The AI Lyceum

The AI Lyceum

por Samraj Matharu
Sociedad y CulturaTecnología

How AI Is Changing Education, Ethics, and the Future of Work [Tina Austin] #26

‘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 AI EPISODE HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 1:06 ➤ AlphaFold, science, and getting students excited about AI 2:26 ➤ Preparing students for jobs in a post-GenAI world 3:31 ➤ Human wisdom vs artificial intelligence 4:39 ➤ Moltbook, AI agents, and strange new digital experiments 7:05 ➤ AI-only conferences and what they reveal 10:20 ➤ How businesses should measure AI success 15:04 ➤ Morals, ethics, and whether AI ethics really exists 18:40 ➤ The Socratic AI Framework and why frameworks matter 21:20 ➤ Tina’s framework for critical thinking in education 25:20 ➤ Can thinking be measured? Metacognition, evidence, and learning 29:44 ➤ Determinism, interpretability, and risk in medicine 35:48 ➤ Sci-fi, surveillance, and where AI may take society 40:03 ➤ Healthcare, AlphaGenome, and cautious optimism 46:00 ➤ Foresight, prediction, and helping students earlier 47:03 ➤ Wisdom, intelligence, and deciding which problems matter 48:21 ➤ Closing reflections on agency and responsibility This 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.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 #AI #Education #AIEthics #FutureOfWork #CriticalThinking #HigherEducation #TheAILyceum
E26
6 abr 2026
50:52

How Wondercraft Is Changing AI Video for Business [Wondercraft CEO, Dimitris Nikolaou] #25

'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 HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 1:54 ➤ Why Wondercraft is called Wondercraft 3:51 ➤ From Imperial and Palantir to Y Combinator 7:29 ➤ Proving a startup idea early on 9:42 ➤ Why long-term vision matters 11:43 ➤ AI slop, business video, and real utility 14:48 ➤ The missing layer between models and useful products 16:47 ➤ Why Wondercraft moved from audio into video 19:42 ➤ Building a lean, high-performance team 24:07 ➤ Dimitris’s favourite interview questions 29:00 ➤ Luck, hard work, and career inflection points 32:27 ➤ Where AI video is heading 34:49 ➤ Inference, APIs, and working with FAL 36:59 ➤ Advice for founders starting in AI today 40:11 ➤ Why AI is not the real differentiator 44:02 ➤ Dimitris’s closing advice for aspiring founders Listen to The AI Lyceum® 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 #AI #AIVideo #Wondercraft #GenerativeAI #Startups #YCombinator #VideoCreation #FutureOfWork
E25
29 mar 2026
44:23

Agentic Advertising: How AI Agents Will Buy and Sell Media [IAB Tech Lab, Shailley Singh] #24

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 Singh What 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. HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 1:42 ➤ Why agentic AI is the next big shift in advertising 7:25 ➤ Agentic real-time bidding explained 12:40 ➤ From campaign KPIs to business outcomes 16:29 ➤ Standards, protocols and avoiding fragmentation 22:20 ➤ Human in the loop: from operator to architect 28:11 ➤ AI slop, provenance and content quality 35:28 ➤ The future of AI in marketing and advertising 44:34 ➤ Is AI a bubble? 52:05 ➤ Final thoughts: speed vs precision WE 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.com Samraj 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
E24
12 mar 2026
57:12

The Magic Mirror: The Journey to $3M a Month [Sunil Jindal, Magic AI] #23

'When you see that image of yourself on the screen, suddenly it feels much more possible' - Sunil Jindal, Co-Founder, Magic AI What 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 HIGHLIGHTS 0:00 ➤ 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 with MEMORABLE 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.
E23
2 mar 2026
46:35

Governing AI at Scale: Understanding Bias & Fairness [Dr. Chiara Gallese, Digital Ethics Prof] #22

'We should improve our critical thinking' — Chiara Gallese As 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 Highlights 0:00 ➤ Intro / Guest Welcome 2:40 ➤ Does AI ethics improve business outcomes? 8:55 ➤ Inside the EU AI Transparency Code of Practice 15:30 ➤ Stochastic vs deterministic systems 22:10 ➤ Where bias enters AI systems 30:45 ➤ Emotional intelligence and attachment 38:20 ➤ Disclosure, labelling, and stigma 45:10 ➤ Critical thinking in the AI era 50:30 ➤ Final reflections Key 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.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 Hosted by Samraj Matharu — Certified AI Ethicist (Oxford) | Visiting Lecturer (Durham) #AI #AIAct #AIGovernance #DigitalEthics #Bias #Fairness #Transparency #ResponsibleAI #CriticalThinking
E22
15 feb 2026
52:26

