Christof Koch is a pioneering neuroscientist and one of the most prominent advocates of a scientific approach to consciousness. He has spent decades working at the intersection of neuroscience, philosophy, and computation. Christof is one of the foremost proponents of Integrated Information Theory (IIT) — a radical proposal that attempts to explain consciousness in terms of causal structure.  IIT begins not with the brain, but with experience itself. It takes as its starting point what is undeniable: that something is happening right now — that experience exists. It then looks at the features of conscious experience, for example, that is unified yet composed of parts, and contentful. From there, it builds a theory describing which physical systems support conscious states.   In this conversation, Christof and I explore what a scientific theory of consciousness might need to achieve, and why behavior alone — even the impressive feats of AI is not enough. Nor indeed is any computational account of consciousness: consciousness is about structure, two structures may lead to the same outcomes, but their form might mean that one is conscious and the other not.   But we also touch on experience beyond theory — Christof's reflections on psychedelic experiences and the dissolution of the self. This is a conversation about what it means to be a whole, what makes a system truly unified — and what it might take to understand, and perhaps even expand, the field of consciousness.  Christof's latest book is Then I Am Myself the World: What Consciousness Is and How to Expand It.

Infinity may seem simple, just the absence of limits. But the closer we examine it, the more it unravels into paradox and mystery. Can some infinities be larger than others? How can an infinite hotel be fully booked yet still have room for more guests? In this episode of Multiverses, I'm joined by Adrian Moore, professor of philosophy at Oxford, to explore these questions. We dive into Hilbert's Hotel, Cantor's revolutionary work on transfinite numbers, and the philosophical and even theological implications of the absolute infinite—the place where maths itself seems to break down. Along the way, we ask: Is infinity something we can ever truly grasp? Or does it forever retreat beyond our understanding? If you like these topics, where science, maths give way to the unstable ground of philosophy ... subscribe! Adrian's academic homepage [https://www.philosophy.ox.ac.uk/people/adrian-moore] Adrian's book: The Infinite [https://www.amazon.co.uk/Infinite-Problems-Philosophy-W-Moore/dp/0415252857]  

Mind-wandering is often dismissed as a distraction, an idle drift away from productive thought. But what if this spontaneous movement of the mind is not just a quirk of cognition but a fundamental feature of how we think, create, and find meaning?   Our guest, Kalina Christoff Hadjiilieva, is a Professor of Psychology at the University of British Columbia where she leads The Cognitive Neuroscience of Thought Laboratory. Her work explores the neural mechanisms behind mind-wandering, uncovering how our brains shift between goal-directed focus and free-flowing exploration.   Kalina argues that mind-wandering is not a failure of attention but an essential cognitive process—one that fuels creativity, problem-solving, and insight. While some scientists define mind-wandering narrowly as thinking about anything other than the task at hand, she proposes a broader, more dynamic definition: mind-wandering is thought moving freely, unconstrained by immediate demands or rigid patterns.   Neuroscience has long favored studying controlled, deliberate cognition. The executive brain functions—the ones we can track, measure, and influence—are often given priority. But Kalina points out that the vast majority of brain activity is spontaneous and unexplained. She advocates for a shift in perspective: instead of treating free thought as noise, we should recognize its role in structuring our experiences, shaping our beliefs, and allowing us to make sense of the world.   Mind-wandering, Kalina suggests, is not just about distraction—it is about discovery.

Scientific discoveries can often be codified in simple laws, neatly stated in textbooks with directions on applying them. But the enterprise of science is embedded in society. It depends on individuals and economies. It is far from simple to answer the question: How did we get these laws?  Patricia Fara is an Emeritus Fellow of Clare College, Cambridge. She is a former president of the British Society for the History of Science and has written Science: A Four Thousand Year History,  Newton: The Making of Genius, and numerous other books.  Patricia discusses the way we often mythologize individual scientists and how the notion of genius has changed over the centuries. She also highlights lesser-known figures, such as Hertha Ayrton, whose contribution should not be measured merely in scientific breakthroughs, but in how they paved the way for further women scientists.

