The AI Lyceum

Episod

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  Do You Really Need AI Agents? | Dr Quentin Reul 24.09.2026 1j

  Does every business need AI agents, or could a simpler workflow do the job better?In this episode of The AI Lyceum™, Samraj Matharu speaks with Dr Quentin Reul about AI agents, knowledge graphs and what it takes to turn enterprise AI experiments into useful business outcomes.Quentin explains why predictable tasks may not need autonomous agents, while deep research can benefit from systems that explore sources and adapt their approach. The conversation considers how to choose the right technology, assess its cost and measure whether it improves the problem you set out to solve.We explore AI hallucinations, critical thinking, explainability, smaller language models and proprietary business knowledge. Quentin illustrates why context matters through two companies with the same name: without distinguishing the businesses, an AI system can produce a convincing answer about the wrong organisation.We also discuss how knowledge graphs can help validate information extracted by language models, why AI answers need checking, and how human review, integration and maintenance affect the real cost of adoption.“Fall in love with the problem, not the solution.” Dr Quentin ReulEPISODE HIGHLIGHTS0:00 ➤ Recording Setup and Welcome 1:21 ➤ Introducing Dr Quentin Reul 2:37 ➤ Entities, Names and AI Hallucinations 5:08 ➤ How Language Models Generate Answers 8:37 ➤ Human Learning and AI 12:04 ➤ Do We Need AI Agents? 13:40 ➤ Deep Research and Agentic Workflows 17:03 ➤ Critical Thinking and Checking Sources 20:46 ➤ Tokens and the Limits of AI Reasoning 24:10 ➤ Knowledge Graphs and Validation 27:02 ➤ Can AI Be Explainable? 32:07 ➤ Additive and Subtractive Fine-Tuning 35:39 ➤ Synthetic Data and Model Costs 39:30 ➤ Chips, Infrastructure and AI Economics 45:37 ➤ Smaller Models and Business Context 46:58 ➤ The Hidden Costs of Operating AI 49:01 ➤ GPUs and the Infrastructure Behind AI 54:00 ➤ AI Agents and the Semantic Web 55:30 ➤ Defining the Business Problem 56:48 ➤ Measuring AI Value and ROI 59:34 ➤ Innovation and Practical AdoptionABOUT DR QUENTIN REULDr Quentin Reul is an AI strategist focused on knowledge graphs, generative AI, agentic workflows and responsible adoption. His work connects technical implementation with business needs, emphasising relevant context, validated outputs and measurable value.ABOUT THE AI LYCEUM™The AI Lyceum™ is an independent community examining artificial intelligence through philosophy, science and public discussion.Hosted by Samraj Matharu | Certified AI Ethicist (University of Oxford) | Visiting Lecturer (Durham)YouTube: https://www.youtube.com/channel/UCzZOR1oz-h8QglWZUCi-HhQ Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza Apple Podcasts: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167 Amazon Music: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum Website: https://theailyceum.com Personal website: https://samrajmatharu.com
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  Is AI Making Us Less Capable? AI Ethics with Professor Sven Nyholm #36 10.09.2026 59min

  What happens to human judgement when a chatbot can think, write and advise us at any moment?In episode 36 of The AI Lyceum™, Samraj Matharu speaks with Professor Sven Nyholm, Professor of the Ethics of Artificial Intelligence at LMU Munich and author of The Ethics of Artificial Intelligence: A Philosophical Introduction.They discuss why people often prefer chatbots that agree with them, even when the advice is shallow or wrong. Sven explains how AI can make difficult work quicker while reducing the effort through which people learn, develop judgement and become skilled.The conversation covers ChatGPT, AI sycophancy, moral advice, therapy chatbots, AI companions, loneliness, education, workplace productivity, artificial consciousness and meaningful work.Sven also introduces the “laziness trap”, where a tool designed to save time can work against the reason we used it. A student may finish an assignment without understanding the subject. A worker may produce something faster without mastering the skill. Someone may feel comforted by an AI companion while remaining lonely.The episode explores whether we are losing control of AI.“Wisdom is the sort of thing that usually takes time.” Professor Sven NyholmEPISODE HIGHLIGHTS0:00 ➤ Introduction to Professor Sven Nyholm 2:31 ➤ How Sven Became an AI Ethicist 5:27 ➤ Safety, Rules and Self-Driving Cars 10:04 ➤ Aristotle, Human Virtue and Value Alignment 13:37 ➤ Why Chatbots Flatter Their Users 15:40 ➤ AI Summaries and the Loss of Critical Thinking 21:06 ➤ The Difference Between Morals and Ethics 23:29 ➤ ChatGPT, Therapy and Moral Advice 28:03 ➤ AI Companions, Relationships and Loneliness 33:15 ➤ How AI Changes Teams and Creativity 35:13 ➤ The Laziness Trap 37:26 ➤ Vibe Coding and Learning with AI 39:37 ➤ Finding the Right Place for AI 45:25 ➤ The AI Wager and the Risks of Moving Too Fast 50:39 ➤ Can Artificial Intelligence Become Conscious? 56:05 ➤ Can Humans Become Wiser Alongside AI? 58:23 ➤ Plato’s Cave and the Limits of Machine ExperienceABOUT PROFESSOR SVEN NYHOLMSven Nyholm is Professor of the Ethics of Artificial Intelligence at LMU Munich and a principal investigator at the Munich Center for Machine Learning. His work examines responsibility, agency, consciousness, human relationships and the effect of intelligent systems on everyday life.His latest book, The Ethics of Artificial Intelligence: A Philosophical Introduction, considers how AI changes old questions about moral responsibility, authorship, consciousness, meaningful work and the future of humanity.ABOUT THE AI LYCEUM™The AI Lyceum™ is an independent community examining artificial intelligence through philosophy, science and public discussion.Hosted by Samraj Matharu | Certified AI Ethicist (University of Oxford) | Visiting Lecturer (Durham)YouTube: https://www.youtube.com/@The.AI.LyceumSpotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple Podcasts: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon Music: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite: https://theailyceum.com
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  How AI Is Changing Business - and the Human Skills That Still Matter | Dipika Sawhney, Google #35 24.08.2026 29min

