humans Need Apply: Winners and Losers in the Age of Smart Machines] was identifying five ways that humans can add value to the work of smart machines. The appeal of augmentation Think about what is it that humans bring to the party. Automation, in a way, is a kind of a downward spiral. If everybody's automating something in an industry, the prices decline, and margins decline, and innovation is harder because you’ve programmed this system to do things a certain way. So, as a starting assumption, I think augmentation is a much more appealing one for a lot of organizations than, ‘We're going to automate all the jobs away.’ Guaranteed job programs If I were a leader in the United States, I would say the people who are going to need the most help are not so much the knowledge workers who are kind of used to learning new stuff and transforming themselves, to some degree, but the long-distance truck drivers. We have three million in the United States, and I think you'll probably see autonomous trucks on the interstate, maybe in special lanes or something, before we see it in most city, before we see autonomous cars in most cities. That's going to be tougher, because truck drivers probably, as a class, are not that comfortable in transforming themselves by taking courses here and there, and learning the skills they need to learn. So in that case, maybe we will need some guaranteed income programs—or, I'd actually prefer to see guaranteed job programs. There's some evidence that if you have a guaranteed income, you think, ‘Well, maybe they'll take up new sports or artistic pursuits,’ or whatever. Turns out, what most people do when they have a guaranteed income is, they sleep more and they watch TV more, so kind of not good for society in general. Guaranteed job programs worked in the Great Depression for the Civilian Conservation Corps, and artists and writers and so on, so we could do something like that. Whether this country would ever do it is not so clear. The (lacking) economic value of AI In a way, what’s missing in the AI conversation is the same thing I saw missing when I started working in analytics: it's a very technical conversation, for the most part. Not that much yet on how it will change key business and organizational processes—how do we get some productivity out of it? I mean, we desperately need more productivity in this country. We haven't increased it much over the past several years—a great example is health care. We have systems that can read radiological images and say, ‘You need a biopsy, because this looks suspicious,’ in a prostate cancer or breast cancer image, or, ‘This pathology image doesn't look good. You need a further biopsy or something, a more detailed investigation,’ but we haven't really reduced the number of radiologists or pathologists at all, so what's the economic value? We've had these for more than a decade. What's the economic value if we're not creating any more productivity? I think the business and social and political change is going to be a lot harder for us to address than the technical change, and I don't think we're really focusing much on that. I mean, there's no discussion of it in politics, and not yet enough in the business context, either.

The O'Reilly Radar Podcast: The value humans bring to AI, guaranteed job programs, and the lack of AI productivity.This week, I sit down with Tom Davenport. Davenport is a professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a fellow at the MIT Center for Digital Business, and a senior advisor for Deloitte Analytics. He also pioneered the concept of “competing on analytics.” We talk about how his ideas have evolved since writing the seminal work on that topic, Competing on Analytics: The New Science of Winning; his new book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, which looks at how AI is impacting businesses; and we talk more broadly about how AI is impacting society and what we need to do to keep ourselves on a utopian path.Here are some highlights: How AI will impact jobs In terms of AI impact, there are various schools of thought. Tim O'Reilly's in the very optimistic school. There are other people in the very pessimistic school, thinking that all jobs are going to go away, or 47% of jobs are going to go away, or we'll have rioting in the streets, or our robot overlords will kill us all. I'm kind of in the middle, in the sense that I do think it's not going to be an easy transition for individuals and businesses, and I think we should certainly not be complacent about it and assume the jobs will always be there. But I think it's going to take a lot longer than people usually think to create new business processes and new business models and so on, and that will mean that the jobs will largely continue for long periods. One of my favorite examples is bank tellers. We had about half a million bank tellers in the U.S. in 1980. Along come ATMs and online banking, and so on. You'd think a lot of those tasks would be replaced. We have about half a million bank tellers in the United States in 2016, so... Nobody would recommend it as a growth career, and it is slowly starting to decline, but I think we'll see that in a lot of different areas. And then I think there will be a lot of good jobs working alongside these machines, and that's really the primary focus of our book [Only Humans Need Apply: Winners and Losers in the Age of Smart Machines] was identifying five ways that humans can add value to the work of smart machines. The appeal of augmentation Think about what is it that humans bring to the party. Automation, in a way, is a kind of a downward spiral. If everybody's automating something in an industry, the prices decline, and margins decline, and innovation is harder because you’ve programmed this system to do things a certain way. So, as a starting assumption, I think augmentation is a much more appealing one for a lot of organizations than, ‘We're going to automate all the jobs away.’ Guaranteed job programs If I were a leader in the United States, I would say the people who are going to need the most help are not so much the knowledge workers who are kind of used to learning new stuff and transforming themselves, to some degree, but the long-distance truck drivers. We have three million in the United States, and I think you'll probably see autonomous trucks on the interstate, maybe in special lanes or something, before we see it in most city, before we see autonomous cars in most cities. That's going to be tougher, because truck drivers probably, as a class, are not that comfortable in transforming themselves by taking courses here and there, and learning the skills they need to learn. So in that case, maybe we will need some guaranteed income programs—or, I'd actually prefer to see guaranteed job programs. There's some evidence that if you have a guaranteed income, you think, ‘Well, maybe they'll take up new sports or artistic pursuits,’ or whatever. Turns out, what most people do when they have a guaranteed income is, they sleep more and they watch TV more, so kind of not good for society in general. Guaranteed job programs worked in the Great Depression for the Civilian Conservation Corps, and artists and writers and so on, so we could do something like that. Whether this country would ever do it is not so clear. The (lacking) economic value of AI In a way, what’s missing in the AI conversation is the same thing I saw missing when I started working in analytics: it's a very technical conversation, for the most part. Not that much yet on how it will change key business and organizational processes—how do we get some productivity out of it? I mean, we desperately need more productivity in this country. We haven't increased it much over the past several years—a great example is health care. We have systems that can read radiological images and say, ‘You need a biopsy, because this looks suspicious,’ in a prostate cancer or breast cancer image, or, ‘This pathology image doesn't look good. You need a further biopsy or something, a more detailed investigation,’ but we haven't really reduced the number of radiologists or pathologists at all, so what's the economic value? We've had these for more than a decade. What's the economic value if we're not creating any more productivity? I think the business and social and political change is going to be a lot harder for us to address than the technical change, and I don't think we're really focusing much on that. I mean, there's no discussion of it in politics, and not yet enough in the business context, either.

