Podcasts about responsible ai

Theodora Skeadas is back for round two, and we packed in a lot! In Part 1, we got into red teaming, AI governance, and social scoring. This time we went wider, starting with what's happening to remote work and who gets left behind as companies pull people back into offices, tighten visa rules for trust and safety roles, and automate outsourced content moderation jobs. We talk about the "portfolio life" as a way to future-proof your career instead of betting everything on one role, what happened to Twitter's workforce demographics after the layoffs, and Theo's survivor-centered approach to fighting AI-generated intimate image abuse. We also make the case for treating cloud infrastructure as a public utility, and dig into the climate and water costs of data centers. Whew! Chapters 00:00 - Felicia and Rachel intro: Spider-Man's Vulture and class solidarity 11:02 - Remote work 18:45 - The case for a "portfolio life" 24:33 - Centering survivors in the fight against AI-generated intimate image abuse 32:13 - The case for treating cloud infrastructure as a public utility 35:54 - Data centers, water, and the climate cost of cloud infrastructure 46:41 - Panpsychism, consciousness, and AI Visit us at InclusionGeeks.com to stay up to date on all the ways you can make the workplace work for everyone! Check out Inclusion Geeks Academy and InclusionGeeks.com/podcast for the code to get a free mini course.

What should AI actually do for us, rather than simply what can it do?In this episode of Ethics and Innovation by Oxford+ brought to you by Equinox, host Susannah de Jager speaks with Dr Caroline Green, Director of Research at Oxford's Institute for Ethics in AI, about care as one of the defining ethical questions of the AI age. Caroline explains what care means inside a regulated social care system, why OpenAI and Anthropic have started borrowing the language of caregiving, and where she thinks that borrowing should worry us.The conversation moves between the very specific and the very broad: carebots collecting data while they chat to residents, the Oxford framework that helps providers question technology suppliers properly, a week in Dharamsala learning how Tibetan communities use AI to preserve their language, and the civic AI work she is developing with Ambassador Audrey Tang. New Stanford research published this month found that people with smaller social networks who turn to AI companions for emotional support report lower well-being, which makes Caroline's warning about caring-sounding systems timely. Two phrases anchor the episode: serving, not harming, and connection, not convenience.(00:00) - Welcome to Oxford+ (01:42) - What Care Actually Means (03:55) - Why Big Tech Has Adopted the Language of Care (05:53) - Job Displacement and the Doom Narrative (08:15) - Dharamsala, Monasteries and Tibetan Language AI (11:59) - What Makes Us Distinct as Humans (14:26) - The Oxford Framework for Responsible AI in Care (17:13) - Carebots and the Line between Task and Relationship (23:26) - Ageing Societies and the Rights of Older People (26:54) - Young People, Trust and Over-Reliance on AI (33:16) - Civic AI and the Ethics of Care (37:36) - Hope, Harm and the Civic Space Dr. Caroline Green: Dr Caroline Emmer De Albuquerque Green is Director of Research and Head of Public Engagement at the Institute for Ethics in AI, University of Oxford, where she leads the Accelerator Fellowship Programme. She is one of the UK's leading voices on the responsible use of AI in health and social care. Caroline co-led the Oxford Project on the Responsible Use of Generative AI in Social Care and wrote its April 2025 white paper setting out a value-led approach, work that led to the AI in Care Alliance whose vision and priorities were agreed at the second AI in Social Care Summit in March 2026. She also leads Truth and Trust: AI and Young People, a research collaboration with the BBC announced in February 2026. Caroline holds an LLB from the University of Edinburgh, an MSc in Human Rights from the LSE, an MA in Investigative Journalism from City University and a PhD in Gerontology from King's College London.Connect with Caroline on LinkedInSusannah de Jager: Susannah is a seasoned professional with over 15 years of experience in UK asset management. She has worked closely with industry experts, entrepreneurs, and government officials to shape the conversation around domestic scale-up capital.Connect with Susannah on LinkedIn and Subscribe to the Oxford+ Newsletter for Exclusive ContentOxford+ is hosted by Susannah de Jager and supported by Equinox.Produced and Edited by Story Ninety-Four in Oxford.

Leigh Felton believes we can benefit from AI systems without surrendering to them if we carefully consider the environments and behaviors we promote while deploying AI.Kimberly and Leigh discuss the power of perspective; organizations as people; using AI consciously; the AI environment and library etiquette; how AI use shapes human behavior; whether AI systems are adaptive; AI authority and narrow optimization; the gap between lived experience and historical data; the AI Emperor's new clothes; quiet organizational failures; and who benefits from humanizing AI.Leigh Felton is the President of the AI for Job Security Foundation. Leigh applies her extensive experience leading communications, business strategy and operations at the world's largest tech companies to help organizations make conscious decisions about and with AI. Related Resources:I Could've Been CEO Yesterday V1: But AI Algorithms Say I'm a DEI Risk Today (book)I Could've Been CEO Yesterday V2: Does AI Decide Who'll Be CEO Tomorrow? (book)Inside Power w/ Leigh Felton (newsletter)A transcript of this episode is here.

In this episode, Les Clonch, Vice President and Chief Information Officer, Scottish Rite for Children, discusses responsible AI adoption, cybersecurity, enterprise data strategy and the importance of governance and change management in navigating rapid technology advancements. He also shares how Scottish Rite is building technology capabilities and preparing its workforce to use AI effectively while keeping patient care and organizational priorities at the center.

Your crews are at capacity, you're turning down work, and the bench behind them is thin. You already know the answer involves bringing new people in, and you also know that handing a trainee a courthouse assignment isn't training.Brent, Steve, and Brandon walk through what Dudley built this year: roughly 100 checkpoints a landman needs exposure to, about 20 paid mentors, and more than a dozen energy management graduates working a six-month program. They get into why day rates finally started moving, what client backing looks like inside an MSA, and why nobody in land can define responsible AI yet.If you're growing a team without giving up the quality your clients hired you for, start here.Key Topics & Timestamps00:59 - Episode Intro01:29 - Summer Recap04:29 - Company Midyear Update07:52 - Mentor Program Pipeline18:33 - Day Rates and Costs23:27 - AI Disruption and Policy32:58 - AI Policy Uncertainty34:05 - Quality Control With AI36:57 - Using Versus Building AI40:42 - Annual Planning Playbook50:02 - College FootballMemorable Quotes"I've never been in a spot where I've turned down so much work, to be honest." — Steve"Training someone isn't just hiring them and throwing them out there. It's being responsible." — Brent"If you don't have young people coming into the industry, what's gonna happen in 10, 15 years?" — Brandon"There's a difference between using AI and building with AI." — KhalilKey TakeawaysBuild the training protocol before you recruit. Dudley mapped roughly 100 checkpoints a landman needs exposure to and lined up paid mentors first, then brought trainees in. Recruiting first and sorting out development later is what gave trainees a bad name.Pay your mentors. Mentoring pulls real time and attention away from billable work. Compensating mentors is what keeps a program alive past its first enthusiastic month.Sell the trainee program as a partnership. Clients fund six months of lower production and come out with ten to twenty landmen dedicated to their projects. Framed that way, Steve hasn't had a client say no.Day rates move when you explain the business, not the ask. Insurance, benefits, compliance, and now AI tooling all cost money. Walking clients through that math gets further than twenty years of asking for more.Free AI tools are a confidentiality problem. Contractors pasting client data into consumer chatbots are breaking the same agreements they signed. Approved-tool lists and contract language are the fix, and both belong in your MSA conversations now.Give every goal an owner. Annual planning holds up when each objective carries a named owner and a monthly progress update that goes out to the whole company, misses included.Help us improve our podcast! Share your thoughts in our quick survey.ResourcesKudu SuiteAmerican Association of Professional LandmenNeed Help With A Project? Meet With DudleyNeed Help with Staffing? Connect with Dudley StaffingStreamline Your Title Process with Dudley Select TitleWatch On YouTubeFollow Dudley Land Co. On LinkedInHave Questions? Email usMore from Our HostsConnect with ⁠Brent⁠ on LinkedInConnect with ⁠Khalil⁠ on LinkedInConnect with Brandon on LinkedInConnect with Steve on LinkedInConnect With UsReady to protect your land projects with integrated legal and title support? Our Dudley Select Title division works seamlessly with experienced oil and gas counsel to keep your deals on track and defensible. Contact us to learn how our complete energy partnership approach includes the legal expertise that matters when stakes are high.

Crystalyn Stuart-Loayza, Head of AI Transformation at Plus Company, joins the Shiny New Object Podcast to break down four principles for getting it right: process over policy, AI as a "tool mate", a Builder's Code, and better disclosure.

What separates organizations experimenting with AI from those successfully turning it into real business value? In this episode, Life Accelerated host, Olivier Lafontaine, speaks with Robi Krempus, Vice President and Head of AI for Global Wealth and Asset Management at Manulife Wealth and Asset Management, about how the organization is moving AI beyond prototypes and into production. Robi shares Manulife WAM's approach to applying AI across investment management, distribution, and operations, emphasizing the importance of business collaboration, governance, and designing solutions around real organizational needs. The conversation explores lessons from deploying AI-powered sales enablement tools, driving adoption, and measuring impact through data-driven outcomes. Robi highlights why organizations should focus on high-value use cases, balance complexity with business impact, and build the right foundations to scale AI responsibly across the enterprise. Key Takeaways: AI creates the most value when organizations move beyond experimentation and build solutions around real business needs through close collaboration with users. Successful AI adoption requires strong governance, clear business cases, and a path to production that turns prototypes into measurable outcomes. Scaling AI responsibly means prioritizing high-value, lower-complexity use cases first while building the foundations needed for long-term transformation.   Jump Into the Conversation: (00:00) Meet Robi Krempus (03:48) Leading AI for Manulife Wealth and Asset Management(05:20) Applying AI Across Investment, Distribution, and Operations(06:31) Why Data and Measurement Matter for AI Success(07:50) Moving Generative AI From Experimentation to Production(09:20) Building AI Governance and Organizational Readiness(12:59) Creating AI-Powered Sales Enablement Tools(15:16) Building Custom AI Solutions for Business Needs(16:33) Cross-Functional Teams Driving AI Implementation(17:51) Encouraging AI Adoption Across Sales Organizations(21:28) Personalization and Compliance in AI-Generated Content(23:08) Measuring AI Value Through Business Outcomes(24:38) Lessons Learned From Scaling AI Solutions(27:11) Choosing the Right AI Use Cases(29:23) The Future of AI in Wealth and Asset Management(33:11) Closing Thoughts on Enterprise AI Transformation   Resources: Connect with Robi Krempus: https://www.manulife.com/ca/en/personal/group-plans/resources/bio/robi-krempus Connect with Robi Krempus on LinkedIn: https://www.linkedin.com/in/robi-krempus-ba121135/  Learn more about Manulife Wealth & Asset Management: Manulife Wealth and Asset Management  Connect with Olivier Lafontaine: https://www.linkedin.com/in/olivierlafontaine/

The following article of the Professional Services industry is: “From Ethics to Profitability: How Responsible AI Powers Business” by Jaime Moreno, Founder & CEO, COMPLIA.