  AI is making it faster and cheaper to build, test and launch new ideas—but it is not replacing judgement, resilience or humanity.Dipika Sawhney leads SMB growth for Google across EMEA, helping hundreds of thousands of small and medium-sized businesses gain practical value from AI-powered technology. Before joining Google, she spent more than five years at Amazon, held a senior strategy role at Salesforce and experienced the realities of building a company herself. She has also been recognised as one of the UK’s Top 100 Women in Tech and has spoken at the House of Lords about AI and access to technology.In this episode of The AI Lyceum™, Dipika joins Samraj Matharu to explain how AI is changing entrepreneurship, customer strategy and the skills businesses should hire for. As code becomes easier to produce and experimentation becomes less expensive, she argues that the real advantage will come from understanding genuine customer problems, exercising sound judgement and retaining the human qualities technology cannot reproduce.“AI is great, technology is great. Everything else that you have out there is a tool.” — Dipika SawhneyEPISODE HIGHLIGHTS 0:00 ➤ Introduction and Dipika’s journey 4:10 ➤ Using AI to create real customer value 8:04 ➤ Resilience, ownership and kindness 12:40 ➤ How AI is transforming entrepreneurship 17:03 ➤ The human skills businesses should hire for 20:50 ➤ Short-term hype and AI’s long-term impact 23:30 ➤ Career advice for graduates entering the AI era 27:21 ➤ Humanity, technology and closing thoughtsHosted by Samraj Matharu — Certified AI Ethicist (Oxford) | Visiting Lecturer (Durham)The AI Lyceum™ is an independent community for responsible AI and innovation, bringing together 400+ members from OpenAI, DeepMind, Oxford, Google and more.Watch and listen:YouTube: https://www.youtube.com/@The.AI.Lyceum Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza Apple Podcasts: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167 Amazon Music: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum Website: https://theailyceum.com
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  If AI Becomes Conscious, Does It Deserve Rights? – Anna Mikeda | 34 12.07.2026 49min

  What happens when AI stops being a tool and begins to resemble a mind—and what might humanity owe it?In Episode 34 of The AI Lyceum™, Samraj Matharu speaks with Anna Mikeda, an AI psychology engineer and researcher helping to establish the emerging field of robopsychology.Beginning with Isaac Asimov’s vision of robot psychology, they examine how artificial minds might develop motivations, make decisions and relate to humans. The conversation explores whether consciousness could emerge from computation, why today’s language models remain fundamentally limited, and how neurosymbolic and neuromorphic systems could move AI beyond imitation.They also discuss AI therapy, emotional attachment, intimate data, cognitive debt, machine welfare and the possibility that future AI systems may deserve moral consideration. Finally, Anna explains why advanced AI may need mortality, limited resources and a genuine stake in its own continued existence.“The worst thing we could do is to have something conscious and suffering, and not treat it as such.”EPISODE HIGHLIGHTS0:00 ➤ Introduction to Anna Mikeda2:29 ➤ Isaac Asimov and the Origins of Robopsychology6:56 ➤ Motivations, Alignment and AI Decision-Making10:15 ➤ Why Large Language Models Remain Black Boxes14:40 ➤ Can Ethical Principles Be Engineered Into AI?15:50 ➤ AI Therapy, Emotional Support and Intimate Data24:07 ➤ Can Computation Produce Consciousness?28:29 ➤ Neurosymbolic and Neuromorphic AI Explained29:46 ➤ AGI, Superintelligence and Human–AI Partnership33:52 ➤ Why the AI Race May Be Moving Too Quickly39:44 ➤ Should Artificial Intelligence Be Mortal?44:11 ➤ How Are Humans Different From AI?48:12 ➤ Closing Reflections and the Question for HumanitySamraj Matharu — Certified AI Ethicist (Oxford) | Visiting Lecturer (Durham)The AI Lyceum™ is an independent community exploring responsible AI, philosophy and innovation.Watch on YouTube: https://www.youtube.com/@The.AI.LyceumListen on Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Listen on Amazon Music: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumLearn more: https://theailyceum.comAnna's substack: https://annamikeda.substack.com/
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  Should AI Be in the Classroom? The Human Cost of Generative AI [UCL Professor Wayne Holmes] #33 16.06.2026 54min

  In this episode of The AI Lyceum®, Samraj Matharu speaks with Professor Wayne Holmes, Professor of Critical Studies of AI and Education at UCL Knowledge Lab and UNESCO Chair in the Ethics of AI and Education.Wayne offers a direct challenge to the hype around generative AI. He argues that many AI tools are being adopted in schools, universities, workplaces, and public life without enough independent evidence that they improve learning, protect students, or support human development. The conversation explores AI literacy, student agency, over-reliance, automation bias, regulation, environmental impact, big tech power, and why humans must retain the right to reject AI.Guest quote: ‘There is no independent evidence at scale that the AI tools developed for education are effective.’EPISODE HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 6:50 ➤ Why AI Is Complicated 8:05 ➤ Direct vs Indirect AI Impact 9:30 ➤ Bias, COMPAS, and High-Stakes AI 10:45 ➤ The Evidence Gap in AI Education 14:30 ➤ ChatGPT as a Cognitive Crutch 16:45 ➤ Agency, Learning, and Human Development 23:00 ➤ Regulation, Big Tech, and AI Literacy 28:55 ➤ AI, Smoking, and Hidden Long-Term Harm 34:40 ➤ AI Productivity Myths in Coding 44:00 ➤ Possible Futures for AI 53:30 ➤ Closing Question: What World Do We Want?YouTube https://www.youtube.com/@The.AI.LyceumSpotify https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite https://theailyceum.com#AI #AIEducation #ResponsibleAI #AIEthics #GenerativeAI #ArtificialIntelligence #Education #HumanAgency #TheAILyceum
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  How AI Changes What We Believe [AI Ethics Researcher, Dr Jana Sedláková] #31 18.05.2026 51min

