AI Moonshot — Nell Watson On The Near & Not So Near Future Of Intelligence

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, … Read more

Thinking Beyond Language — Anna Ivanova on what LLMs can learn from the brain

LLMs talk like us, but they don’t think like us. In brains, thinking goes beyond language.

Anna Ivanova’s work vividly illustrates this. Her experiments probe how certain forms of reasoning don’t need the language area of the brain.

Subjects with aphantasia (or severe damage to their language faculties) can not only play chess, they can reason about the probability of situations. Expressing surprise at a picture of a swimmer biting a shark for example.

Perhaps even more surprisingly, reading through computer code scarcely requires the language area of our brains. Computer languages are not treated the same as natural languages.

These examples show that concepts and cogitation don’t reside only in our language system.

This has implications for how we think about thought. We certainly cannot equate it with language, and it may have no neat correspondence with any one thing. Language may be the best surface mapping or reflection of a deeper, multifaceted set of activities.

Anna also argues that AI needs to progress beyond monolithic language models. Architectural modularity either needs to emerge or be put in by design. The latter is certainly happening: RAG is the modularisation of memory, while ChatGPT’s code interpretation (AKA advanced data analysis) corresponds to a specialization for logical and mathematical manipulation. How well these map to what the brain does … we shall see.

Anna’s website has links to her publications and other podcasts and videos discussing her work.

Words. What are they good for? — Nikhil Krishnan on Ordinary Language Philosophy

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 The University of Cambridge and frequent contributor to 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.

Nikhil has recently started a podcast, Minor Books, with Raph Cormack hunting down forgotten works of literature. Like the books themselves, this podcast is a semi-hidden treat. Listen on the web here. And on Apple Podcasts here.


James Robinson: [00:00:00] I’m James Robinson, and this is Multiverses. I’m in Venice for a few days, and I don’t speak good Italian. I can’t express myself, conceal myself, promise, or do all the things that I more or less adeptly can normally do with language. In fact, there’s some things one can only do with language. You can’t write a will or a law using the medium of contemporary dance.

So this is a really powerful tool. As with all really powerful tools, it’s worth putting it under the microscope sometimes. And that’s what we’re doing this week. Our guest is Nikhil Krishnan, a philosopher who’s done stints at the universities of both Oxford and Cambridge, and he’s written a wonderful book, A Terribly Serious Adventure, which traces the origins and development of ordinary language philosophy.

Ordinary language philosophy was a movement within analytic philosophy more broadly. And it paid very close attention to the way that we use the words of everyday life. One of the central ideas was instead of [00:01:00] spending too much time thinking about the big words like free will and agency, which are quite unmoored from our everyday talk, let’s think about instead the simpler words, or the simpler practices.

How do we excuse ourselves? What’s the language of excuses? Thank you. And one of the outcomes was that when one does this, you see that our languages may be more nuanced than we think. For example, by accident and by mistake might seem completely synonymous to you. But when one thinks about it enough, we’ll all agree that there are actually instances where it’s right to say by mistake and not by accident.

And the reverse is true. And we’ll get into some examples of that in the podcast. The upshot of this is, if our language is more nuanced than we think, might think, then perhaps the world is more nuanced than initially meets the eye. And actually, we already know this. Like, it’s buried within our language and all we need to do is kind of uncover it.

We have this wonderful mine of [00:02:00] knowledge within us, but it takes some reflection to, uh, probably extract the, the minerals, extract the, the wonderful gold that’s there. If you’re watching this on YouTube, you might notice that the image quality is a little bit, uh, iffy later. Uh, I had some problems uploading the, the video.

Um, however, the images may be fuzzy, but I think the words are precise. So, I hope you enjoy this as much as I did.

Nicole Krishnan, welcome to Multiverse.

Nikhil Krishnan: Hello. It’s great. It’s great to be here, James.

James Robinson: Um, so you’ve written something a little bit unusual, which is a kind of history book of philosophy. Um, there’s something of a tradition in analytical philosophy to kind of kick the ladder away as it were, and forget [00:03:00] how.

how ideas were produced. But it seems appropriate in this spirit to give a little bit of the history of yourself. Tell us what was it that brought you to philosophy?

Nikhil Krishnan: Well, I came into philosophy more or less by accident, like I think a lot of people. There are people who have stories of Lying awake at night from the age of three, pondering other questions they subsequently discovered were philosophical ones.

I don’t think that was it for me at all. I think I started out just being interested in the humanities generally. So, fiction, history, those are the things I remember being interested in as a child. And it was really through history that I discovered that there was a little bit of history called the history of ideas or intellectual history.

And I found that somehow more interesting than the sort of history that’s about, you know, why exactly did the First World War happen. Um, [00:04:00] and It was by beginning to read some of those, uh, texts, um, starting from Plato onwards. And I said, you know, this is a lot of fun. And it was really a discovery to me when I realized that the thing that was being done in those texts was not something that was stuck in the past.

People were still doing this. There were still philosophers and it wasn’t essential to being a philosopher that you were dead and in the past. So, um, once I began at university, I think I went in there thinking I was going to do You know, social science history. That was the kind of thing I was interested in.

Um, and then discovering that I was rather more interested in actually doing the thing that the philosophers were doing, uh, rather than learning about all the other stuff around them. So I think that’s what took me to the subject.

James Robinson: When you started studying philosophy at university, did it match up to what you were expecting, you know, particularly if you’ve been reading the Greeks and there’s a kind of vision I think that many people have of, [00:05:00] well, philosophy is something, as you say, that was conducted by, uh, a philosopher.

Yeah. you know, now dead, um, bearded men, I suppose. Um, and it’s about, well, it’s a very ponderous subject, um, you know, striving for depth and looking at these huge questions. Um, and my impression is that when one actually studies philosophy at university, it’s, it’s, it’s, It’s a kind of different enterprise.

Um, did you feel any sense of surprise or, um, did this seem kind of continuous with your expectations?

Nikhil Krishnan: Well, I slightly overstated in the book for, uh, for, for rhetorical effect, really. Um, It’s true that I was hoping for a subject that would be a tiny bit more continuous with the rest of the humanities.

The idea was that to do history was also to be interested in, you know, how the texts are constructed in the way that you’d study them if you were doing English literature. And, um, it would [00:06:00] involve knowing something about the language and the context, the historical worlds in which they were constructed.

Um, and a little bit of sensitivity to the way in which philosophy fits into the world now. What exactly is it doing? How is it intervening in the big questions that people are asking you, even if they’re not academic philosophers? And it’s true, early on at least, I discovered that that wasn’t quite how one is taught it, at least in the English speaking world.

I think it might be slightly different if you’re doing it in Germany or Italy or France, but certainly where I was doing it, which was in the UK in the um, late 20th century. 2000s. The sense was that we treated this subject as a largely a technical one, or more precisely, what it is to learn the subject is to learn a set of techniques, some of which are fairly technical, formal, sometimes bordering on the mathematical.

Um, and in general, one tried to put aside historical questions, stylistic questions as much as we could. Uh, now I should say in the long run, it’s turned out [00:07:00] that there is a way of doing philosophy. That’s. Fits all these different things together that it has the technical side is about ingenuity and precision and clarity But that also is able to draw on History and literature and anthropology and whatever else really you want to draw on But I think it was generally a wise thing for my education not to have been like that at the start Certainly for me given my own temperament with a tendency to sort of for always try and look at things You As broadly and connectedly as possible for someone to insist that nope, we’re just looking at this argument I want to know what the premises are and what the conclusion is.

So in the beginning I sort of resented it Um, it seemed like I was being stopped from getting onto the really interesting stuff but I think it was the most useful education I could have had putting me away from my natural tendencies and Excesses and instead saying there’s a method Uh, it was good enough for Aristotle.

You’re going to learn to do it yourself. Uh, and I think over time I have learned to do that and I’ve learned to integrate it with all the other things I’m interested in. [00:08:00]

James Robinson: Yeah, there’s a, a really nice view review of your book by Kathleen Strokes. He sort of describes philosophy as, um, well, the way that it’s taught in British universities, at least largely being as, as if an alien is approaching a problem and just has no, none of the kind of, um, historical context, but it’s just approaching something for the first time, which, you know, there is a certain sense of liberty in that kind of, um, you know, when one is not weighed, overly weighed down by tradition and yet has available the techniques of the tradition, um, that, that can be, um, yes, liberating.

And it’s interesting, your book, um, From what I understand, it sort of dates back to the period, I guess, where this move away from embedding philosophy very much within [00:09:00] the traditions of history and classics occurred. And I’m thinking particularly of how the degree of PPE, or modern greats, Uh, I should say that’s philosophy, politics, and economics, and it’s not just personal protective equipment, which is probably what comes to most people’s minds these days.

Um, so that degree was, was, was founded in, in, in 1920. And previously, I, I think the only way that one could study philosophy at Oxford was, was by, by studying, um, greats, which was a mixture of history and, um, classical languages and philosophy. And so, you know, Now, that move wasn’t designed to change the pursuit of philosophy.

It had very practical, um, purpose at heart, if I understand correctly. And it was just, we want to educate better administrators and maybe politics and economics are useful things. Um, but yes, I don’t, I don’t know if that, that, you know, maybe I’m overstating the impact of, [00:10:00] of, um, the creation of PPE, but it does seem at least to me, It’s intriguing that it happened at this time, um, early on in the 20th century, um, when the tide, I think, was, was changing and philosophy was becoming sort of shedding some of its past perhaps.

Nikhil Krishnan: Yeah, I think, um, that’s, I’d say that’s more or less, uh, accurate. Now my book is specifically a history of philosophy at Oxford in the first 60 years of the 20th century, but really primarily focusing on the period after the war. So 1945 to 1960 is the period I really, really sink my teeth into. But some of what happens after the war, some of the really interesting action that occurs there, um, happens because of the groundwork that had been done uh, in the period between the wars.

And one of those things, as you rightly said, was the move away from philosophy as a subject you could only study as part of the four year classics degree into something which you could study at least in one other, uh, possible degree [00:11:00] course which was the Philosophy, Politics, and Economics course, and, uh, that was the course I studied myself, sort of a hundred years after it had been uh, founded.

Now, in the immediate, um, context of, of that decision, I think part of what was going on there was, uh, was really an anxiety, a quite legitimate anxiety that this was a period when slowly but surely a British society was becoming a little bit more democratic, the suffrage was expanding, larger number of people wanted to go to university, and if you insisted that anyone who was interested in philosophy would have to do classics, that meant that you could really only.

Select your students from the people who had already done Greek and Latin at school. Um, and I mean there was a much larger number of those Back in the early 20th century than and then would be the case now But even then the numbers were declining and there were people for whom it just seemed unfair I mean It doesn’t seem true that you have to know The ancient languages as a condition of being able to do philosophy for one thing There are perfectly good [00:12:00] translations of the works and there’s a great deal of philosophy.

That’s not in ancient languages I mean philosophy has been You know, carried on, uh, in languages other than, than, than Latin. And it has been, uh, it’s been done in French. I mean, it’s happening in German, it’s happening in Italian, and it’s happening in English. And it seems like a shame to exclude a large class of potential students from it.

So, um, one side effect of that is what you mentioned. Um, so once you go into this degree, not thinking of it as a branch of the classics, not really as a branch of, uh, textual analysis, you can do, uh, something. Well, it’s something that was nicely captured by a former colleague of mine, the late Hugh Mellor, a wonderful, um, um, metaphysician and philosopher of science, um, and he was once asked by someone from a more historical, historically minded discipline what he worked on, and he said causation.

And someone said, Kant or Hume? And he said, no, no, I don’t do Kant and Hume. I do what Kant and Hume did. And I really like that distinction, uh, the distinction between the activity itself [00:13:00] and the study of other people who have engaged in that activity. Um, I think that once you take the subject to be a subject, Uh, a matter of doing the thing itself, doing philosophy, not just studying what other philosophers did, then sure, you can still read the philosophers, because in the same way that if you’re doing physics, you’re going to read what other physicists say.

But the task eventually is not to write a history of physics, it’s to do some physics yourself. There’s no reason why the same thing shouldn’t be true of philosophy, too.

James Robinson: And I, I think it reinforces this idea that there is,

it’s something of a leveler, the way that philosophy is, is, is practiced. People arrive at university and they have very different ideas. Mathematical abilities, um, they may be, you know, they may have a wonderful, uh, historical mind and lots of historical knowledge, um, but it’s not really going to help them that much when they study philosophy, uh, unless they spent some years kind of boning up on, um, you know, [00:14:00] exactly the sort of things which is taught at university.

But, um, I don’t think those things tend to be taught so much in, in schools. So everyone comes with almost as, as a blank slate. Um, And the things that are going to be most useful to them are actually just a keen ability to analyze and, um, interrogate, um, often how, how language is used. At least that, that is a kind of central thread to, um, philosophy nowadays.

Um, and again, this, this, come squarely back to the period in which, um, you know, the 20s before the war, uh, and 30s, um, I think that teed everything up and started to put language and by language, I mean, demotic language, ordinary language, not the ancient languages, you know, [00:15:00] right at the center of, of philosophy, perhaps too much so.

And we can come onto that. Um, but, um, you know, Suddenly it was a, or it must have been a breath of fresh air.

Nikhil Krishnan: Yeah, absolutely. Uh, I can agree with all of that. The leveling power of a philosophy which doesn’t require some specific body of knowledge that would require a specific kind of education, uh, in advance of you doing philosophy.

I think it’s a drawing on, uh, things that you already have to hand. If you’ve had the most minimal kind of education, I’m sure you need to be able to read and write and be able to. Think and talk in complete sentences. Given that the main subject of philosophy is everyday phenomena as we articulate them through our language.

And we already know our language. We know our native languages. So, um, the possibility of being able to reflect on these large questions, but [00:16:00] without, but without the intermediary of some, uh, difficult text, was liberating to people. To be able to say, I can talk about what it is to perceive something just by looking at these, uh, these words.

How do I use the word perceive? See? Hear? Smell? Feel? Etc. And the possibility of making progress by drawing on experiences and knowledge we already have without the need for any specialist training was bound to make it a subject that would attract people who didn’t have that sort of training, understandably, because they hadn’t been to the sorts of schools which would provide you with that sort of training.

