Ep. 14 | I Want AI to Do My Washing, Not My Creative Writing | The AI Values Podcast with Ming Tang

Ep. 14 | I Want AI to Do My Washing, Not My Creative Writing | The AI Values Podcast with Ming Tang

89% of UK organisations are deploying agentic AI. Only 21% have mature AI governance to match. What happens when you automate to death, and who pays?In Episode 14 of The AI Values Podcast, Edosa Odaro and Lindley Gooden are joined by Ming Tang, former Chief Digital, Data & Technology Officer at NHS England, for one of the most grounded conversations this podcast has produced on what responsible AI leadership actually demands. No hype. No techno-optimism. Just hard-won evidence from one of the most consequential AI and digital transformations in UK public sector history, applied directly to the decisions every board and C-suite faces right now.GUEST: MING TANG [https://www.linkedin.com/in/ming-tang-043a2411/]Ming Tang is a senior digital, data, and technology leader with a long track record of delivering large-scale transformation and value through modern digital platforms, data, and AI-enabled services. She led digital technology and data for NHS England, one of the largest technology functions in the entire UK government, and drove the work to create a digital-first NHS, encompassing AI diagnostics, electronic records, and national cybersecurity resilience.WHAT IS COVERED► "I want AI to do my washing, not my creative writing." Ming Tang draws the line most organisations miss: what AI should do, and what it should never touch. Get this wrong and everything starts to sound the same.► The fallacy of efficiency. Automating what you already do doesn't create value. It locks you in. Ming Tang on why efficiency without a reimagined outcome is a strategic trap, backed by what she saw at the NHS.► Human in the loop, NHS-style. Ming Tang's team built a four-agent framework to run checks inside clinical pathways. The human doesn't review every output. The human decides where the risk is. That's the difference.► The pre-mortem question. Before you deploy, ask: what don't you want AI to do to your organisation? Ming Tang says most boards skip this. She thinks it's the most important question in the room.► Cybersecurity is the agentic AI risk nobody is taking seriously enough. Bad actors are deploying millions of agents to probe your weak points. One gets through, and millions get paid. Ming Tang on why "doing more than the minimum" is now the floor, not the ceiling.⏰ EPISODE TIMESTAMPS00:00 — AI Governance in the NHS: What Should AI Never Be Allowed to Do? 03:03 — Ming Tang's Career, From Pharmaceuticals to NHS England06:58 — AI Augmentation vs. Replacement — What Does the Ideal Look Like?13:29 — The Fallacy of Efficiency: Why Automating to Death Locks Your Organisation In18:30 — Entry-Level Jobs, Critical Thinking, and the Generation AI Is Quietly Leaving Behind24:39 — Human in the Loop in Healthcare: The NHS Framework for AI Accountability32:20 — Cybersecurity, Agentic AI, and Why C-Suites Are Still Unprepared39:46 — Leadership Now: "What's One Decision You Need to Make Right Now?" — Ming's Answer──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more: https://www.theaivalues.org ◼ Reach out: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org◼ Co-hosts: Edosa Odaro [https://www.linkedin.com/in/edosa/] & Lindley Gooden [https://www.linkedin.com/in/lindleygooden/]