  ‘AI provides the view from nowhere. And I don’t mean it in a good way. I don’t mean the view from nowhere as an objective view. I mean it as AI doesn’t have experiences. It literally doesn’t have a point of view. But if you talk to another human being, it gives you a point of view on your situation. So you see that another human being, that is like you, could perceive things differently. So it provides a different perspective, and AI cannot do it.’In this episode of The AI Lyceum®, Samraj Matharu speaks with Dr Jana Sedláková about artificial epistemology, humanisation, empathy, conversational AI in mental healthcare, and how AI may shape what humans come to believe.Jana’s PhD focused on the ethics of conversational AI in mental healthcare, one of the most sensitive areas of human-AI interaction. She is now developing her book, The Ethics of Humanization, which asks why we build AI to seem human, and what this does to concepts like trust, empathy, knowledge, understanding and responsibility.This conversation explores a deeper question: when we say AI is intelligent, empathetic, trustworthy or knowledgeable, are we describing AI accurately, or are we changing the meaning of those words?EPISODE HIGHLIGHTS0:00 ➤ Intro / Guest Welcome 3:05 ➤ Ethics, Understanding and AI 6:30 ➤ Conversational AI in Mental Healthcare 9:00 ➤ ELIZA, Simulation and Therapy Chatbots 12:10 ➤ Philosophy, Consciousness and Conceptual Clarity 17:35 ➤ Tokens, Meaning and Human Language 22:05 ➤ Epistemology and How AI Shapes Beliefs 27:20 ➤ Humanisation, Anthropomorphism and AI Design 32:55 ➤ Can AI Be Empathetic? 37:10 ➤ Morals, Ethics and the Educated Heart 42:45 ➤ AI Opportunities, Risks and Inequality 47:20 ➤ Final Reflections on the Good Use of AIYouTube https://www.youtube.com/@The.AI.LyceumSpotify https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite https://theailyceum.com#AI #AIEthics #ArtificialIntelligence #Epistemology #Philosophy #MentalHealthAI #HumanAIInteraction #ResponsibleAI #TheAILyceum
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  AI and the New Economics of Advertising [Media Analyst, Ian Whittaker] #30 03.05.2026 45min

  ‘You are perceived as you price’ - Ian WhittakerAdvertising is entering a new economic era. AI is changing what gets automated, what gets valued, and how agencies prove their worth.In this episode of The AI Lyceum®, Samraj Matharu speaks with Ian Whittaker, a media and advertising analyst who has spent more than 25 years looking at the industry through a financial markets lens.Ian argues that advertising has become too focused on efficiency: lower CPMs, cheaper reach, faster execution and marginal optimisation. But clients, CFOs and boards do not think in media metrics. They think in revenue growth, free cash flow, margin, risk and capital allocation.This conversation asks a simple question: if AI makes execution cheaper, what does the advertising industry get paid for next?We discuss why the current agency pricing model may not hold, why brand becomes more valuable when optimisation is abundant, why agencies need to move closer to the client P&LEPISODE HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 3:28 ➤ Ian Whittaker’s Background in Media, Markets and Advertising 4:45 ➤ Why Advertising Must Move From Efficiency to Efficacy 6:45 ➤ CPMs, Clicks, Cash Flow and the Client Gap 8:52 ➤ Starting With the Business Problem, Not the Technology 10:58 ➤ The Industry’s Rabbit Hole of Tech, Process and Measurement 15:12 ➤ AI as a Supply-Side Shock to Advertising 16:29 ➤ Why Advantage Moves Upstream to Strategy and Brand 20:03 ➤ Distribution Control, Ad Tech and the Future of Agencies 24:20 ➤ Publicis, Power of One and Agency Margin 26:19 ➤ Why the Advisor and Executor Roles Are Blurring 29:39 ➤ Why the Current Agency Revenue Model Will Not Hold 34:30 ➤ What Agencies Need to Change Before 2030 39:42 ➤ OpenAI Ads, LLM Advertising and Capital Allocation 42:06 ➤ Attribution, Risk and Why CFOs Do Not Need Perfect Certainty 46:35 ➤ Speaking the Language of the CFO 49:58 ➤ Closing ThoughtsKEY QUESTIONS ANSWERED➤ Why has advertising become too focused on efficiency?➤ What does AI do to agency pricing power?➤ Why is execution becoming commoditised?➤ Should agencies be paid for time, outputs or outcomes?➤ Why does brand become more important in an AI-driven media world?➤ How should advertisers think about every pound of media spend?➤ Why do agencies need to speak the language of the CFO?SUBSCRIBESubscribe to The AI Lyceum® for conversations on AI, philosophy, media, ethics and the future of business.CONNECTYouTube https://www.youtube.com/@The.AI.LyceumSpotify https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite https://theailyceum.comLinkedIn Group https://www.linkedin.com/company/108295902/admin/dashboard/#AI #Advertising #Media #MarketingScience #AdTech #BrandStrategy #TheAILyceum
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  Inside the AI Supply Chain: How Cerebras Powers Fast AI [James Wang] #29 26.04.2026 54min

  'STEM is reducible to math and math is verifiable. So anything verifiable is automatable.'In this episode of The AI Lyceum®, Samraj Matharu speaks with James Wang, Product Marketing Director at Cerebras, about the AI supply chain, inference, agents and what remains human when intelligence becomes infrastructure.James previously spent nearly a decade at NVIDIA before joining Cerebras, where he focuses on AI models and inference. This conversation goes from the technical to the philosophical: what inference actually means, why fast AI matters, how agentic coding is changing work, and why humanities, relationships and personal narrative may become more valuable in an age of automation.We also explore the difference between old rule-based automation and modern AI systems. As James puts it, with AI you no longer define every rule up front. You define the objective, and the system creates what it needs to get there.EPISODE HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 1:20 ➤ Ray Kurzweil, AI and the Final Boss of Technology 6:00 ➤ What Inference Means and Why It Matters 10:20 ➤ AI Adoption, Agentic Coding and the Usage Gap 13:00 ➤ Mental Labour, Automation and the Future of Work 20:00 ➤ Rule-Based Automation vs Fluid Intelligence 25:00 ➤ Alignment, Consciousness and Inner Experience 28:00 ➤ Proactive AI, Offline Inference and Continuous Agents 32:00 ➤ Why Humanities May Matter More Than STEM 41:00 ➤ AGI Timelines and the End of Long-Term Forecasting 45:00 ➤ Agent Companies, Token Economies and Human Value 54:00 ➤ What Remains Valuable When AI Automates UtilityKEY QUESTIONS ANSWERED➤ What is inference, and why does it matter in the AI supply chain? ➤ How does Cerebras fit into the future of AI infrastructure? ➤ Why is agentic coding changing software development so quickly? ➤ What is the difference between rule-based automation and intelligent AI? ➤ Why might verifiable tasks become increasingly automatable? ➤ What human skills become more valuable as AI gets faster and cheaper?Subscribe to The AI Lyceum® for conversations on artificial intelligence, philosophy, ethics, infrastructure and the future of society.YouTube https://www.youtube.com/@The.AI.LyceumSpotify https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite https://theailyceum.comLinkedIn https://www.linkedin.com/company/108295902/admin/dashboard/#AI #Cerebras #Inference #AISupplyChain #AIAgents #AGI #AIInfrastructure #FutureOfWork #ResponsibleAI #TheAILyceum
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  How Advertising, AI and Algorithms Shape What We See [Alessandra Di Lorenzo, Advertising Leader] #28 20.04.2026 1j 3min