James Robinson: And I think when, if we think back to when these, when these, ideas started to really gain currency. Um, there was perhaps even more in enthusiasm for them. And indeed the, the title of your book, A Terribly Serious Adventure, um, comes from a piece of travel writing by, uh, Ernest Nagel, who’s, um, as you recount so, so beautifully is, is sort [00:17:00] of just doing this wonderful philosophical tour of Europe, going to all the grand cities where philosophy is, is, is being practiced.

And in, and Vienna, he’s kind of really. Puzzled to see people so excited. Um, and this is, this is the time of the logical positivists who, um, who are really iconoclastic in, in, in some ways and their program, you know, it goes something, if I’m going to very crudely sketch, sketch it out. It’s something like, um, you know, Philosophy has completely lost its way, um, it’s become unmoored from reality, um, and the only things that kind of have any meaning are, um, things that can be deduced from empirical data, uh, you know, either directly or through some kind of inferential chains, or things which are, uh, logically free.

Deducible. So something has to be demonstrable, either empirically or in some logical way. Um, [00:18:00] and, you know, really grappling with this idea, they kind of come to the conclusion that just so much of philosophy is just nonsense. I mean, literally nonsense doesn’t doesn’t have any meaning at all and can just be thrown out.

So this is like, you know, um, revolutionary stuff in some ways. It’s clearly really exciting to a kind of cohort of, uh, or a generation around Europe, I guess. Um, and you also point out that, um, you know, perhaps this is linked to other things going on in Europe and Austria, particularly at the time. Um, this is the one place where people can break free intellectually.

Um, uh, It’s a, doesn’t require any resources, uh, other than, you know, that same kind of looking inwards or looking at outwards at language, however one thinks of it. Um, and, and [00:19:00] also looking at what science is doing. There’s a huge respect for science from the logical positivists. In fact, they essentially thought that philosophy would just end up being subsumed within science.

And once you cut off all the, the dead wood, what would be left was essentially a particular way of. Science and logic. Science and logic. Yes. Yes. Um, I mean, one should say that that program didn’t really wind up the way they thought philosophy still exists, and for good reasons, I think, um, but, but I, I do love the kind of spirit of enthusiasm with which it was, was started.

And I think that must have really helped propel this, this idea, um, throughout Europe, I suppose.

Nikhil Krishnan: Yeah, I think that’s right. Um, The thing about the Logical Apostrophes, in addition to all the intellectual stimulation they, they certainly provided and the kinds of provocations, uh, they represented, one important thing about them is just how energetic they were, um, at the [00:20:00] logistics of making philosophy happen.

Uh, there were places, uh, other places in the world where philosophy usually happened, in, you know, someone gave a long lecture, someone wrote a long book. And what the positivists are doing is to say, let’s experiment with our forms, both in the sense of the literary forms, let’s try and have lots of short papers, rather than long books.

And let’s start organizing conferences, let’s start getting people moving across Europe, hanging out with each other, trying out their ideas in each other, sort of testing them, improving them. And that was an idea I suppose they would have got from the kind of form that science was beginning to take, in particular physics.

Um, so they’re always organizing these enormous international congresses, as they’d call them. And then you’d be in Paris and there’d be British philosophers and Italian philosophers and German and Austrian philosophers that would all be hanging out and sharing these ideas. And they’d all go out and they’d start publishing in, um, Uh, journals, and they started new journals, right?

There was a journal that came out of Vienna itself, and then there was an English language journal called, uh, Analysis, which is founded in this period, [00:21:00] and the main rule for getting published in Analysis is, uh, keep it short. And the hope is that by keeping it short, you can have lots of little snappy exchanges, you know, little paper, little response, little paper, little response.

And what you won’t have is this, here’s my big theory of the universe and how everything is connected to everything else. Rather, here’s a little problem, and here’s my take on it. And someone says, no, that doesn’t work, here’s a better view. And the hope was that philosophy would actually begin to make progress in a way that it hadn’t made before, because, it’s, it’s Every idea was articulated in terms of these enormous systems.

It was very hard to compare ideas between systems because it seemed like everything depended on everything else within that system. And unless you really kind of got in there and mastered the entirety of Hegel’s phenomenology or whatever, uh, you had no chance of being able to assess any one of its claims.

But the idea that we can now take philosophy as a series of little problems and puzzles and try to make progress on each one of them. One of them individually in the hope that eventually it will all come together nicely. But you didn’t try and put them together at the start. The unity of the [00:22:00] system was something that would emerge later on.

James Robinson: Those are really interesting points. Yeah. So I, yeah, I, I, that had never struck me, but that these kind of methods, both in terms of bringing lots of people together, um, somewhat in the sciences, you say, Uh, or the spirit of, as you say, of, of science and, and one of course thinks of everything that was happening in quantum mechanics and, um, what was going on in Copenhagen and the, and the way that people were being brought together there by Bohr, for example.

But I also, it also comes to my mind. You know, the, the French artistic movements, um, like the Dionysus and so on, who were also bringing together groups of people coming up with like pamphlets and, um, you know, all these kind of different movements going on. Um, hard to know who was taking inspiration from whom, but maybe it was all part of the spirit of the age.

Um, and then of course, this idea, as you say, of breaking philosophy down. So instead of. these monolithic undertakings, [00:23:00] um, trying to be precise and break off pieces and, and problems, which clearly I think both those aspects really do endure. Um,

Nikhil Krishnan: yeah.

James Robinson: Yeah.

Nikhil Krishnan: I mean, in some ways they endure, um, precisely because Well, the positivists themselves, I mean, they had this spirit, as you say, of let’s write a look at the individual problems, let’s write shorter papers, let’s have lots of meetings and share ideas.

But on the other hand, they were motivated by this one very large idea, uh, which was that we can give A principle which will tell us the difference between what is meaningful and what is meaningless and certain kinds of, uh, human discourse, certain uses of language, in particular, religious language, ethical language, aesthetic language, that stuff is, is meaningless and should be understood in some other way as, you know, attempts to persuade, attempts to manipulate or have a psychological effect and express emotions, that sort of thing.

And I think. [00:24:00] Over time, one thing that emerged was that the spirit of that same kind of more scientific minded philosophy eventually undermined even that idea within positivism itself. I think the really sensible idea and the one that I think is essential to the Oxford stage in the development of this philosophy, is that they really took to heart the idea that philosophy is best done piecemeal.

Don’t try to have one principle, which will try to tell you the difference between the meaningful and the meaningless. Just look at each bit of language on its own terms. Try and work out what it’s trying to do. Don’t go in there having already, uh, prejudged the matter, right? Let the discourse, let the use of language determine what kind of theory or, uh, account best suits it.

So in that way, the spirit of positive and the scientific spirit of, you know, falsification testing, verification and so forth, you might think actually undermined what initially seemed like the essence of the positivist project. But in a way it was, um, in a way almost truer to the spirit of that project, that the spirit of the project was not really [00:25:00] some thesis that they were trying to defend.

It was rather a certain approach to how philosophy should be done and a way in which philosophy can learn something from the way in which sciences are done.

James Robinson: Yeah. So I, I, I guess one summarizes that. You know, the grand thesis was something like, well, we can just knock off all this dead wood, um, because it doesn’t really, doesn’t have any sense attached to it.

But then of course, when one looks more carefully, um, Surprise, surprise, all these kind of metaphysical questions are ones which are actually really important and bear upon everyday language and practices in all sorts of surprising, intriguing ways, and therefore just cutting them off. Just one lops off a huge part of, um, you know, one is unable to explain in a certain sense, the actual.

Yeah, simple phenomena of life. Um, there’s a beautiful line from your [00:26:00] book where you say, um, something like, you know, ordinary language held that language should be accountable or what we should say becomes accountable to what we do say.

Music: Yeah.

James Robinson: Um, and that kind of. Spirit, I guess, is very much in this empirical spirit again, that, um, what as philosophers, the, the, um, the way that, um, particular issues are discussed should pay attention to the words that are used within philosophy, um, that, that they need to be informed by the evidence of the way that words actually are used, um, Yeah, I thought that was very, very nicely put.

And again, just shows the continuity of spirit there, even if, um, in many ways, the, the grand [00:27:00] structure of logical positivism fell down, um, It’s key insight that philosophy needs to move forward in a kind of scientific way, uh, lives on. Yeah. Perhaps tell us, how did, um, yeah, how, how did, how were these ideas, uh, received in Oxford?

How did they come to Oxford? Um, as it’s quite intriguing to me. just, you know, how the world in general worked then, um, in some ways it seemed quite slow for things to, to filter through, you know, it wasn’t that someone would go and post something on Twitter or X as it is now and, uh, suddenly everyone would be debating it next day in, in Oxford.

It was much more kind of word of mouth and, uh, missionaries being sent out and coming back as it were.

Nikhil Krishnan: Yeah, that’s right. And that’s part of the excitement of writing a history like this is tracing those connections. Uh, so one, um, The way in which ideas are transferred then [00:28:00] is through the publication of journals.

Now journals are not a thing that have always existed, right? They have, they had to be, that idea had to be invented. The idea of a certain kind of publication which comes out, I don’t know, every few months, uh, at least. and which puts together relatively short pieces of work, which are then debated and discussed and people write responses and responses to responses.

I mean, that’s something that really starts to emerge in the late 19th century. Before then, I mean, there are still venues for publication, but they tend to be slightly more generalist, learned periodicals, something like the Westminster Review. It’s the kind of thing where, uh, John Stuart Mill, Thomas Carlyle, those kinds of grand Victorian figures, the places they would have published.

It’s important that they are generalist Um, venues, but something a bit like, say, the London Review of Books would be today. They’re perhaps a little bit more learned than that, but, but very much in that kind of vein. But a journal is something that requires slightly more, uh, a more specialist readership.

You [00:29:00] can count on them understanding certain words, certain terms of art. You can understand, you can count on them to, sit down and, and pay attention when you make a really, really complicated argument over the course of 15 pages. And you don’t have to try to entertain them quite as much as you would when you were writing for the older style of publication.

So, these journals start to exist. There’s one called Mind, uh, that’s published out of Scotland. There’s, uh, Analysis, which I briefly mentioned, which, uh, um, comes out in the 20s and 30s. There are a bunch of American journals at this point, including the Philosophical Review. Um, and there’s, uh, a journal called Erkenntnis, which is, um, uh, a journal that’s published out of, of the, the positivist world in Vienna.

So, uh, they’re getting the information through there. Libraries then, like now, have subscriptions to these journals. But you mentioned missionaries as well. So some people actually go and travel to these cities and they say, sure, I mean, we get bit of an idea of what’s going on through the journals, but the journals are always, you know, a couple of days, a couple of years out of date.

And so you really need to be there. That’s why Ernest Nagel, the American philosopher you mentioned, [00:30:00] travels to Cambridge and then Vienna and then to Prague to see what people are doing. And A. J. Ayres, this British philosopher who has heard a little bit about interesting stuff happening in Vienna from his old tutor, Gilbert Ryle.

And Gilbert Ryle says, yeah, why don’t you go to Vienna? I know this guy called Moritz Schlick. I’ll write you a letter of introduction. Go and hang out with him. He’ll make sure you get some sort of visiting position at the university. You can go and attend lectures. You can improve your German. And Eyre does that, and he spends a little while there, and he comes back and says, Right, I’m really persuaded by this philosophy, but no one’s really written about it in English.

And he very luckily gets a contract from this trendy publisher called Victor Galanx. Um, which generally publishes kind of lefty books, uh, in this period. Trendy lefty books, that’s his kind of thing. And you say, oh, here’s a young radical philosopher. I have no idea what he’s on about and his nature of meaning and so forth, but some people seem to be really into it.

So why don’t we give him a contract and get him to write a book? And he does. And then as soon as he does, [00:31:00] He’s in Oxford at a period when there’s a bunch of other philosophers of roughly the same age, and they’re mid to late twenties, and they all hang out in these kind of all male bachelor rooms in one of the Oxford colleges, and they’re going over each chapter line by line, coming up with objections, coming up with, uh, objections, um, responses and counter objections.

So, um, lots of the philosophy, on the one hand, it’s happening in these public places, right? These large international congresses and journals, but some of it’s happening in these more private settings. So basically you and your mates hang out and discuss what’s just been published in the journal and sometimes you publish what You come up with sometimes you don’t or rather you think that saying it to your mates is a species of publication I mean you’re making it public, right?

You’re not leaving it entirely private. So trying to reconstruct the history of what was said in these sorts of Um, uh, private ish meetings, uh, is, is one of the enjoyable aspects of, of the research for the book. You know, trying to find little notes and minutes that someone who left behind and say, Oh, that’s what, [00:32:00] then they discuss that idea, which eventually becomes that paper published 15 years later.

James Robinson: Yeah, it is so fascinating in the book to, to see the enterprise of philosophy in, in progress, as it were, and to understand just how important it is, these, uh, meeting groups, and there’s just various different ones going on, uh, among different generations of philosophers. It seems like a new generation needs to have its space, and so they, they come up with their own, um, meeting group, and, um, you know, they’ll be having, uh, tea or maybe something a little bit stronger, uh, depending on, On the Arab day, but, um, all meeting and and and not in the spirit of these aren’t debates that they’re having their discussions, their conversations.

Um, and you put it so beautifully in the book that both agreement. Well, both disagreement and agreement are permitted. Yeah, I mean,

Nikhil Krishnan: the other way around, both agreement and disagreement are permitted. The really [00:33:00] remarkable there wasn’t that disagreement was permitted. I think that you can take for granted.

It was perfectly fine to agree as well.

James Robinson: Exactly, exactly. And, and there was a hope that, you know, they would come up with some kind of consensus. Um, and, um, perhaps we should mention one of the kind of central figures to, to, to emerge at the, at this point, who I think was a bit of a thorn in the side of, of, uh, AJR was, uh, so, you know, As you mentioned, people would kind of start knocking holes in, um, the arguments of the Leucozoidal positivists as relayed by, uh, Ayer in his book, um, uh, The Problem of Knowledge, I think.

Um, and one of the, the chief, uh, hole knockers, uh, I can’t remember if it’s, I don’t know if it’s you who described me as such or if it’s, uh, just, uh, the name from the time. I think it’s a quotation

Nikhil Krishnan: from Isaiah Berlin describing him, you know, he’d be watching these debates between J. L. Austin and A. J. Ayer, and he described Austin as the hole knocker.