AI can do many things equally well as humans: such as writing plausible prose or answering exam questions. In certain domains, AI goes far beyond human capabilities — playing chess for instance. We might expect that nothing prevents machines from one day besting humans at every task. Indeed, it is often asserted that, in principle, everything (and more) within the range of human cognition will one day fall within the ken of AI. But what if there are concepts and ways of thinking that are off-limits to any machine, yet not so for humans? Selmer Bringsjord, Professor in Cognitive Science at RPI joins us this week and argues we need to rethink human thought. Selmer argues that humans have been able to grasp problems that machines cannot — humans are capable of hypercomputation. Hypercomputation is computation above the Turing limit, as such it can solve problems beyond the power of any machine we can currently conceive. In particular, Turing computation cannot encompass infinitary logic, yet humans have been able to reason effectively about the infinite. Similarly, Gödel's theorem points to a class of riddles machines cannot reach, yet human genius has identified. This is a huge topic, accepting Selmer's arguments entails accepting that human minds work in a way that evades our understanding — their mechanisms obeying mechanics of which we are wholly ignorant. Whether or not you agree with Selmer's conclusions, this is a brilliant exploration of the boundaries of thought. Links * Selmer's Academic Homepage [https://kryten.mm.rpi.edu/selmerbringsjord.html] * RPI AI and Reasoning Lab (RAIR) [https://rair.cogsci.rpi.edu/]

There is no consensus on what minds are, but there is plenty of agreement on where they can be found: in humans. Yet human consciousness may account for only a small proportion of the consciousness on our planet.   Our guest, Kristin Andrews, is a Professor of Animal Minds at the University of York, Ontario, Canada. She is a philosopher working in close contact with biologists and cognitive scientists and has spent time living in the jungle to observe research on orangutans.   Kristin notes that comparative psychology has historically resisted attributing such things as intentions, learning, consciousness, and minds to animals. Yet she argues that this is misguided in the light of the evidence, that often the best way to make sense of the complexity of animal behavior is to invoke minds and intentional concepts.   Recently Kristin has proposed that the default assumption — the null hypothesis — should be that animals have minds. Currently, biologists examine markers of consciousness on a species-by-species basis, for example looking for the presence of pain receptor skills, and preferential tradeoffs in behavior. But everywhere we have looked, even in tiny nematode worms, we find multiple markers present. Kristin reasons that switching the focus from asking "where are the minds?" to "what sort of minds are there?" would prove more fruitful.   The question of consciousness and AI is at the forefront of popular discourse, but to make progress on a scientific theory of mind we should draw on the richer data of the natural world.   * Kristin's website [https://www.kristinandrews.org/] has links to her books and papers.  * As an introduction to her thinking How To Study Animal Minds [https://www.goodreads.com/en/book/show/51763564-how-to-study-animal-minds] is a gem of a book.

Things happen. Or they don't. How then should we make sense of claims that something might happen? If all these claims do is express doubt, then the puzzle can be easily resolved. But if the claims capture some objective feature of the world, what is it? Our guest is Alastair Wilson, a professor of philosophy at the University of Leeds. He takes chance seriously, in particular, he is a realist about our modal claims (claims like "either candidate could win" or "if Szilard hadn't got Spanish flu, the atom bomb would not have been invented") may be true or false, not just opinions or expressions of ignorance. Alastair does this by connecting our modal talk to Everettian quantum mechanics. He argues that modal claims are assertions about the many worlds within the universal wavefunction. If in all worlds where Szilard did not succumb to Spanish flu, the atom bomb was never invented, then this claim would be true. It is a bold and fascinating way of bringing physics and metaphysics together. What can happen, what is possible, what could have been? These become questions for natural science. * Alastair's website [https://alastairwilson.org/] * Nature of Contingency: Quantum Physics as Modal Realism [https://www.amazon.co.uk/Nature-Conti...]