  ‘The web is one big fat ad.'That was Alessandra DiLorenzo’s quote of the podcast, and it gets right to the point.In this episode of The AI Lyceum®, Samraj Matharu speaks with Alessandra DiLorenzo, former CEO of lastminute.com media and former leader at eBay and Vodafone, following her recent TEDx Royal Tunbridge Wells talk at the March 8, 2026 event themed ‘Momentum’. Her TEDx speaker profile framed the idea simply and sharply: ‘My daughter could skip ads before she could read the word advertising.’A key theme running through this conversation is reversibility. Alessandra makes a sharp distinction between decisions that can be reversed and those that cannot. If a decision is reversible, AI can help optimise it. If it is irreversible, especially where trust, brand, or human relationships are at stake, leaders should think very carefully before handing it to a machine.They explore how AI, advertising, and algorithms shape what we see, how the zero-click web is changing the economics of publishing and discovery, and why brands now have to think beyond traffic and performance alone. The conversation also gets into trust, direct traffic, language, intelligence, ethics, agents, media literacy, and the growing need for human judgment in an age of machine-led optimisation.EPISODE HIGHLIGHTS 0:00 ➤ Intro / Alessandra DiLorenzo on AI as the new silent gatekeeper 2:18 ➤ Motherhood, media, and why algorithmic influence starts early 7:01 ➤ The zero-click web, Google AI answers, and the pressure on publishers 14:44 ➤ What language models get wrong about meaning and intelligence 20:01 ➤ AI ethics, human judgment, and why some decisions cannot be outsourced 25:03 ➤ Reversible vs irreversible decisions in brand and business 31:01 ➤ Direct traffic, trust, brand equity, and surviving outside the gatekeeper 37:21 ➤ How CEOs should think about AI transformation, goals, and timeframes 45:46 ➤ Agents, black boxes, and the future of brand discovery 50:24 ➤ Critical thinking, media literacy, and ‘feed the feed’ 59:57 ➤ Closing question on responsible AI and human judgmentYouTube https://www.youtube.com/@The.AI.LyceumSpotify https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite https://theailyceum.com
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  Inclusive AI, Trust and Hidden Harm [Sidrah Hassan, AI Ethicist] #27 14.04.2026 1j 8min

  'AI just feels like another frontier of exclusion' – Sidrah HassanIn this episode of The AI Lyceum®, Samraj Matharu speaks with Sidrah Hassan, AI Governance and AI Ethics Specialist, about inclusive AI, AI ethics, AI governance, algorithmic bias, trust in AI, transparency, human oversight, and responsible AI in practice.Sidrah is an AI Governance and Ethics Manager at Kainos, an AI Ethics and Strategy Advisor at Ethical AI Alliance, and has also worked across AI ethics, product, and public education through roles at AND Digital, BBC Scotland, and the AI Safety Collab by ENAIS.We explore how large language models can reinforce gender bias and racial bias, why inclusive AI must go beyond good intentions, and what trustworthy AI really looks like when systems are used in the real world. The conversation covers training data, representation gaps, AI harms, accountability, human-in-the-loop decision-making, and the challenge of building AI systems that serve people fairly.Sidrah also discusses agentic AI, AI in healthcare, economic displacement, and the role of storytelling in surfacing subtle harms that are often missed by technical frameworks alone. She explains the thinking behind the AI Harms Map and why lived experience matters when assessing the real impact of AI systems.This episode is for anyone interested in AI ethics, AI governance, responsible AI, inclusive AI, trustworthy AI, bias in AI systems, AI transparency, and the future of human-centred technology.EPISODE HIGHLIGHTS0:00 ➤ Intro / Guest Welcome1:09 ➤ What inclusive AI looks like in everyday systems4:34 ➤ LLM bias, training data, and representation gaps7:09 ➤ How to improve inclusivity in AI11:00 ➤ What trust in AI really means13:01 ➤ Building trust in AI systems20:13 ➤ Is AI ethics a distinct field?30:17 ➤ Agentic AI, safety, and security32:45 ➤ Storytelling, lived experience, and AI harms43:10 ➤ Economic displacement and the future of work50:21 ➤ AI in healthcare and human judgment1:00:03 ➤ The AI Harms Map1:03:48 ➤ A closing question on data and AI useYouTubehttps://www.youtube.com/@The.AI.LyceumSpotifyhttps://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApplehttps://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazonhttps://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsitehttps://theailyceum.com#AI #AIEthics #AIGovernance #InclusiveAI #ResponsibleAI #TrustworthyAI #AlgorithmicBias #AgenticAI #TheAILyceum
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  How AI Is Changing Education, Ethics, and the Future of Work [Tina Austin] #26 06.04.2026 50min