Thomas Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College in Massachusetts. He is an author, the co-founder of the International Institute for Analytics, a Fellow at the MIT Initiative on the Digital Economy, and Senior Advisor to Deloitte Analytics. He has spent the last 30 years focused on the Sociology of Information, studying and teaching about how people and organizations use information. He currently teaches MBAs at Babson College about Analytics, Cognitive Technologies, Big Data, and Knowledge Management. Thomas is the co-author of the new book, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. In the book Thomas and co-author Julia Kirby discuss the rise of job automation and how humans can secure their place in the workplace in the midst of this shift by using the 5 alternative strategies they lay out. The move towards automation in the workplace, while not new, is a controversial subject that is becoming a large part of our current work economy. There are two camps of people today, those who are opposed to the move towards automation and those who are embracing it. The people who are opposed are scared about the implications of automating jobs. They feel that this shift in our economy will create chaos and wipe out jobs for humans. The camp of people who are embracing it feel that automating certain jobs could be a good thing and that we will always find a way to create new jobs for humans. Thomas talks about how reality is somewhere in the middle of the two camps. While automation could cause some jobs to be at risk, it may not be as perilous as some people may think. He talks about how most jobs have several tasks to them, some of them are automatable and some aren’t. In the podcast he gives an example explaining how automation could help lawyers cut down on the time they take to search through documents and contracts for items pertaining to a case. This process probably only takes up about 20% of what lawyers actually do, so as Thomas mentions, this automation wouldn’t completely replace lawyers, but perhaps in a law firm of 10 lawyers, the automation would relieve the workload to the point where they can do with 8 lawyers instead of 10. In an Oxford study done in 2013 they estimated that 47% of U.S. jobs are automatable. People such as Stephen Hawking and Elon Musk have been very vocal about their concerns with the future of human jobs and our very existence in light of this rapid shift to automation. However, when you look at jobs that have already moved towards automation, such as bank tellers, it shows that the move may not be as rapid as they think. In the 1980s there were a half a million bank tellers, and today, there are still half a million bank tellers despite the invention and implementation of ATMs. While automation may not take over human jobs at an alarmingly quick rate, it is still something we need to be aware of. Automation, bots, and software are getting to the point now where they are becoming more capable of taking over knowledge jobs, whereas before they were only taking over labor intensive jobs such as manufacturing. Because of this, Thomas and Julia felt it was important to write their book that, first of all, encourages augmenting human labor with smart machines as opposed to completely replacing humans with machines and, secondly, shows people five ways to make themselves irreplaceable in the workplace. What you will learn in this episode: Is automation a new thing? Whether or not jobs are in jeopardy because of the growing use of automation and bots 5 steps you can take to be sure your job is secure The kinds of jobs that will be affected by automation and which ones will be safe Some encouraging examples of automation being used today In the move towards automation, what does this mean for organizations? What does it mean for individuals? How we can prepare for automation The timeline for automation and when automation will become mainstream Where the future of automation is going Links From The Episode: tomdavenport.com/ Only Humans Need Apply On Amazon.com   (Music by Ronald Jenkees)