The launch of ChatGPT was a "Sputnik moment". In making tangible decades of progress it shot AI to the fore of public consciousness. This attention is accelerating AI development as dollars are poured into scaling models.   What is the next stage in this journey? And where is the destination?    My guest this week, Nell Watson, offers a broad perspective on the possible trajectories. She sits in several IEEE groups looking at AI Ethics, safety & transparency, has founded AI companies, and is a consultant to Apple on philosophical matters.  Nell makes a compelling case that we can expect to see agentic AI being soon adopted widely. We might even see whole AI corporations. In the context of these possible developments, she reasons that concerns of AI  ethics and safety — so often siloed within different communities — should be understood as continuous.    Along the way we talk about the perils of hamburgers and the good things that could come from networking our minds.   Links * Nell's book: Taming The Machine: Ethically Harness The Power Of AI  [https://www.amazon.co.uk/Taming-Machine-Ethically-Harness-Power/dp/1398614327] * Multiverses home [http://multiverses.xyz]

Physics helps get stuff done. Its application has put rockets in space, semiconductors in phones, and eclipses on calendars.  For some philosophers, this is all physics offers. It is a mere instrument, albeit of great power, giving us control over tangible things. It is a set of gears and widgets (wavefunctions, strings, even electrons) to crank out predictions.  In contrast to instrumentalists, scientific realists argue that the success of theories shows that they map onto the structure of the world, symbols in equations carry the imprint of real entities. This is an old debate in the philosophy of science. While we touch on some arguments for either position, this episode focuses on the phenomenology of physics researchers. What do physicists believe?   Céline Henne is a philosopher at the University of Bologna. Alongside Hannah Tomczyk and Christopher Sperber she has fielded the most comprehensive survey of the attitudes of physicists towards the reality of the objects of their study. From looking at the answers to dozens of questions from several hundred physicists, they have distinguished several camps of belief.  It's an elegantly designed survey, simply reading the questions forces a consideration of one's own position.    * Take the survey at Multiverses.xyz [https://scientificrealism.multiverses.xyz/]to see if you are an instrumentalist or a realist (or a bit of both) * Céline's homepage [https://www.celinehenne.com/]

It can be tempting to consider language and thought as inextricably linked. As such we might conclude that LLM's human-like capabilities for manipulating language indicate a corresponding level of thinking.    However, neuroscience research suggests that thought and language can be teased apart, perhaps the latter is more akin to an input-output interface, or an area of triage for problem-solving. Language is a medium into which we can translate and transport concepts.  Our guest this week is Anna Ivanova, Assistant Professor of Psychology at Georgia Institute of Technology. She's conducted experiments that demonstrate how subjects with severe aphasia (large-scale damage to the language area of their brains) remain able to reason socially. She's also studied how the brains of developers work when reading code. Again the language network is largely bypassed.   Anna's work and other research in cognitive science suggest that the modularity of brains is central to their ability to handle diverse tasks.  Brains are not monolithic neural nets like LLMs but contain networked specialized regions.   * Anna's website: https://anna-ivanova.net/ * Multiverses home: multiverses.xyz