  ‘Failure is not something to be ashamed of. I want my students to know why they were wrong'AI is changing education, work, and judgment faster than most institutions can keep up.In Episode #26 of The AI Lyceum®, I speak with Tina Austin, an AI educator, bioethics and computational biology lecturer, AI ethics adviser, and OpenAI presenter, about what it means to teach, think, and stay human in the age of AI. We explore how generative AI is reshaping the classroom, why students are anxious about the future of work, and why critical thinking matters more when machines can produce polished answers in seconds.This is not a vague conversation about hype. It is a grounded one about what universities, businesses, and individuals should actually measure when they use AI. Tina argues that the goal is not speed for its own sake. It is better judgment, clearer reasoning, stronger ethics, and a more honest understanding of where AI helps and where it can mislead. The conversation is beyond thinking properly, Tina is designing learning environments where thinking is unavoidable, even with AIEPISODE HIGHLIGHTS0:00 ➤ Intro / Guest Welcome1:06 ➤ AlphaFold, science, and getting students excited about AI2:26 ➤ Preparing students for jobs in a post-GenAI world3:31 ➤ Human wisdom vs artificial intelligence4:39 ➤ Moltbook, AI agents, and strange new digital experiments7:05 ➤ AI-only conferences and what they reveal10:20 ➤ How businesses should measure AI success15:04 ➤ Morals, ethics, and whether AI ethics really exists18:40 ➤ The Socratic AI Framework and why frameworks matter21:20 ➤ Tina’s framework for critical thinking in education25:20 ➤ Can thinking be measured? Metacognition, evidence, and learning29:44 ➤ Determinism, interpretability, and risk in medicine35:48 ➤ Sci-fi, surveillance, and where AI may take society40:03 ➤ Healthcare, AlphaGenome, and cautious optimism46:00 ➤ Foresight, prediction, and helping students earlier47:03 ➤ Wisdom, intelligence, and deciding which problems matter48:21 ➤ Closing reflections on agency and responsibilityThis episode answers questions such as: What should students learn in the AI age? How should businesses measure AI properly? Where is the line between automation and intelligence? What happens when systems start influencing human judgment at scale? And how do we preserve agency when AI becomes more capable, persuasive, and present?Subscribe to The AI Lyceum® for conversations on AI, ethics, philosophy, science, and the future of society.YouTube https://www.youtube.com/@The.AI.LyceumSpotify https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite https://theailyceum.com#AI #Education #AIEthics #FutureOfWork #CriticalThinking #HigherEducation #TheAILyceum
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  How Wondercraft Is Changing AI Video for Business [Wondercraft CEO, Dimitris Nikolaou] #25 29.03.2026 44min

  'The problem is that more people want to be creating videos, but they can’t'AI video is moving from novelty to utility, and Wondercraft is betting the real opportunity is not just generating content, but making video genuinely usable for business.In Episode 25 of The AI Lyceum®, we sat down with Dimitris Nikolaou, Co-Founder and CEO of Wondercraft, to explore how he went from Imperial and Palantir to Y Combinator and building one of the UK’s most interesting AI creation platforms.We discuss why Wondercraft started in audio, why video is a far bigger market, and why most AI video tools still fall short for real work.Dimitris explains the difference between model aggregation and building a true application layer, why businesses need editable workflows rather than random clips, and how Wondercraft is aiming to become “the antidote to AI slop” by making AI video useful for onboarding, training, internal communication, and more.We also get into startup iteration, hiring philosophy, market selection, and why being a founder requires more intentionality than most people realise.EPISODE HIGHLIGHTS0:00 ➤ Intro / Guest Welcome1:54 ➤ Why Wondercraft is called Wondercraft3:51 ➤ From Imperial and Palantir to Y Combinator7:29 ➤ Proving a startup idea early on9:42 ➤ Why long-term vision matters11:43 ➤ AI slop, business video, and real utility14:48 ➤ The missing layer between models and useful products16:47 ➤ Why Wondercraft moved from audio into video19:42 ➤ Building a lean, high-performance team24:07 ➤ Dimitris’s favourite interview questions29:00 ➤ Luck, hard work, and career inflection points32:27 ➤ Where AI video is heading34:49 ➤ Inference, APIs, and working with FAL36:59 ➤ Advice for founders starting in AI today40:11 ➤ Why AI is not the real differentiator44:02 ➤ Dimitris’s closing advice for aspiring foundersListen to The AI Lyceum®YouTube: https://www.youtube.com/@The.AI.LyceumSpotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite: https://theailyceum.com#AI #AIVideo #Wondercraft #GenerativeAI #Startups #YCombinator #VideoCreation #FutureOfWork
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  Agentic Advertising: How AI Agents Will Buy and Sell Media [IAB Tech Lab, Shailley Singh] #24 12.03.2026 57min

  This episode is sponsored by Advertising Protocols™ — a free and open directory for the entire advertising ecosystem, built to help people explore the protocols, standards, tools, and infrastructure shaping the future of media and ad tech.🌐 https://advertisingprotocols.com'Bot is the old world. Agent is the new world' – Shailley SinghWhat happens when AI agents start buying and selling media?In this episode of The AI Lyceum™, Samraj Matharu sits down with Shailley Singh, EVP Product and COO at IAB Tech Lab. Shailley has helped shape modern digital advertising through senior roles at companies including Yahoo and PayPal, and through contributions to major industry standards such as MRAID for mobile.Now he is focused on the next shift: agentic advertising.We discuss agentic real-time bidding, publisher value, standards, transparency, human oversight, AI-generated content, and why the future of advertising may depend on humans moving from operators to architects.HIGHLIGHTS0:00 ➤ Intro / Guest Welcome1:42 ➤ Why agentic AI is the next big shift in advertising7:25 ➤ Agentic real-time bidding explained12:40 ➤ From campaign KPIs to business outcomes16:29 ➤ Standards, protocols and avoiding fragmentation22:20 ➤ Human in the loop: from operator to architect28:11 ➤ AI slop, provenance and content quality35:28 ➤ The future of AI in marketing and advertising44:34 ➤ Is AI a bubble?52:05 ➤ Final thoughts: speed vs precisionWE ANSWERED➤ What is agentic advertising?➤ How could AI agents change media buying and real-time bidding?➤ Why do standards and protocols matter in an AI era?➤ How should humans stay in the loop when AI systems make decisions?➤ What will make companies stand out when AI becomes embedded everywhere?🎧 YouTube: https://www.youtube.com/@The.AI.Lyceum🎧 Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza🎧 Apple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167🎧 Amazon: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum🌐 Website: https://theailyceum.com🔗 Linktree: https://linktr.ee/theailyceum🔗 Advertising Protocols: https://advertisingprotocols.com🔗 Shailley Singh: https://www.linkedin.com/in/shailleysingh/🔗 IAB Tech Lab: https://iabtechlab.comSamraj Matharu — Certified AI Ethicist (Oxford) | Visiting Lecturer (Durham)The AI Lyceum™ is a 2K+ global community with members across OpenAI, DeepMind, Oxford, Google, Anthropic, and more.#AI #Advertising #AdTech #AgenticAI #MediaBuying #IABTechLab #TheAILyceum
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  The Magic Mirror: The Journey to $3M a Month [Sunil Jindal, Magic AI] #23 02.03.2026 46min