Smart machines are coming, so what are we doing about it? Instead of cowering in fear, what if we took a proactive approach? What if there were a playbook we could use to anticipate and thrive in an increasingly automated world? In his book, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, Thomas Davenport, offers ways to accomplish that goal. His book is a guide for employees and students who want to know what they can do to work successfully with smart machines. Tom is a Professor in Management and Information Technology at Babson College and co-founder of the International Institute for Analytics. He is also a Fellow of the MIT Initiative on the Digital Economy and a Senior Advisor to Deloitte Analytics. He teaches analytics and big data at Babson, Harvard, MIT, and Boston University and has written over 17 books In this interview, we talk about: What the number of bank tellers working today can tell us about smart machines 10 reasons to look over your shoulder for smart machines in your own work What separates humans from machines The 4 markers of machine smartness and which one we are living now Why employers should aim for augmentation vs automation wherever possible How smart machines can liberate us to do more creative and valuable work Augmentation at its best in freestyle chess How we can step in with machines in the workplace Why we would want to step up with machines in the workplace What it looks like to step forward with machines in the workplace How we might step aside with machines in the workplace How some are stepping narrowly with machines in the workplace Why every organization needs an Automation Leader Why we need to get past STEM as the only solution The important role organizations play in providing professional learning Why Tom argues against universal basic income How companies can be more resilient in a digital age with increased competition The fact that so few of our political leaders are talking about this big shift Selected Links to Topics Mentioned @tdav http://www.tomdavenport.com/ Oxford Study on The Future of Employment Bricklaying Robots Ex Machina Freestyle chess Former WaMu Risk Officer Stretch by Karie Willyerd 2020 Workplace Report If you enjoy the podcast, please rate and review it on iTunes. For automatic delivery of new episodes, be sure to subscribe. As always, thanks for listening! Thank you to Emmy-award-winning Creative Director Vanida Vae for designing the Curious Minds logo, and thank you to Rob Mancabelli for all of his production expertise! www.gayleallen.net LinkedIn @GAllenTC

Nearly half of all working Americans could risk losing their jobs because of technology. It's not only blue-collar jobs at stake. Millions of educated knowledge workers—writers, paralegals, assistants, medical technicians—are threatened by accelerating advances in artificial intelligence. The industrial revolution shifted workers from farms to factories. In the first era of automation, machines relieved humans of manually exhausting work. Today, Era Two of automation continues to wash across the entire services-based economy that has replaced jobs in agriculture and manufacturing. Era Three, and the rise of AI, is dawning. Smart computers are demonstrating they are capable of making better decisions than humans. Brilliant technologies can now decide, learn, predict, and even comprehend much faster and more accurately than the human brain, and their progress is accelerating. Where will this leave lawyers, nurses, teachers, and editors? In Only Humans Need Apply, Thomas Hayes Davenport and Julia Kirby reframe the conversation about automation, arguing that the future of increased productivity and business success isn't either human or machine. It's both. The key is augmentation, utilizing technology to help humans work better, smarter, and faster. Instead of viewing these machines as competitive interlopers, we can see them as partners and collaborators in creative problem solving as we move into the next era. The choice is ours.  We were joined by Thomas Davenport co-author of the book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. To learn more about Thomas Davenport visit: www.thomasdavenport.com Personal Finance Cheat Sheet Article: http://www.cheatsheet.com/personal-finance/how-schools-can-improve-their-personal-finance-education.html/ Financial Advisor Magazine Articles: http://www.fa-mag.com/news/advisors-stay-the-course-amid-monday-s-market-drop-22864.html?section=3  http://www.fa-mag.com/news/on-it-s-80th-anniversary–advisors-consider-social-security-s-impact–future-22784.html?section=3 You can listen live by going to www.kpft.org and clicking on the HD3 tab. You can also listen to this episode and others by podcast at: http://directory.libsyn.com/shows/view/id/moneymatters or www.moneymatterspodcast.com #KPFTHOUSTON #Juliakirby  

If anything represents the new new thing in our technological age, it's the arena of artificial intelligence.  From the factory floor to the glittering glass office of law firms, smart machine are doing job, after job, after job. The conversation about jobs going offshore is so yesterday.  Today it’s robots and algorithms that are the threats. Manufacturing is only the beginning.  Service sector jobs, clerical jobs, accounting, paralegal, are all starting to be done by machines.  Drones will soon do deliveries and driving,  perhaps the largest bastion of blue collar jobs, will, within 10 years, be replaced by the autonomous vehicles. So what’s left for humans?  As machines start to program themselves, as we’ve seen with autonomous cars, as more and more higher level functions are done by machines, what’s a human to do? That the subject of Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, a new book by Julia Kirby. My conversation with Julia Kirby: 

There's no question automation is taking over more and more aspects of work and some jobs altogether. But we're now entering a "third era" of automation, one which went from taking over dangerous work to dull work and now decision-making work, too. So what will it take to deal with a world -- and a workplace -- where machines could be thought of as colleagues? The key lies in distinguishing between automation vs. augmentation, argue the guests on this episode of the a16z Podcast, IT management professor Thomas Davenport and Harvard Business editor Julia Kirby, who authored the new book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. But the argument isn't as simple as saying humans will just do the creative, emotionally intelligent work and that machines will do the rest. The future of work is complex and closely tied to the need for structure, identity, and meaning. Which is also why linking the discussion of things like "universal basic income" to the topic of automation isn't just unnecessary, but depressing and even damaging (or so argue the guests on this episode).