Words. (Huh? Yeah!) What are they good for? Absolutely everything. At least this was the view of some philosophers early in the 20th century, that the world was bounded by language. ("The limits of my language mean the limits of my world" to use Wittgenstein's formulation over the Edwin Starr adaptation) My guest this week is Nikhil Krishnan a philosopher at University of Cambridge and frequent contributor to the The New Yorker His book A Terribly Serious Adventure, traces the path of Ordinary Language Philosophy through the 20th century. We discuss the logical positivists (the word/world limiters) and their high optimism that the intractable problems of philosophy could be dissolved by analysis. Their contention that the great questions of metaphysics were nonsense since they had no empirical or logical content. That program failed, but its spirit of using data and aiming for progress lived on in the ordinary language philosophers who put practices with words under the microscope. Hoping to find in this data clues to the nuances of the world. This enterprise left us with beautiful examples of the subtleties of language. But more importantly, it is a practice that continues today, of paying close attention to our everyday behaviors and holding our grand systems of philosophy accountable to these. Listen to discover things you know, but didn't know you knew — like the difference between doing something by accident vs by mistake. Do check out Nikhil's own podcast,  Minor Books, on iTunes [https://podcasts.apple.com/us/podcast/the-minor-books-podcast/id1725818257]  or Acast [https://shows.acast.com/minor-books]  (00:00) Intro (02:49) Start of conversation: Philosophical background and history (04:47) The Evolution of Philosophy: From Ancient Texts to Modern Debates (16:46) The Impact of Logical Positivism and the Quest for Scientific Philosophy (38:35) J.L. Austin's Revolutionary Approach to Philosophy and Language (48:43) The Power of Everyday Language vs the Abstractions of Philosophy (49:11) Why is ordinary language so effective — Language Evolution? (52:30) Philosophical Perspectives on Language's Utility (53:28) The Intricacies of Language and Perception (54:48) Scientific and Philosophical Language: A Comparative Analysis (57:14) Legal Language and Its Precision (01:07:33) LLMS: The Future of Language in Technology and AI (01:10:33) Intentionality and the Philosophy of Actions (01:18:27) Bridging Analytic and Continental Philosophy (01:33:46) Final Thoughts on Philosophy and Its Practice)

Music may be magical. But it is also rooted in the material world. As such it can be the subject of empirical inquiry.  How does what we are told of a performer influence our appreciation of the performance? Does sunshine change our listening habits? How do rhythms and melodies change as they are passed along, as in a game of Chinese whispers? Our guest is Manuel Anglada Tort, a lecturer at Goldsmiths, University of London. He has investigated all those topics. We discuss the fields of Empirical Aesthetics and cultural evolution experiments as applied to music.  * Manuel's website with PDFs and links to papers [https://www.manuelangladatort.com/] * Multiverses.xyz [https://%20multiverses.xyz/] Chapters (00:00) Intro (03:35) Start of conversation: Music Psychology and Empirical Aesthetics (07:54) Genomics and Musical Ability (18:25) Weather's Influence on Music Preferences (31:57) The Repeated Recording Illusion (43:24) Empirical Aesthetics: Does Analysis Boost or Deflate Wonder? (49:59) Music Evolution and Cultural Systems (52:18) Simulating Music Evolution in the Lab (1:01:27) The Role of Memory and Cognitive Biases in Music (1:05:33) Comparing Language and Music Evolution (1:20:37) The Impact of Physical and Cognitive Constraints on Music (1:31:37) Audio Appendix

If all my beliefs are correct, could I still be prejudiced? Philosophers have spent a lot of time thinking about knowledge. But their efforts have focussed on only certain questions. What makes it such that a person knows something? What styles of inquiry deliver knowledge? Jessie Munton is a philosopher at the University of Cambridge. She is one of several people broadening the scope of epistemology to ask: what sort of things do we (and should we) inquire about and how should we arrange our beliefs once we have them? Her lens on this is in terms of salience structures. These describe the features and beliefs that an individual is likely to pay attention to in a situation. They are networks that depend on the physical, social, and mental worlds.  In a supermarket aisle, what is salient to me depends both on how products are arranged and my food preferences. Very central nodes in my salience structure (for example this podcast) might be awkwardly linked to many things (multigrain rice ... multiverses). This is a rare and wonderful thing. Philosophy that is at once interesting and useful. Links * Jessie's home page: https://jessiemunton.wixsite.com/philosophy * Jessie on X: https://twitter.com/alabalawhiskey *  Multiverses home: https://multiverses.xyz Chapters (04:20) Welcome and Introduction to the Discussion (04:53) Exploring the Essence of Epistemology (06:31) Expanding the Boundaries of Traditional Epistemology (10:50) Understanding vs. Knowledge: Diving Deeper into Epistemology (12:42) The Role of Evidence and Justification in Beliefs (23:59) Salience Structures: A New Perspective on Information Processing (34:22) Applying Network Science to Understand Salience Structures (43:41) Exploring Social Salience Structures and the Impact of Cities (48:15) Exploring the Complexity of Attention and Salience (48:30) The Challenge of Modeling Attention Mathematically (48:57) Linking Attention to Real-world Outcomes (50:01) Differentiating Causes of Attention and Their Impacts (50:53) The Role of Individual and Social Responsibility in Shaping Attention (52:19) Influence of Media and Technology on Salience Structures (55:44) The Potential of Augmented Reality and Large Language Models (00:47) The Personalization Dilemma of Search Engines and Social Media (01:05:38) Exploring the Ethical and Practical Implications of Information Access (01:22:53) Concluding Thoughts on Salience and Information Consumption