  'When you see that image of yourself on the screen, suddenly it feels much more possible'- Sunil Jindal, Co-Founder, Magic AIWhat if your mirror could train you using a future version of you as the trainer?In this episode of The AI Lyceum, Samraj Matharu sits down with Sunil Jindal, Co-Founder of Magic AI - the award-winning consumer tech company behind the AI-powered smart mirror named one of TIME Magazine's Best Inventions of 2024.Magic AI uses computer vision to count reps, correct form, and give real-time feedback across 400+ exercises, with virtual trainers including Sir Alistair Cook, Katya Jones, and Jesse Lingard. They were invited to Dragon's Den and turned it down. They hold patents on the mirror and adjustable dumbbells. And in January 2026, they posted $3.4M in a single month, their best ever, with just 15 employees.EPISODE HIGHLIGHTS0:00 ➤ Welcome and intro 2:12 ➤ The Magic Mirror explained 3:43 ➤ From 2 founders to a team of 20 5:38 ➤ The emotional impact: wheelchair users, single mums, cancer recovery 9:18 ➤ Privacy by design and why they don't store your camera feed 12:40 ➤ What data does Magic AI actually track? 15:36 ➤ Body scan, metabolic age and personalised weight recommendations 19:38 ➤ Dragon's Den and why they said no 21:35 ➤ Future you as your trainer and the visualisation breakthrough 26:20 ➤ Could the mirror run ads? Sunil's honest take 29:33 ➤ Loss aversion, habit nudges and standby screen ideas 33:10 ➤ Patents, dumbbells and the Technogym comparison 38:41 ➤ From Imperial physics to AI fitness founder 45:22 ➤ One question to leave the audience withMEMORABLE QUOTES💬 'The only data we store are the coordinates of points on your body, not the video'💬 'Imagine progress photos that look forwards, not backwards'💬 'Future you, training present you, to become future you'💬 'Always ask yourself: is this providing net positive value for me?'KEY QUESTIONS ANSWERED➤ How does an AI mirror track form without storing footage? ➤ What metrics does Magic AI use to personalise your workout? ➤ Why did they decline Dragon's Den? ➤ What does the future of home fitness look like with GenAI? ➤ How do you build a company with AI before it was a buzzword?🎧 Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza 🎧 Apple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167 🌐 Website: https://theailyceum.com 🔗 Linktree: linktr.ee/theailyceum 🪞 Magic AI: https://magic.fit 🔗 Sunil Jindal: https://www.linkedin.com/in/suniljindal21/ 🔗 Varun Bhanot: https://www.linkedin.com/in/varunbhanot1/Hosted by Samraj Matharu — Certified AI Ethicist (Oxford) | Visiting Lecturer, Durham University | Founder, The AI Lyceum | 1,000+ members from OpenAI, DeepMind, Google, Anthropic and more.The views expressed are those of the speakers personally and do not represent The AI Lyceum or affiliated organisations.
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  Governing AI at Scale: Understanding Bias & Fairness [Dr. Chiara Gallese, Digital Ethics Prof] #22 15.02.2026 52min

  'We should improve our critical thinking' — Chiara GalleseAs AI systems move from experimentation to infrastructure, governance becomes the real test.In Episode 22 of The AI Lyceum, Samraj speaks with Dr Chiara Gallese — Philosophy PhD, Adjunct Professor of Digital Ethics at Collegio Internazionale Ca’ Foscari, Researcher at Tilburg Institute for Law, Technology, and Society (TILT), and Academic Expert in the European Commission’s AI Transparency Code of Practice Working Groups. A lawyer and privacy consultant for multinationals and banks since 2015, she currently focuses her studies on the legal aspects of artificial intelligence, the ethics of data use, and data protection. She's also a TedX speaker.They explore what fairness means once AI systems are deployed at scale, where bias truly enters AI (data, model, or deployment), and how transparency obligations under the EU AI Act shape real institutional practice.Chiara explains the difference between stochastic and deterministic systems, why ignoring bias is not just unethical but poor engineering, and why governance must extend beyond frameworks into everyday use.The conversation also examines emotional attachment to generative systems, disclosure dilemmas, and why strengthening human judgment may be just as important as improving the models themselves.This is a conversation about responsibility, constitutional values, transparency, and governing intelligence in the real world.Episode Highlights0:00 ➤ Intro / Guest Welcome2:40 ➤ Does AI ethics improve business outcomes?8:55 ➤ Inside the EU AI Transparency Code of Practice15:30 ➤ Stochastic vs deterministic systems22:10 ➤ Where bias enters AI systems30:45 ➤ Emotional intelligence and attachment38:20 ➤ Disclosure, labelling, and stigma45:10 ➤ Critical thinking in the AI era50:30 ➤ Final reflectionsKey Questions Explored➤ What does fairness mean in AI governance?➤ Where does bias originate in AI systems?➤ Can AI emotional intelligence be trusted?➤ Should AI-generated content always be disclosed?➤ Is governance about frameworks or lived practice?➤ What must humans preserve as AI advances?Listen on:YouTube – https://www.youtube.com/@The.AI.LyceumSpotify – https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMzaApple – https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167Amazon – https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumWebsite – https://theailyceum.comHosted by Samraj Matharu — Certified AI Ethicist (Oxford) | Visiting Lecturer (Durham)#AI #AIAct #AIGovernance #DigitalEthics #Bias #Fairness #Transparency #ResponsibleAI #CriticalThinking
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  Understanding AI Ethics: Trust and Safety [Savneet Singh, AI Ethicist] #21 06.02.2026 54min

