MULTIVERSES

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/]

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)

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

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

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

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

To stop global warming it is not enough to stop atmospheric CO2 rising. That is not the meaning of net zero. Despite net zero being a core concept in the Paris Agreement, it appears to be much misunderstood. The idea of net zero can be traced back to the work of Myles Allen, Professor of Geosystem Science at Oxford and a veteran of several IPCC assessments. Myles explains the original intent of net zero and what we really need to aim for: zero transfer of carbon between the geosphere (Earth's crust) and everywhere else (oceans, land, atmosphere). Myles also makes a strong case that, if we want to hit the 2050 goals we need to invest more heavily in large-scale geological carbon capture and storage. Many climate activists worry that such a policy would detract from the progress of renewables and give the fossil fuel industry carte blanche to continue emitting. But Myles points out that our reliance on fossil fuels is not falling as quickly as we need, and CCAS is technologically viable, economically feasible, and essential to reaching true geological net zero. * Multiverses website [https://multiverses.xyz/] * Myles' academic home page [https://www.ox.ac.uk/news-and-events/find-an-expert/professor-myles-allen] * Resources on Net Zero from Oxford [https://netzeroclimate.org/] (00:00) Intro (2:29) What is net zero? (4:12) Net zero is not a stable state but dynamical (6:20) If we stabilise concentrations of CO2 we would see half as much warming again (9:10) The meaning of net zero is often confused (12:20) The danger of carbon accounting double counting (16:56) The difficulty of establishing additionality (19:52) Geological net zero is what was originally meant by net zero (21:30) There are no significant natural sources or sinks of carbon between the biosphere and geosphere (27:25) COP 28: the fossil fuel industry has got to be part of the solution (30:50) "It is almost dangerous to claim it's possible to solve the climate crisis without getting rid of CO2 on a very large scale … injecting it back into the Earth's crust" (32:30) Phasing out fossil fuels altogether is effectively letting the industry off the hook (32:45) To what extent can we trust the fossil fuel industry? The potential dangers of CCAS (35:30) "The cost with today's technology of recapturing CO2 from the atmosphere and storing under the North Sea … " is such that the natural gas industry could recapture all emissions and still be profitable at current prices (40:10) Carbon pricing has failed: people do the cheapest thing first and the costly, slow-to-develop things (e.g. CCAS) are not coming fast enough (42:20) The difficulty of getting a carbon capture flywheel going (45:05) Intermittent energy supply is not a problem for carbon capture (45:45) Is biochar a viable alternative to geological carbon capture? (47:08) Biochar can't hit the scale we need (48:55) Extended producer responsibility (50:10) eFuels (synthetic fuels) (50:44) Final comments: we have the technology but we need to be realistic, we need to start taking carbon back

Could AI's ability to make us fall in love with be our downfall? Will AI be like cars, machines that encourage us to be sedentary, or will we use it like a cognitive bicycle — extending our intellectual range while still exercising our minds? These are some of the questions raised by this week's guest Santiago Bilinkis. Santiago is a serial entrepreneur who's written several books about the interaction between humanity and technology. Artificial, his latest book, has just been released in Spanish [https://www.amazon.com/Artificial-inteligencia-contorno-humano-Spanish-ebook/dp/B0CHHL4667]. It's startling to reflect on how human intelligence has shaped the Earth. AI's effects may be much greater. Links: * Santiago's book Artificial co-authored with Mariano Sigman [https://www.amazon.com/Artificial-inteligencia-contorno-humano-Spanish-ebook/dp/B0CHHL4667] * Multiverses.xyz [https://multiverses.xyz/] Outline: (00:00) Intro (2:31) Start of conversation — a decade of optimism and pessimism (4:45) The coming AI tidal wave (7:45) The right reaction to the AI rollercoaster: we should be excited and afraid (9:45) Nuclear equilibrium was chosen, but the developer of the next superweapon could prevent others from developing it (12:35) OpenAI has created a kind of equilibrium by putting AI in many hands (15:45) The prosaic dangers of AI (17:05) Hacking the human love system: AI's greatest threat? (19:45) Humans falling in love may not only be possible but inevitable (21:15) The physical manifestations of AI have a strong influence over our view of it (23:00) AI bodyguards to protect us against AI attacks (23:55) Awareness of our human biases may save use (25:00) Our first interactions with sentient AI will be critical (26:10) A sentient AI may pretend to not be sentient (27:25) Perhaps we should be polite to ChatGPT (I, for one, welcome our robot overlords) (29:00) Does AGI have to be conscious? (32:30) Perhaps sentience in AI can save us? It may make it reasonable (34:40) An AGI may have a meaningful link to us in virtue of humanity being its progenitor (37:30) ChatGPT is like a smart employee but with no intrinsic motivation (42:20) Will more data and more compute continue to pay dividends? (47:40) Imitating nature may not necessarily be the best way of building a mind (49:55) Is my job safe? How will AI change the landscape of work? (52:00) Authorship and authenticity: how to do things meaningfully, without being the best (54:50) Imperfection can make things more perfect (but machines might learn this) (57:00) Bernard Suits' definition of a game: meaning can be related to the means, not ends. (58:30) The Cognitive Bicycle: will AI make us cognitively sedentary or will it be a new way of exercising our intellect and extending its range? (1:01:24) Cognitive prosthetics have displaced some intellectual abilities but nurtured others (1:06:00) Without our cognitive prosthetics, we're pretty dumb (1:12:33) Will AI be a leveller in education? (1:15:00) The business model of exploiting human weaknesses is powerful. This must not happen with AI (1:24:25) Using AI to backup the minds of people