Why do whales live longer than hummingbirds? What makes megacities more energy efficient than towns? Is the rate of technological innovation sustainable?   Though apparently disparate the answer to these questions can be found in the work of theoretical physicist Geoffrey West. Geoffrey is Shannan Distinguished Professor at the Santa Fe Institute where he was formerly the president.    By looking at the network structure of organisms, cities, and companies Geoffrey was able to explain mathematically the peculiar ways in which many features scale. For example, the California Sea Lion weighs twice as much as an Emperor Penguin, but it only consumes 75% more energy. This sub-linear scaling is incredibly regular, following the same pattern across many species and an epic range of sizes. This is an example of a scaling law.   The heart of the explanation is this: optimal space-filling networks are fractal-like in nature and scale as if they acquire an extra dimension. A 3D fractal network scales as if it is 4D.  *   Geoffrey's web page [https://www.santafe.edu/people/profile/geoffrey-west]  *  Geoffrey's book: Scale [https://www.amazon.co.uk/Scale-Universal-Organisms-Cities-Companies/dp/1780225598] Chapters (00:00) Introduction (02:56) Start of conversation: Geoffrey's Career Journey (03:25) Transition from High Energy Physics to Biology (09:05) Exploring the Origin of Aging and Death (11:20) Discovering Scaling Laws in Biology (12:30) Understanding the Metabolic Rate and its Scaling (25:40) The Impact of the Molecular Revolution on Biology (28:39) The Role of Networks in Biological Systems (49:07) The Connection between Fractals and Biological Systems (01:00:29) Understanding the Growth and Supply of Cells (01:01:07) The Impact of Size on Energy Consumption (01:01:46) The Role of Networks in Growth and Supply (01:02:30) The Universality of Growth in Organisms (01:03:13) Exploring the Dynamics of Cities (01:06:12) The Scaling of Infrastructure and Socioeconomic Factors in Cities (01:07:36) The Implications of Superlinear Scaling in Cities (01:11:50) The Future of Cities and the Need for Innovation

It's easy to recognize the potential of incremental advances — more efficient cars or faster computer chips for instance. But when a genuinely new technology emerges, often even its creators are unaware of how it will reshape our lives. So it is with AI, and this is where I start my discussion with Peter Nixey. Peter is a serial entrepreneur, angel investor, developer, and startup advisor. He reasons that large language models are poised to bring enormous benefits, particularly in enabling far faster & cheaper development of software. But he also argues that their success in this field will undermine online communities of knowledge sharing — sites like StackOverflow — as users turn away from them and to LLMs. Effectively ChatGPT will kick away one of the ladders on which its power is built. This migration away from common forums to sealed and proprietary AI models could mark a paradigm shift in the patterns of knowledge sharing that extends far beyond the domain of programming. We also talk about the far future and whether conflict with AI can be avoided. * Follow Peter on Linkedin [https://www.linkedin.com/in/peternixey/] or X @peternixey [https://twitter.com/peternixey] * Intentional.io [https://intentional.io/] — service for meaningful time management Peter is building * Show home: multiverses.xyz [https://multiverses.xyz] Chapters (00:00) Introduction (02:44) Start of Conversation (03:20) The Lag Period in Technology Adoption (06:48) The Impact of the Internet on Productivity (11:30) The Curious UX of AI (19:25) The Future of AI in Coding (29:06) The Implications of AI on Information Sharing (41:27) AI and Socratic learning (46:57) The Evolution of Textbooks and Learning Materials (49:01) The Future of AI in Software Development (51:11) The Existential Questions Surrounding AI (01:05:16) Evolutionary Success as a lens on AI (01:13:29) The Potential Conflict Between Humans and AI (01:14:24) An (almost) Optimistic Outlook on AI and Humanity