This week on Catalyst, Tammy is joined by NTT Data's Chief Strategy Officer Roli Agrawal for a conversation about implementing technology that works for everyone. Roli shares about her upbringing in India and how the privileges and discriminations she experienced made her passionate about fighting inequities. Roli shares her perspective on how bias creeps into AI systems, and what leaders can do to catch it early. They discuss what a responsible AI framework — trusted, ethical, secure, fair, and sustainable — looks like in practice, and why building datasets that reflect society is both a moral and a business imperative. Please note that the views expressed may not necessarily be those of NTT DATALinks: Roli Agrawal Learn more about Launch by NTT DATASee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Where should B2B leaders draw the line when using AI to create content? In this episode of Grounding AI, Donna Peterson shares an ethical struggle she has been thinking about as AI makes it easier to generate entire podcasts, blogs, case studies, presentations, and other thought leadership. Donna uses AI regularly. She trains companies on AI and believes it can be an extremely useful business tool. But there is an important distinction between using AI to organize and communicate your expertise and allowing AI to manufacture expertise that was never yours. For B2B companies with expensive products, complex services, and long sales cycles, that distinction matters. Buyers need to trust that the experience, opinions, case studies, and knowledge associated with your company are real. Donna discusses how she uses AI for brainstorming, challenging her thinking, organizing ideas, and making her own knowledge easier to communicate without asking AI to do the thinking for her. She also shares a simple question leaders can use when reviewing AI-assisted content: Where did the thinking come from? Was it based on your company's actual experience? A real customer? Your research? A real project? Your team's expertise? Your own opinions? AI should help your company communicate its expertise more effectively. It should not manufacture expertise your company does not have. If your team is using AI for B2B marketing, thought leadership, case studies, blogs, podcasts, or other business communications, this is an important conversation to have. Grounding AI is presented by World Innovators, helping B2B companies reach the right audiences, communicate clearly, build trust, and use AI responsibly in their marketing and business strategy. *** Reach out to dpeterson@worldinnovators.com if you'd like help building a marketing strategy that builds relationships and/or AI training for individuals or full teams.*** Visit www.worldinnovators.com for more resources on building stronger marketing and leadership strategies.*** Subscribe to the Grounding AI podcast for weekly insights into marketing, leadership, and the future of AI.

Today's guest is Clare Hickie, Chief Technology Officer, EMEA at Workday. Founded in 2005, Workday is a leading enterprise software company that provides cloud-based solutions for human capital management (HCM), finance, planning and AI-powered business operations. Workday serves more than 11,500 organizations worldwide, including over 65% of the Fortune 500. Workday helps businesses streamline operations, improve workforce management and make faster, data-driven decisions through its secure, intelligent cloud platform.In her role with Workday, Clare partners with senior business and technology leaders to help organizations transform how they manage people, finance and AI. With more than 30 years of experience in enterprise technology, Clare began her career on the customer side, spending 15 years at GSK before joining Workday in 2018. She is a recognized leader in responsible AI, cloud transformation and enterprise innovation, with a strong focus on building trusted, human-centered AI solutions that deliver measurable business impact.In the episode, Clare discusses:0:00 How AI conversations evolved from skepticism to agentic productivity5:51 Co-creating with customers to deliver proven AI outcomes7:19 How Workday's AI agents deliver significant productivity gains9:06 Creating consistent AI experiences built on a unified platform12:46 Responsible AI requires governance, transparency and risk management17: 33 How trust and responsible AI drive lasting customer adoptionTo find out more about all the great work happening at Workday, check out the website www.workday.com

Hallucinations are an eternal problem in generative AI in particular, and while it's true that large language models (LLMs) require vast amounts of data, the quality of that information will affect the quality of the output.What can businesses do to ensure they're using AI both effectively and responsibly?In this episode of the ITPro Podcast, Jane and Ross are joined by Amanda Stent, head of AI strategy and research in the office of the CTO at Bloomberg, to examine what responsible AI is, how organizations can use it, and what has been achieved at Bloomberg.Highlights"The (Bloomberg) terminal gives users access to more than 17,000 news providers, not just Bloomberg News, more than 1000 research brokers, more than 400 million documents from companies themselves, and billions and billions and billions of ticks – that's prices – every day for equities, bonds, commodities, derivatives, any kind of financial instrument you can think of. So, in that context, accuracy is paramount. If we hallucinate or do something that's otherwise incorrect, markets may move, and that might be bad.""We have guardrails that we run on every input to and output from a Gen AI system ... (which) are specific to financial services. For example, we don't want users to be injecting code into our systems. That's a generic guardrail, and we also are in the business of offering financial information, but not financial advice. So if you say. What's a buy case for IBM? We should give it to you. If you say, 'Should I buy IBM?' we should say, 'Nope, I can't answer that question because that's not something we're in the business of doing', and that's a finance-specific guardrail.""We have analysts using our AI systems to ... help them write their research reports more quickly, more easily to cover more companies, to understand the context of a company with its sector and its industry, to write on-demand reports for clients instead of a monthly or a quarterly report. We have portfolio managers doing the same thing, writing on-demand reports for clients using AI instead of quarterly reports. So these are some of the new ways in which people are using AI. But to me, traditionally it was about efficiency and signal generation. And today I think it's about effectiveness. So it's helping people become more effective in how they use AI."LinksAI hallucinations, accuracy still top concerns for UK tech leaders as adoption continuesThis new technique could improve AI output accuracy by 80% – and tackle hallucinations once and for allThe ITPro Podcast: Why doesn't more data produce better results?Bloomberg's Responsible AI Research: Mitigating Risky RAGs & GenAI in FinanceBloomberg Survey: How London's finance workforce is embracing AI on its own terms