James Robinson: Yes, yes, and [00:34:00] Ayer is trying to patch up the wall, which, as, no, as soon as it patched up as J. L. Austin, um, Yeah, knocks in another another dent. Um, I should say as well, J. L. Austin is one of my favorite J. L’s. J. L. Borges, Jennifer Lopez, J. Lo, of course, and J. L. Austin. Um, and very much a figure of the times. Uh, I guess both, both, both personally and philosophically.

Um, so very much a kind of English person of a certain class. Um, yeah. One gets the impression that he was, yeah, somewhat straight laced, but also had a very keen sense of humor. Um, um, and it’s very interesting to contrast him, of course, with, with Wittgenstein, very different character, even though both of them had this, this, um, great respect for language, um, and [00:35:00] pursuing their philosophy using ordinary language and, and, and, um, You know, both in ordinary language and using it as the kind of key data, I suppose, for it.

Um, but, um, yeah. As we mentioned, uh, in some ways Austin really took on the positivist spirit of, of, of using, of being very scientific in his approach. Um, but it, one does get the impression that, um, poor Mr. Eyre was very, um, frustrated by the fact that no, no, no wall could be constructed because, Yeah. Uh, everything would just be, um, Dismantle, I suppose.

Music: Yeah, that’s right. What we’re thinking about is

Nikhil Krishnan: the difference between two philosophical temperaments, isn’t it? There’s people who want a system that takes the whole universe and connects it, uh, and says here’s the essence of things. And there’s the other people who think, well, the universe is really complicated and [00:36:00] messy, and what we need is something equally messy to do justice to the messiness of reality itself.

So they’re not looking to unify things, and they’re okay with not having a theory that connects everything. And so the knocking of holes then is an expression of that Yeah, let’s just live with, with messiness, kind of, of temperament. I mean, there’s a famous line from someone else who attends these meetings in this period, uh, Isaiah Berlin, who later on becomes a famous historian of ideas.

And, uh, he writes an essay called The Fox and the Hedgehog. Or is it The Hedgehog and the Fox? Which is partly an essay about Leo Tolstoy and the sort of weird reflections on the nature of history that you find in, uh, War and Peace. Um, The basic idea is from a fragment of this ancient Greek poet, from whom we have only one line surviving, and that line goes, The fox knows many things, but the hedgehog knows one thing.

And he uses [00:37:00] that as a way of dividing up thinkers, writers, philosophers, scientists. There’s the hedgehog thinkers, who want one big idea which connects everything. And there’s the foxes, who think you need one. You know, plenty of different ideas. So, you know, Plato is supposed to be a hedgehog, and Aristotle is supposed to be a fox, and, um, someone like Shakespeare would be a fox as well, because it’s really hard to pin him down on anything.

There’s just lots of different human characters and variety. And I suppose Austen would count as being at least, to put it a little bit boringly, methodologically a fox. Don’t assume at the start that it’s all going to join up. Just try and talk about each thing on its own terms. And one other slogan that becomes, uh, really influential in this period is a remark from an 18th century, uh, thinker called Bishop Butler.

And Butler is famous for saying, Everything is what it is and not another thing. And in one sense, that’s a completely trivial statement, right? A tautology. In another sense, it’s a really useful thing to be reminded of, which is don’t try [00:38:00] and say, Oh, this thing you’re looking at is actually just an example of this other thing, right?

Ethical discourse is just like aesthetic discourse is just like religious discourse. Let’s use one principle to, uh, one principle to define the essence of each. Instead, no, attend to each one on its own terms. Ethics is ethics and not aesthetics. Aesthetics is aesthetics and not religion, et cetera. And I think once you bring the spirit of that into philosophy, you’re a slightly less inclined to want to make everything link up.

You’re just willing to say, let’s just talk about each thing by itself.

James Robinson: Yes, yes, yes. And I think that’s, that’s beautifully put. Um, perhaps we can give some kind of. More concrete impression of what, um, Austin’s methods were, some examples of the holes that he knocked, perhaps, in walls, um, because he would probably be turning his grave about how abstractly we’ve been talking about him, given that he was all about the precision and, you know, getting down to the business.

of um, [00:39:00] of things which I, one really enjoys this in his writing.

Nikhil Krishnan: Sure, uh, so perhaps the best way into this aspect of Austen’s work is to talk about what used to happen at Uh, these meetings he used to run, uh, after the war. So just very briefly, it might be worth saying that, you know, Austen had been a promising young philosopher in the, in the 30s, beginning to do some important work on, you know, language and epistemology.

And then suddenly he gets called up for war service. And he spends most of the war doing intelligence work, reaching a quite senior level. And I strongly recommend a recent biography by Mark Rowe, His Complete Life of Austin, much more details than the portrait you get in my book, where, you know, he’s a central figure in my book, but I didn’t do anything like the level of intense archival work that Rowe’s done.

It’s a really enjoyable account of his war work. But one thing that, uh, Austin learned from doing intelligence work during the war was that you didn’t make advances. [00:40:00] In intelligence by having one genius sit down and try and work out everything. You just needed lots of little reports of saying, well, this is what’s happening in this bit of Normandy.

And this is what, this is a little thing we encrypt, uh, decrypted at Bletchley park, and we just put these two things together and say, aha, this is what the Germans are up to, but it takes time. It takes effort. And most importantly, it takes cooperation. One genius can’t do it all. And he said, well, it seems like an intractable problem.

The problems of military intelligence, we solve them through cooperation. Why not think exactly the same thing could be done with the big problems of philosophy? So take a problem such as, um, free will, right? There’s a way of thinking about this problem on which there’s one single question, which is what is free will and do we have it?

And some people say, oh, yes, we do. And it’s really important. And, um, on the other hand, you have people who say, nope, we don’t. Um, complete illusion, um, we need to get rid of it and get rid of all the social practices that [00:41:00] seem to assume that we have free will. Things like, you know, blaming and praising and punishing and so forth.

Now, what Austin would do with something like that is, is to say, well, hang on a second. What on earth is a will? What on earth is it for it to be free? Um, Do we really need one concept that’s meant to do all this different work? One thing that’s going to be on the one hand, a theory of action, something that distinguishes supposedly human actions from animal behavior, something that can be the grounds of our entire set of extremely complex practices of blaming and praising and punishing.

He says, well, it’s not clear in advance that we have one thing that’s presupposed by all of these practices. Why not instead look at each one of these phenomena? each one of these activities on its own terms. So the paper in which he makes this point, uh, absolute classic, really represents his style and his approach.

It’s called A Plea for Excuses. And in this, uh, in this paper, one of the things he’s doing is to say, [00:42:00] look at the phenomena that we currently regard under a very, very general label, the label of responsibility. Now stop using that big word responsibility, instead look at the various ways in which we try to explain, extenuate, and give excuses for our actions.

And think about what’s happening in each one of these cases. And so he makes a bunch of very, very subtle distinctions. Um, on the one, for instance he says, the idea that everything can be divided into either free or not free. Right, and then you have a big debate between which things fall on which side of the divide.

Instead, you realize there are many, many ways in which things can be unfree. For instance, something could be unfree as an action because it was an accident. It could be because it was something done, uh, unwittingly. It could be unfree because it was coerced. It could be unfree because it was inadvertent.

And these are distinctions which our language is already able to make. We’ve [00:43:00] got all these different words, which is why we distinguish between doing something unwittingly and doing it unwillingly, doing it inadvertently, doing it accidentally, and doing it by mistake. And the idea that there’s one thing called freedom, which underlies all of these different cases, or if you like, the thing that is absent in all these different cases.

He says, well, we have no reason to assume that. And once you start looking at the phenomena, it’ll turn out there is not one thing. The word freedom actually is an enormous philosophical abstraction, which, far from connecting, unifying different phenomena, actually makes us think. There’s only one thing going on.

Well, actually, there’s, well, dozens of things that are going on. And the hope is that philosophy will start attending more closely to these different phenomena. I’ll ask what the difference is between an accident and a mistake. And by trying to uncover the various ways in which our actions can get it wrong, something can be off about them, you’ll understand everything that needs to be said about freedom.

There will be no further question about this big abstraction called freedom left to ask anymore. So, um, the word they’d often use [00:44:00] there would be that we’ve not solved the problem of free will, we’ve dissolved it. We’ve turned it into dozens of different problems, and each one requires its own methods, its own approaches, and a different set of phenomena, uh, that we need to examine in order to, to dissolve them.

But once we have reached that, in a way, we have addressed the thing we were worried about. It’s just, it turns out that the one thing we thought we were worried about wasn’t one thing after all.

James Robinson: It, it, it’s complete wizardry when one reads that paper, because, for example, Austen starts off with many terms, which.

One would say, okay, well, these are just synonyms, right? These mean the same things, accidentally and, um, you know, by mistake and so on. But then it shows very clearly that actually we do appreciate the difference between, uh, these terms. Well, similarly, um, you know, the example with, um, um, I know, yawning. Um, does one, does one either yawn involuntarily or voluntarily?

[00:45:00] Well, neither, neither seems right. So it’s clear that. Somehow, linguistically, we, or, you know, we don’t want to say that things are either voluntary or involuntary. Um, there is a kind of, our language is, is somewhat finer than that. Um, and of course, the, yeah, the mistake and the, um, by mistake and on, uh, by accident is, is just a beautiful example and involves, uh, kind of classic.

thought experiment of Austen, of donkeys being shot, a farmer going out to his field, and in one circumstance, a donkey, uh, he sort of, um, he doesn’t recognize, or he, his own donkey, and shoots it. The other one he’s, um, mistaken as the identity and the other case, um, he does take a bead on the correct donkey, but then the blasted, his neighbor’s blasted donkey just steps in front of the last moment.

And there’s, you know, clearly an [00:46:00] accident there. And one’s like, Oh gosh. So there is a difference between these terms, which I’d always thought that I had been employing kind of indiscriminately and at a whim. Um, but actually, you know, there’s some, there’s some deeper structure here, which, um, You know, anyone in principle can recognize in their own language.

Um, so it’s truly eyeopening, um, just how much data one has access to, or just how much, you know, how much mileage one can make, um, by sort of armchair philosophizing, although of course that’s a very unfair thing to say, because as we’ve mentioned, so much of the progress that Austin made was, uh, not sitting on his own, but, um, discussing things with, with other people.

Nikhil Krishnan: Yeah, that’s right. And the hope is that, I mean, this wasn’t always borne out by his own practice. I think it’s clear that he was a fairly charismatic person who, whom everyone deferred to. So, um, some of the more democratic elements of, of the, of the practice, I think, weren’t [00:47:00] always borne out in how he himself ran it.

He’s just one of these people who like to be in charge, but you know, that’s a, that’s not a problem in the method itself. It’s just as conceivable that The, that set of methods could be employed by someone with, um, a less, um, authoritative manner and someone who could actually allow it to be fully democratic.

And a good deal of subsequent philosophy which uses these methods is democratic in that way, right? It’s, it hasn’t got Austin breathing down your neck, telling you what you’re supposed to say. It’s, um, in the spirit of people saying, this sounds a bit odd. I wonder why. And someone saying, Hmm, I wonder if we put it this way, that might make it a little bit, a little bit better.

And I find myself just constantly in. Um, conversations which basically are conversations in that style, um, not always in an academic setting. These things come out constantly, and I think having read some Austen, it means that I’m utterly, utterly fascinated with these little, uh, nuances of, you know, Of ordinary language usage.

I mean, one of the remarks that one of the people who [00:48:00] participated in these meetings of Austin, one point he sort of bursts out and he says, how clever language is, and that really is something you start to feel, you realize, as you said, the way you put it was in terms of data, the amount of data to which we have access just by having, uh, learned her language, any language.

Uh, is really staggering, the amount of stuff that’s already in there, the number of distinctions that are already being made. And that really brings into focus the, the arrogance of a kind of philosophy which says, you know, let’s put all that aside. And let’s sort of invent a new term, which I just sort of came up with half an hour ago, sitting in my armchair.

And we’re going to talk about that. We’re going to talk about appearance and reality. We’re going to talk about, I don’t know, reality and illusion. We’re going to talk about freedom and, um, coercion, whatever it is. And you say, well, Language is much more complicated than that. You are cleverer than that.

And you’re making yourself stupid because of bad philosophical habits you’ve acquired from the tradition, right? And that’s the reason why we should reject the tradition. Stop [00:49:00] doing it in terms of these enormous abstractions. Attend to the enormous resource you have, uh, uh, to handle ready.

James Robinson: Yes, I completely agree.

I, I do want to sort of, um, um, I do want to say, though, one thing that’s always, I found a little disappointing is that no one has made that case, at least to my knowledge, very clearly for why language is, is so powerful in this sense. And one gets hints of it in, in Austin’s own, uh, work and words where he, he says sort of something like, you know, these concepts that have hung around over, you know, so many generations, uh, have kind of, I don’t know, I can’t remember his terminology, but there’s the sense that they’ve become battle hardened or they’re, you know, they’re any, if they weren’t useful, they wouldn’t have hung around so, so much.

Um, but of course, one wants a little bit more than that, because it’s [00:50:00] very easy to find counter examples, particularly in sciences and technology, where it is the new concepts and terms, which are actually. Far more successful than, than the old ones. You know, we have quarks and glue-ons and, and all these wonderful, rich ontology of things that have been, um, invented but not invented, discovered, I suppose.

Um, and they’ve replaced earlier things like ether and humans and, and so on. Um. And, you know, so clearly there’s good evidence that, um, at least from the sciences, at least, um, there can be huge benefits from bringing in new terms. And perhaps that’s what’s inspired some, um, philosophers in, in, in other traditions.

Um, but, um, one final thing I, I will say is that, um, you know, I, I, I’ve talked to some linguists who are working on language evolution. And what that does show is that, um, certainly grammar, um, [00:51:00] and the marvelous structural properties of, of, of language do emerge almost spontaneously as a, um, as a series of symbols is passed through generations, um, in such a way that that grammar will map onto, um, um, the concepts of similarity that are kind of pre linguistic and existing in the, the people.

So, for example, um, you know, you may have completely random words for photo, um, photographer, um, I don’t know, photography, uh, that, that have no bear, bear no relation to each other at the, at the beginning of one of these kind of, um, language evolution experiments. And then just over time, they will evolve to have, um, some kind of similar structure.

