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Conspicuous Cognition Podcast: Daily Summaries Delivered
by Dan Williams
A podcast about big questions in philosophy, psychology, evolution, politics, artificial intelligence, and more.
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- 3 weeks ago52 min
Steven Pinker on AI Doom and Consciousness
Steven Pinker thinks the case for AI doom rests on confused assumptions about intelligence and motivation.In September, the rationalist and blogging legend Scott Alexander challenged him to a public debate on the topic. Pinker declined, setting out his objections in an open letter instead, and Alexander has since replied at length.In this episode, Henry Shevlin and I talk to Pinker about how his views on AI connect to his broader ideas about intelligence, motivation, evolution, and progress. We also put several objections to him (including some that feature in Alexander’s reply) and ask whether the rapid progress in AI over the past few years has changed his mind about anything.It has, at least when it comes to neural networks.Along the way, we discuss instrumental convergence, evolutionary analogies for AI, whether AI systems could be conscious, why he would not sacrifice any human welfare for the sake of AI welfare, and why so many intellectuals are pessimistic about technology. At the end, we ask him what would have to happen for him to concede that Alexander and others were right. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.conspicuouscognition.com/subscribe
- Aug 19, 20261h 54m
Navigating the Intelligence Explosion (with Fin Moorhouse)
Dan and Henry are joined by Fin Moorhouse to discuss what an AI-driven "intelligence explosion" might look like: rapidly accelerating science, factories building factories, radical abundance, space expansion, and the profound political, ethical, and social challenges that remain even if advanced AI is "aligned". They also debate AI consciousness, illusionism, digital minds, and whether consciousness is necessary for thinking about AI welfare and rights.Fin currently works at Google DeepMind and speaks here in a personal capacity. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.conspicuouscognition.com/subscribe
- Jul 21, 20261h 16m
Who Will Control Europe’s AI Future? (with Judith Dada)
Europe risks entering the age of advanced AI without the infrastructure needed to control its own future.In this episode, Henry and I speak to Judith Dada, co-author of Europe 2031, about its warning that Europe could become dangerously dependent on American AI companies and infrastructure.We discuss:- Whether Europe is underestimating the speed and significance of AI progress- What a fictional scenario can tell us about the future- Why AI adoption may lag behind technical progress- Whether Europe needs its own OpenAI- Why Judith thinks Europe should invest heavily in data centres and compute- Whether European control of compute would provide real geopolitical leverage- The tensions between AI sovereignty, economic growth, regulation and environmental goals- What human abilities may become more valuable as intelligence becomes abundant This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.conspicuouscognition.com/subscribe
- Jul 3, 20261h 32m
Can Humanity Survive Superintelligence? (with Robert Wright)
Robert Wright joins Dan Williams and Henry Shevlin to discuss his new book, The God Test: Artificial Intelligence and Our Coming Cosmic Reckoning.Bob argues that AI is not merely another powerful technology. It is a moral, political, and even cosmic test for humanity: can we coordinate as a species before the race to superintelligence destabilises society, geopolitics, and the future of human agency?We discuss:• Why Bob thinks AI is a “God test” for humanity• Whether current AI systems really understand meaning• Why the AI revolution may be more significant than the internet, electrification, or the Industrial Revolution• The case for slowing down AI development• AI, China, and the dangers of a race to superintelligence• Whether American AI dominance could backfire• How AI might empower authoritarianism• Dan’s challenge that AI discourse may be too negative and alarmist• Whether AI is a “normal technology”• Evolution, purpose, consciousness, and Bob’s more speculative cosmic arguments This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.conspicuouscognition.com/subscribe
- Jun 16, 20261h 16m
What If Artificial Intelligence Progress Explodes? (with Benjamin Todd)
Benjamin Todd, co-founder of 80,000 Hours, joins Dan and Henry to discuss whether artificial intelligence progress could become explosive.Benjamin explains why he thinks transformative artificial intelligence by 2030 is a serious possibility, how feedback loops in artificial intelligence research could accelerate progress, and why the most important risks now go beyond classic alignment problems. The conversation covers artificial intelligence timelines, bottlenecks in chips and research talent, the future of work, mass unemployment, concentration of power, engineered pandemics, space governance, and how young people should think about their careers in a rapidly changing world.Topics discussed include:• Why 80,000 Hours increasingly focuses on artificial intelligence• The case for short timelines to transformative artificial intelligence• Whether artificial intelligence progress could become explosive• Feedback loops in artificial intelligence research• Chip bottlenecks, data centres, and geopolitical risk• Whether artificial intelligence will cause mass unemployment• Why “become a plumber” may be bad career advice• Alignment, control, and concentration of power• Misuse risks, engineered pandemics, and future governance• How to think clearly under extreme uncertaintyBenjamin Todd is the co-founder of 80,000 Hours and the author of 80,000 Hours, a new book about how to choose a career that is both personally rewarding and socially impactful. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.conspicuouscognition.com/subscribe