Ep. 13 | Who Decides the Trade-Offs Built Into Every AI? | ft. Tolu Adebekun

AI values are not created by AI capability alone. 95% of enterprise AI fails to deliver measurable ROI. The real problem is not the technology: it is alignment, leadership, and whether anyone in your organisation has actually defined what value means.In Episode 13 of The AI Values Podcast, Edosa Odaro is joined by data and AI professional Tolu Adebekun, stepping in for regular co-host Lindley Gooden. What follows is a sharp conversation about the gap between what organisations invest in AI and what they actually get back. This episode addresses the core failure of AI organisational alignment: the assumption that capability automatically produces value. It does not. And the downstream consequences, from fragmented organisations to concentrated power in very few hands, are playing out right now across every sector.THIS WEEK: A HEAD-TO-HEAD. Edosa Odaro and Tolu Adebekun take two angles on one problem: if most AI initiatives fail, and if capability is not the same as value, what exactly is leadership responsible for?► The sliding scale of AI anxiety. Edosa argues that the residual concern most people carry about AI is not about models or benchmarks. It is about relevance: their job, their judgment, their future. This anxiety runs from entry-level workers to the C-suite, and most organisations are managing it badly.► The AI amplification effect. "If you were terrible before, now that you've got AI to magnify that, you're just going to be worse." Tolu names what the data confirms: AI amplification works in both directions. Organisations with strong governance are pulling further ahead. Broken ones are breaking faster.► The biggest misconception in AI. "More capability would automatically mean more value. Unfortunately, it absolutely does not." Edosa draws on the spear analogy to separate capability vs value AI strategy: a pile of spears does not feed your family. Only the outcome does.► Every AI system has AI trade-offs built in, and most leaders have no idea who decided them. Whether you are using Claude, ChatGPT, or a traditional tool, someone has already decided the balance between speed, visibility, automation, and human judgment.► AI power concentration is now the leadership question. Tolu puts it plainly: fewer than 100 people have the influence to build the systems that billions now use. "I don't know a time in the world where we gave a few people lots of power and it went really well." 00:00 - AI Values: What People Are Really Worried About With AI01:17 - AI Governance: The Sliding Scale From Experts to Everyday Workers08:14 - Responsible AI Leadership: When Individual Anxiety Becomes Organisational Risk10:37 - AI Change Management: Why COVID Is the Right Analogy for AI Disruption16:14 - AI Amplification Effect: Why Good Organisations Win More and Broken Ones Break Faster24:53 - Capability vs. Value AI: The Biggest Misconception in AI Explained42:41 - AI Trade-Offs: Already Built Into Every System You Use44:35 - AI Power Concentration: Less Than 100 People Deciding AI for All of Us──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more: https://www.theaivalues.org ◼ Reach out: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch [https://pages.theaivalues.org] ◼ Co-hosts: Edosa Odaro [ https://www.linkedin.com/in/edosa/] & Lindley Gooden [https://www.linkedin.com/in/lindleygooden/]◼ Special guest: Tolu Adebekun [https://www.linkedin.com/in/toluadebekun/]

Ep. 12 | 80% of AI Unused: How to Be in the 20% That Works | Nicolas Averseng | The AI Values Podcast

80% of data and AI products in organisations are never used. That is not a pilot problem; it is an AI value management crisis happening at scale right now.In Episode 12 of The AI Values Podcast, Edosa Odaro and Lindley Gooden sit down with Nicolas Averseng, Chief Product Officer at DataGalaxy and founder of Yui, one of the world's first dedicated AI value management platforms. This is one of the most practically uncomfortable conversations the podcast has produced. Nikola introduces what he calls "the fallacy of efficiency": the idea that the 30% productivity gains promised by agentic AI and GenAI deployments rarely materialise once they meet a CFO's scrutiny, and he explains why this trap catches even the most capable organisations. If your AI business case rests on efficiency gains, AI risk management, or responsible AI governance, this episode is required listening for your board.ABOUT NICOLAS AVERSENG:Nicolas Averseng is Chief Product Officer at DataGalaxy. He previously founded Yui, one of the world's first value management platforms for data and AI investments, which was acquired by DataGalaxy. He specialises in transforming data and AI governance from a compliance exercise into a genuine catalyst for value creation, and works with senior leaders globally to close the gap between AI investment and AI ROI.◼ Nicolas Averseng: https://www.linkedin.com/in/naverseng/WHAT IS COVERED:► The 80% problem: why the majority of data and AI products in organisations are never adopted, and the root cause most CDOs and boards refuse to acknowledge until it is too late► The fallacy of efficiency: how the promise of AI-driven productivity gains disappears when it meets the CFO's budget review, and why efficiency alone is the wrong objective for responsible AI implementation► The foundation-building trap: why organisations spend years building data platforms nobody uses, and how outcome-led AI implementation and minimum viable use cases change the equation entirely► AI value versus AI risk: Nikola's core argument, captured in his own words ("There is no value story without the downside"), explains why AI governance and AI risk management are not separate conversations, and how the EU AI Act is forcing this realisation even on organisations that resist it► The 14-month CDO problem: why chief data officers burn out before they deliver, what the average tenure of 12–24 months tells us about the state of AI value management, and what genuinely fixes it⏰ EPISODE TIMESTAMPS:00:00 — Cold open: years building a data platform nobody could use00:45 — Lindley introduces the 80% stat, what is it really costing us?04:49 — The foundation-building trap: why organisations build before they think08:15 — Starting from the end: the minimum viable AI use case approach12:09 — What does "value" actually mean? ROI vs. genuine user benefit16:40 — AI's wider cost: employment, ESG, client relationships, trust20:19 — The fallacy of efficiency: why GenAI's 30% promise rarely shows up24:26 — Are organisations getting better? Closing reflections──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more: https://www.theaivalues.org ◼ Reach out: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org◼ Edosa Odaro: https://www.linkedin.com/in/edosa/◼ Lindley Gooden: https://www.linkedin.com/in/lindleygooden/

Ep. 11 | World Models, AI Autonomy & AGI: Is Intelligence Enough? | The AI Values Podcast