Um, And so there seems to be that, you know, perhaps there’s something there which could be availed by to make something of an argument for at least language mapping well on to the concepts that we [00:52:00] have. But it’s again, I, I wish one could go somewhat further and really, you know, prove the worth of language, um, beyond the fact that, oh, wow, like these, these kind of, um, exercises which Austin and others have performed are just so convincing, um, but perhaps they, the fact that they’re convincing is just because they’re all in, in language and they’re still locked within that same structure, right?

Nikhil Krishnan: Um, yeah. Yeah, sorry, I made a few things on the table. I think we can say a fair bit more than that. So, it seems initially that, I mean, Austen himself, like other philosophers of his generations, really doesn’t like talking about methods. He just wants to use them, right? He wants to do the thing, do the philosophy, rather than talk about what one is doing and doing it.

So there’s very little in the way of self conscious, I suppose. reflection on the method being used, but every now and then you’ll get a little, you know, obitur dictum, kind of passing remark, [00:53:00] which is supposed to illuminate what’s being done. And one phrase, um, totally ugly phrase that, uh, Austin uses to describe what he’s doing is linguistic phenomenology.

Very crudely, the idea is that it’s, you’re not interested in the words themselves, rather, you’re interested in looking at reality in as subtle, perceptive, fine grained a way as possible. And the hope is that the words will help you to do that. So having better words, more precise words, subtler, more nuanced words, will enable you to perceive something in the world, right?

And there’s um, later philosophers inspired by Austen who use analogies with things like art criticism. Or even just something like wine tasting. Now, I mean, wine tasting is not a thing I do myself, but I gather that there is a whole vocabulary. Of how one talks about wine and at the beginning, you say, I mean, what on earth is to say that is summary PT and a little bit apocalyptic or whatever it is people say to, uh, [00:54:00] to describe a wine, but the people who really do this stuff clearly are getting something out of that language, right?

That they’re able to articulate something that was a note that was in the wine, that the language enabled them to, to see, perceive. Better. So the same, I think, the hope is that the same thing can be true all other phenomena. You think there’s one undifferentiated mass of stuff. And someone says, no, no, no, look really closely.

Don’t you see that thing and that thing and that thing? So that’s what I understand to be the point here. The point isn’t just let’s make as many distinctions as we can. The point is that in making the distinction we’ll see something in the world itself that we weren’t able to see before. And then you ask yourself, well Sure, we can always make as many distinctions as we like.

Not all of them matter equally. And indeed, part of one thing that, uh, the development of science tells us is that a lot of good science happens because, you know, we thought there was hydrogen and there was helium and there was neon, there was argon, uh, [00:55:00] but it turns out that understanding something about the structure of atoms would connect together all these different elements.

Say, this is what’s going on, right? It’s to do with atomic number, which is definitely not a term of, of ordinary language. And we don’t say proton and neutron. That’s, that’s a word that emerges from within, um, science. So, the question has to be, well, fine, science comes up with one of these words, but that’s when the test begins.

Do people actually go on to, to use that word? We know through, through history, there have been abandoned scientific theories, which came up with interesting terms. There are these kind of pseudosciences like phrenology. which claimed to be able to explain human psychology and behavior by looking at bumps on skulls.

And it turned out that that stuff was completely meaningless. But of course, along the way, it came up with, um, a great many subtle distinctions and varieties of skulls. They didn’t survive. No one’s interested in phrenology anymore. Quite rightly, it turned out that it just didn’t do what you wanted a genuine science to do.

Now, I think [00:56:00] science is in many important ways, a special case. I think we should expect science to tell us things that are counterintuitive, uh, that don’t map onto how we wouldn’t really think of the world, because a lot of what science deals with are not the stuff of, of everyday life, right? It’s, it’s precisely attempt to look beyond the conditions of everyday life.

It seems a little bit weirder to think that the same thing would be the case for philosophy, especially when it’s philosophy of something very, very everyday, like, you know, praising and blaming to use the example I just did, or just, you know, what is it to see something? The idea that you could have a vocabulary that was utterly disconnected from and could replace all of our language in these sorts of phenomena sounds to me much less likely, at least to start with, right?

You’d need a very strong argument to persuade me of that. So the hope is that what we’ll do is to stress test our language. And some bits of language will survive the stress test. And that’s definitely going to be the case in the sciences, right? Not every neologism that a scientist has come up with has actually caught on.

There’s a reason [00:57:00] why. Quark did catch on because it did, um, explanatory work that alternatives to it didn’t. And so, and you can think of other such areas of human life which are really good for stress testing concepts. One particularly good one is, uh, is the law. That a lot of the law, um, lots of people kind of think of the law as being, you know, there’s this book which has all the laws in it.

But of course, I mean, it’s, it’s very unusual for law, certainly in the kind of common law world. But really the way in which law develops is by saying, Here’s a principle we got from this one particular case, but we tried to apply to another case and it didn’t quite fit. So we sort of modify it a bit. We make another distinction and so it goes.

So over time, you’ll find that if there are certain terms which are appearing in quite a lot of, of laws in, in statutes or in case law, it’s because that language was found to be especially useful as a way of. Drawing attention to, to, to the phenomena, right? So, um, even when, say, I don’t know, Supreme Court justices is faced with a question like, [00:58:00] Are gig economy workers employees or not?

And you realize the word employee and worker can sometimes be used interchangeably, but they’re clearly not the same. And the whole point about the gig economy is that it seems to make us, force us to draw a distinction between these two classes of people. And then you say, to what extent is, um, an Uber driver like an employee of a more traditional sort, someone who has a contract and someone who has a regular salary and someone who gets, uh, various sorts of protections of employment against.

Um, summary dismissal, et cetera. And you realize, well, in some ways they are, in some ways they aren’t. And then a judge actually has to look at the phenomena, right? By saying, how do we normally describe employees? How many of those features are present in the particular case of a gig worker? And just, by the way, the particular, uh, judgment I’m talking about, um, I’ve suddenly forgotten, uh, what the name, I think, was something like Uber and, uh, Aslam, A S L A M.

And [00:59:00] the Supreme Court Justice who wrote the judgment on that was himself originally trained as a philosopher, Lord Leggett. And you can really see some of that kind of subtle attention to language, how we talk about work and employment. That’s at work in the background of the kinds of principles he draws.

And in that particular case, he decided that given some of the things that, uh, Uber workers are required to do. They clearly are much more like employees than, than Uber itself wanted to, to allow. Uh, so that’s a case I think where we are really drawing on the resources of our ordinary language to illuminate something about, in this case, an incredibly important economic, political, uh, legal phenomenon.

And I think all of that is very much in the spirit of the Austinian approach to philosophy.

James Robinson: Yeah, I think that’s very well put. And, um, yes, as you say, it’s, it, looking at these edge cases, um, trying to push the limits. Um, and, and one is reminded of, you know, Wittgenstein’s famous dictum, the limits of my language, the limits of our world, which I don’t entirely agree with.

But of course, if [01:00:00] you want to really out delineate something, the best place to look is, is at the edges and the, and the most, um, you know, imagining these, uh, interesting, um, often somewhat unlikely scenarios, such as the donkeys being shot in a, in a field. Um, and, and, and, um, but of course, One wonders, you know, how far can one push the limits of language?

Um, is it always fair to expect our language to be up to the task? Of course, in physics and technology, as we’ve mentioned, there’s clearly examples where it’s not, and a new term is completely, um, uh, necessary and appropriate. Um, But of course, one, you know, what I’m thinking of is, well, a couple of things.

On the one hand, the kind of, um, thought experiments of people like Bernard Williams and others, in terms of personal identity, [01:01:00] where, um, We ask ourselves, so what would happen if a person went through a teleportation device and, and then we make various kind of little tweaks on, on that experiment to, to really tear apart our, um, concept of, of identity.

Um, but of course, maybe identity is just not the right concept to use anymore, or maybe we need, we need to abandon some of the baggage. Um, the other thing that comes to mind is popular, um. Saying from, or aphorism from Edgar, uh, Dijkstra, um, the question of whether a computer can think is no more interesting than the question of whether a submarine can swim, you know, clearly saying that these kind of questions are, are just splitting hairs.

Um, I, and I, I really do disagree with that. And I think the reasons I disagree are very much linked to, um, the enterprise that, that Austin was interested in, because, you know, of course, whether something can think, um, [01:02:00] If we, if we agree that that’s the appropriate way of describing what it’s doing, that locks it into a whole web of other things, you know, it, it, it may mean that, you know, does that mean that we need to think of it as being conscious if it thinks, or, you know, perhaps not, but it certainly locks it into a, a certain, um, system of, of, uh, of language.

And. We cannot ignore how, how much of an effect that has on, on, on, on the way that we, um, ourselves think of something. Um, But yes, I, I do, what I, what I do worry is that even, um, for these questions of, of, of thinking, identity and consciousness, um, where, you know, there is a tension between wanting to employ these terms, um, which have stood us [01:03:00] so well in the past, um, but then there is the possibility that, um, Things are so, you know, there will be such a radical change in the way that things are that they may no longer continue to serve their purpose.

Yeah, I think that’s

Nikhil Krishnan: going to be right for something like thinking. It may just be that. We thought there was one thing here called thinking and either machines do it or they don’t. But it turns out really what we need is, um, uh, an idea, a bit of terminology that allows us to see that these kinds of things come on a, on a spectrum.

Uh, there are degrees to which something counts as, as a thought. And that initially seems a bit weird, you know, either something is or isn’t thinking, seems to be our initial assumption, but maybe that’s not one that’s, um, justified once you really think about the phenomena. And once you do think about the phenomena, you realize, well, it turns out it wasn’t, [01:04:00] it isn’t a new problem that’s revealed by, You know, reflecting on robots and AIs, maybe this is a problem we already had with animals, right?

Do animals think? I mean, sort of yes, sort of no. Maybe the problem is in thinking that the whole question has to be asked in terms of the word thinking. And again, the Austinian moral is really useful here. Why are we so invested in that word? Maybe there’s a way of describing all the things animals can do and all the things that AI can do and some of them will be pretty much identical to the things that are involved in human thought.

Some of them won’t be. We can just talk about what they can and can’t do and maybe that’ll be all there is to say. And the further question of whether, Thinking is a notion we need to apply many more, maybe one we have to give up, right? So the question, going back to your very helpful analogy there, can submarines swim?

It seems like it’s equally, um, okay to say yes or no, and in a way it kind of feels weird whatever you do say in that case. Right? Um, because on the one hand, you think swimming is just moving in water, then well, yeah, of course they do. [01:05:00] If on the other hand, you think swimming involves the movement of limbs, either hands and legs or flippers or fins, then it doesn’t seem that submarines have got those, certainly not literally.

But then you ask yourself, why do we need to make this distinction? What is it doing for us? What’s the purpose of drawing it in the first place? And Initially you say, well, I can’t think of any human context in which you have need to make that distinction. But then you could imagine a legal context in which it starts to become important.

Say there was a um, you know a bylaw of some lake saying swimming is not permitted in the lake and someone said well I’ve got a submarine in there. Um, and you say well On the one hand, it seems that the question is about whether they’re swimming in the lake or not, but maybe what that the submarine makes, forces you to think about is, is not do they swim or not, but rather what was the purpose of the prohibition on swimming, right?

So maybe it was that And it was worries about privacy. Maybe it was concerns about effects on marine life. Um, maybe it was about hygiene. I mean, it could be any number of things. So what, [01:06:00] um, you’re then forced to do is to ask, well, if it was about privacy, then clearly, uh, the submarine is violating the privacy of, I don’t know, uh, uh, those landowners or water owners.

And so it should come under the same prohibition. So in one way, you kind of have answered the question. You’re saying they do swim, but what really what you’re saying is they count as doing the same sort of thing as swimming would be doing. So, sure, in a sense, they’re not swimming, but there’s a reason why you should still include them within the scope of this prohibition.

So, really, the spirit I’m doing here is going a little bit beyond Austin. It’s going to a wider tradition of pragmatism, where you think about language not in terms of, Does it represent the world correctly, but rather does it do the thing we need it to do? And what that forces you to ask yourself is what does it what do we need it to do?

What are the expectations we have of this bit of language and a great deal of legal language technological language scientific language develops Because it turns out we have a need [01:07:00] that is not adequately um satisfied by our existing language and that’s the point at which the new development happens sort of Language starts to make, the new language starts making room for itself.

It just sort of tears apart the old distinctions and makes new ones. And when you get a good distinction in technology or science, which does that, um, you’ll find that it does then survive the Darwinian test that Austen himself has imposed. It will survive the test of time until we get a new technology and maybe we’ll need new language for that.

James Robinson: Yes. Kind of continuing on with the, the, the theme of, um, large language models and. Machines that may or may not think, um, I’m, I’m mindful of the, um, title of Austin’s book, you know, how to do things with words. And one of his kind of, um, great contributions, other than the, I suppose, kind of just series of techniques that, and, and, and, uh, the method that he, [01:08:00] um, uh, really helped me.

Pioneered, popularized, I’m not sure the best way of terming it, but, um, his kind of theory of speech acts, which is really, I suppose, just one very key insight that, um, you Um, you know, in, in uttering something, um, we can be doing more than one thing at once. And so, you know, the arrangements of our words aren’t just arrangements.

They can actually do things. They can perform acts. We can, uh, we can name a ship, we can make a bet, um, we can promise each other things and threaten each other. And, and these are not just, um, arrangements, they, they, they come with some kind of, um,

One thing that really strikes me about, um, LLMs at the moment is, you know, the extent to which they just manipulate, uh, symbols and move them around. Um, my impression is that that is the [01:09:00] correct way of thinking about them and they can’t, you know, They can’t place a bet. They can’t, um, uh, promise, threaten, and so on.

Although they might look like they’re threatening you, uh, if they’ve been, you know, badly programmed. Um, but, um, You know, at some point, uh, perhaps there will be links up to, uh, particular agencies and, um, abilities that would allow them to go beyond just manipulation of words. And then we will end up in a, in a, in a place where, for example, I don’t know, a machine could bid at auction for one, right?