Would you trust AI at only 80% accuracy? What about for your enterprise? KPMG Chief Digital Officer Kelle Fontenot explains why AI success cannot be measured by headcount reduction alone - and how synthetic data can help companies test agents safely, protect sensitive information, and focus on the moments that matter most to employees. -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In Episode 679 of the New Media Show, host and Podcast Hall of Famer Rob Greenlee welcomes Samara Beth Hurley, founder and CEO of Samara Beth & Co., for a wide-ranging conversation about experiential branding, audience trust, personal authority, storytelling, live events, artificial intelligence, and the growing value of real human relationships. Creators have more ways than ever to attract attention through podcasts, video, social media, newsletters, events, books, speaking, search, and AI-powered discovery. But attention is only the beginning. The deeper challenge is turning attention into trust, trust into authority, and authority into relationships that can support a lasting creator brand or business. Samara brings more than 30 years of experience across events, experiential branding, public relations, marketing, publishing, coaching, speaking, and business strategy. She explains why memorable experiences engage more than the mind. They involve emotion, physical presence, environment, story, and multiple senses, making them more likely to remain with an audience. The central idea of the episode is that content may introduce people to a creator, but experiences can make that creator memorable. From Attention to Experience: Why creators need more than visibility, impressions, downloads, views, or followers.  Samara explains that an immersive experience can involve all five senses and create a much deeper memory than a conventional piece of content. This can happen through an in-person event, retreat, workshop, book, video, virtual presentation, conversation, or carefully designed brand interaction. The goal is not simply to be seen. The goal is to make people feel something meaningful and consistent enough that they remember the creator, trust the message, and understand the value behind the brand. Samara also explains why events should be reverse-engineered around the desired audience result. Before selecting the venue, visuals, entertainment, content, or promotion, creators should determine what they want people to believe, feel, remember, and do after the experience. Credibility, Confidence, and Congruence: One of the central frameworks Samara shares is her three-part trust formula: – Credibility – Confidence – Congruence Credibility comes from experience, demonstrated knowledge, proof, media appearances, testimonials, awards, published work, results, and a consistent record of showing up. Confidence develops through practice. Samara discusses how speaking, presenting, selling, training, and communicating become stronger through repetition rather than waiting to feel completely prepared. Congruence means that the person audiences encounter across a website, podcast, social profile, book, stage, event, media appearance, and personal interaction should feel recognizably connected. Omnipresence With a Strategy: Samara describes herself as an “omnipresence fairy godmother” and explains why creators need to appear across multiple relevant platforms, media formats, and public channels. But omnipresence does not mean publishing without direction. Creators need a strategy that connects social media, podcasts, video, PR, books, articles, television appearances, events, awards, websites, and public profiles. Rob and Samara discuss the danger of throwing content onto platforms without a clear understanding of the audience, purpose, brand position, or desired business outcome. A creator may be visible everywhere but still be difficult to understand. The strongest public presence creates repeated, credible signals around who the person is, what they know, what they stand for, and why their work matters. Personal Brand Versus Business Brand: Samara explains the distinction between a personal brand and a business brand. A personal brand is connected to the individual's name, expertise, story, reputation, values, speaking, publishing, and long-term legacy. A business brand may be structured so it can grow beyond the founder, employ a larger team, scale independently, and potentially be sold. Not every creator needs both. – A coach, speaker, consultant, author, or experienced executive may only need a strong personal brand. – A founder building a company that can eventually operate without them may need a separate business identity and brand architecture. Turning Personal Stories Into Authority: How frequent moves, career changes, family experiences, loss, divorce, business transitions, and personal reinvention shaped Samara’s current work. The conversation examines when personal experience becomes a valuable market asset rather than simply a private story. Samara argues that people connect to stories because stories help audiences see themselves inside another person's experience. A strong creator does not need to reveal every private detail. A personal experience can be adapted, anonymized, reframed, or presented as a client, family, or community example when appropriate. The purpose is not personal exposure for its own sake. The purpose is to make knowledge relatable, memorable, and useful to the audience. Samara also describes how she integrated memoir elements into her business book, “WIN YOUR BRAND: The Unapologetic Playbook for Becoming Iconic”. Her personal stories support the larger lessons about branding, resilience, visibility, relationships, and authority. When the Brand Leaves the Screen: Why in-person events, retreats, masterminds, workshops, intimate gatherings, and community experiences may become more important as digital content becomes more abundant. Large conferences can provide scale and visibility, but smaller events can create stronger relationships. A person may speak to thousands of people from a major stage but only build genuine relationships with a smaller number through meals, conversations, workshops, shared activities, informal gatherings, and follow-up. Samara believes the market is moving toward more intimate experiences where participants can meet one another, build trust, share knowledge, and form partnerships. The most valuable part of an event may happen over coffee, dinner, a walk, a workout, a shared hotel stay, or a conversation after the scheduled programming has ended. Those interactions can create referrals, clients, collaborations, partnerships, friendships, and long-term business value. Creating Immersive Virtual Experiences: Not every creator or audience member can travel. Storytelling, visual design, direct eye contact, shared activities, gifts, music, food, demonstrations, physical materials, and guided participation can make virtual experiences more engaging. A virtual event cannot fully replicate physical presence, but it can be designed to foster stronger emotional engagement. Storytelling remains one of the most powerful tools. When a creator describes a setting, emotion, challenge, sound, physical feeling, or moment in detail, the audience can begin to experience that story even when they are not physically present. Samara supports the use of AI for research, workflow automation, idea development, organization, operational support, and production assistance. But warn against using AI in ways that create a false impression or weaken the audience's confidence in the creator, thereby breaking trust. Rob discusses his decision to label The New Media Show as human-hosted and his earlier consideration of creating an AI-generated co-host or clone. They explore how synthetic voices, avatars, cloned appearances, generated scripts, and automated media could become increasingly difficult to distinguish from human-created work. The risk is not simply that AI content exists. The larger risk is that an audience believes it is interacting with a real person and later discovers that it was misled.  Transparency, consent, rights, voice protection, likeness protection, and responsible disclosure will become more important as these technologies improve. Many of these tools remain inconsistent. They may produce images that do not resemble the person, use generic language, miss the creator's personality, or create more work rather than saving time. Samara advises creators not to purchase every new tool simply because an early price or lifetime deal appears attractive. The AI marketplace is crowded, and many products have not yet reached a reliable level of quality. Creators should begin with a clear problem, test the technology, measure the result, and determine whether the tool actually improves the work. Professional photography, original video, custom design, trusted partners, and human creative judgment continue to matter. Content Repurposing Versus New Content: The conversation also explores the tension between repurposing existing material and creating new content for specific platforms. AI can help extract clips, rewrite posts, summarize interviews, search archives, and transform old material into different formats. But audiences and platforms may still respond more strongly to content created for the current moment. Samara explains that her social media team encouraged her to reduce some repurposing and create more original, audience-directed content. The larger lesson is that efficiency should not replace relevance. Creators need a balance between extending the value of existing work and continuing to produce fresh ideas, stories, and perspectives. Relationships Are the Long-Term Advantage: The episode returns repeatedly to the value of relationships. Platforms, algorithms, content formats, AI systems, and business models will continue changing. A creator's strongest long-term assets may be credibility, relationships, reputation, trust, lived experience, professional network, and the ability to create meaningful human connection. AI can help operate the systems behind a business. AI can automate repetitive tasks, support follow-up, organize information, and free up more time. Samara's argument is that creators should use some of that saved time to be with people, attend events, build relationships, have conversations, and create experiences that technology cannot easily reproduce. Discussion Highlights – Why attention alone does not create trust or authority – How immersive experiences engage memory and emotion – Using all five senses in events, books, media, and brand experiences – Samara's three Cs of trust: credibility, confidence, and congruence – The difference between omnipresence and unstructured content publishing – Why creators need a clear personal-brand strategy – When a separate business brand is necessary – Turning lived experience into relatable authority – Using storytelling without exposing every part of private life – Why smaller, intimate events can create deeper relationships – Making virtual experiences more engaging and memorable – The value of books, speaking, PR, awards, podcasts, and media appearances – Balancing content repurposing with original platform-specific work – Using AI for research, automation, ideas, and workflow support – The limits of AI avatars, generated imagery, and creator clones – Protecting voice, likeness, intellectual property, and reputation – Why professional photography and original creative assets still matter – The importance of transparency when using AI – Using AI to create more time for real human relationships – Why networking after an event may be more valuable than the formal sessions – The movement toward smaller retreats, workshops, summits, and masterminds – Building a legacy while still being able to experience it Chapter Markers: 00:42 Why creator brands need more than content 02:22 Introducing Samara Beth Hurley 04:00 How experiences engage the five senses 05:20 Reverse-engineering events around audience outcomes 06:23 Building connection in person and virtually 08:47 Audience attention, energy, and human presence 09:32 Omnipresence across platforms and media 11:25 Samara's three Cs of trust 12:06 Building confidence through repetition 13:28 Congruence and consistency across a brand 14:25 Turning personal history into a relevant story 16:20 Content overload and the need for strategy 18:48 Why creators need a personal-brand strategy 20:11 Building a legacy while living it 21:06 Personal brands versus business brands 22:01 Separating private life from professional content 24:05 Executive transitions and second-act personal brands 25:50 Recession-proofing a business 26:32 The growing trust recession 27:54 What an immersive brand means today 29:25 Creating immersive retreats, workshops, and masterminds 30:31 Bringing experiential elements into virtual media 32:04 Storytelling that helps audiences feel present 34:17 Why relatable content performs 35:52 Using memoir and personal experience in a business book 37:20 Turning stories into business and brand value 38:29 Building trust through partners and vendors 39:52 Using AI to help shape stories and scripts 41:04 The difficulty of making AI speech feel human 41:55 Human-hosted media and the future of creator clones 44:04 Content scraping, archives, and AI repurposing 45:14 When repurposed content stops performing 46:12 Problems with AI-generated images and avatars 47:20 Why creators should stop buying every new AI tool 48:21 The coming AI platform shakeout 50:37 How established brands survive technology shifts 51:14 How creators should use AI today 52:15 AI for research, editing, and practical support 53:04 Why professional photos and original assets still matter 54:00 AI, copyright, likeness, and intellectual property 55:44 Using AI without replacing the creator 57:04 Transparency and disclosure 58:24 Adapting without losing human credibility 59:21 Trust must be earned 01:00:01 Why intimate events are returning 01:02:01 Relationship building versus event scale 01:03:23 Why smaller gatherings can be more memorable 01:04:42 Samara's future television and media plans 01:06:05 AI can create more time for human connection 01:07:05 Why the best networking happens after the event 01:08:41 Using automation to support real relationships 01:09:06 Responsible AI and protecting audience trust 01:10:03 Why Rob chose not to create an AI co-host 01:11:01 Avoiding deception with synthetic media 01:12:18 Where to find Samara Beth Hurley 01:13:05 “WIN YOUR BRAND” and Samara's audiobook plans About the Guest: Samara Beth Hurley, professionally known as Samara Beth, is the founder and CEO of Samara Beth & Co. She is an experiential branding strategist, event producer, speaker, author, business coach, and entrepreneur with more than 30 years of experience across events, public relations, branding, marketing, publishing, community building, and business development. Her work focuses on helping entrepreneurs, executives, authors, speakers, and creators turn expertise and personal stories into immersive brands that operate consistently online and offline. Samara is the author of “WIN YOUR BRAND: The Unapologetic Playbook for Becoming Iconic”, a combination of personal storytelling, branding strategy, resilience, and practical frameworks for building a memorable brand. Samara Beth & Co. https://samarabethandco.com Samara Beth Personal Website https://samarabeth.com WIN YOUR BRAND: The Unapologetic Playbook for Becoming Iconic https://brands.samarabethandco.com/winyourbrandbook Samara Beth Hurley on LinkedIn https://www.linkedin.com/in/samarahurley Samara Beth & Co. on Instagram https://www.instagram.com/samarabethandco About the Host: Rob Greenlee is a 2017 Podcast Hall of Fame inductee, Chair of the Podcast Hall of Fame, and a longtime new-media executive, creator, strategist, and industry leader.  He is the founder of Trust Factor Lab. The New Media Show https://newmediashow.com The New Media Show on YouTube https://youtube.com/@TheNewMediaShow New Media Show Audio on Apple Podcasts https://podcasts.apple.com/us/podcast/new-media-show-audio/id392545649 Rob Greenlee https://robgreenlee.com Rob Greenlee on LinkedIn https://www.linkedin.com/in/robgreenlee Rob Greenlee on YouTube https://youtube.com/@RobGreenlee Podcast Hall of Fame https://podcasthall.com AI Disclosure AI tools were used to create a video and audio introduction clip, episode images, help organize and edit this episode and its description, and create chapter markers from the completed Episode 679 transcript. The recorded conversation, human performances, guest perspectives, editorial direction, final review, and responsibility for the published content remain with actual human Rob Greenlee and Samara Beth Hurley.The post IRL Experiences Build Trust and Authority | Samara Beth Hurley #679 first appeared on New Media Show.