Understanding AI Ethics: Trust and Safety [Savneet Singh, AI Ethicist] #21

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 Singh As 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 wrong EPISODE HIGHLIGHTS 0:00 ➤ Intro 1:50 ➤ What does "trust" really mean in AI? 4:41 ➤ Transparency, guardrails, and human-in-the-loop 7:22 ➤ Trust vs confidence 9:33 ➤ AI-generated journalism and fabricated facts 11:15 ➤ Misinformation, deception, and human responsibility 14:49 ➤ AI psychosis and emotional attachment 21:07 ➤ Losing clarity about the human–AI relationship 24:27 ➤ Supportive tools vs emotional substitution 28:49 ➤ Guardrails, free will, and ethics by design 30:20 ➤ "Digital littering" and everyday ethics 33:54 ➤ Why AI literacy matters for all ages 36:26 ➤ One practical guardrail every business should use 39:51 ➤ Trusting AI when you doubt your own judgment 42:26 ➤ Teaching children how to use AI responsibly 46:55 ➤ Why AI agents still feel risky 52:22 ➤ The accountability gap 54:00 ➤ 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
E21
6 feb 2026
54:14

AI's Biggest Blind Spot: Culture, Not Code [Dr. Nina Begus, Berkeley] #20

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 Programmes https://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 Begus AI 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 HIGHLIGHTS 0:00 ➤ Intro 3:00 ➤ What humanities reveal about AI 10:00 ➤ Academia meets Silicon Valley 13:00 ➤ "Will I be replaced?" — the 2023 question 17:00 ➤ Writers respond: First Encounters book 21:00 ➤ The Pygmalion myth in modern tech 24:00 ➤ Ex Machina & artificial companions 28:00 ➤ Neuralink, neuroethics & mind crime 33:00 ➤ Ethics from the start vs band-aid approach 36:00 ➤ Getting the transformer paper day one 42:00 ➤ Are transformers the future? 45:00 ➤ Determinism vs creativity in AI 48:00 ➤ The black box problem 53:00 ➤ Tokenization: language without meaning 58:00 ➤ Trust vs reliability in machines 1:02:00 ➤ 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-lyceum ABOUT THE AI LYCEUM The AI Lyceum explores AI, ethics, philosophy, and human potential — hosted by Samraj Matharu, Certified AI Ethicist (Oxford) and Visiting Lecturer at Durham University.
E20
30 ene 2026
1:00:43

#19 - AI Is a Question Machine: Teaching Thinking, Not Answers [Casandra Sibilin, Philosophy Lecturer, CUNY]

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 HIGHLIGHTS 0:00 ➤ Intro / Guest welcome 3:10 ➤ Why AI isn’t an oracle 9:20 ➤ Philosophy as AI literacy 15:40 ➤ Flipping the interaction: AI that asks questions back 23:30 ➤ Dialectic thinking vs hype and panic 31:10 ➤ Anthropomorphising AI: bug or feature? 38:50 ➤ Ethics, growth mindset, and responsible AI tutors 46:00 ➤ Education in 2050: AI tutors and human community 53:30 ➤ 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-lyceum ABOUT THE AI LYCEUM The 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.”
E19
21 ene 2026
56:29

#18 – Thinking With AI: What Can’t Be Automated? [Peter Danenberg, Google DeepMind]

“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 HIGHLIGHTS 0:00 ➤ 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-lyceum ABOUT THE AI LYCEUM The 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
E18
13 ene 2026
1:43:27

#17 – The Future of Law with AI: Making Sense of It All [Stephen Dnes, Lawyer]

“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 HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 3:00 ➤ Defining data, information, and regulation 8:00 ➤ Why law always lags innovation 13:00 ➤ GDPR vs the EU AI Act: a structural tension 18:00 ➤ Hazard vs risk and the limits of precaution 24:00 ➤ Mens rea, strict liability, and AI systems 32:00 ➤ Agentic contracts and responsibility chains 41:00 ➤ Disintermediation and the future of advertising markets 50:00 ➤ Trust, brands, and humans leaving the loop 58:00 ➤ Artificial intelligence vs artificial wisdom 1:05:00 ➤ Law, philosophy, and the role of human judgment 1:09:00 ➤ 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 LYCEUM https://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
E17
5 ene 2026
1:11:28
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