- Jun 2, 20261h 9m
Academics Must Wake Up on AI (with Alexander Kustov)
The political scientist Alexander Kustov recently published a Substack post with a provocative claim: that AI can already do social science research better than most professors. The post went viral. It attracted more than a million views and over a thousand responses, many of them very angry. (Some people even demanded that Alex’s university fire him.)In this conversation, we talk about this controversy and the claims that triggered it, including:* What agentic AI tools like Claude Code and Codex can already do for research, from coding and data analysis to literature reviews, translation, and brainstorming, and why only around 20% of quantitative social scientists currently use them.* What best predicts whether researchers adopt or reject AI: ignorance, openness to experience, methodological background, or the awkward role of self-interest.* How much published academic research is genuinely mediocre, and whether the cause is laziness, lack of skill, or a broken incentive structure, with a detour through the replication crisis and some high-profile fraud cases.* Whether AI will raise the quality of research or simply flood the literature with more slop, and what journal editors could do about it.* Whether AI can be genuinely creative or only recombine what already exists, by way of Margaret Boden’s three kinds of creativity, Thomas Kuhn on paradigm shifts, and AlphaGo’s “Move 37”.* The fight over AI writing and detection tools like Pangram, and why current disclosure norms end up punishing the honest.* The angry response to Alex’s series, and what is really driving reflexive opposition to AI among academics.Conspicuous Cognition is a completely reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Links and further reading* Alexander Kustov — Alex’s homepage, with an overview of his research on immigration, public opinion, and effective governance.* Popular by Design — Alex’s Substack on public opinion, persuasion, and the politics of getting good ideas adopted.* Academics Need to Wake Up on AI — followed by a Part II and Part III* Pangram — the AI-detection tool discussed at length, which labels text as human, AI-assisted, or AI.* AlphaGo versus Lee Sedol — the 2016 match, including the famous “Move 37” that Henry raises as a candidate for genuinely transformative machine creativity.* Margaret Boden — the cognitive scientist whose distinction between combinational, exploratory, and transformative creativity frames part of the discussion.* The Structure of Scientific Revolutions — Thomas Kuhn’s account of normal science and paradigm shifts, referenced in the exchange about AI and discovery.* “AI Is a Better Researcher Than You” — The Chronicle of Higher Education‘s account of the controversy around Alex’s series.Transcript* Please note that this transcript is lightly AI-edited and may contain minor mistakes. Dan Williams: Welcome back. I’m Dan Williams, and I’m back with my co-host, Henry Shevlin. Today we are honoured to be joined by Bluesky’s favourite academic, Alexander Kustov. Alex is a political scientist at the University of Notre Dame and the author of one of my favourite Substacks, Popular by Design. His primary research is on immigration and public opinion, but that’s not really what we’re going to be talking about today. We’re going to be talking about a fascinating and hugely viral series he published at his Substack titled “Academics Need to Wake Up on AI,” about what AI can already do when it comes to research,
- May 21, 20261h 18m
Are We Building Conscious AI Servants?
Richard Dawkins recently announced in UnHerd that, after spending three days talking with an instance of Claude he christened “Claudia,” he had been moved to expostulate: “You may not know you are conscious, but you bloody well are!” This produced a lot of mockery and criticism. But however one feels about Dawkins’s specific case, his reaction might become much more common as AI systems become increasingly intelligent. In this episode, which Henry Shevlin and I recorded live on Substack (hence the slightly lower video quality), we discussed his first essay on his new Substack Polytropolis, “Behaviourism’s Revenge“, as well as his second, “The House Elf Problem,” on the ethics of designing AI systems that genuinely love being our servants. Henry’s central empirical prediction is that public attributions of consciousness to AI are likely to massively outpace the science, and that consciousness science is so theoretically chaotic that there is no expert consensus to push back. His most provocative philosophical claim is that a core assumption underlying many people’s scepticism — that consciousness is a deep natural kind, distinct from behaviour and from how we are inclined to interpret a system — may be much harder to defend than it looks. The result is what he calls “behaviourism’s revenge”.This conversation connects to previous episodes with Anil Seth, Robert Long, and Rose Guingrich, but also touches on a wide range of new questions and controversies in the metaphysics, the politics, and ethics of the AI consciousness debate, which is going to become increasingly important in the coming years. Topics* Dawkins, Claude, and why even the sceptics might feel the pull to attribute consciousness or “sentience” to AI* Whether consciousness sceptics are destined to “go extinct” — and how this maps onto political and cultural fault lines* Anthropomimesis vs. raw intelligence as drivers of consciousness attribution* Why consciousness science can’t replicate the public–expert consensus we see for climate or vaccines* The case for (and against) metaphysical behaviourism: is it as mad as it seems?