AI governance is becoming essential as businesses automate more decisions and connect artificial intelligence to sensitive corporate data. Nicky Downing, Founder and Chief Executive Officer at Guideline BizTech, explains why organisations must build trust, ethics, and accountability into AI systems from the beginning. She introduces RUBIQ Hub, an AI-first digital trust platform designed to help enterprises adopt AI responsibly, securely, and at scale. The discussion examines why many AI projects fail when they begin as isolated technology initiatives without sufficient business context. Downing explains the importance of governance, risk management, compliance, clear objectives, and ethical frameworks before automation is introduced. She also argues that people must remain accountable for AI-supported decisions. The human-in-the-loop model can allow businesses to automate repetitive work while reskilling employees for oversight, communication, and higher-value roles. For South African companies, the episode offers practical guidance on protecting confidential information, avoiding uncontrolled public AI tools, and ensuring that AI agents operate within defined responsibilities. 0:00 Intro 1:02 Nicky Downing's governance journey 4:19 Building trustworthy enterprise AI 11:49 Why trust matters in AI 17:33 The biggest AI adoption risks 25:21 Keeping humans in the loop 28:32 How the Ethos governance layer works Follow MyBroadband: X - https://twitter.com/mybroadband Facebook - https://www.facebook.com/mybroadband Instagram - https://www.instagram.com/mybroadband/ Website - https://mybroadband.co.za/news/ #AIGovernance #ResponsibleAI #ArtificialIntelligence

Sarah Barrington shifts from simply asking “real or fake?” to deeply considering the ways AI and synthetic media influence our notions of culture, identity and trust.   Kimberly and Sarah discuss her road from the fast track of F1 to the frontlines of AI; the genesis of photography; supercharging existing harms with GenAI; the unsavory roots of synthetic media; microtargeting and information warfare; the liar's dividend; content detection and digital identity; the agentic AI challenge; culture, identity and relevance; Mythos, AI access and proliferation; anti-regulatory narratives; the nuclear analogy; equipping policy makers and the public; questioning everything; and true AI enablement. Sarah Barrington is an AI researcher and PhD Candidate at UC Berkeley where she is part of Professor Hany Farid's digital forensics lab. She also holds multiple cybersecurity positions. A specialist in generative AI & deepfake analysis, Sarah's work has been cited at the Nobel Prize Summit, on NPR, by the UN and in numerous publications.  Related Resources: David Attenborough and the Voice That Revealed a Planet (article) Sarah's Research and Publications (website) The DeepSpeak Dataset Get Real Security Labs A transcript of this episode is here. 

Lately, a new framework has been creeping into AI boosterism: "harm reduction," or "responsible use." Education technology scholar dr. sava saheli singh joins Alex and Emily to unpack narratives around automation inevitability in the classroom. Spoiler alert: they're not actually "reducing harm" to students at all!An interdisciplinary scholar and filmmaker, sava is currently working on a research project examining secondary school teachers' experiences of genAI use, and making a film about the future of AI in education. Her speculative short film series on the harms of surveillance technology is available at screeningsurveillance.com.References:"Harm Reduction: A Strategy to Mitigate the Risks of AI"Also referenced: MAIHT3k newsletter, "How to talk about 'AI' without adding to the anthropomorphization"UNESCO "AI competency framework for students"Fresh AI Hell:Hallucination rebranded as "critical confabulation""Pennsylvania Board of Medicine Alleges Unlawful Practice of Medicine by an AI Chatbot""Google's smart home AI will be able to use clothing to identify people""Medicare AI program made them suffer in pain. Now they want answers""Why do these Castro gay bars have TSA-style face scanners?""County With 37 Data Centers Asks Schools to 'Conserve Electricity'"Palate cleanser: "Florida AG sues OpenAI, seeks to hold CEO Altman personally liable"Palate cleanser: "Norway imposes near ban on AI in elementary school"Check out future streams on Twitch. Meanwhile, send us any AI Hell you see.Find our book The AI Con here, and MAIHT3k merch here.Subscribe to our newsletter via Buttondown.Follow us!EmilyBluesky: emilymbender.bsky.socialMastodon: dair-community.social/@EmilyMBenderAlexBluesky: alexhanna.bsky.socialMastodon: dair-community.social/@alexTwitter: @alexhannaMusic by Toby Menon.Artwork by Naomi Pleasure-Park. Production by Ozzy Llinas Goodman.

Summary In this episode, Chad Burmeister interviews Jean-Marc Chanoine, Chief Sales Officer at Templafy, about AI transformation, its impact on sales and organizations, and responsible AI practices. They explore how AI is revolutionizing content creation, sales processes, and the future skills sales professionals need to thrive. Key topics AI transformation in sales Content automation and quality Responsible AI and ethical considerations Chapters 00:00 Introduction to AI in Sales 01:30 Customer Experience Transformation with AI 05:14 Creating Effective Sales Presentations 08:39 Measuring AI Impact on Sales 13:19 Misconceptions About AI 17:47 The Role of Human Responsibility in AI 29:43 Skills for the AI-Augmented Sales Professional   The AI for Sales Podcast is brought to you by BDR.ai, Nooks.ai, and ZoomInfo—the go-to-market intelligence platform that accelerates revenue growth.Skip the forms and website hunting—Chad will connect you directly with the right person at any of these companies.

Data innovation isn't about buying better tools. As Dallas and Cleveland show, it's about how leaders listen, support risk-taking, and work alongside agencies. The result? A culture where innovation thrives, and scales. Host Stephen Goldsmith speaks with Brita Andercheck, Chief Data Officer in Dallas, and Liz Crowe, Chief Innovation and Technology Officer in Cleveland, about how they drive transformative change across city governments. From reporting structures to how you listen to agencies to going out into the field yourself, they share the unglamorous work that actually drives transformation. In this episode, you'll learn: How to strike the balance between centralization and decentralization Why a problem-first approach beats technology-first Why data teams should measure their ROI The importance of collaboration and relationships How to create psychological safety so teams "fail smart" Guest: Dr. Brita Andercheck – Chief Data Officer and Director of the Office of Data Analytics and Business Intelligence, city of Dallas Dr. Liz Crowe – Chief Innovation and Technology Officer, city of Cleveland Listener Survey: bit.ly/datasmartpod Music credit: Summer-Man by Ketsa About Data-Smart City Solutions Data-Smart City Solutions, housed at the Bloomberg Center for Cities at Harvard University, is working to catalyze the adoption of data projects on the local government level by serving as a central resource for cities interested in this emerging field. We highlight best practices, top innovators, and promising case studies while also connecting leading industry, academic, and government officials. Our research focus is the intersection of government and data, ranging from open data and predictive analytics to civic engagement technology. We seek to promote the combination of integrated, cross-agency data with community data to better discover and preemptively address civic problems. To learn more visit us online and follow us on LinkedIn.

Most EdTech companies pitch schools before they understand how decisions get made inside them. School budgets are tight, sales cycles are long, and trust is hard to earn and easy to lose. In a market this crowded, the vendors who succeed are rarely the loudest ones. They are the ones who understand what a school leader is weighing before they ever pick up the phone.Smita Kolhatkar has sat on both sides of that equation. She spent 15 years in high tech before becoming an educator, and today she is Assistant Head for Innovation, Responsible AI and EdTech at Gideon Hausner Jewish Day School in Palo Alto. She evaluates new products constantly, built her school's AI Tinkery program to teach AI literacy from kindergarten up, and has a clear, specific list of what earns her trust and what ends a conversation before it starts.In this conversation, Smita walks through her actual buying process: the no-gos that end a pitch immediately, why conference expo halls still outperform months of email outreach, and why a single "no" from her can quietly close the door at several other schools too. It's a clear look at what that decision-making looks like from the other side of the table, for anyone marketing or selling into K-12.What You'll LearnThe specific deal-breakers that end a vendor conversation immediately, including SSO integration and cross-platform compatibilityThe buying signals that earn her attention, and the outreach habits that shut a conversation down fastWhy a single school leader's "no" often reaches ten other schools through her professional networkWhy conference expo halls remain one of her most valuable discovery channels, even in a digital-first marketWhy AI literacy needs to start at age five, and how her school's AI Tinkery program puts that into practiceHer take on the no-screens debate, and why treating EdTech as all-or-nothing misses the real question schools are askingWhy It MattersEdTech companies are working in one of the toughest sales environments in years: tighter budgets, longer sales cycles, and a market flooded with AI tools faster than schools can evaluate them. What Smita describes is not just one school's experience, it is a window into how school leaders across the country are making these calls right now. She is not only a buyer, she is a connector: when something works, it moves through her professional network, and when something falls flat, that travels just as fast. For EdTech marketers and sales teams, the lesson is that a sale is never just to one person. The trust built or lost in a single conversation compounds across an entire network of schools.Resources Mentioned in this Episode:Gideon Hausner Jewish Day SchoolThe K-8 school where Smita serves as Educational Technology and Innovation Director.AI Tinkery at HausnerThe maker-style AI lab Smita built for students to experiment hands-on with AI tools and concepts.AI Tinkery at Stanford GSEThe Stanford Graduate School of Education program that inspired Smita's AI Tinkery model, credited to Dr. Karin Forssell.Stanford Accelerator for LearningAn overview of the Stanford initiative behind the AI Tinkery framework.AI Quests and Day of AIA resource Smita references for structured AI literacy activities.Hour of AI A companion resource to Hour of Code, focused specifically on AI literacy."The Learning Frontier"Hausner's AI in Education confererence for educators.Smita Kolhatkar on LinkedIn

Key TakeawaysAI can either help reduce healthcare inequities or magnify existing bias, depending on how it is designed, trained, governed, and used.Responsible AI requires transparency, representative data, community participation, and clear accountability when tools fail or cause harm.Health equity work cannot be treated as philanthropy; it requires shared ownership across health systems, government, industry, nonprofits, and communities.Health systems must address existing bias in clinical language, protocols, and care delivery before expecting AI to fix systemic problems.Trust is built through transparency, shared power, community partnership, and honest conversations about the harms patients still experience today.ResourcesConnect with Tanisha Sullivan on LinkedIn.Follow Sanofi on LinkedIn and explore their website. Connect with Dr. Chris Pernell on LinkedIn.Follow the NAACP on LinkedIn and explore the website.Connect with Kimberly Wells on LinkedIn.Follow Ascension on LinkedIn and explore their website.