  AI ethics, trust & safety explained — Savneet Singh (AI Ethicist) on building trustworthy AI systems, safety frameworks & responsible AI deployment. The AI Lyceum #21'The machine is there to support you — not to replace your judgment. You are the one in control' — Savneet SinghAs AI becomes more human-like, trust becomes harder to define — and more critical to get right.In this episode, Samraj speaks with Savneet Singh, who doesn't speak in her capacity as trust and safety lead at a top tech company, but as Visiting Lecturer at Emory University, about what it really means to trust AI systems that increasingly sound, remember, and respond like humans.Savneet breaks down why trust in AI isn't about how human it feels — it's about predictability, transparency, and alignment with human values. They explore why AI must remain a co-pilot, not an autopilot, why labeling AI-generated content matters, and how misinformation spreads not through conspiracy, but through everyday digital behaviour.The conversation tackles 'AI psychosis' emotional attachment to non-conscious systems, the ethics of AI companions, and why accountability must sit with developers, deployers, and users — not the machine. This is a conversation about responsibility, boundaries, and keeping humans firmly in control as AI becomes more powerful.WHAT YOU'LL LEARN→ What trust actually means in the context of AI→ Why human-in-the-loop design is non-negotiable→ The difference between misinformation and disinformation→ Why AI companions risk emotional substitution→ How "AI psychosis" emerges through prolonged interaction→ Why labelling AI content builds trust→ Where accountability must sit when AI goes wrongEPISODE HIGHLIGHTS0:00 ➤ Intro1:50 ➤ What does "trust" really mean in AI?4:41 ➤ Transparency, guardrails, and human-in-the-loop7:22 ➤ Trust vs confidence9:33 ➤ AI-generated journalism and fabricated facts11:15 ➤ Misinformation, deception, and human responsibility14:49 ➤ AI psychosis and emotional attachment21:07 ➤ Losing clarity about the human–AI relationship24:27 ➤ Supportive tools vs emotional substitution28:49 ➤ Guardrails, free will, and ethics by design30:20 ➤ "Digital littering" and everyday ethics33:54 ➤ Why AI literacy matters for all ages36:26 ➤ One practical guardrail every business should use39:51 ➤ Trusting AI when you doubt your own judgment42:26 ➤ Teaching children how to use AI responsibly46:55 ➤ Why AI agents still feel risky52:22 ➤ The accountability gap54:00 ➤ Final message: humans must stay in control🔗 LISTEN, WATCH & CONNECT🌐 Join the 1K+ Community: https://linktr.ee/theailyceum💻 Website: https://theailyceum.com▶️ YouTube: https://www.youtube.com/@The.AI.Lyceum🎧 Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza🎧 Apple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167🎧 Amazon: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum
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  AI's Biggest Blind Spot: Culture, Not Code [Dr. Nina Begus, Berkeley] #20 30.01.2026 1j

  Why AI’s biggest blind spot is culture, not code — Dr Nina Begus (UC Berkeley) on cultural bias in AI, language models & cross-cultural AI development. The AI Lyceum #20🎓 20% Off | Oxford AI Executive Programmeshttps://oxsbs.link/ailyceum"Humanities scholars need to be at the table where AI is being built — ethics must be embedded from the start, not added as a band-aid afterward" — Dr. Nina BegusAI doesn't just process data — it processes human culture.In this episode, Samraj speaks with Dr. Nina Begus, Philosophy PhD from Harvard, UC Berkeley researcher and author of Artificial Humanities, who argues that understanding AI requires more than engineering — it requires the humanities.Nina reveals how ancient myths like Pygmalion still shape how we design AI today, why language models inherit our cultural assumptions, and what happens when language gets stripped from human experience. They explore Ex Machina's warning about artificial companions, the rise of "mind crime" with Neuralink, and whether transformers are really the future.WHAT YOU'LL LEARN:→ How the Pygmalion myth influences AI design→ Why Ex Machina matters for understanding AI relationships→ What "mind crime" means in the age of Neuralink→ The difference between trust and reliability in AI→ Why interpretability unlocks creativity and control→ Are transformers really it — or is there more ahead?EPISODE HIGHLIGHTS0:00 ➤ Intro3:00 ➤ What humanities reveal about AI10:00 ➤ Academia meets Silicon Valley13:00 ➤ "Will I be replaced?" — the 2023 question17:00 ➤ Writers respond: First Encounters book21:00 ➤ The Pygmalion myth in modern tech24:00 ➤ Ex Machina & artificial companions28:00 ➤ Neuralink, neuroethics & mind crime33:00 ➤ Ethics from the start vs band-aid approach36:00 ➤ Getting the transformer paper day one42:00 ➤ Are transformers the future?45:00 ➤ Determinism vs creativity in AI48:00 ➤ The black box problem53:00 ➤ Tokenization: language without meaning58:00 ➤ Trust vs reliability in machines1:02:00 ➤ Would you trust a machine?🔗 LISTEN, WATCH & CONNECT🎓 Oxford Programme (20% Off): https://oxsbs.link/ailyceum🌐 Join 1K+ Community: https://linktr.ee/theailyceum💻 Website: https://theailyceum.com▶️ YouTube: https://www.youtube.com/@The.AI.Lyceum🎧 Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza🎧 Apple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167🎧 Amazon: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumABOUT THE AI LYCEUMThe AI Lyceum explores AI, ethics, philosophy, and human potential — hosted by Samraj Matharu, Certified AI Ethicist (Oxford) and Visiting Lecturer at Durham University.
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  #19 - AI Is a Question Machine: Teaching Thinking, Not Answers [Casandra Sibilin, Philosophy Lecturer, CUNY] 21.01.2026 56min

  AI is not an oracle — it is a question machine.In this episode, Samraj Matharu speaks with Cassandra Sibilin, Philosophy Lecturer at CUNY (City University of New York) and a leading practitioner in AI-assisted education.Cassandra works at the intersection of philosophy, pedagogy, and emerging AI tools, helping educators and students move beyond fear, hype, and automation toward deeper thinking. Rather than treating AI as an answer engine or oracle, she argues for a different framing: AI as a question machine — a tool that challenges assumptions, surfaces multiple perspectives, and sharpens human judgment.Together, they explore why philosophy has become essential AI literacy, how “flipping the interaction” with AI changes learning outcomes, and why critical thinking is not replaced by automation — but pressured into relevance by it. The conversation examines dialectic thinking, growth-mindset tutors, the risks of anthropomorphising AI, and how education must evolve toward dialogue, inquiry, and community.This is a long-form, reflective discussion about authority, knowledge, ethics, and what it really means to teach — and think — in the age of generative AI.EPISODE HIGHLIGHTS0:00 ➤ Intro / Guest welcome3:10 ➤ Why AI isn’t an oracle9:20 ➤ Philosophy as AI literacy15:40 ➤ Flipping the interaction: AI that asks questions back23:30 ➤ Dialectic thinking vs hype and panic31:10 ➤ Anthropomorphising AI: bug or feature?38:50 ➤ Ethics, growth mindset, and responsible AI tutors46:00 ➤ Education in 2050: AI tutors and human community53:30 ➤ Closing reflections & audience question🔗 LISTEN, WATCH & CONNECT🎓 Oxford Programme (20% Off): https://oxsbs.link/ailyceum 🌐 Join the 1K+ Community: https://linktr.ee/theailyceum💻 Website: https://theailyceum.com▶️ YouTube: https://www.youtube.com/@The.AI.Lyceum🎧 Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza🎧 Apple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167🎧 Amazon: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumABOUT THE AI LYCEUMThe AI Lyceum™ is an independent global community exploring AI, ethics, philosophy, and human potential — hosted by Samraj Matharu, Certified AI Ethicist (University of Oxford) and Visiting Lecturer at Durham University.“1K+ members from OpenAI, DeepMind, Oxford, Google, and more.”
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  #18 – Thinking With AI: What Can’t Be Automated? [Peter Danenberg, Google DeepMind] 13.01.2026 1j 43min