Are philosophy and science entirely different paradigms for thinking about the world? Or should we think of them as continuous: overlapping in their concerns and complementary in their tools? David Papineau is a professor at Kings College London and the author of over a dozen books. He's thought about many topics — consciousness, causation the arrow of time, the interpretation of quantum mechanics — and in all of these he advocates engagement with science. The philosopher should take its cue from our best theories of nature.For example, a philosophical account of causation must pay attention to the way this concept is used in the sciences. But the philosopher can also be a servant of science. Philosophers are undaunted, excited even, by apparent paradoxes and where such thorny problems pop up in science this is where philosophical tools can be brought to bear. For instance, when quantum mechanics appears to suggest cats are alive and dead, the philosopher's interest is piqued (even as the physicist's attention may wane). * David's website [https://www.davidpapineau.co.uk/] * Transcript and notes on Multiverses.xyz Chapters (00:00) Intro (02:41) Start of conversation (02:46) Unraveling the Mystery of Scientific Methods (03:45) The Shift in Philosophy of Science (04:03) The Role of Truth in Scientific Investigation (05:34) The Evolution of Scientific Methodologies (06:32) The Arrogance of Philosophy in Science (08:58) The Progress of Science and its Challenges (10:21) The Role of Data in Scientific Disputes (11:26) The Struggle of Early Modern Science (14:52) The Continuity of Philosophy and Science (15:28) The Role of Philosophy in Resolving Theoretical Contradictions (18:08) The Replication Crisis in Science (32:15) The Asymmetry of Time & Thermodynamics (42:45) The Everlasting Role of Philosophy in Science? (42:53) Philosophy and Its Puzzling Subjects (43:55) Artificial Intelligence & Philosophy (44:39) The Turing Test and AI (45:18) The Consciousness of AI (46:11) The Mystery of Consciousness (46:51) Is there a fact of the matter to consciousness? (48:59) The Consciousness of Machines (50:13) Different takes on consciousness (51:43) The Consciousness of Artificial Intelligence (53:23) Consciousness & Emergence (53:59) The Moral Standing of AI (01:05:23) The Future of Causation Studies

Why do men do less housework? What happens when an apology is offered? What are we looking for when we ask for advice? These are the sorts of problems drawn from everyday experience that Paulina Sliwa intends to resolve and in doing so make sense of the ways we negotiate blame and responsibility. Paulina is a Professor of Moral & Political Philosophy at the University of Vienna. She looks carefully at evidence accessible to us all — daily conversations, testimony from shows like This American Life, and our own perceptions — and uses these to unravel our moral practices. The results are sometimes surprising yet always grounded. For example, Paulina argues that remorse is not an essential feature of an apology, nor is accepting that behavior was unjustified. This is illuminating for its insights into moral problems, but I also really enjoyed seeing how Paulina thinks, it's a wonderful example of philosophical tools at work. Links * Paulina's website [http://paulinasliwa.weebly.com/] with links to many of her papers * Multiverses.xyz [https://multiverses.xyz/] Milestones (0:00) Into (3:00) Start of conversation: grand systems vs ordinary practices of morality (5:30) Philosophy and evidence (6:39) Apologies (8:40) Anne of Green Gables: an overblown apology (10:50) Remorse is not an essential feature of apologies (12:00) Apologies involve accepting some blame (15:30) Why apology is not saying I won't do it again (17:17) Essential vs non-essential features of apologies (18:12) Apologies occur in many different shapes, is a unified account possible? (20:00) Moral footprints (24:10) Apologies and politeness (26:20) Tiny apologies as a commitment to moral norms (29:50) Moral advice — verdictive vs hermeneutic (making sense) (33:30) Moral advice doesn't need to get us to the right answer but it should get us closer (36:30) Perspectives, affordances and options (38:40) Perspectives vs facts (46:45) Housework: Gendered Domestic Affordance Perception (49:40) Evidence that affordances are directly perceived (and not inferred) (52:00) Convolutional neural networks as a model of perception (53:00) Environmental dependency syndrome (54:30) Perceptions are not fixed (59:30) Perception is not a transparent window on reality (1:01:00) Tools of a philosopher (1:03:20) A Terribly Serious Adventure - Philosophy at Oxford 1900-60 — Nikhil Krishnan (1:04:50) Philosophy as continuous with science (1:06:17) Philosophy is not a neutral enterprise: (1:09:00) Santa: Read letters! (1:10:10) Apologise less

