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

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 ► LLMs are not enough": why Lindley argues that without physical awareness, AI cannot be trusted in medical tech, sports science ► Do AI systems need arms and legs? Why giving autonomous AI physical form is not an engineering decision but a values question ⏰ EPISODE TIMESTAMPS: 00:00 [https://www.youtube.com/watch?v=KfKo7lmkMFM] — The AI illusion: mistaking language fluency for genuine understanding 01:06 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=66s] — LLMs vs world models: what the difference actually means in practice 02:09 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=129s] — AGI and ASI: which architecture leads to general intelligence? 03:28 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=208s] — Arms, legs, and autonomy: the embodied AI question nobody wants to answer 04:54 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=294s] — Case study: the flood, the fleet, and the limits of LLM reasoning 06:35 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=395s] — Silicon Valley, fewer guardrails, and the autonomy debate 08:03 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=483s] — Causality, consequence, and what AI needs to understand an ecosystem 09:17 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=557s] — "We're giving human expectations to non-human systems" 10:20 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=620s] — Augmentation or transformation? The values-first answer 12:12 [https://www.youtube.com/watch?v=KfKo7lmkMFM&t=732s] — A direct challenge: have this conversation in your own organisation

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 has seen both sides: what makes AI succeed at scale, and why the human side is the part most leaders get wrong. ◼ Connect with her on LinkedIn: https://www.linkedin.com/in/amyshinash/ [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 [https://www.theaivalues.org] ◼ Reach out: podcast@theaivalues.org [podcast@theaivalues.org] ◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org [https://pages.theaivalues.org] ◼ Edosa Odaro: https://www.linkedin.com/in/edosa/ [https://www.linkedin.com/in/edosa/] ◼ Lindley Gooden: https://www.linkedin.com/in/lindleygooden/ [https://www.linkedin.com/in/lindleygooden/]

Ep. 9 | The Lost Language of AI Value, Nobody Speaks The Same Language | The AI Values Podcast

Only 15% of organisations can put a hard number on the AI value they've delivered to their board. Not a technology problem a language one. This is where AI value gets lost. In Episode 9 of The AI Values Podcast, Edosa Odaro and Lindley Gooden go head-to-head on one of the most uncomfortable diagnoses in AI leadership today: organisations aren't failing because the technology doesn't work they're failing because strategy, operations, and influence each speak a completely different dialect. And nobody is translating. 🎙 THIS WEEK: A HEAD-TO-HEAD No guest. Just two hosts, one research-backed problem, and a genuine divergence of views. Edosa brings the governance and leadership accountability lens. Lindley brings the communications, storytelling, and what-he-hears-from-senior-leaders lens. They find common ground exactly once and even that took 20 minutes. 📌 WHAT IS COVERED: ► Why only 15% of organisations can put a hard number on the AI value delivered to their board and what the other 85% are doing instead (McKinsey) ► The three languages of AI that fragment organisations: strategy, operations, and influence and why no one in the room is genuinely multilingual ► What Edosa Odaro calls "the value fog": the organisational blind spot in which AI value exists but is completely invisible to the people who need to see it most ► Why bad news about AI stops moving upward and why that silence is more dangerous than any technical failure: "Everyone stops talking. That is the issue." ► The case for an AI translator role inside organisations — the bridge function most businesses have not hired, named, or even defined yet ► Why Edosa believes CEOs should not need a PhD in AI to lead effectively and what the actual solution is, if it isn't technical education ► The policy-versus-practicality disjoint: what senior leaders tell Lindley behind closed doors that AI has become disconnected from the rest of the business ► Whether agentic AI systems can solve the AI communication problem — or whether the lost language of AI value is fundamentally a human failure ► "Value has got to be the thing that brings everyone together and that language needs to be clear" where both hosts ultimately land, despite the disagreement ► What responsible AI governance actually requires from boards: not technical depth, but translatable clarity — and the cost of getting this wrong in 2026 ⏰ EPISODE TIMESTAMPS: 00:00 — Cold open: "The lost language of value" 00:38 — Edosa and Lindley introduce the episode 01:31 — The three languages of AI: strategy, operations, and influence 02:17 — Why aren't organisations multilingual? 03:07 — The research gap: 85% can't read the data; only 15% can report value to boards 07:35 — Should organisations build an AI translator role? 08:49 — Edosa introduces "the value fog" — AI value that exists but cannot be seen 11:43 — The CEO PhD debate: do leaders need to become more technical? 13:32 — Policy vs practicality: the AI disjoint Lindley hears from senior leaders 18:22 — Value as the unifying language — where the disagreement resolves

Ep. 8 | Make AI Work: Stop Selling AI, Start Selling The Outcome | The AI Values Podcast