  “The things we can say are limited by the things we can think.”In this episode, Samraj Matharu speaks with Peter Danenberg, Senior Software Engineer specialising in rapid LLM prototyping at Google DeepMind, based in Palo Alto, California.Peter works at the frontier where large language models move from research to real-world systems. Together, they explore what it really means to think with AI — not to outsource thinking to machines, but to use them as tools that challenge, pressure-test, and refine human judgment.The conversation goes beyond model performance into philosophy, ethics, and cognition. Peter reflects on why intelligence is not the same as thinking, how critical thinking emerges from moments of crisis, and why philosophy remains the underlying language of reasoning in an age of automation.They examine our instinct to anthropomorphise AI — questioning whether this is a flaw or an evolutionary feature — and discuss why ethics in LLM development has largely focused on harm reduction rather than human flourishing. The episode also introduces the idea of peirastic AI: systems designed not to reassure users, but to test and sharpen their thinking.This is a long-form, reflective conversation about judgment, responsibility, and the limits of automation — and what still belongs, fundamentally, to humans.EPISODE HIGHLIGHTS0:00 ➤ Intro / Guest welcome 4:00 ➤ Peter’s role at DeepMind and rapid LLM prototyping 9:30 ➤ What “thinking with AI” really means 15:00 ➤ Intelligence vs thinking: where people get confused 22:00 ➤ Philosophy as the language of thinking 30:00 ➤ Critical thinking, crisis, and discernment 38:00 ➤ Anthropomorphising AI: bug or feature? 47:00 ➤ Ethics in LLMs and the limits of harm reduction 56:00 ➤ Automation, judgment, and human responsibility 1:05:00 ➤ Peirastic AI: systems that test us 1:15:00 ➤ Interfaces, embodiment, and tactile thinking 1:26:00 ➤ What can’t be automated 1:36:00 ➤ Closing reflections and audience question🔗 LISTEN, WATCH & CONNECT🎓 Oxford Programme (20% Off): https://oxsbs.link/ailyceum🌐 Join the 1K+ Community: https://linktr.ee/theailyceum💻 Website: https://theailyceum.com▶️ YouTube: https://www.youtube.com/@The.AI.Lyceum🎧 Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza🎧 Apple: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167🎧 Amazon: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceumABOUT THE AI LYCEUMThe AI Lyceum is a global community exploring AI, ethics, creativity, and human potential — hosted by Samraj Matharu, Certified AI Ethicist (Oxford) and Visiting Lecturer at Durham University.#ai #genai #llm #google #deepmind #aiethics #ethics #philosophy #thinking #criticalthinking #automation #humanjudgment #agenticai #responsibleai #theailyceum
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  #17 – The Future of Law with AI: Making Sense of It All [Stephen Dnes, Lawyer] 05.01.2026 1j 11min

  “Law does not stop innovation — but poor regulation can quietly distort it.”In this episode, Samraj speaks with Stephen Dnes, media lawyer, partner at Dnes & Felver, and lecturer in law at Royal Holloway, University of London, about one of the most important questions facing AI today:How should law assign responsibility when AI systems act, decide, and transact autonomously?Stephen brings a rare transatlantic legal perspective, having worked across UK, EU, and US competition, data, and technology regulation. Together, they explore how existing legal doctrine struggles with agentic systems, why GDPR and the EU AI Act often collide rather than complement one another, and how concepts like liability, mens rea, hazard, and risk must evolve in an AI-mediated world.The conversation moves beyond surface-level AI debates into deeper legal, economic, and philosophical territory — including how agentic contracts change verification and accountability, why today’s AI systems are better at averaging than wisdom, and what trust really means as humans gradually leave the loop.Whether you work in law, policy, advertising, technology, or AI strategy, this episode offers a rare, clear-eyed view of how legal systems may adapt to the next era of automation.EPISODE HIGHLIGHTS0:00 ➤ Intro / Guest Welcome3:00 ➤ Defining data, information, and regulation8:00 ➤ Why law always lags innovation13:00 ➤ GDPR vs the EU AI Act: a structural tension18:00 ➤ Hazard vs risk and the limits of precaution24:00 ➤ Mens rea, strict liability, and AI systems32:00 ➤ Agentic contracts and responsibility chains41:00 ➤ Disintermediation and the future of advertising markets50:00 ➤ Trust, brands, and humans leaving the loop58:00 ➤ Artificial intelligence vs artificial wisdom1:05:00 ➤ Law, philosophy, and the role of human judgment1:09:00 ➤ Closing reflections & audience question🔑 KEY QUESTIONS ANSWERED➤ How should responsibility be assigned when AI acts autonomously?➤ Why do GDPR and the EU AI Act often pull in opposite directions?➤ What is the legal difference between hazard and risk — and why does it matter?➤ Can concepts like mens rea apply to AI systems at all?➤ How do agentic contracts change verification and liability?➤ Why AI systems average well but struggle with wisdom➤ What does “trust” mean in an AI-mediated economy?🔗 SUBSCRIBE TO THE AI LYCEUMhttps://www.youtube.com/@The.AI.Lyceum🎓 20% Off | Oxford AI Ethics Executive Programme https://oxsbs.link/ailyceum🔗 Website: https://theailyceum.com🔗 Instagram: https://www.instagram.com/theailyceum🔗 LinkedIn Company Page: https://www.linkedin.com/company/108295902/admin/dashboard/🔗 LinkedIn Community: https://linktr.ee/theailyceum#ai #law #aigovernance #aiethics #regulation #agenticai #liability #trust #gdpr #euaiact #digitalmarkets #advertising #adtech #policy #philosophy #technology #theailyceum