* Daniel Dennett, the consciousness stance, and the difference between behaviourism and interpretationism* What is consciousness for? Function, evolution, and the limits of “facilitation hypothesis” arguments for AI* Live Q&A: are we just confusing intelligence with consciousness? Are LLMs designed to trick us? Is the public always wrong?* Our credences on contemporary LLM consciousness (and why Henry is more sceptical than Dan)* The House Elf Problem: if we could design AI to genuinely love being our servants, would that be fine — or monstrous? (Dan is sympathetic to the former answer - Henry, much less so)* Brainwashing vs. education, and whether constraining a mind’s preferences caps its hedonic ceiling* Why this is a golden age for philosophy — which makes it so tragic that philosophy departments are closingTranscript* Please note that this transcript is lightly AI-edited and may contain minor errors. IntroductionDan: Welcome. I’m Dan Williams, author of the Conspicuous Cognition Substack, and I’m here with Henry Shevlin, author of the spanking new Substack Polytropolis. Today we’re going to be doing something a little bit different. We’re going to be talking about Henry’s first published essay on Polytropolis, titled “Behaviorism’s Revenge: On Human–AI Relationships and the Future of Consciousness Science.”Henry and I have already had a few conversations about this general topic, including with previous guests like Rose Guinrich, Anil Seth, and Rob Long. So please do go check out those conversations if you’re interested in this kind of stuff. But today we’re not merely going to be treading the same ground. We’re going to be using the spicy takes in Henry’s essay as a springboard for hopefully going beyond the material we’ve covered in the past.To kick things
- May 4, 20261h 21m
Aliens, Superintelligence, and the Future of Science (with David Kipping)
Most conversations about artificial intelligence are focused on Earth: jobs, misinformation, education, politics, science, regulation, consciousness, safety, and the future of human society. But AI—and especially the possibility of reaching “AGI” (artificial general intelligence) and “superintelligence”—forces us to think on much larger scales. If advanced AI is possible, why hasn’t it already emerged elsewhere? If civilisations can build self-replicating probes, artificial scientists, or planet-scale computational systems, why does the universe still look so natural? And if intelligent life is common, where is everyone?In this episode, Henry and I discuss these and many other questions with David Kipping, Associate Professor of Astronomy at Columbia University, where he leads the Cool Worlds Lab. David’s research spans exoplanets, exomoons, Bayesian inference, technosignatures, and the search for life and intelligence beyond Earth. He is also one of the best science communicators working today through the Cool Worlds YouTube channel and podcast.Among other topics, we discussed:* David’s Red Sky Paradox: if most stars are red dwarfs, and red dwarfs live for vastly longer than stars like the Sun, why do we find ourselves orbiting a yellow star?* Whether anthropic reasoning — reasoning from the fact of our own existence — is a profound scientific tool, a philosophical minefield, or both.* The reference class problem: when we reason about “observers like us”, who or what exactly counts as being like us?* The Doomsday Argument, and why some apparently bizarre forms of probabilistic reasoning can nevertheless be powerful.* The Fermi Paradox: if the universe is so large, and if life or intelligence is not fantastically rare, why don’t we see clear evidence of extraterrestrial civilisations?* Whether advanced civilisations would spread through the galaxy using self-replicating probes — and why the absence of such probes might be one of the strongest constraints on extraterrestrial intelligence.* How recent developments in artificial intelligence affect the Fermi Paradox. If humanity is close to building systems that can massively accelerate science and engineering, shouldn’t someone else have got there first?* Whether artificial intelligence makes the simulation argument more plausible.* David’s experience using artificial intelligence in scientific research, and why a meeting at the Institute for Advanced Study changed how he thinks about the role of these tools in science.* Why David thinks artificial intelligence already has something close to “coding supremacy”, but is still far from being able to do science autonomously.* The risks of AI-generated scientific slop: papers, peer review, and training data polluted by low-quality machine outputs.* Whether artificial intelligence will make science more productive, or instead strip it of some of its deepest human value.* Why the future of science communication may depend on better collaboration between academic institutions and independent creators.Links and further reading* Cool Worlds Lab — David’s research group at Columbia University, focused on extrasolar planetary systems, exomoons, habitability, technosignatures, and related questions.* Cool Worlds on YouTube — David’s excellent science communication channel, covering astronomy, exoplanets, alien life, the Fermi Paradox, cosmology, and much else.* Cool Worlds Podcast — David’s podcast, featuring conversations on astronomy, technology, science, engineering, and related topics.* Cool Worlds Podcast: “We Need To Talk About Artificial Intelligence” — the solo episode in which David reflects on artificial intelligence and science after a meeting at the Institute for Advanced Study.* David Kipping’s Columbia profile — short institutional profile with background on his research.Conspicuous Cognition is a reader-supported publication. To receive new pos
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