In the final episode of Season 15, Charles Suggs and Emma Whamond are joined by James Gray, co-author of Designing Elixir Systems with OTP, to talk about what has changed in software development and what still holds true. Years after the book's release, many of its core ideas around architecture, boundaries, supervision, and system design remain deeply relevant, even as AI tools reshape how developers learn, build, and collaborate. James brings a unique perspective to the conversation: he is an experienced Elixir and OTP educator who only recently began using LLMs in his own workflow. He shares what surprised him, where the tools have been useful, where they have created risk, and what happened when Claude accidentally wiped his local development database. The conversation explores how AI can speed up parts of the work while making foundational knowledge, code review, testing, and clear system boundaries even more important. To close the season, James and the hosts reflect on what developers should hold onto as the stack continues to shift. They discuss responsible LLM usage, the changing role of pair programming, who owns the mental model when AI helps write code, and why Elixir's long-standing strengths may matter even more in an AI-assisted development world. James is scheduled to speak at ElixirConf 2026, September 10–11 in Chicago, and the Elixir Wizards will be there too! Join us and the broader Elixir community, and use promo code Elixirwizards for 10% off in-person or virtual tickets at https://elixirconf.com/ Key topics discussed in this episode: James Gray's work on Designing Elixir Systems with OTP What still holds true in Elixir system design Layered architecture and durable software fundamentals Functional core, imperative shell in modern applications Supervision trees as application lifecycle maps Why boundaries still matter in AI-assisted development What AI changes about learning and building software What AI does not change about software design James' first month using LLMs When Claude erased a local development database Trust, verification, and responsible LLM usage The risk of AI-generated boundary violations Pair programming, mental models, and developer judgment Ethical and legal questions around AI tools Why OTP concepts still matter in distributed systems How Elixir thinking applies to AI agent workflows What developers should preserve as the stack shifts James' upcoming ElixirConf talk Links mentioned: Java Programming Language https://www.java.com/en/ Perl Programming Language https://www.perl.org/ Ruby Programming Language https://www.ruby-lang.org/en/ Best of Ruby Quiz by James Gray https://www.google.com/books/edition/Best_of_Ruby_Quiz/bMggAQAAIAAJ Designing Elixir Systems with OTP https://pragprog.com/titles/jgotp/designing-elixir-systems-with-otp/ RubyConf talk: Boundaries by Gary Bernhardt https://youtu.be/yTkzNHF6rMs Book: Real-World Event Sourcing by Kevin Hoffman https://pragprog.com/titles/khpes/real-world-event-sourcing/ Broadway Library https://elixir-broadway.org/ Supervision Trees https://elixir.hexdocs.pm/supervisor-and-application.html PostgreSQL https://www.postgresql.org/ ClickHouse https://clickhouse.com/ GenServer https://elixir.hexdocs.pm/GenServer.html Programming as Theory Building by Peter Naur https://pages.cs.wisc.edu/~remzi/Naur.pdf “A computer can never be held accountable, therefore a computer must never make a management decision.” – IBM Training Manual, 1979 Oban https://oban.pro/ Anthropic Claude Fable https://www.anthropic.com/claude/fable Claude Design https://claude.com/product/design Tidewave Agentic Dev Environment for Phoenix and Rails https://tidewave.ai/ 2x – nine months later: We did it https://ideas.fin.ai/p/2x-nine-months-later James Gray's Blog https://programmersstone.blog/about/ ElixirConf https://elixirconf.com/ ExMex https://exmexconf.com/Special Guest: James Gray.

Renée Cummings channels the spirit of due process while envisioning a radically imaginative world in which the benefits of ethical AI innovation are available to all. Kimberly and Renée discuss her radical optimism; finding joy in justice; AI's criminal misadventures; bringing an ethical imagination to AI; creative innovation; our responsibility to the future; AI as a public health challenge; the social contract and duty of care; how governance, data, and trust intertwine; due process as core to intelligence; child protection and the AWARE (algorithmic awareness and responsible engagement) campaign; giving love a break; and why responsibility requires honesty.   Renée Cummings is a Professor of Practice at the University of Virginia School of Data Science as well as a Nonresident Senior Fellow and Co-Director of the AI Equity Lab at the Brookings Institution. Renee also serves as the Co-Chair of the Global Academic Network at the Centre for AI and Digital Policy (CAIDP). Related Resources: Michigan Technology Journal: An Invitation to Partner (article) The A.W.A.R.E Initiative (Press Kit) Who is Raising Your Child? (A.W.A.R.E Initiative publication)  A transcript of this episode is here. 

In today's Cloud Wars Minute, I look at how Microsoft is helping schools move from AI experimentation to effective deployment. Highlights 00:08 — There isn't a sector that AI hasn't impacted, and with the proliferation of these technologies, it's important to examine individual sectors and analyze the effect of AI on them, both positive and negative. 00:23 — To understand where things are working and where they aren't. And that's what Microsoft has done with its 2026 "AI in Education" report. I want to share some of the key findings from that report with you today. Ultimately, AI has become mainstream in education, with 92% of students and education leaders, and 88% of educators, having used AI for school-related purposes. 00:60 — Adoption is increasing. In fact, 58% of education leaders report that their institutions are already implementing or scaling AI initiatives. According to the report, the biggest gap identified is the need for training, with both educators and students requesting more structured support. In fact, 66% of educators want AI training on a monthly or quarterly basis. 01:15 — While 52% of students are also seeking regular AI training. The priority highlighted in the report is responsible AI use, with 41% of students and 42% of educators citing academic integrity as a leading concern. Now, in response, Microsoft has announced new AI capabilities across Microsoft 365 Education and its broad education platform. 01:40 — These include AI-assisted unit planning for teachers, student AI guidelines, learning groups, enhanced classroom experiences in the Learning Zone, Copilot Notebooks, and a Study and Learn agent in Copilot Chat. The overall message from this research is that the focus in education is shifting from access to AI to its responsible deployment, with improvements needed in training, governance, and classroom-ready tools. Visit Cloud Wars for more.

Just because AI can, does it mean AI should?   Data cited in Kyndryl's 2026 People Readiness Report suggests increasing numbers of leaders will soon answer the question with, “Yes.”   The People Readiness Report found that 81% of respondents expect within 12 months, autonomous AI agents will make decisions with material business impact for their organizations. How will they get there? Particularly when roughly half of the respondents cite questions about bias, transparency, explainability and trust as top barriers to activating their AI strategy?   The barriers are matters of responsible AI. In this episode, AWS joins us with a perspective on how—and how well—organizations are working toward a future AI makes decisions with material business impact.   Featured experts   Diya Wynn, Responsible AI Lead, Amazon Web Services (AWS)  Tony De Bos, Global GTM and Consult leader for Security & Resilience, Kyndryl

AI is no longer a future trend. It is reshaping how organizations lead, innovate, and create impact today, and nonprofits are no exception.  DeAnna Hoskins is the President and CEO of JustLeadershipUSA, an organization led by formerly incarcerated people. She also served as a senior policy advisor during the Obama administration. Her experience in government and nonprofit leadership gives her a unique view on how technology, policy, and community work can come together to create positive change. During the conversation, DeAnna explains why nonprofits should invest in AI training before adopting new tools. She mentions that AI should support people, not replace them, and that human oversight is always important. She also talks about the need to reduce bias in AI, to create clear guidelines for its use, and to continue learning as the technology evolves. Furthermore, DeAnna discusses the role of philanthropy in funding AI education and helping organizations build the skills they need.  In this episode, you will be able to:  Recognize the value of AI training. Use AI with human oversight. Build responsible AI guidelines. Identify AI bias and risks. Create long-term AI strategies. Use AI to support teams. Understand AI funding needs. Get all the resources from today's episode here.  Support for this show is brought to you by Donor Perfect. Our friends at Donor Perfect really understand fundraising on so many levels. Stay aligned while working online with a seamless and secure payments experience for your donors and your team. Empower donors to give where they are, whenever they like, automate data entry, and process online, monthly, and mobile payments, and accept payments over the phone. Connect with me:  Instagram: https://www.instagram.com/_malloryerickson/ Facebook: https://www.facebook.com/whatthefundraising YouTube: https://www.youtube.com/@malloryerickson7946 LinkedIn: https://www.linkedin.com/mallory-erickson-bressler/ Website: malloryerickson.com/podcast Loved this episode? Leave us a review and rating here: https://podcasts.apple.com/us/podcast/what-the-fundraising/id1575421652 If you haven't already, please visit our new What the Fundraising community forum. Check it out and join the conversation at this link. If you're looking to raise more from the right funders, then you'll want to check out my Power Partners Formula, a step-by-step approach to identifying the optimal partners for your organization. This free masterclass offers a great starting point.

Send us Fan MailFor years, the AI industry has operated under a simple assumption: talent is global.That assumption is beginning to break.As governments increasingly view advanced AI as a matter of national security—not just commercial competition—companies are finding themselves caught between innovation, geopolitics, immigration policy, and global talent markets.In this episode of FUTUREPROOF., Jeremy sits down with David Krueger, AI researcher and professor, to explore one of the biggest shifts happening beneath the surface of the AI boom.Together they discuss: Why AI is becoming a geopolitical asset rather than simply another technology.  The implications of limiting access to frontier AI research.  Whether restricting international talent ultimately strengthens—or weakens—the United States.  How companies should think about trust, security, and collaboration.  The unintended consequences of an increasingly fragmented AI ecosystem.  Whether we're entering a technological Cold War—and what that means for everyone else. This conversation goes well beyond one company's policies. It's about who gets to build the future, who gets left behind, and how national security is reshaping one of the fastest-moving industries in history.