Yeah. And their, you know, their action of saying, uh, I don’t know, 65 or whatever the number is, um, is, is not just an arrangement of words in a certain sense, but we would, at least again, in our ordinary language, we would think of it as placing a bid. Um, and. You know, even if it, yeah, it just strikes me as [01:10:00] interesting as, you know, whatever, even if those machines are patiently not conscious, um, right.

The fact that we start to, we would be compelled, I think, uh, you know, any sensible person would say, oh, that, that, you know. You know, robot just placed a bid for you, we’d be compelled to use some of the language, which has this, um, this baggage of intentionality. Um, even if we don’t regard the machine as having, um, intentions.

Um, and yes, I just don’t know. Uh, the right approach here. Right.

Nikhil Krishnan: Um, There’s a few things, since you’ve mentioned intentions in particular, it might be useful to bring in another philosopher, uh, who is kind of the philosopher of intention, someone called Elizabeth Anscombe. She and Austen kind of loathed each other personally, but I mean one of the things I try and do in my book is to show that these people who personally disliked each other were actually basically onto each other.

the same insight, and for reasons of personal animosity, never quite saw [01:11:00] just how, uh, how much of an intellectual affinity there was. So, Elizabeth Anscombe is, uh, was a student of Wittgenstein’s, and she returned to Oxford after the war. She taught there for 20 years, and one of the early bits of writing she publishes in the late 1950s is a little monograph called Intention.

Right. And then one of the things I think she very usefully does is to try to wean us off a very natural and tempting way of thinking about what an intention is, right? By thinking about it as a certain kind of conscious mental state. Uh, which, um, is kind of private to your mind, so you kind of know what you intend to do.

It’s something that’s inside the private theatre of your mind, and then, of course, you could reveal your intention through your actions, or by saying what you intend to do, etc. But ultimately, it’s a thing that’s going on, in some metaphorical sense, inside your head. And [01:12:00] she wants to say, well, that’s just not the right way of thinking about intention.

It’s not a thing that’s going on inside anything else. It’s not a thing that is going on. Rather, she says, why don’t you think about it this way? Think about words like intentional, intentionality, intentionally, and think about them as a form of description, a form of description of actions. And when you bring actions under that description, uh, that tells you a little bit about how you are thinking about that action.

So stop looking for a thing called an intention. You can sort of look inside a brain and find this one state that’s going to be the intention. She thinks, you don’t need to do that, and you probably shouldn’t do that anyway. So here’s some examples she uses, right? She asks ourselves, um, think about how we describe animal movements.

I think in thinking about things like AIs, it’s always, always a good idea to think about non human animals. I think it’d be really illuminating because on the one hand, we’re still talking about a creature with some level of consciousness, but not a human level of consciousness. So it [01:13:00] helps us to separate our ideas about consciousness from our ideas about what’s distinctively human.

So she says, observe a cat stalking a bird. And observe a cat kind of trying to fall on its feet and sort of tripping. Now, it seems clear that one of those two things is something the cat is doing intentionally, and the other is a thing that it isn’t. Like the cat slipping, or So it seems like the language of intention is one we can perfectly well ascribe to, at least non human animals, right?

But then you ask ourselves, well, how many intentions can we ascribe to the animal, right? So now take a dog that’s digging the garden. And you can ask yourself, why is the dog digging in the garden? And you say, ah, because it’s burying the bone. Yeah, that’s a thing we know dogs do. So there’s no mystery at all.

There’s nothing particularly controversial about saying that in digging the hole, the dog is trying to bury the bone. Right. But suppose you then say, oh, in digging the hole, the dog is trying to bury the bone so it can return to it next Tuesday. [01:14:00] That seems much less likely, right? We just don’t think that animals are capable of that further thought.

So it looks like the very notion of an intention is, is not either you have one or you don’t. It seems like the concept is already a bit messy. That includes things like, In doing one thing, you were trying to do something else. And that’s clearly something that can be the case for animals. And I suspect it could be true of a machine.

There’s now the further question of, um, whether, so in raising my hand at the auction, I thereby committed myself to paying certain money, a certain amount of money. That’s kind of what a bid is, right? To bid on something just means if there are no higher bids, then you’ve got to pay up. Now, there’s a question of whether a machine could, you know, incur an obligation.

And that seems a bit tricky. And I said, no, you, what the, this kind of process of reflection makes you do is to think of what has to be the case about something or someone such that they could incur obligations. Right now, in this particular [01:15:00] case, actually, it seems like maybe what we could say is what’s going to happen is that once The machine has made that noise, 65, and it turns out no one said anything higher.

What will happen is that it puts into, uh, that puts into motion a chain which will mean a certain amount of money is deducted from a certain bank account, right? And there might be certain legal principles which say that you can’t now stop that. In the same way that, uh, would happen in the case where we’re talking about a human being in its own and that person’s obligations.

Now, what we’re doing is clearly slightly stretching the boundaries of what words like bidding, promising, intending, um, being obligated and so forth are doing. But, again, in that kind of pragmatist spirit I introduced earlier, we ask ourselves, what are these concepts for? Don’t first say we’ve got these concepts, now do they apply?

Ask ourselves what the concepts are doing for us in the first place. And you can think of very good reasons why we might want a [01:16:00] system where a machine is in a position to put in a bid, right? It’ll just mean something slightly different. It doesn’t mean, oh, the machine should be ashamed of itself if it doesn’t pay up afterwards.

That whole language of shame and guilt and so forth isn’t going to apply to the machine. But the idea that there are now legal restrictions on whether Um, the money’s allowed to stay in the bank account or not. That seems to me to be entirely meaningful here. So again, we’re doing the Austinian thing.

We’re taking one concept and showing that actually it’s covering a wide range of phenomena. And what the situation makes us do is to draw those distinctions. Once we have drawn them, We don’t have to worry so much about whether that was really a bid or not, right? We could just say that all the consequences of making a bid will happen in the case where the machine makes those noises.

Do we need to worry about whether it was a bid? Well, that just seems like a fetish for answering the question of was it, wasn’t it? We don’t need to answer that question anymore. I myself feel no longer worried about that question once I’ve said all the things I just have.

James Robinson: Yeah, I [01:17:00] think that’s a wonderful example of the, the method in, in action.

Um, yeah, and it, it does, yes, well, in some ways it’s, um, to say, well, things are more complicated, right? Again, our language is, is, is actually up to the task. We do use it in very subtle ways. Um, and perhaps where we run into error is we, we latch on to some of the most controversial, um, big terms, consciousness.

Uh, free will, and we immediately want a question to, well, is it, isn’t it, right? And maybe the answer is, well, you know, those things are actually, um, you know, let’s think of some of the, um, more common words we are on, uh, stronger footing with. Um, uh, so, you know, for consciousness, one might think instead of, yeah, thinking, reasoning, um, saying, even asking, you know, what [01:18:00] are all the verbs that one associates, that can one associate with this?

And perhaps some of them will apply to machines and, and some won’t, and the ones that do may apply in certain situations and, and not others. And perhaps there’s maybe a better word that, um, we can use. Um, but yeah, I, I. Yeah, it really shows how applicable this, this, this way of doing things, this way of philosophizing is to this day.

Um, I have many more things we could talk about, um, but perhaps we can, I don’t know, well, maybe we can finish with something a little bit, uh, fun, uh, so, um, I’ve talked previously with Simon Critchley, who’s from sort of straddles, I guess, the analytic and continental traditions. Um, and, and, and maybe it would be fun just to, uh, I don’t know, contrast these two and lament the fact that perhaps they were moving apart.

So the continental [01:19:00] tradition, one might think of Sartre and the French, uh, Um, philosophers of, of, of that time, phenomenologists and, um, and also some, uh, Germans like, uh, Heidegger and Roussel and so on, um, a bit earlier, uh, There’s a beautiful quote that you, uh, have from Iris Murdoch in your book where she says, um, she’s describing a book by Gilbert Ryle, um, actually very much on the topic we were just discussing where Gilbert Ryle is trying to, it’s called The Concept of Mind, and he’s trying to, um, dismantle a bit of a straw man, Cartesian view of the world where things are either conscious or not.

And he’s trying to say, well, look, um, you know, if we, if we, if we pay careful attention to our categories, we’ll just see that. This is a problem that kind of just, just dissolves. But his book is, is, is rather quaint in, in some ways. And she says, The concept of mind evokes a world in which people play [01:20:00] cricket, cook cakes, make simple decisions, remember their childhood, go to the circus, not the world where they commit sins, fall in love, say prayers, or join the Communist Party.

And, um, So, yeah, what is, imagine on the one hand, uh, Gilbert Ryle, you know, in tweeds with elbow patches and a pipe, which, uh, I think it’s not an unfair description of him. And on the other hand, you know, the French philosophers in leather jackets with, um, Galois cigarettes. Um,

Discuss. Um, yes, where do we, what can we say about this? And, and, um, you know, can a rapprochement

Music: be

James Robinson: made between, between these worlds or, or, or should we just think of philosophy as, as, as, um, you know, a few different disciplines that really don’t need to talk to one another on the, on the one hand, this continental tradition, which is, you know, rather textual, um, [01:21:00] looks very much at the ideas as they attach to particular people, um, really is striving to understand, um, and express something about the human condition, um, in a kind of, rather grand sense.

And this kind of analytical Christian trying to break things down into their smallest pieces, um, concerned with, um, um, using language in a precise, clear way, throwing away, um, you know, not so interested in who generated a particular idea, but really just trying to avail themselves of arguments. Um, firstly, is that kind of a rare classification?

Nikhil Krishnan: Plenty of things to say on that, almost kind of too many things. I mean, one pedantic thing to say at the start is that, of course, there isn’t a thing called a The Continental Tradition, and some people would say there isn’t a thing called the Analytic Tradition either. These are all kind of

Music: invented

Nikhil Krishnan: [01:22:00] traditions.

They’re labels we apply to what were in fact diverse and disparate, internally quite differentiated activities or histories. And that is true, but it’s also true that you can draw a rough sort of line, um, in the way that you did, right? So one very crude way of drawing the line would be to say, what do you think is the most important thing for philosophy to be?

Is it important that it be clear, or do you think it’s important that it be deep? And then you’ve got all the clear philosophers on one hand and the deep philosophers on the other. Then that immediately makes you ask, well, why does it have to be one or the other, right? So very pointedly, the epigraph I chose for my book is one, uh, well, there are two philosophers I use as my epigraphs.

One is Nietzsche and the other is Bergson, Henri Bergson, a French philosopher. And it’s kind of, it was meant to be a deliberate irony that in a book that’s very, very English. Right, um, I [01:23:00] choose to start things off with quotations from Nietzsche and Baxall. So the Nietzsche quotation is, Those who know they are deep, strive for clarity.

Those who would like to seem deep to the crowd, strive for obscurity. And the Baxall quotation is, There is no philosophical idea, however deep or subtle, that cannot and should not be expressed in everyone’s language. Now, what I was trying to do there was to say that Uh, it isn’t either or, uh, and indeed, you might even think that being clear can be a way of being deep, right?

But, uh, There’s a further question now, which is what is clarity itself? And it turns out that there might be more than one way for something to be, to be clear, right? There are bits of philosophy which sort of, since it’s, uh, analytic philosophy as we’ve been calling it, which are clear But the way in which they try to make things clear is by setting everything out in, I don’t know, numbered propositions Uh, they introduce new terms of art, you know, they use abbreviations, um, [01:24:00] they set things out in formal arguments, premise one, premise two, conclusion.

Um, and sure, sometimes that can make things clear, but I think we’re all aware that sometimes those are themselves devices of obfuscation, ways of wearing the clothes of clarity, having features that clear prose has, but that actually doesn’t make things clearer at all. And that’s especially true of the formalism.

And I know this because I’ve been on the other side of it, particularly as a graduate student, and I’m trying to be all impressively analytic. And I just go about Numbering everything for no good reason. I mean, things that would actually be a lot easier to read and understand if I just wrote them out as a, uh, fluent paragraph.

But I think, oh, it looks more serious when we, um, set it out using numbers, um, bits of unnecessary logical notation to go with it. We don’t need this stuff. We don’t always need it. Right. So the question is going to be what forms, what styles best serve the end of clarity? And [01:25:00] sometimes it could be formalism, sometimes it won’t be.

Sometimes avoiding formalism could be precisely the thing we need to do. And then there’s a further question, which is, Um, just because something is clear, does that mean it can’t have other virtues? Right? And that’s where someone like, uh, Nietzsche is an especially important figure within the Continental Tradition.

Sure, there are some bits of Nietzsche which, you know, who knows what he’s on about. There are other sentences which are the most extraordinarily clear things you’ll ever read. But there’s not a single logical symbol in them. Right. It’s Nietzsche in the mood of someone writing, uh, in his aphoristic mood, he’ll come up with one of these statements and like, I don’t know, man does not strive for happiness, only the Englishman does.

You go slam, that’s such a good line, such a good line, and In it is contained a critique of a certain kind of British utilitarianism, right? Maybe the critique is right, maybe it’s wrong. Clearly that needs further discussion. But there’s something about the, what’s boiled down into that one very simple sentence with no fancy words at all.

So I think the, the [01:26:00] question we should really be asking is not analytic versus continental, but rather what kind of style. Do we want to aspire to in philosophy? And more specifically, what extent can philosophical writing be expressive, right? Not just report on, this is how things are, right? But, but also express something of one’s view of the world, what one values, what one cherishes, what one thinks is important, what ought to be salient, et cetera.

And it’s clear that all philosophical writing is doing that anyway. It’s just that the particular style that we are taught, if we’re educated in the analytic tradition, is one which says, no, the style you will be going for is one that is as, uh, un expressive as possible, right? The one that doesn’t use emotive language, that uses as few metaphors as possible.

And in general, I think that’s a virtuous tendency. It’s good for us to be taught to write like that. But every now and then, even within the analytic tradition, you’ll have writers who just Loosen the strings just a tiny bit, right? And I think it’s all the more effective in these writers. Some of them I [01:27:00] mentioned, Iris Murdoch is one, Bernard Williams is another, there’s one who doesn’t appear in the book, but is really extraordinary in this, a chap called Richard Walheim, and he’s one of these writers who will write an incredibly careful Paragraph of prose.