Life. What is it? How did it start? Is it unique to Earth, rare or abundantly distributed throughout the universe? While biology has made great strides in the last two hundred years, these foundational questions remain almost as mysterious as ever. However, in the last three decades, astrobiology has emerged as an academic discipline focused on their resolution. Already we have seen progress, if not aliens. The success of the space telescope Kepler in discovering exoplanets may come to mind. Equally important is the work to understand how we can demarcate biological from abiotic patterns — when we can be sure something is a genuine biosignature (evidence of life) and not a biomorph (looks like life, but is the product of other processes). Our guest this week is Sean McMahon, a co-director of the UK Centre for Astrobiology. Sean takes us through the field in general and gives particularly thoughtful insights into these epistemological problems. He also cautions that we may need a certain psychological resilience in this quest: it may require generations of painstaking work to arrive at firm answers. * Sean's website [https://seanmcmahon.co.uk/] * Multiverses.xyz [https://multiverses.xyz/] * Tartan Taridgrade podcast [https://open.ed.ac.uk/the-tartan-tardigrade-podcast/] Corrections In the intro, I say Enceladus is a moon of Jupiter. Nope, it's one of Saturn's moons. Milestones (00:00) Intro (3:22) Start of discussion: astrobiology as where biology meets the physical science (6:00) What is life? (9:30) Life is a self-sustaining chemical system capable of Darwinian evolution — NASA 94 (10:44) Life is emergent, therefore hard to define (12:00) Assembly theory — beer, the pinnacle of life? (14:22) Schrodinger & DNA (15:45) Von Neumann machine behavior as defining life (17:00) All life on Earth we know comes from one source (22:55) How did life emerge on Earth (26:40) The most important meal in history — emergence of eukaryotes (28:20) The difficulty of delineating life from non-life (33:30) How spray paint looks like life (35:30) ALH84001 (39:00) How false positives invigorated exobiology (44:05) The abiotic baseline (46:30) Chemical gardens (49:30) Is natural selection the only way to high complexity? (54:55) Sci-fi & life as we don't know it (58:45) Kepler & exoplanets (1:00:00) It may take generations (1:03:40) Sagan's dictum: Extraordinary claims require extraordinary evidence (1:08:50) Technosignatures: Gomböc, Obelisk, not Pulsar (1:12:00) Can we prove the null hypothesis (no life)