Join us as Faye Ellis breaks down what responsible AI actually looks like in practice on Amazon Bedrock - live demos included, straight from her prep for the AWS Generative AI Developer Professional certification. Faye walks through the NIST AI risk framework's core characteristics of trustworthy systems, then demos two hands-on builds: a RAG pipeline using S3 Vectors as a low-cost knowledge base, and Bedrock Guardrails blocking financial advice, prompt injection attacks, and sensitive information in real time. You'll learn the difference between prompt engineering and guardrails, how contextual grounding checks catch hallucinations before they reach a user, why data cleaning and deduplication matter as much for cost and sustainability as for bias, and what Faye wishes she'd known going into one of AWS's hardest professional-level exams. Timestamps 0:00 Welcome & Introduction 9:28 What Makes an AI System Trustworthy - The NIST Framework 15:19 Famous AI Failures - From ChatGPT Code Leaks to Biased Systems 22:56 Building RAG with Bedrock Knowledge Bases and S3 Vectors 26:29 Live Demo - Setting Up RAG with S3 Vectors 31:19 Prompt Engineering and Bedrock Prompt Management 34:46 What Are Bedrock Guardrails and How They Work 41:22 Live Demo - Blocking Financial Advice, Jailbreaks, and PII 53:00 Preparing for the AWS Generative AI Developer Professional Exam 59:04 Resources and Wrapping Up How to find Faye: https://www.linkedin.com/in/fayeellis/ https://app.pluralsight.com/profile/author/faye-ellis Links from the show: https://aws.amazon.com/bedrock/ https://skillbuilder.aws/ https://aws.amazon.com/certification/

Langithemba Mazibu – Senior manager: IT analysis, Information Regulator SAfm Market Update - Podcasts and live stream

Join us for an insightful episode of The Brand Called You as host Ashutosh Garg speaks with Jyothika Raju, Co-Founder and Program Director of ImpactAI Foundry.Discover how Jyothika's journey—from studying engineering in Bengaluru to leading initiatives at the intersection of artificial intelligence, public policy, and social impact—has shaped her vision for responsible AI.In this conversation, she explores:What responsible and accountable AI truly meansThe challenges NGOs and nonprofits face when adopting AIWhy capacity building is more valuable than technology dependencyPractical AI solutions already transforming the social sectorThe importance of collaboration between governments, universities, startups, and nonprofitsActionable advice for young professionals pursuing careers in AI for social good

Join us for an insightful episode of The Brand Called You as host Ashutosh Garg speaks with Jyothika Raju, Co-Founder and Program Director of ImpactAI Foundry.Discover how Jyothika's journey—from studying engineering in Bengaluru to leading initiatives at the intersection of artificial intelligence, public policy, and social impact—has shaped her vision for responsible AI.In this conversation, she explores:What responsible and accountable AI truly meansThe challenges NGOs and nonprofits face when adopting AIWhy capacity building is more valuable than technology dependencyPractical AI solutions already transforming the social sectorThe importance of collaboration between governments, universities, startups, and nonprofitsActionable advice for young professionals pursuing careers in AI for social goodWhether you're passionate about artificial intelligence, nonprofit innovation, public policy, or ethical technology, this episode offers valuable insights into building AI that creates meaningful and lasting impact.

Reggie Townsend: Making Responsible AI Irresistible Responsible AI has a design problem. Too often, it is treated as a compliance exercise, a policy document, or a late-stage control, when it should be the operating system that enables organizations to innovate with confidence. In this episode of Scouting for Growth, Sabine VanderLinden welcomes back Reggie Townsend, Vice President of AI Ethics, Governance and Social Impact at SAS, to explore one compelling idea: making responsible AI irresistible. Drawing on decades of experience helping enterprises embed trustworthy AI into their operations, Reggie explains why governance must evolve from abstract principles to practical systems people actually use. As organizations race to deploy generative and agentic AI, the conversation has shifted. Responsible AI is no longer just about avoiding harm—it is about creating the conditions for innovation, resilience, and long-term competitive advantage. Boards are asking tougher questions. Regulators are raising expectations. Employees increasingly need guidance they can apply in real-world decisions, not just policies they acknowledge once a year. This conversation is essential listening for CEOs, board directors, Chief Risk Officers, compliance leaders, AI product teams, and founders navigating the transition from responsible AI intentions to responsible AI execution.   KEY TAKEAWAYS One of the biggest insights I took from this conversation is that responsible AI is fundamentally a design challenge. We have spent years writing principles and policies, yet many organizations still struggle to translate those aspirations into everyday decisions. Reggie reminded me that if governance feels complicated, disconnected, or burdensome, people will naturally work around it. Our challenge as leaders is to make responsible behavior the easiest path rather than the hardest one. I was also struck by how governance is becoming inseparable from business strategy. As generative and agentic AI systems begin making increasingly autonomous decisions, governance can no longer be treated as a legal or compliance function operating at the edge of the organization. It has to become part of product design, procurement, operations, and executive decision-making. Trust is no longer something we communicate after deployment; it is something we engineer from the beginning. Another important theme was the preservation of human agency. While AI can dramatically enhance productivity and decision-making, Reggie reminds us that organizations must remain intentional about where humans stay accountable. The future is unlikely to be defined by replacing people with AI, but by designing systems where humans and intelligent machines complement one another in transparent and meaningful ways. However, perhaps my greatest takeaway is that responsible AI should become a competitive advantage rather than a regulatory obligation. Organizations that embed governance in their innovation will move with greater confidence because customers, regulators, employees, and investors will increasingly reward trust. Making responsible AI irresistible is ultimately about making good governance so practical, intuitive and valuable that people actively choose to adopt it—and that may prove to be one of the most important leadership capabilities of the next decade.   BEST MOMENTS "Responsible AI isn't about slowing innovation. It's about creating the confidence to innovate at scale." – Reggie Townsend "If responsible AI feels like extra work, we've designed it wrong. We have to make it irresistible." – Reggie Townsend "Governance shouldn't be something you visit once a year. It should be embedded into every decision, every workflow, and every system we build." – Reggie Townsend "The question isn't whether AI will make decisions. It's whether we've designed those decisions to preserve human agency." – Reggie Townsend "Trust isn't something you add after deployment. It's something you architect from the very beginning." – Reggie Townsend "We're moving from governing models to governing systems of intelligence—and that's an entirely different challenge." – Reggie Townsend "The organizations that thrive won't be the ones that adopt AI the fastest. They'll be the ones that build trust the fastest." – Reggie Townsend "Responsible AI is no longer just an ethics conversation. It's becoming a leadership conversation, an operational conversation, and ultimately a competitive advantage." – Sabine VanderLinden "As AI becomes more autonomous, our responsibility as leaders becomes even more intentional." – Sabine VanderLinden "The future belongs to organizations that can turn responsible AI from a policy into a practice." – Sabine VanderLinden   ABOUT THE GUEST Reggie Townsend is Vice President of AI Ethics, Governance and Social Impact at SAS, where he leads SAS' global AI Ethics, Governance and Social Impact organization. His remit includes the company's Data & AI Ethics Practice, AI & Society initiatives, AI Governance Advisory, Standards, Regulations & Risk Intelligence programs, and Accessible & Adaptive AI efforts. He drives SAS' work on trustworthy, human-centric innovation across products, policies, and partnerships.  Reggie is recognized as one of the clearest voices in responsible and trustworthy AI. He has served as a member of the White House National AI Advisory Committee, sits on the board of EqualAI, and works at the intersection of responsible innovation, enterprise governance, social impact, and emerging AI regulation. In this conversation, he explores how organizations can turn AI governance from a source of friction into a driver of adoption, accountability, and growth.    ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you're interested in sponsoring the podcast, reach out to the team at hello@alchemycrew.ventures

Subscribe now for an ad-free experience. Danny and Derek welcome to the show journalist and author Robert Wright to talk about the potential and pitfalls of the AI revolution. They discuss how neural networks learn, the differences between predictive and generative AI, machine consciousness, job displacement, the environmental costs of data centers, how capitalism is shaping the AI race, and the need for international regulation. Read Robert's new book The God Test: Artificial Intelligence and Our Coming Cosmic Reckoning. Learn more about your ad choices. Visit megaphone.fm/adchoices

Danny and Derek welcome to the show journalist and author ⁠Robert Wright⁠ to talk about the potential and pitfalls of the AI revolution. They discuss how neural networks learn, the differences between predictive and generative AI, machine consciousness, job displacement, the environmental costs of data centers, how capitalism is shaping the AI race, and the need for international regulation.Read Robert's new book The God Test: Artificial Intelligence and Our Coming Cosmic Reckoning.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

How will artificial intelligence impact jobs, workforce development, and the future of American manufacturing? In this episode of the Optimistic Outlook, Siemens USA CEO Ann Fairchild sits down with U.S. Senator Ted Budd of North Carolina to discuss the future of work in the age of AI. Building on insights from a recent U.S. Senate hearing focused on artificial intelligence and workforce transformation, they explore how AI is reshaping industries, creating new opportunities for workers, and driving innovation across the U.S. economy. Senator Budd shares why concerns about widespread job displacement are increasingly being replaced by conversations about productivity, workforce augmentation, and the growing demand for AI skills. Together, he and Ann examine the role of industrial AI, workforce training, public-private partnerships, and education in preparing Americans for the jobs of the future. The conversation also explores how AI can help strengthen U.S. manufacturing, accelerate reshoring efforts, improve competitiveness, and support responsible innovation. Rather than replacing people, they argue that AI has the potential to empower workers, enhance human capabilities, and unlock new economic opportunities. Whether you're interested in artificial intelligence, workforce development, manufacturing, economic policy, or the future of jobs, this episode offers an optimistic perspective on how technology can help build a stronger future for American industry and the people who power it. Topics discussed: Artificial intelligence and the future of work AI workforce development and job creation Industrial AI and manufacturing innovation Workforce training and AI skills Reshoring and strengthening U.S. manufacturing Responsible AI adoption Public-private partnerships and economic competitiveness Show Notes: Siemens VP Addresses Congress on Industrial AI: https://www.siemens.com/en-us/company/insights/us-stories/siemens-vp-addresses-congress-on-industrial-ai/

this week, we sit down with NYU professor and director of the Center for Responsible AI, Dr. Julia Stoyanovich, to break down what artificial intelligence actually is, how it works, and why understanding it matters more than ever. from chatgpt and ai companions to job loss, human connection, and the environmental impact of ai, we explore the technology without the hype or fear. whether you use ai every day or you're still skeptical of it, this conversation is all about separating fact from fiction and learning how to think more critically about the tools shaping our future. let's get into it!Julia's website: https://airesponsibly.net/Alice in Algorithmia: http://r-ai.co/alice Algorithmia: Happy Birthd-AI: http://r-ai.co/birthd-AIfollow ease:Instagram: ⁠https://www.instagram.com/ease⁠TikTok: ⁠https://www.tiktok.com/@easethepodcast⁠Spotify: ⁠https://open.spotify.com/show/51x8OhqmT9r3HLyenR52ER?si=40cfd03133084508⁠Website: https://www.easethepodcast.com/follow nailea:Instagram: ⁠https://www.instagram.com/naileadevora/⁠TikTok: ⁠https://www.tiktok.com/@billlnai⁠YouTube: ⁠https://www.youtube.com/naileadevora⁠follow justus:Instagram: ⁠https://www.instagram.com/justusbrycee/⁠TikTok: ⁠https://www.tiktok.com/@justilocks⁠© 2025 ease Hosted on Acast. See acast.com/privacy for more information.