There’s a, um, there’s a little bit there about the nature of desire, right? So it starts with, you know, S has a desire for phi. It’s got all these kind of, um, algebraic symbols to start with. And it talks about the difference between consistency between, um, different beliefs and how all our beliefs have to kind of cohere.

But all our desires don’t have to cohere because the same demand of consistency, um, doesn’t apply to them. And then he just breaks out in this extraordinary metaphor. Our desires Each one of our desires may be seen as a little keyhole, but it is not true that once one turns the key, the door will open onto one beautiful garden.

I’m slightly misquoting. It’s slightly more elegant than that. But it brings out really effectively something about the difference between different [01:28:00] sorts of mental states, and I find it. All the more convincing because of the coherence and precision of the metaphor, right? But the fact that the metaphor itself serves the ends of clarity, and that it’s clearly been thought through a great deal, doesn’t mean it doesn’t also have the kind of power that a good piece of literary writing can have.

Right? So I think the best philosophical writers do have that kind of, uh, literary distinction on top of all the philosophical virtues they have. Now, is it something we can all achieve and we can all achieve consistently? Probably not, because that kind of thing is really, really, really hard. And it’s particularly hard if you’re a first year undergraduate, first being taught to write, uh, in a new form that’s utterly unlike anything you’ve been asked to write at school.

So of course, I, I understand why the insistence of the

As part of its training to insist on clarity and the judicious use of formalism. But I think that’s something we need slowly to break away from. Just allow ourselves just a bit more in the way of metaphor and expressiveness [01:29:00] when we think it aids, uh, what it is we’re trying to achieve, which is clarity and insight.

James Robinson: Yeah, I think that’s, that’s very nicely put. I, I, I would agree that I think one of the virtues of, um, analytic philosophy is, well, these lovely examples and illustrations that are used that, that, that, that often are just great.

indicate that a very creative mind is at work. Some of these, some of the flawed experiments that are devised are just, yeah, so ingenious. Um, and those are passed around very readily, um, and can be kind of just extracted from a work and related, you know, completely different language, but one gets the idea of the donkeys and so on.

Um, and so, But unlike in the, uh, you know, in the, I hesitate to call it Continental Tradition, because you’re absolutely right. It’s, it’s, it is [01:30:00] just the name is, uh, somewhat offensive. But, um, you know, in other ways of doing philosophy, um, you know, it might be quotes and texts that are passed around, um, which, um, I think, uh, You know, perhaps better way, you know, would permit for more of, um, yes, a little bit more liberty and, um, precision and something touching and continuous with, you know, poetry, with, uh, history to, to, to, to, to breathe through the works.

Yeah, I, I mean, maybe, I don’t know if you see any signs that, um, this is something that, that, that is happening, that if, that, that people are becoming generally a little bit looser, or is it just philosophers here and there, um, pushing, uh, testing the limits of what is acceptable?

Nikhil Krishnan: Yeah, I mean, my [01:31:00] own inclination is to say that There has never been a period of philosophy in which everyone wrote the same way, right?

There were always outliers, um, and the particular form that the expressiveness of philosophers will take will kind of depend on Where we are in the world where we are in history So what it was to be an elegant writer in the 1950s was to write like someone who’d spent the last 20 years reading a lot of Greek and Latin texts.

So, I mean, I like that style myself, but it’s only one way of being elegant, right? You, you go into the 60s, 70s in American philosophy, and they don’t have the same background at all. They haven’t been to those sorts of schools, haven’t had a classical education, but they may have had a scientific education, and some of what’s interesting about their writing is how it’s been informed by Uh, some elements of scientific style, right?

Not just bad, clunky scientific style, good scientific style. Right? And then you go on, particularly in American writing, you see people using colloquialism a great deal [01:32:00] more, right? There’s a paper by Hilary Putnam called something like Meaning Ain’t Just in the Head. And that’s a very nice way of using demotic English, like the really informal register of English for rhetorical effect, but there’s other writers, one of them, especially fond of called David Lewis.

Um, real master of English prose, not because he’s sort of flowery or florid full of metaphors that he uses a few of them every now and then. Um, but there’s something about, uh, the way in which he’s able to mix registers, go back and forth between. Sounding like someone wearing a tweed jacket and someone wearing, uh, uh, leather and smoking, uh, uh, uh, gauloise.

So, um, it’s always possible, I think, to mix things up, and people always have. And what you mix with what is partly a matter of your personal formation and the culture of your time. So, um, I generally kind of encourage it. I think your experiments with literary style can fail, uh, but that’s [01:33:00] because anything you do with writing can fail.

It can fail for argumentative reasons. It can fail for stylistic reasons. So there’s no really safe way of not failing. Um, and lots of people think that, oh, the safe thing to do is just to write boringly. Well, sure. In one sense, you won’t embarrass yourself. Another way, you will just bore the reader. And I think we should all be a little bit more courageous.

Sometimes, um, be more scared of boring people than you are of slightly embarrassing yourself. Um, and I think all writing would be better if we were less frightened of, of, uh, embarrassment.

James Robinson: Yes. So we need to hold ourselves accountable to the right way of using words, but maybe that extends to a beautiful way of using words as well.

Well, this has been, uh, yeah, a real pleasure. I don’t know if you have any kind of final comments, maybe advice for people either studying philosophy or thinking about studying philosophy about, um, that, uh, I think you’ve given a great flavor of, of, uh, [01:34:00] what it is to, uh, not only be a philosopher throughout these wonderful years of the 20th century, but you know, what the, what it involves these days as well.

But I wonder if you have anything you’d like to add.

Nikhil Krishnan: Yeah, sure. Um, I think, um, the thing I generally say, um, To people who ask about studying philosophy is there’s a there’s a there’s a bad way of thinking about philosophy where you think of it as a repository of, of wisdom, right, where you see philosophy as a simple variety of self help or therapy.

And I don’t think it’s going to be a simple variety of that, at least, right, because I think that what’s valuable about right, because I think that what’s valuable about philosophy is not the value of its conclusions, which is one reason that I slightly resist, um, a certain kind of self help book every now and then.

Just titles like, I don’t know how Aristotle can, can change your life. I kind of want to say, it’s not that he can’t [01:35:00] change your life. He absolutely can. He changed mine. But the way in which he changes lives is by involving you in an activity. And that’s the thing that helps. It’s a bit like, and maybe people do this more than they used to, but the difference between playing the video game yourself and watching someone else playing it, I mean, sure, it’s a thing you can, or perhaps more, more to the point, um, watching someone on YouTube, doing a workout and doing the workout yourself.

I think the really valuable thing comes with philosophy as with all these other examples is from doing it yourself. And sure, you can do it well, you can do it badly. And it takes a while before you’re in the position to do it well, but that’s the thing that’s really valuable. Uh, really try and make the question your own and try to answer it yourself.

And when you read texts and read works of philosophy, what you’re looking for in them is a spur to your own thoughts. You’re not looking, uh, at them as putting down some set of truths, which you can now sort of take on without really [01:36:00] understanding how they got there. I think that’s almost worse than useless.

Um, to, to treat the results of philosophy as the thing that’s most important about them. For a person intending to study it, I think it will make you better, not because it will tell you the truth about the universe, um, but it’ll be, make you better at pursuing it for yourself. So I think, um, What we want really is, is a sense of philosophy as something one does, not, and that’s something which essentially can’t be written down.

It’s only something, it’s something that only you can do for yourself.

James Robinson: Wonderful. Thank you so much, uh, Nikhil. This has been a real treat. Um, yes. That’s great. Thank you very much for having me, [01:37:00] James.

Why knowledge is not enough — Jessie Munton

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 on 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.


James Robinson: [00:00:00] Hi, Jesse Munton.

Thank you for joining me. Hi James, thanks for having me. Um, so in your book, which you have forthcoming, there’s a wonderful line where you say there is nothing so satisfying to a philosopher as offering a caricature of some set of positions, labeling it the traditional view, and then establishing that own new position as superior to this mythical view that no one holds.

 and that’s just a beautiful characterization of what I see in, in so many places, in so many papers. and I think it’s perhaps a good starting point for what we’re going to discuss today. So epistemology, it’s this word which I think only gets used in philosophy. so Maybe we want to set out the straw man for what traditionally epistemology has been most concerned with, what it is.

And then, and then we can sort of get into your program of maybe some of the lacuna and things it’s missing. Yeah.

Jessie Munton: Thanks James. Also, I wonder if it’s not too [00:01:00] much of a tangent, if I can say a little bit about like what, what epistemology is, or the oddity of this word that like you say, really only gets used in, in philosophy.

Yes. I think it’s really strange that we don’t have a non fancy term for the kind of stuff that epistemology is concerned with. So I guess I think of myself as primarily a philosopher of mind, so I’m interested in how the mind works, and then epistemology feels to me like the normative dimension of that.

So, in particular in relation to sort of when we’re processing information, so there’s kind of good ways of doing that and there’s bad ways of doing that. And actually we have loads of folk terms that we use all the time that are to do with that kind of normative evaluation. So when we call people, you know, stupid or idiotic or often what we’re saying is that they’re not very good at processing and dealing with information and they’re not doing it in ways that we want.

And then philosophers have these kinds of fancy, more technical evaluative terms, like talking in terms of whether beliefs or other attitudes are justified or whether they’re rational and then, have very detailed specifications of that. But I do think it’s curious that, everybody is familiar with the idea [00:02:00] of ethics or morality.

That’s kind of normative dimensions of behavior at large and whether they’re good or bad in some global sense. I think it’s strange that we don’t have a folk term for for epistemology. so yeah, I guess the, the hopefully not too much of a straw man in epistemology that I call traditional epistemology that I’m reacting to is a vision of it is very particularly concerned with, evaluating belief states in particular, um, and the question of whether or not they amount to knowledge, and thinking primarily in terms of kind of justification, whether beliefs are justified or not.

So it’s a way of doing epistemology that’s very oriented towards, or even sort of restricted to, states which are propositional. So they need to be truth apt, so they can be true or false, and so that we can decide if they’re justified or unjustified. And then my concern, I guess, is that leaves out huge chunks of our mental life that don’t take a form that can be readily understood in terms of a set of propositions, which may be true or [00:03:00] false, which can be justified and unjustified.

So we’ve got these kinds of philosophical terms of art, like justification, and they’ve been developed to apply specifically to propositional states for the most part. But there’s all sorts of things which are going to fall outside of that, but which Intuitively, I take to be relevant to that project of understanding how we can deal with information.

Now, of course, you might have a view of epistemology where its subject matter is by definition restricted to that stuff that it has the tools to deal with. So propositional beliefs and the question of whether things justify the question of whether things are knowledge, in which case you’re not going to see that there’s a, there’s a problem here.

So part of what I’m interested in doing, I suppose, is expanding what we conceive of as relevant to epistemology. And I think I see increasingly that I think there’s a lot of people who are interested in doing that with me. I’m in no way on my own in this project, but I think increasingly there’s a gentle divide between people who think of there’s a kind of subject matter of epistemology proper, and there’s like a very [00:04:00] specific kind of epistemic normativity.

that is not going to interact with other kinds of normativity, it’s not going to speak to them in some common language, versus people who are thinking, actually, I think there’s, there’s, no particularly good reason to restrict the epistemic in the way that it traditionally has been, and we need to develop the resources to kind of expand beyond that.

 I wonder if it’s helpful to give an example of what, like, an area where it feels like, yeah, we probably do want to go a bit more expansive than epistemology traditionally has done. Yeah,

James Robinson: sure. First let me say, I really like your definition of epistemology as the normative aspects of the philosophy of mind.

So sort of what we should do as minds, I guess, if someone had pushed me to give a definition of epistemology, I would say something like the study of knowledge. But then that’s like, well, isn’t that everything? Like, isn’t that physics? Isn’t that chemistry? Isn’t that? Yeah. Um, And so that, that really, um, [00:05:00] narrows it down a little bit.

And as you say, I think it’s not so much of a straw man, certainly in my experience. when I did a little bit of epistemology, it was introduced as, the study of knowledge. What is knowledge? Knowledge is true. Justified beliefs. And then, as you say, there’s quite a lot of focus on, well, are things truth apt or not?

Are they even candidates for truth? Or are they things like, I don’t know, is Trump an idiot? Is that something that can be true or false? Or is it just like an opinion that doesn’t have that kind of status or can’t have that kind of status? and then secondly, what is this justification point? And again, massive can of worms, which, Arguably, maybe too much time has been spent on, maybe not, but there’s certainly other interesting questions, uh, to look at.

 So yeah, I, I really love that definition, but yeah, perhaps, yeah, give some, yeah, maybe give, give some color to that. What, what, what are the kind of questions that come

Jessie Munton: up? So, so, so actually you just saying then that view of [00:06:00] epistemology as a study of knowledge, which I think is quite, is quite widespread and would be a common way of, of defining it.

So, I mean, here’s a couple of things that you, that I think that’s never seemed terribly intuitive to me. So there’s this influential strand of epistemology called knowledge first epistemology, which, um, I think it’s been very productive and very helpful in some respects, but I think I’ve never found very natural, the view that epistemology or that what we’re geared towards doing is primarily oriented around knowledge.

So here’s like a couple of phenomena, which you might think are really important that escape that. So one is understanding. So I think with a lot of people, I think of understanding as a state that’s maybe richer than knowledge. So you can kind of know stuff without really deeply understanding a subject matter.

 and so intuitively there’s a bit more going on when you understand something than just knowing a list or a set of propositions about that particular subject matter. It’s something to do with kind of grasping how those fit together or grasping a set of explanatory relations that hold between them.

And [00:07:00] then of course there is a project, amongst kind of knowledge firsters where they want to understand understanding in terms of knowledge states. So they’ll just say yeah, sure there’s more to it, but it’s just special kinds of knowledge states. So it’s knowledge states that relate these other propositions to one another.

 whereas I think I’d prefer to say that we can get a more natural and a more adequate account of what understanding is, if we let ourselves free from the commitment to doing everything in terms of knowledge states and say maybe there’s something to my mind distinctively structural. We’ve actually, we’ve got a PhD student here at Cambridge, Adham Al Shazly, who’s working on an account of understanding as involving a particular kind of structure to the knowledge states that you have that I’m very sympathetic to.