Many animals play. But why?  Play has emerged in species as distinct as rats, turtles, and octopi although they are separated by hundreds of millions of years of evolution.  While some behaviors —  hunting or mating for example — are straightforwardly adaptive, play is more subtle. So how does it help animals survive and procreate?  Is it just fun? Or, as Huizinga put it, is it the primeval soil of culture?  Our guest this week is Gordon Burghardt, a professor at The University of Tennessee and the author of the seminal The Genesis of Animal Play: Testing the Limits where he introduced criteria for recognizing animal play.  Gordon has spent his career trying to understand the experience of animals. He advocates for frameworks such as critical anthropomorphism and the umwelt so we can judiciously adjust our perspectives. We can play at being other. This week Multiverses is brought to you by ... the internet.  Links * Multiverses.xyz [https://www.multiverses.xyz/podcast/how-why-do-animals-play-gordon-burghardt/] * The Genesis of Animal Play: Testing the Limits [https://direct.mit.edu/books/oa-monograph/4951/The-Genesis-of-Animal-PlayTesting-the-Limits] * Gordon's academic homepage [https://eeb.utk.edu/people/gordon-burghardt/] Milestones (00:00) Introduction (2:20) Why study play? (4:00) Criteria for play (5:00) Fish don't smile (5:50) The five criteria: 1. incompletely functional (7:40) 2. Fun (endogenous reward) (8:20) 3. Incomplete (9:45) 4. Repeated (10:50) 5. Healthy, stress free (13:30) Play as a way of dealing with stress (but not too much) (16:40) Parental care creating a space for play (17:45) Delayed vs immediate benefits (20:45) Primary, secondary and tertiary play (26:00) Role reversal, imitation, self-handicapping: imagining the world otherwise (31:00) Secondary process: play as a way of maintaining systems (33:37) Tertiary process: play as a way of going beyond (34:45) Komodo dragons with buckets on their heads (39:22) Critical anthropomorphism (42:40) Umwelt — Jakob von Uexküll (49:18) Anthropomorphism by omission (53:00) Play evolved independently — it is not homologous (53:45) Do aliens play? (1:00:10) Play signals — how to play with dogs and bears (1:04:00) Inter species play (1:09:00) Final thoughts

Language is the ultimate Lego. With it, we can take simple elements and construct them into an edifice of meaning. Its power is not only in mapping signs to concepts but in that individual words can be composed into larger structures.  How did this systematicity arise in language? Simon Kirby is the head of Linguistics and English Language at The University of Edinburgh and one of the founders of the Centre for Langauge Evolution and Change. Over several decades he and his collaborators have run many elegant experiments that show that this property of language emerges inexorably as a system of communication is passed from generation to generation.  Experiments with computer simulations, humans, and even baboons demonstrate that as a language is learned mistakes are made - much like the mutations in genes. Crucially, the mistakes that better match the language to the structure of the world (as conceived by the learner) are the ones that are most likely to be passed on. Links * Simon's website with art, music, and talks on language evolution  [https://www.simonkirby.net/] * Simon's academic homepage [https://www.ed.ac.uk/profile/simon-kirby] * Simon on X [https://twitter.com/simonkirby?lang=en] * Multiverses Podcast home [https://www.multiverses.xyz/] Outline (00:00) Introduction (2:45) What makes language special? (5:30) Language extends our biological bounds (7:55) Language makes culture, culture makes language (9:30) John Searle: world to word and word to world (13:30) Compositionality: the expressivity of language is based on its Lego-like combinations (16:30) Could unique genes explain the fact of language compositionality? (17:20) … Not fully, though they might make our brains able to support compositional language (18:20) Using simulations to model language learning and search for the emergence of structure (19:35) Compositionality emerges from the transmission of representations across generations (20:18) The learners need to make mistakes, but not random mistakes (21:35) Just like biological evolution, we need variation (27:00) When, by chance, linguistic features echo the structure of the world these are more memorable (33:45) Language experiments with humans (Hannah Cornish) (36:32) Sign language experiments in the lab (Yasamin Motamedi) (38:45) Spontaneous emergence of sign language in populations (41:18) Communication is key to making language efficient, while transmission gives structure (47:10) Without intentional design these processes produce optimized systems (50:39) We need to perceive similarity in states of the world for linguistic structure to emerge (57:05) Why isn't language ubiquitous in nature … (58:00) … why do only humans have cultural transmissions (59:56) Over-imitation: Victoria Horner & Andrew Whiten, humans love to copy each other (1:06:00) Is language a spandrel? (1:07:10) How much of language is about information transfer? Partner-swapping conversations  (Gareth Roberts) (1:08:49) Language learning  = play? (1:12:25) Iterated learning experiments with baboons (& Tetris!) (1:17:50) Endogenous rewards for copying (1:20:30) Art as another angle on the same problems