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jeff Kunins, Chief Product Officer and Chief Technology Officer at Axon, the company that created the Taser and the body cameras federal agencies wear. Axon ingests more video per year than YouTube, and with a market cap of approximately $32.9 billion and $2.78 billion in revenue, growing 33% year over year, it is one of the highest-growth companies in the S&P 500. What you'll learn:How law enforcement agencies are using AI inside body cameras and Tasers to save lives, not just hit metrics.Why Axon declared a public moratorium on facial recognition AI for six years and what finally changed.How Axon embeds external activists and researchers directly into product manager squads as a design input, not a compliance process.Building first-party AI models for real-time license plate detection while using foundation LLMs for everything else.Key takeaways:Axon created the Taser and the body cam, and now ingests more video per year than YouTube. Most people have never heard of them.Build only what you must to be differentiated. Everything else, license from the best available source.Ethics review is not a compliance burden. When embedded in the product lifecycle, external critics help you see around corners and design better products.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jeff KuninsSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Ryan Bishara and Christian Lau team up on an AI and data playbook that delivers an engaging, penalty free experience for LAFC employees and fans on and off the pitch.   Ryan, Christian and Kimberly discuss LAFC's innovative ethos; building an analytics and data program from the pitch up; LAFC's AI plays; making mistakes and continuous learning; keeping AI onside with responsive governance; prioritizing joy and the human experience; if convenience and privacy can co-exist; staying accessible and engaging fans; and how analytics/AI continue to play out in a rapidly evolving ecosystem.  Ryan Bishara and Christian Lau serve as the EVP of Revenue & Strategy and Chief Technology Officer, respectively, at the LA Football Club (LAFC).  A transcript of this episode is here.

Good services don't start with the city's org chart or budget lines. They start by understanding the resident's actual journey — and all the hidden time, paperwork, and friction that comes with it. Host Stephen Goldsmith speaks with Dr. Kim Leary, director of the Good Services Lab at the Bloomberg Center for Cities at Harvard University, about how listening is an active skill, why selection bias shapes who gets heard, and how cities can use AI and resident-centered design to create services that actually work for everyone. In this episode, you'll learn: Why "good services" means residents can find, understand, and use them without insider knowledge How selection bias shapes civic engagement and why mayors must ask "who's not in the room?" How AI can help identify missing constituencies and unnoticed solutions in comparable cities Why organizing around the resident's journey changes service delivery How to measure progress at baseline, midpoint, and endpoint to track what's actually improving Guest: Dr. Kim Leary – clinical psychologist, professor, and director of the Good Services Lab at the Bloomberg Center for Cities at Harvard University Listener Survey: bit.ly/datasmartpod Music credit: Summer-Man by Ketsa About Data-Smart City Solutions Data-Smart City Solutions, housed at the Bloomberg Center for Cities at Harvard University, is working to catalyze the adoption of data projects on the local government level by serving as a central resource for cities interested in this emerging field. We highlight best practices, top innovators, and promising case studies while also connecting leading industry, academic, and government officials. Our research focus is the intersection of government and data, ranging from open data and predictive analytics to civic engagement technology. We seek to promote the combination of integrated, cross-agency data with community data to better discover and preemptively address civic problems. To learn more visit us online and follow us on LinkedIn.

What does responsible AI actually look like once you move beyond the headlines and start deploying it inside highly regulated businesses? In this episode, I speak with Richa Kaul, Founder and CEO of Complyance, about one of the biggest challenges facing enterprise AI today: building systems that people can trust. As companies race to adopt AI across every part of the business, governance, risk management, and compliance are no longer back-office functions. They are becoming central to every conversation about innovation. Richa shares the personal experiences that inspired her to build Complyance, from her work in public sector technology and legal AI to her long-standing passion for data privacy. We discuss why trust has become one of the defining themes of enterprise AI and why businesses must think beyond their own AI initiatives to also understand the risks introduced by third-party vendors. One of the most interesting parts of our conversation focuses on the difference between compliance and risk. Rather than viewing compliance as a box-ticking exercise or a cost center, Richa explains why AI has brought risk discussions directly into the boardroom. Business leaders are now asking deeper questions about how customer data is handled, how AI decisions are governed, and what safeguards need to exist before new technologies are deployed at scale. We also explore how AI is changing governance itself. Traditional compliance has often relied on manual reviews and simple pass-or-fail checks, but Complyance is applying agentic AI to introduce greater context and human-like judgment into governance workflows. Richa explains how that approach is helping reduce manual effort while allowing teams to focus on higher-value risk decisions rather than repetitive administrative work. Our conversation also covers practical advice for companies introducing AI into regulated environments. From evaluating third-party vendors and defining acceptable risk thresholds to adopting emerging AI standards and maintaining transparency throughout the process, Richa offers thoughtful guidance for leaders trying to balance innovation with accountability. Along the way, we also discuss Complyance's recent $20 million Series A investment led by Google Ventures and what that recognition means for the company's mission to modernize governance, risk, and compliance with AI. If your business is investing in AI while trying to strengthen trust, transparency, and responsible innovation, this episode offers a timely look at how governance is evolving alongside the technology itself. As AI becomes embedded into more business processes, how is your company building trust while still giving teams the freedom to innovate?

Theodora Skeadas has spent her career at the messy, consequential intersection of technology, governance, and harm reduction, long before "responsible AI" became a job title. She studied philosophy and government, witnessed the Arab Spring firsthand, spent years at Twitter facilitating the Global Trust and Safety Council, and now heads AI red teaming at Humane Intelligence while also serving as a PhD researcher at King's College London, board co-chair of the Integrity Institute, and advisory board chair of All Tech is Human. As she put it: she sleeps occasionally! We get into what red teaming is and why everyone, not just researchers and AI labs, should be doing it. We also talk about how trust and safety and AI governance are more connected than the headlines suggest, what social scoring actually means (yep, like that Black Mirror episode), the human cost of Meta pulling its content moderation contracts, what it takes to get into responsible tech right now, and how companies should be thinking about AI in hiring and performance reviews.  We didn't even get into all of our questions, so we had to do a part 2... stay tuned! Chapters 00:00 - Felicia and Rachel get into it... Knicks win, New York City, and the need for human connection 09:30 - Theo's origin story: philosophy, the Arab Spring, and landing in responsible tech 14:51 - Twitter's Trust and Safety Council, AI governance, and why they're more connected than you'd think 19:01 - Red teaming: what it is, who does it, and why everyone should be involved 24:30 - Guardrails: from social media deny lists to the EU AI Act 30:33 - Meta, BPO contracts, and the global human cost of cutting content moderation 32:34 - Social scoring: from Black Mirror to reality 37:31 - Online fraud, vulnerable populations, and the case for critical thinking 42:07 - Getting into responsible AI: honest advice for a crowded, shrinking field 50:33 - AI in the workplace and the global picture: governance, bias, language gaps, and what's next Visit us at InclusionGeeks.com to stay up to date on all the ways you can make the workplace work for everyone! Check out Inclusion Geeks Academy and InclusionGeeks.com/podcast for the code to get a free mini course.

Today's episode of the Punk CX podcast features a chat I had with Katja Forbes, Author, Advisor & Keynote Speaker, about her new book: Machine Customers: The Evolution has Begun: How AI that buys is changing everything. We talk about what exactly a machine customer is, what proportion of both B2B and B2C transactions are likely to be driven by machine customers in five years time, if we are seeing Doc Searls' Vendor Relationship Management (VRM) brought to life with this, what sort of agents will there be, who will provide them and what happens to “shopping”…..so many questions! This interview follows on from my recent interview – Responsible AI isn't an optional layer, it must be foundational – Interviews from Pegaworld 2026 Pt2 – and is number 593 in the series of interviews with authors and business leaders who are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees.

Chaitra Vedullapalli from Women in Cloud discusses the future of local commerce, the impact of AI, and the importance of adaptive leadership in the economic landscape. Chaitra discusses a topic that should be on every business leader's radar: the shift toward local commerce and how AI, community partnerships, and economic access are reshaping the way we buy, sell, and connect. Key TakeawaysWomen in Cloud's mission and accomplishmentsThe shift towards local commerce and trust-buildingThe role of AI in personalization and scalabilityEcosystem orchestration and powered marketplacesResponsible AI use and human element in technologyChapters00:00Introduction to Chaitra and Her Mission02:36Women in Cloud: Empowering Women in the AI Economy05:16The Next Trillion Dollar Opportunity: Local Commerce08:06Community Powered Marketplaces and Economic Engagement10:58The Role of AI in Local Commerce13:59Human Element in AI and Commerce16:39Hot Takes on Current Trends and Future Opportunities22:13Closing Thoughts and Call to ActionConnect with Chaitra and Women in Cloudhttps://www.linkedin.com/in/chaitrav/ https://in.linkedin.com/company/women-in-cloud

For nearly 160 years, the International Telecommunication Union has helped the world communicate across borders, from the telegraph to the telephone, television, satellite, the internet, and now AI. In this episode of Tools and Weapons, Brad Smith sits down with Doreen Bogdan, Secretary-General of the ITU, to discuss why connectivity remains one of the world's most important foundations for opportunity. The conversation explores the 2.2 billion people who are still unconnected, the estimated $2.8 trillion needed to connect the world by 2030, and the partnerships required to reach the hardest-to-connect communities. Doreen shares stories from the field, including a refugee camp in Chad where a small computer center gives people access to learning, health care, financial tools, and family connections. Brad and Doreen also discuss the rise of AI for Good, the challenge of scaling solutions that address real-world needs, and the role of global cooperation in shaping responsible AI governance. From early warning systems that can help save lives during natural disasters to digital skilling and infrastructure investment, this episode examines how technology can create opportunity when access, trust, and partnership come together. Listen to the full episode and join the conversation about building a more connected and inclusive digital future.