Another phenomenon that I think influences me a lot is I just think often we’re nowhere near gaining knowledge insofar as knowledge is like, it’s a really high epistemic standard. So loads of the time what we’re grappling with is uncertainty and how we manage uncertainty. And the Knowledge First program is going to say, yeah, of [00:08:00] course, that’s completely true, but the right ways of dealing with uncertainty are all going to be understood in terms of our ability to gain knowledge.

 maybe that’s right, but I tend to think that we might kind of free ourselves up a bit here if we don’t always have knowledge as the key goal state, or if we think of this project a bit more expansively as just not always involving the study of knowledge per se. So the kinds of things which motivate me to want to go beyond the traditional paradigm that’s oriented towards kind of belief states and propositional states in particular, are things like, I think the gathering of evidence is a really good example here.

So one way of thinking about whether or not a belief is justified, which I think’s very, very plausible says that it’s justified if it’s like a portion to your evidence in the right way. So I think that fits with how we ordinarily evaluate people around us all the time. So, if your friend has a load of information about how it would be sensible for their child to be vaccinated and then they maintain a belief that it would be unwise for their child to be vaccinated.

In the face of that contrary evidence, you feel like, look, [00:09:00] I’m not sure you’re really, this isn’t really a rational belief. You’re not thinking sensibly about this. So that insight seems absolutely right. But then there’s this extra bit to the picture, which is, where have you got your evidence from? Or have you gone about?

Gathering your evidence and typically evidentialists have not wanted to engage very much with that part of the picture So they’ve kind of wanted to draw a line that says look you’ve got a body of evidence Now, what is it rational and sensible to do in the face of that? And then that’s going to determine whether or not your belief is justified But of course, there are all sorts of terrible ways of gathering evidence that are going to get you some set of evidence That is extremely skewed or partial.

So if your friend has only gathered evidence about vaccination by um talking to somebody that they met in the bakery or something, then that’s not like a great basis on which to go and form the belief. And so their belief might be perfectly proportioned to the evidence they have, but if they haven’t gone about gathering that evidence in a sensible way, then it doesn’t seem like we should think that their normative status is tickety boo.

 but once we get into the business of evaluating, like, how you gather evidence or what evidence you should have, that’s [00:10:00] like an enormous question that traditional epistemology just doesn’t at the moment have. Lots of resources to deal with

James Robinson: This is really an important point. And it, it makes me think of Bayesianists. This seems very, popular now, particularly in kind of, , the rationalist and affective altruism community that That people kind of term themselves a Bayesian and, that’s great, but what you point out is that you can be a Bayesian and update your beliefs, but if you’re going out and looking for the in the wrong sources of evidence, you can still go down some rabbit hole and probably end up with a horribly skewed set of beliefs.

The other thing that I’m just reminded of is,, Paulina Sliwa, previous guest, I think seems to share this view that just getting to knowledge states, there’s more to our epistemic behavior than that. And, and so she talks about, , you know, moral, inquiry, As a process of moving through different [00:11:00] perspectives, and a perspective is something richer than just a set of propositional beliefs, as I understand correctly, it gives you this kind of set of options, points out what are the ways that you can proceed, um, so she has this example of someone who’s been, who’s been raped, but doesn’t think of it as rape initially.

 and then in coming, going through a process and moving through different perspectives, she ends up with the, um, Not only a different set of propositional beliefs about that, but a very different framework for looking at lots of things and for thinking about what to do next, I suppose. , so yeah, I, yeah, I think I, I agree that just trying to, just trying to hold onto this picture of epistemology as, as coming up with a set of true beliefs firstly misses out on the richness of the end point, but it doesn’t explain either.

currently how we, how we [00:12:00] choose or how we get to develop beliefs.

Jessie Munton: Yeah, yeah, I think that’s right. I’m very sympathetic to how Paulina’s thinking about, about those things in terms of kind of perspectives. I think it’s interesting that Liz Camp as well has some very influential work. I think Paulina’s partly influenced by as well of, thinking in terms of.

a kind of perspective or a frame on a particular question and how that might both guide your inquiry and then also itself be a kind of, epistemic goal state to be in the right version of that.

James Robinson: So yeah, What are we aiming for then? Is it, if it’s not propositional, what is the object of study, perhaps better put, if it’s not a set of propositions that we’re trying to evaluate, is it something like Elizabeth Camp or as Paulina’s drawn on?

that work, perspectives or frames, right? Are these the sort of things that epistemologists should be thinking about?, or are there some other ways of kind of assessing the set of beliefs that we have?

Jessie Munton: Yeah, it’s a really [00:13:00] good question. I’m not sure I have a, complete or straightforward answer to it at this stage.

I suspect that my ultimate answer would be kind of pluralist, that I suspect there might be multiple epistemic goods and goal states that sit alongside one another and that don’t always talk to each other. entirely coherently. and actually, I guess I probably hold something like a similar view about ethics.

 but my ethical views are underdeveloped, so we won’t go into those. But so, I mean, one thing I think is important, and this might sound a bit at odds with some of the stuff I was saying, but I think the resolution of uncertainty is key, whether or not we think of that as amounting to knowledge or not.

So I do think that sort of just in virtue of being an epistemic agent and kind of standing within this rational space, you have a standing investment in sort of understanding where you are located in possible space and narrowing that down as far as possible. And actually, so that sounds like quite a kind of reductive element in our epistemology, but I think it can make sense of quite a lot of things.

So for [00:14:00] instance, why should you pursue one inquiry rather than another? I mean, I think that’s going to depend on lots and lots of normative factors, not all of which are even epistemic. But I think a significant part of it, from an epistemic point of view, is that you want to pursue the inquiries which are most efficiently going to locate you in logical space.

So in general you want to zone in on these big questions which are going to get to the heart of something. So I think part of what we care about is sort of inquiries that kind of fasten on to, to big joints that are going to efficiently narrow down the, the options around you. I think that’s part of it.

But I also think that you could potentially have somebody who’s perfectly located in themselves in logical space and knows exactly how things are and they’re still going to be perhaps, Ways in which we could evaluate agents who’ve reached that state against one another and think one of them is better than the other.

So, yeah, there might in addition be things we want in terms of, an appreciation of the [00:15:00] significance of some information over other information, or even just a kind of prioritization of information that’s going to be, more significant or more important than other information. And what that idea of significance or importance is, again, like, do we want that to be purely epistemic, or do we want it to be something that overflows the epistemic to reflect the kinds of broader practical or ethical concerns we have.

Probably the latter, I think, and that means it’s going to be very context sensitive., so, yes, I don’t know how satisfying that answer is. No, I think

James Robinson: that gives colour on a couple of points. I mean, firstly, this idea of,

if propositions are, equally weighted, it doesn’t give us any clue to Why people seem to set fixate on certain things or, or, why of all the billions of propositions that we, , we believe presumably in our daily lives, only some of them occur to us., So I guess traditional epistemology again, bit of a straw man, [00:16:00] but it.

It doesn’t really tell us about what people do with their beliefs or think about how beliefs are prioritized in their, in their minds.

Jessie Munton: That’s interesting. And I think, I mean, one thing I might want to add as well is we maybe don’t just want to think of, um, beliefs necessarily in this way, but also maybe states that we’re not quite sure if they’re beliefs or not, or states which definitely don’t seem to be beliefs or not. So as well as forming beliefs about the world, I don’t know, you might have,.

suspicions and background hunches and worries and anxieties and things like that, which aren’t exactly beliefs, but they’re sort of in the mix. You might also have desires. You might have a kind of effective state. So, sometimes I think we perseverate on particular beliefs, either because, or like bits of information, because.

 perhaps they make us feel a bit anxious or otherwise maybe we perseverate on them because actually they soothe that anxiety. So the, the, role of kind of the valence of these attitudes is interesting because I think positive and negative valence can cause us to kind of [00:17:00] perseverate more on particular beliefs.

And it feels like there might be ways in which sometimes that’s sometimes you, you want certain beliefs to kind of loom large because they are Explanatorily very important and significant other times you don’t because the influences that are causing them to do that don’t seem like they’re the right kind of influence but it’s a job I think to tease apart like when it’s appropriate for something to kind of loom large and when it’s not.

And again, it might be that if something makes you anxious from a practical perspective, it is appropriate that it would be at the forefront of your mind, but from an epistemic perspective, it might be kind of dominating in a way that’s that’s illegitimate. So I guess part I think you’re absolutely right that this.

This question of like, what do we do with the states that we have, be they beliefs or something else is, is really important and something that again, like epistemology hasn’t said loads about. And maybe some of my interest in that comes from thinking a bit about, um, sort of philosophy of psychiatry. And often I think some of the conditions that psychiatry is interested in.

Involve difficulties that arise in people’s lives [00:18:00] because they are not kind of managing the Informational states they have in the ways that the majority of the population do or they’re doing it in ways that cause particular problems For them and so from in my mind that again this is kind of where the philosophy of mind and the epistemology link up is that we need kind of norms that can do justice to Those kinds of phenomena and help us pinpoint the ways in which things might be going wrong.

Yeah, I was

James Robinson: thinking of, Uh, Mr. Dick in David Copperfield, who has this fixation on the, the head of King Charles, I think. So, he’s always trying to write his memoirs and this guy just, you know,

Jessie Munton: King Charles

James Robinson: keeps on popping up and he can’t stop thinking about him. and his kind of, well, you know, King Charles was beheaded.

So the head is, this kind of gruesome object in, in Mr. Dick’s mind, I guess. , And yeah, this is probably something where Mr. Dick’s beliefs about King Charles may all be on the money, right? And all [00:19:00] his beliefs in general can be on the money, but there’s something wrong, right? There’s something pathological, that’s going on.

And to a lesser extent, we all have these kind of mini pathologies, like things that we, we, we care about too much or care about too little. even though, again, many other beliefs may be correct. , We. Yeah, we might give undue attention to certain ones. , and, and you have this kind of nice way of, I guess, codifying this in, in terms of salience structures.

 so perhaps you can kind of take us through what, what that concept is like and how it can arrange all our beliefs and maybe some of these other things as well, hunches and, and, and so on.

Jessie Munton: Yeah, yeah, I feel like I should be better at giving a succinct explanation of salient structures at this point than I, than I probably yet am.

But, but the kind of idea is you’ve got an individual and they’re located within what I think of as a kind of informational landscape. So there’s all sorts of things that they could, um, attend to at any given moment, and attention is really key to this. Attention is very minimal, so it’s not some [00:20:00] very psychologically involved account of attention, it’s just the idea that when you attend to a bit of information, you um, give over your kind of mental focus to it at that moment in a way that then allows you to process it further or to do other things on the basis of it.

So this informational landscape, some of the stuff that’s in it is kind of internal to the mind of the individual. So it might be exactly like memories that you have or beliefs that you’ve already formed because you’ve encountered certain information in the past. Some of it is is external. So, you know, the kind of books that are in a room that you’re in, you could attend to them by visually looking at them at a particular moment.

Or, you know, if you imagine that you’re in a cafe and there’s a conversation going on around you and there’s another one at the other table, you can kind of tune in and out of different conversations and that’s you attending to one conversation. You can then use that information versus you kind of attending to another one.

So I think of all the like uncountably many things an individual could attend to at any one given moment as attendabilia. We can just So just a term to refer to them all and then the idea is that we could sort of imagine This individual is like a [00:21:00] node in a network and there are going to be sort of links so many links But each of those links is weighted in a way that reflects the probability that the individual will attend to that particular bit of information next and then as you attend to that it’s going to kind of shift and this network of items that you could attend to is going to depend on the particular context you’re in, it’s going to depend on the task that you have at a given moment, so it shifts a lot depending on context, but still we can generalize in ways that abstract over perhaps longer time periods over which you have attended to particular items.

And what we can get out of this, so this is what a salient structure is, is a kind of, It really, I think it’s best understood as a kind of model of the mind and the things it can attend to as a kind of network and then some significant aspects of the mind and how it operates are going to emerge at the level of the topology of that network.

So, for instance I really like your David Copperfield example. , so. For that individual, that, that head is [00:22:00] becoming a very dominant node in this network. That it doesn’t matter what task they’ve got or what context they’re in, their mind is continually kind rerouting through that. And then that lets us describe the ways in which sometimes that might be appropriate.

Maybe that is Helpfully allowing them to act in the world. Maybe it’s helping them resolve uncertainty. But sometimes you can get this kind of calcification into structures that are organized around a particular topic or particular preoccupation that are not helping you do that. And I think you’re absolutely right that this is all on a kind of continuum.

Like we’re all doing some of this all the time. So In the book as well I use the example of my oldest son who’s like very preoccupied with football at the moment and like so many topics of conversation come back to football so if you’re talking about countries like his knowledge of countries is really organized around his knowledge of football and that’s kind of harmless enough but there probably are ways in which it’s blocking him from accessing new information that might be rewarding and along various axes to him.

 and then, you know, maybe you’ve got relatives in your life as well who might have, you know, particular beliefs that they really perseverate on. so I think [00:23:00] this could be quite a powerful way of thinking about., sort of the mind in a way that that frees us a little bit from that propositional bias that I was talking about before, because it could be that all of an individual’s beliefs are perfectly accurate, but the problem is just that they’re really perseverating on a small subset of them.

or, you know, you could have agents who score equally in terms of how much knowledge do you have about the world, but one of them has a salient structure that feels like it’s organized in a way that lets them kind of function better, lets them function better as an inquirer as well, and as somebody who wants to learn new stuff about the world, and the other one has a salient structure which isn’t really letting them do that., and so it’s putting, it’s sort of shifting our focus a bit to kind of the, the organization of information., and, and it’s very, it allows that that can arise from a huge number of factors. So some of them might be again, like factors that are internal to the individual, but some of them are just going to be the social context that you’re located in and the ways in which that kind of compels you to attend to some information.

So adverts are a really obvious example of that. Like you don’t have a choice about what adverts are [00:24:00] in your environment as you walk down the street, but that’s going to change what you’re attending to simply because it’s, Giving you stuff to attend to right there. And often it’s doing it in a way that’s deliberately designed to capture your attention with, you know, bright colors and pictures of attractive people.

Yeah, I,

James Robinson: I think that is a wonderful succinct, explanation of what a salience structure is, , or as succinct as, as one can give. , yeah, let me read back some things to make sure that,. I’ve got it correct. So, it, it kind of encodes the accessibility of, of information to us. And that involves both, the physical world and one’s internal world, and even the, the social world, which is maybe some mixture of internal and physical worlds.