What if 40% of your workforce is quietly correcting AI hallucination every single month and the productivity gain you booked never actually arrived? Edosa Odaro and Lindley Gooden sit down on Episode 8 of The AI Values Podcast with David Edam a data and AI transformation leader who has spent two decades inside some of the most operationally complex organisations on the planet — for an uncomfortable conversation about AI governance, AI risk management and the hidden work of generative AI in the enterprise. This is not the demo-day story. It is what happens after the hype dies down, the boardroom goes quiet, and someone has to make AI actually deliver value in regulated industries where mistakes have real-world consequences. THIS WEEK: A GUEST EPISODE Our guest is David Edem, a data, cloud and AI transformation leader who has worked across global oil & gas, energy infrastructure and global SaaS building production AI inside multi-billion-pound asset environments where decommissioning, safety, and engineering integrity are not theoretical. David brings the practitioner's view of what changes when AI meets operational complexity, and why "the last 10%" is the part most leaders quietly misjudge. ◼ Guest LinkedIn: https://www.linkedin.com/in/david-edem/ [https://www.linkedin.com/in/david-edem/] WHAT IS COVERED: ► Why AI doesn't replace work it relocates it, and the hidden work of generative AI is now showing up in every team's calendar ► The Microsoft + Workday "workslop" stat: 40% of workers correcting AI-generated errors every month, and what it really means for AI productivity in 2026 ► Inside oil & gas: how decades of engineering drawings, seismic data and well trajectories became a one-year AI project instead of a several-year, multi-million-pound rebuild ► Innovators, sceptics and the delayers nobody talks about: the third group in every boardroom that quietly kills AI decisions ► Why you should never walk into a boardroom selling AI — you walk in selling the outcome (boardroom storytelling for AI adoption) ► "AI wants you to be happy. It gives you good results and it makes stuff up." — David on AI hallucination, confidence, and why the last 10% of AI requires humans ► Efficiency vs trust: the tension every C-suite is missing, and why human in the loop is not a soft option but the only credible posture ► How the barriers to entry collapsed: the customer success manager with no technical background who became a global AI product leader in 18 months ► Why AI doesn't only replace work it creates work that wouldn't have existed (David's own counter-example to the displacement narrative) ► A practical framing for responsible AI in regulated industries: data quality, human oversight, and the AI value extraction question every board should ask ⏰ EPISODE TIMESTAMPS: 00:00 — Cold open: "AI wants you to be happy" — and it makes stuff up 01:30 — Microsoft's 40%: workers are fixing AI every month (the workslop problem) 04:50 — Meet David Edem: AI inside operationally complex industries 07:10 — Oil & gas, decommissioning, and AI as a shortcut to value 11:40 — Innovators, sceptics — and the delayers nobody talks about 14:00 — Don't sell the AI, sell the outcome — the storytelling gap 16:20 — Hallucination and confidence: why the last 10% needs humans 21:10 — Barriers collapse: from no-code customer success to AI product leader 26:00 — AI doesn't replace work — it creates work that didn't exist 28:20 — Debrief: storytelling, delayers, and what's really at stake

Ep. 7 | Agentic AI Rewrites Your Whole Business | The AI Values Podcast

What if 40% of agentic AI projects are already heading for failure and the first warning sign isn't an error. Instead, it is tension? Edosa Odaro [https://www.linkedin.com/in/edosa/] and Lindley Gooden [https://www.linkedin.com/in/lindleygooden/] go head-to-head on Episode 7 of The AI Values Podcast for the most uncomfortable conversation we've had yet on agentic AI in the enterprise the over-optimisation trap, the human capacity gap, and the one analogy every C-suite needs before bringing AI agents into the business. WHAT IS COVERED: ► Why agentic AI is like bringing George Clooney into a movie the new-actor analogy that explains why AI agents change the whole system, not just a workflow ► Why the first thing agentic AI delivers isn't value it is tension, friction, and the human cost of misaligned speed ► Agentic AI over-optimisation: the 2:30am warehouse moment when the AI didn't fail it worked too well ► Misalignment vs malfunction: the governance distinction every C-suite is missing about agentic AI risks ► Why agentic AI doesn't work in isolation it works inside an ecosystem of humans, processes, and pace ► The trade-off problem: what your AI is optimising against, and the value quietly leaving the building ► AI value vs values: the one question every board should ask before signing the next agentic AI budget line ► Why "trust forward, verify always" is the only credible posture for AI agents in business ► AI agents and workforce transformation what the "we'll just retrain them into data scientists" story really hides ► A practical C-suite guide to preparing your business for agentic AI before the friction shows up ⏰ EPISODE TIMESTAMPS: 0:00 [https://www.youtube.com/watch?v=a_uTBRoGdFI] — Cold Open: Agentic AI Is the New Actor in Your Movie 0:35 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=35s] — Bringing AI Agents Into Your Business: Why a Tool Mindset Breaks 2:09 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=129s] — If It's Transformative, How? Why Tension Shows Up Before Value 4:35 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=275s] — The 2:30am Warehouse: When the Agent Runs Faster Than Its Humans 6:40 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=400s] — Trust, Verify, Communicate: The Honest Conversation Agentic AI Demands 9:04 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=544s] — Tension and Trade-Offs: The Two Things Every Agentic System Brings 11:10 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=670s] — Value vs Values: The Real Question Every Board Should Be Asking 12:20 [https://www.youtube.com/watch?v=a_uTBRoGdFI&t=740s] — Stay in the Conversation: How to Get Involved