AI adoption is no longer just a policy conversation. For many organizations, the bigger question is how to move faster without creating avoidable risk.In this episode of The Tech Trek, Amir Bormand sits down with Aimee Cardwell, CIO and CISO in residence at Transcend, to talk about responsible AI deployment, the tension between speed and control, and how leaders should think about security, compliance, productivity, and customer experience as AI moves through the enterprise.Aimee brings a rare view across the CIO, CISO, and board lens. The conversation gets into why blocking AI often backfires, how prompt redaction can help teams move faster safely, where companies should draw the line on risk, and why some teams may need to rethink old assumptions about tech debt, code ownership, and modernization.Practical Takeaways• Responsible AI depends on the lens. Security, compliance, business, board, and technology teams may all define it differently.• Blocking employee AI usage can create worse outcomes. People may use shadow tools anyway, or teams may fall behind in productivity.• Prompt redaction and enterprise agreements can give teams room to experiment while reducing exposure of sensitive data.• Moving fast is not the same as releasing half finished customer experiences. Bad AI tools can train customers to distrust the entire interaction.• AI may change how teams think about tech debt, refactoring, and whether some legacy systems should be rebuilt instead of patched forever.Timestamped Highlights00:00 Responsible AI deployment and why the definition changes by role02:35 Aimee explains the CIO, CISO, and board perspectives on AI adoption05:14 Why companies that block AI may create shadow usage and slower teams06:52 Prompt redaction as a practical way to let employees experiment safely10:40 How AI risk changes when the data exposure model is different from traditional insider theft15:10 Why releasing poor AI customer experiences can damage trust21:50 Using shared enterprise prompts to raise the quality of AI output across engineering teams26:20 How AI could change the way teams approach security debt and code modernizationOne Line That Stuck“The conversation has flipped, and it is really how can I get the company to go faster.”Pro Tips• Start by identifying what truly makes your business defensible. Not every asset carries the same risk.• Give employees safe paths to use AI instead of pretending they will not use it.• Build shared prompts with engineering standards, approved tools, and company context so teams do not start from scratch every time.• Ask whether old assumptions still hold. Some decisions made sense when changes were expensive, slow, or risky. AI may change that equation.Subscribe to The Tech Trek for more conversations on how modern technical teams are building, hiring, operating, and adapting around AI, data, platform, product, and engineering execution.#ai #agentic #techleadership #engineeringleadership 

Today's episode of the Punk CX podcast is Part Two of a two-parter featuring a series of chats I had with Pega executives while at Pegaworld in Las Vegas a couple of weeks ago. In this episode, I talk with Matt Healy, Senior Director, Product Strategy & Marketing at Pega, and Tara DeZao, Senior Product Marketing Director at Pega. Some of the things we cover include the big themes and takeaways from the event, the future of customer service, ethical AI, the customer engagement blueprint and the new and exciting agentic capabilities of Customer Engagement Studio. This interview follows on from my recent interview with Ken Stillwell, COO & CFO at Pega and Peter Lacroix, Head of Low-Code, Achmea, a long-time customer of Pega's, called Moving from Experimental Pilots to Proven CX Outcomes – and is number 592 in the series of interviews with authors and business leaders who are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees. #PegaPartner

Get in touch - leave me a messageWhat if AI's biggest climate impact isn't chatbots, but cutting real energy waste in buildings, grids, and factories?In this episode of Climate Confident, I'm joined by Philippe Rambach, Chief AI Officer at Schneider Electric, to unpack one of the sharpest tensions in climate tech today: AI is increasing electricity demand, but used well, it may also be one of the tools we need for decarbonisation, emissions reduction, and a faster energy transition.You'll hear why Philippe argues that the real opportunity is not in chasing every shiny new model, but in applying AI to physical systems: reducing peak demand, optimising building energy use, supporting grid operators, and helping companies move from pilots to production. We dig into Schneider Electric's work on using AI to cut energy waste, including the striking claim that in some energy-saving applications, the carbon emitted to run the model can be dwarfed by the energy saved.We also get into the hard bits people love to ignore because apparently spreadsheets and wishful thinking are still considered strategy in some quarters. Why do so many AI pilots fail to scale? Why does domain knowledge matter as much as technical skill? How should businesses think about responsible AI, privacy, policy, net zero, and the operational realities of electrification?This is a practical conversation about AI for energy, not AI theatre.

Maitreya Shah disables harmful notions and aspires to a world in which AI systems honor the humanity and agency of disabled persons rather than using them as a shield.   Maitreya and Kimberly discuss digital tech done well; how society views disabled persons; engaging people with disabilities as leaders and developers; ableist narratives; why ‘fixing' disabilities misses the mark; confusing accessibility with AI for Good; whitewashing bad behavior with assistive tech; the false dichotomy between access and privacy; disability as a diverse identity; the high stakes for AI reliability and trust; the deepening digital divide; the dearth of disability data and resources; entrenched societal biases; and asking rather than deciding for people with disabilities. Maitreya Shah is a lawyer and researcher working at the intersection of tech policy and disability rights. Maitreya current serves as the Technology Policy Director at the American Association of People with Disabilities (AAPD). Related Resources: To Regulate Artificial Intelligence Effectively We Need to Confront Ableism (Article) Maitreya Shah (Profile) A transcript of this episode is here.

Why the most effective communicators help people see not just what's changing, but why it matters to them.For Sinéad Bovell, effective communication isn't just about explaining what's coming next—it's about giving people the confidence and agency to engage with it.Bovell is a futurist, founder of the tech education company WAYE, and an expert advisor to the United Nations AI Advisory Body. Known for making complex topics accessible to broad audiences, she has spent years helping leaders, organizations, and young people understand the implications of artificial intelligence and other transformative technologies. Her approach starts with a simple principle: meet people where they are and connect big ideas to what matters in their lives. “If you scare people too much, if you disempower them, [and] they do unsubscribe from the very activities you need them to lean into.”In this episode of Think Fast, Talk Smart, Bovell joins host Matt Abrahams to discuss how to communicate complexity without overwhelming people and why skills like adaptability and judgment are becoming more valuable in the age of AI. From making emerging technologies more accessible to building trust through relevance and empathy, they discuss what it takes to help audiences engage with change rather than fear it.To listen to the extended Deep Thinks version of this episode, please visit FasterSmarter.io/premium.Episode Reference Links:Sinéad BovellConnect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedIn Chapters:(00:00) - Introduction (01:00) - Explaining Complex Ideas (03:48) - The Future of Soft Skills (06:52) - Talking About AI Without Fear (10:33) - Storytelling for Young Audiences (12:46) - Reaching Young Audiences (15:01) - Career Pivots & Reinvention (16:53) - Becoming a Better Communicator (18:59) - The Final Three Questions (25:09) - Conclusion

Most home service companies don't have a lead problem. They have a follow-up problem. In this episode of Service Business Mastery, Tersh Blissett and Joshua Crouch sit down with Kevin Wu, founder of Leaping AI, to discuss how AI voice agents and automation are helping home service businesses solve some of their biggest call center challenges. From missed calls and slow follow-up times to after-hours booking and lead nurturing, Kevin shares how AI is being used as a practical tool to support customer service teams, improve speed-to-lead, and create better customer experiences without replacing people. The conversation also explores the future of AI-powered call centers, how contractors can automate repetitive tasks, and why business owners should focus on using AI to eliminate bottlenecks instead of simply cutting payroll. What You Will Learn in This Episode Why speed-to-lead is still one of the biggest challenges in home services How AI voice agents help capture missed opportunities The difference between replacing employees and supporting employees Why call centers struggle with consistency and process adherence How AI can improve appointment scheduling and follow-up The role of AI in call monitoring and quality control Why data quality inside your CRM matters more than ever How AI can help clean and organize customer databases The future of automated outbound campaigns The risks of AI abuse and spam calling How responsible AI adoption can improve customer experience Why contractors should start experimenting with AI today If you're looking for ways to improve call handling, increase booked appointments, and build a more efficient service business, this episode is packed with practical insights. Timestamps 00:00 Challenges with contractor responsiveness 03:11 Kevin introduces himself 08:58 Kids' interest in trade careers 09:45 Issues with Customer Support Responsiveness 14:00 AI improving call center efficiency 18:33 Solving data analysis with AI 20:55 Improving business metrics accuracy 25:37 Implementing EOS for business owners 29:31 Focusing on business priorities 32:00 AI for persistent customer follow-up 35:27 Responsible AI use in marketing 39:33 Data export issues in QuickBooks 40:45 Using AI to clean CRM data 43:35 Trying something new for 30 minutes Follow the Host and Guest Tersh Blissett: https://www.linkedin.com/in/tershblissett/ Joshua Crouch: https://www.linkedin.com/in/josh-crouch/ Kevin Wu: https://www.linkedin.com/in/kevin-wu-452a6393/ Connect with Us • LinkedIn - https://www.linkedin.com/company/service-business-mastery • TikTok - https://www.tiktok.com/@servicebusinessmasterypodcast • Facebook Group - https://www.facebook.com/groups/servicebusinessmasterypodcast • Instagram - https://www.instagram.com/servicebusinessmasterypodcast This episode is kindly powered by: UpFrog: upfrog.com  MarketStorm is an AI-powered advertising platform. Results vary by market, budget, and campaign configuration: https://marketstorm.ai/  Get Your 14-Day Free Trial with CallRail!: https://www.callrail.com/sbmpod CompanyCam: https://companycam.com/  Breezy: Capture 25-30% more clients with Breezy AI Agents. Use code 'SBM' to book a demo and get $500 on us: https://getbreezyapp.com/schedule-demo PhoneTAP: Your calls hold the key to growing your business. PhoneTAP gives you instant AI analysis, real customer lifetime value, and tools to coach your team. Learn more: phonetap.ai/demo