What if your organisation's AI strategy rests on a system that doesn't understand the world the way you think it does? Edosa Odaro and Lindley Gooden go head-to-head on Episode 11 of The AI Values Podcast on the debate that is quietly splitting the AI research world in two: LLMs versus world models, pattern recognition versus causal understanding, and the governance question that follows from the answer. This is not a technical forecasting conversation. It is the one your board should have before the next autonomous AI budget line gets signed. WHAT IS COVERED: ► "The biggest problem around AI is that we speak about it as if it actually understands the world": why conflating language fluency with genuine understanding is the most dangerous assumption in AI governance, and what world models offer instead ► The transport company case study: an LLM correctly identifies a flood and reroutes an entire fleet, then causes gridlock, because it cannot model the downstream consequence of its own decision ► LLMs are not enough": why Lindley argues that without physical awareness, AI cannot be trusted in medical tech, sports science, or any domain where the real world pushes back ► Do AI systems need arms and legs? Why giving autonomous AI physical form is not an engineering decision but a values question, and why Silicon Valley's race to remove guardrails is precisely the moment human oversight matters most ► "I feel that we're giving human expectations to non-human systems": the framing that redefines AI alignment as a relationship risk, and what that means for every organisation deploying AI at scale ⏰ EPISODE TIMESTAMPS: 00:00 — The AI illusion: mistaking language fluency for genuine understanding 01:06 — LLMs vs world models: what the difference actually means in practice 02:09 — AGI and ASI: which architecture leads to general intelligence? 03:28 — Arms, legs, and autonomy: the embodied AI question nobody wants to answer 04:54 — Case study: the flood, the fleet, and the limits of LLM reasoning 06:35 — Silicon Valley, fewer guardrails, and the autonomy debate 08:03 — Causality, consequence, and what AI needs to understand an ecosystem 09:17 — "We're giving human expectations to non-human systems" 10:20 — Augmentation or transformation? The values-first answer 12:12 — A direct challenge: have this conversation in your own organisation ABOUT THE AI VALUES PODCAST: The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work. 🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership. ◼ Find out more: https://www.theaivalues.org ◼ Reach out: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org ◼ Hosts: Edosa Odaro [https://www.linkedin.com/in/edosa/] & Lindley Gooden [https://www.linkedin.com/in/lindleygooden/]

Ep. 10 How AI Is Rewriting the Career Playbook | Amy Shi-Nash, PhD | The AI Values Podcast

Most AI projects fail not because the technology fails, but because humans never fully integrate it into their way of working. Amy unpacks what successful AI implementation really looks like, not from the tech side, but from the human side. From boardroom tensions to culture change, career disruption to lifelong learning, this is the conversation most AI podcasts aren't having. THIS WEEK: A GUEST EPISODE Our guest is Amy Shi-Nash, Professor of AI Practice at Monash University and Co-founder & CEO of Occupy. Amy brings more than two decades of hands-on implementation experience across global commercial organisations and academia — building AI that actually changes behaviour, not just processes. She is one of a rare group of practitioners who hasseen both sides: what makes AI succeed at scale, and why the human side is the part most leaders get wrong. ◼ Connect with Amy [https://www.linkedin.com/in/amyshinash/] ⏰ EPISODE TIMESTAMPS: 00:00 — Cold open: "AI changes the shape of work, this is bigger than they say" 01:40 — Why 85–95% of AI projects fail to deliver value 05:00 — Meet Amy Shi-Nash: 25 years making AI work in large organisations 06:10 — What good AI implementation actually looks like (from the human side) 08:40 — The junction between humans and AI: why it determines everything 11:00 — From faster to different: culture change as the real measure of success 13:30 — Real-world examples: users building agents, evolving the system themselves 14:25 — Boardroom tensions: innovators, sceptics, literacy gaps, and time horizons 17:30 — Are we ready? The readiness question every board avoids 19:50 — Consequences: intended, unintended, and unevenly distributed 23:00 — The literacy imperative: AI education across every role and level 25:55 — Job composition change: what AI does and what humans must do 27:45 — Distribution of value: how AI reshapes the organisation's shape 29:00 — Flatter structures, specialist roles, fractional work, and the rise of the entrepreneur 32:00 — Debrief: culture, career paths, and the age of the specialised side hustle ABOUT THE AI VALUES PODCAST: The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work. 🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership. ◼ Find out more: https://www.theaivalues.org ◼ Reach out: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org ◼ Co-Hosts Edosa Odaro [https://www.linkedin.com/in/edosa/] & Lindley Gooden [https://www.linkedin.com/in/lindleygooden/]