The AI Lyceum

The AI Lyceum

by Samraj Matharu
Society & CultureTechnology

Do You Really Need AI Agents? | Dr Quentin Reul

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 Reul EPISODE HIGHLIGHTS 0:00 ➤ 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 Adoption ABOUT DR QUENTIN REUL Dr 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
E37
Sep 24, 2026
1:00:01

Is AI Making Us Less Capable? AI Ethics with Professor Sven Nyholm #36

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 Nyholm EPISODE HIGHLIGHTS 0:00 ➤ 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 Experience ABOUT PROFESSOR SVEN NYHOLM Sven 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.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
E36
Sep 10, 2026
59:44

How AI Is Changing Business - and the Human Skills That Still Matter | Dipika Sawhney, Google #35

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 Sawhney EPISODE 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 thoughts Hosted 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
E35
Aug 24, 2026
29:14

If AI Becomes Conscious, Does It Deserve Rights? – Anna Mikeda | 34

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 HIGHLIGHTS 0:00 ➤ Introduction to Anna Mikeda 2:29 ➤ Isaac Asimov and the Origins of Robopsychology 6:56 ➤ Motivations, Alignment and AI Decision-Making 10:15 ➤ Why Large Language Models Remain Black Boxes 14:40 ➤ Can Ethical Principles Be Engineered Into AI? 15:50 ➤ AI Therapy, Emotional Support and Intimate Data 24:07 ➤ Can Computation Produce Consciousness? 28:29 ➤ Neurosymbolic and Neuromorphic AI Explained 29:46 ➤ AGI, Superintelligence and Human–AI Partnership 33:52 ➤ Why the AI Race May Be Moving Too Quickly 39:44 ➤ Should Artificial Intelligence Be Mortal? 44:11 ➤ How Are Humans Different From AI? 48:12 ➤ Closing Reflections and the Question for Humanity Samraj 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.Lyceum Listen on Spotify: https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza Listen on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167 Listen on Amazon Music: https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum Learn more: https://theailyceum.com Anna's substack: https://annamikeda.substack.com/
E34
Jul 12, 2026
49:54

Should AI Be in the Classroom? The Human Cost of Generative AI [UCL Professor Wayne Holmes] #33

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.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 #AIEducation #ResponsibleAI #AIEthics #GenerativeAI #ArtificialIntelligence #Education #HumanAgency #TheAILyceum
E33
Jun 16, 2026
54:41

How AI Changes What We Believe [AI Ethics Researcher, Dr Jana Sedláková] #31

‘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 HIGHLIGHTS 0:00 ➤ 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 AI 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 #AIEthics #ArtificialIntelligence #Epistemology #Philosophy #MentalHealthAI #HumanAIInteraction #ResponsibleAI #TheAILyceum
E31
May 18, 2026
51:16

AI and the New Economics of Advertising [Media Analyst, Ian Whittaker] #30

Explicit
AI
‘You are perceived as you price’ - Ian Whittaker Advertising 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&L EPISODE 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 Thoughts KEY 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? SUBSCRIBE Subscribe to The AI Lyceum® for conversations on AI, philosophy, media, ethics and the future of business. CONNECT 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 LinkedIn Group https://www.linkedin.com/company/108295902/admin/dashboard/ #AI #Advertising #Media #MarketingScience #AdTech #BrandStrategy #TheAILyceum
E30
May 3, 2026
45:53

Inside the AI Supply Chain: How Cerebras Powers Fast AI [James Wang] #29

'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 Utility KEY 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.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 LinkedIn https://www.linkedin.com/company/108295902/admin/dashboard/ #AI #Cerebras #Inference #AISupplyChain #AIAgents #AGI #AIInfrastructure #FutureOfWork #ResponsibleAI #TheAILyceum
E29
Apr 26, 2026
54:40

How Advertising, AI and Algorithms Shape What We See [Alessandra Di Lorenzo, Advertising Leader] #28

‘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 judgment 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
E28
Apr 20, 2026
1:03:21

Inclusive AI, Trust and Hidden Harm [Sidrah Hassan, AI Ethicist] #27

'AI just feels like another frontier of exclusion' – Sidrah Hassan In 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 HIGHLIGHTS 0:00 ➤ Intro / Guest Welcome 1:09 ➤ What inclusive AI looks like in everyday systems 4:34 ➤ LLM bias, training data, and representation gaps 7:09 ➤ How to improve inclusivity in AI 11:00 ➤ What trust in AI really means 13:01 ➤ Building trust in AI systems 20:13 ➤ Is AI ethics a distinct field? 30:17 ➤ Agentic AI, safety, and security 32:45 ➤ Storytelling, lived experience, and AI harms 43:10 ➤ Economic displacement and the future of work 50:21 ➤ AI in healthcare and human judgment 1:00:03 ➤ The AI Harms Map 1:03:48 ➤ A closing question on data and AI use 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 #AIEthics #AIGovernance #InclusiveAI #ResponsibleAI #TrustworthyAI #AlgorithmicBias #AgenticAI #TheAILyceum
E27
Apr 14, 2026
1:08:45
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