 So it’s a quite a, quite a complicated thing, but I think that’s justified because the information that I’m accessing right now is some. Yeah. Influenced by so many things that my computer’s right in front of me. I’ve got my headphones on. I’m listening to you, but there’s the sky outside and I have all sorts of, you know, beliefs and memories about, that and, and about the [00:25:00] objects in my room, which are based on my past history and, and, and, and so forth.

So my dispositions to attend to, or be distracted by, or focus on certain things, however we want to determine it have lots of complex, determinants., And I want to make sure I really understand what the structure is. Is it, so I am sort of located at a node in the structure.

I’m at a point where all these beliefs can sort of, uh, connect to me or, not necessarily beliefs, but just things that can grab my attention, come on my attention, , as if I start to think about something, for example, if I start to look at the sky now, does that move where I am in the structure?

 or does it indeed change the structure , is the structure something that’s kind of relatively. [00:26:00] stable moment to moment. .

Jessie Munton: Yeah, then that’s an excellent question. And it’s one of the things I think I’ve most struggled with is that, um, intuitively, What you’re likely to attend to at any given moment is in so much flux that it feels like it’s hard to identify something that we could call a sort of stable structure behind it.

So the, the, like, specification I give at the moment is I’m thinking of it in terms of a function from tasks and contexts, so a set of attendabilia and, probabilities that you’ll attend to other, To those attend Belia so that the the weighting of the links between the nodes matters a lot because the nodes the links are so There are so many of them that on their own whether or not you’ve got a link doesn’t tell you very much because you can Move in so many directions so then, as you attend to something new, we can think, I think, as long as the task and the context stay relatively stable, if the salient structure is [00:27:00] staying roughly the same.

One thing I think I want to say is that, I mean, , you have changes in what you’re liable to attend to at any given moment. Not all of those then translate up to a change in the salient structure. So a change in the salient structure, I think we want to reflect something that’s like a bit bigger than that.

 something that’s like a bit more entrenched or that emerges over time and in some way or other. So we need to build in like the ability for, you know, what you’re likely to attend to is shifting all the time. But like what we consider the salient structure is an abstraction from that in a way that not every difference in the probability that you attend to something is then automatically going to translate to a change in the salient structure.

James Robinson: Yeah, that makes sense. And I think it one of the examples you give in your book is of Subway transport systems. So like the tube in London, and they are topological structures. Whenever you look at a tube map, it doesn’t give you the distances, but it just shows you how different stations are [00:28:00] connected.

And this is something like, yeah, a kind of a slice of a salient structure in time where. If you’re at one station, you know, you’re attending to something, it makes it easier to attend to other things. So I suppose we can think of the salient structure as not just encoding exactly what one is able to attend to at.

You know, a certain point, but it gives some idea of as the, as the user’s attention wonders, how that will change what they’re likely to attend to next. Just as with the tube, if you’re at , King’s cross, it’s very easy to get a angel., and if you’re an angel, you, you know it’s somewhat easier to get to, I don’t know, Finsbury park or something. So yeah, your, your point in that structure gives some clues as to what the likely next places that you might end up on.

Jessie Munton: Yeah, that’s exactly right. And then the tube is a [00:29:00] much easier example to work with because it’s very stable because it relies very strongly on this particular physical structure on DeLarga, which is we have to build tube tracks and then we get physical trains and we put them on the tracks and off they go.

And so then the kind of options are very limited compared with your mind and what your mind can do. But we can imagine sort of thinking of a transport network that scales up from that, that doesn’t just include the tube but maybe it’s also including buses and then maybe it’s also including kind of cars and it’s also including individuals and their ability to walk to different places.

So now we’ve got like loads of different factors in the mix that are going to determine how accessible different locations are in the city to different individuals. But we can kind of abstract over all of them and then still say some things about how easy it is for a person to get from x to y. Given this like very complex structure, which is emerging from multiple causes.

So I guess that would be closer to the case of the mind because you’ve got this like multiplicity of causes and you’ve got a lot of flexibility and shiftiness in there, and you don’t just have sort of one physical structure [00:30:00] that is determining what these accessibility relations are.

James Robinson: One of the things I like about salient structures, is that it, it allows you to think it allows you to bring to bear some of the machinery from, network science.

So my objection is to say, well, salient structures are nice things, but why, you know, what do they offer me in terms of. Thinking in terms of perspectives or frames, right? there’s some stuff that’s foregrounded and, and so on. Why do I care about thinking about links between things?

But when I actually think about in terms of links and nodes. We can draw on this, this, this fairly rich, set of, findings within network science. ,So yeah, perhaps kind of give us some ideas of, of the

Jessie Munton: utility of that. Yeah. And I think we have to be, we have to be like cautious here.

So, in a way, networks are really, really cheap. All you need for something to be a network is that you have nodes and you have some kind of. relationship between them. And so, I mean, we can treat almost anything as a network. And then the question [00:31:00] is, what usefulness do we get out of doing that? Or like, what, what are we gaining through thinking in those terms?

For me, a big thing that we gain is that we can think then more structurally about the mind. Like I was saying, we can think in terms of the sort of topology and how that might matter. And so maybe a good example for for my purposes for this is to think about prejudice and the different forms of prejudice can take and how I think thinking in terms of a network might help us capture some of those nuances and differences.

So there’s an extensive debate in philosophy around like what prejudice is and what it takes to be prejudiced. And there are important ingredients in the mix here that aren’t the primary focus of my concern there. So you might think you have to really dislike people in order to be prejudiced against them, or you might think you have to behave in certain ways.

But there’s also, accounts that say, well, the key thing about prejudice is you hold certain beliefs about the group against which you’re prejudiced that are kind of nice beliefs to hold, their content is like negative content. But I think just thinking about that kind of what’s the, what’s the mental [00:32:00] attitude you have to have, that side of the picture, I think there’s lots more sorts of mental attitude that can count as a form of prejudice that don’t necessarily involve kind of explicit negatively valence beliefs.

So, Or, or that do, but we might want distinctions between that. So here’s your kind of classic case would be you’ve got a negatively valence belief. Not only that, but it’s also a kind of, it’s serving as a big hub in your network, so that lots of traffic gets routed through it in the way that we were saying might happen with the David Copperfield example or the football example.

So it’s important that it’s not just that you hold this belief, but that it’s become this kind of important pivots in how you’re thinking about the world or how you’re interpreting new information or how you’re deciding what other information to search for. Like lots of stuff is being kind of rooted through this really core belief at the other side.

We can imagine a situation in which it’s not actually that you hold. negatively valence beliefs about the group in question, but it might just be that, um, kind of [00:33:00] not obviously negatively valence or maybe even positively valence beliefs also have that role of being a kind of hub or a sort of connector of some kind.

So, if you just think it’s so wonderful that women have these caregiving abilities and that, you know, when your colleague is pregnant, you are just. I think that’s just brilliant and that’s like the main thing about your colleague at the moment is that they’re pregnant So that’s kind of when you’re thinking about your colleague That’s become this sort of hub that lots of stuff is being routed through again That’s a problem because in a work context your colleague doesn’t just want you attending to their pregnancy They want you to attend to what they’re up to at work and these other professional concerns that they might have Another way we could think that prejudice might arise might not even be that there’s like some one particular belief that things are organized around, but that, when we step back and we look at these structures of accessibility and how you’re inclined to move between particular beliefs.

Race or gender or whatever category it is ends up looking like a kind of organizing principle in [00:34:00] how you are attending to other things. and so that’s very broad and it might take a lot of different forms, but again, it’s like a something that might look like a form of prejudice, but that doesn’t necessarily involve you having some explicit propositional belief of the right kind.

 Yeah, I think

James Robinson: that’s, those are all really wonderful examples. So the colleague example, one might have lots of true beliefs that, one’s colleague is very good at their job and, um, they did a great, did some great work on this last project, but if just. You fixate on, oh, they’re such a great mom, right?

There, there’s a kind of prejudice in, encoded there. and then, yeah, similarly, if I, I suppose if, as you say, if we organize our beliefs along, racial lines, um, Yeah, we miss out on so much of the nuances of other people if we’re just thinking of them. Oh yeah, they’re, they’re from [00:35:00] this culture and they, you know, I know lots of things about this culture and I’m going to foreground all my knowledge of that when I go and talk to them and I’m not really going to care about their individual, cares and preoccupations.

 I may be on point on all of those things in terms of having only being correct in my knowledge, um, but just the way that I’ve organized it, , leads me astray. , and you’ve mentioned here, yeah, the idea of hubs, which is kind of bringing in some of this, yeah, machinery from, from, from network science.

 One of the points that I enjoyed in your book was you pointed out that we don’t want, we don’t want a kind of completely random, salience structure and that that’s, you know, we understand what randomness looks like in, in, in, in network science. You just kind of have every node connected to other.

Every other completely kind of fairly randomly. And sometimes one meets people who have that, seem to have a bit more of that structure. They will just kind of make these really wonderful random jumps. And actually that [00:36:00] can be a really useful thing in society. I kind of feel like maybe that’s a kind of creative trait.

 but then there’s people who have, you know, very, very focused areas of knowledge. And, uh, when they think about, uh, I don’t know, cars or something, they. They just think about the machinery of it and the mechanics and how it all works, which actually might be kind of too structured, right? They might need more links between that hub and other things.

They might need to care about, I don’t know, the environmental effects of cars, for instance. so you need some kind of balance between having, , very concentrated, isolated, nodes, but also having connections between all your different areas of knowledge and yet not too many connections that everything becomes entirely random.

And there is this kind of notion of small world networks, which one can think of, you know, probably the hubs and spokes models of, of, airports is maybe a good example [00:37:00] where, kind of a regional airport will collect, connect to, um, a hub. So, the East Midlands Airport will connect to Heathrow and so forth and a few others, but it’s not going to fly you to Boston or New York.

 but then you can go through these big hubs, which will take you all across all the way across the Atlantic, and then you’re kind of into a new area of the, of the network where you can take lots of, short hops if you want to. so yeah, I think that, by the way, I love your comment that we need to be careful about applying network science to everything.

, but I, I think that it is, it is useful here. , I don’t know if there’s any kind of more. Mathematical that we can get with it or, or, or, or if just this kind of level of analogy is, is useful enough.

Jessie Munton: Yeah. Like, um, sorry, there’s lots of things I would say in response to what you’re saying, uh, yeah, so, so the small world network, I think it’s really helpful to bring that up.

So a big thing that I think, I mean, the [00:38:00] normative framework that I’m then applying to salient structures, we kind of want two things out of it. One is that you want. information that is relevant to be readily available. And I have a particular kind of epistemic understanding of what relevance is. And the other thing you want is flexibility.

So you don’t just want, like you’re saying, you don’t just want information that’s relevant to one problem. You need to be able to move between that. And the key thing about small world networks is they tend to combine some of those virtues. So you can move easily between kind of centers of information about a particular topic.

I think, I think another good example of small world networks is like. University towns, I think, definitely have this structure. So, within the university, they’re very, very, there’s a lot of very dense connections there, so everybody knows everybody else. Within, uh, in Cambridge, within Addenbrookes Hospital, there’s a lot of connections there.

Everybody knows everybody else. And then you don’t need to have very many people at the university who know somebody at the hospital in order for you to be able to quite easily connect any given individual with, at the hospital, with any given individual at the university. You know, you can add in some schools and you’ve got a kind of a [00:39:00] particular structure of a community there.

 yeah, in terms of getting, mathematically precise, so I feel at the moment like I want to set up a kind of bear trap outside the math department and wait for somebody who does a lot of network science to come by and fall into it and then I can take them away and bully them into, helping me do some of this stuff in like more mathematically precise ways.

One thing in particular that I want to make sense of a bit more at the moment is like how do networks aggregate across individuals to produce social salient structures? And that’s something that I would really appreciate a network scientist helping me. out with. so I’ve been thinking recently about, um, ignorance and forgetting, and I’m wondering about the ways in which ignorance and forgetting at the individual level scale up in such a way that we could talk meaningfully about a social group forgetting something.

I think we can do some of the work we want to at the individual level, some of it, not all of it, in terms of salient structures. And I’m wondering if we can talk more meaningfully about group salient structures. But for that, I think I do need to get more into the nitty gritty of the, of [00:40:00] the maths of the network science.

James Robinson: My last conversation was with Geoffrey West, who is a physicist who look, who’s, who’s looked at the importance of, of networks in terms of, firstly in terms of biology, but then in terms of cities, companies and other kinds of emergent entities.

And he, and he has like a managed to mathematize it really well with his, his colleagues., and actually leads me to. A slightly tangential question. One of his findings is that in cities the kind of pace of life increases and it’s actually really, it’s incredibly consistent how across a large range of features it increases in the same way.

So for example, the number of patents per head, uh, doesn’t just. Double if you double the size of a population, if you double the size of population of a city, it goes up by, uh, 2. 15. So you get this kind of additional 15 percent for free. [00:41:00] Uh, and the same with a number of restaurants, right? You don’t just get, um, more restaurants as you get, as you, as you double the size.

 you get more restaurants per head by 15 percent and so on. And so as you scale up cities, double and double and double again, you get these massive, kind of benefits in certain senses. You also get, problems. You get more crime per head. You get more, um, AIDS cases, probably more COVID cases,, at least a faster rate of them. And where this all leads me, one of the places it led me to thinking was, all these You sometimes just seem to suggest that salience might be a kind of zero sum game, which makes sense, right? If something is more salient to me, then it’s got to be drawing away my attention from something else.

But I also wonder, thinking of Geoffrey West’s work, if, if actually the sort of, um, The amount of salience itself can scale as well. Like in a city, if I’m in Times [00:42:00] Square, I’m getting so much stimulation. Whereas if I’m just sitting in, I don’t know, an empty room at home, I, I may actually think about fewer things.

 there may be, yeah, just less for me to attend to. and I, I don’t know if that’s something that you, you, you thought at all.

Jessie Munton: That’s really interesting. Yeah. I guess one way of reflecting that might be I mean, so I think I, I do think that salience is a kind of nil sum game that any that, well, it’s attention that really is like attention to one thing comes at the cost of attention to another thing.

but there might be ways of still accommodating how it can seem as though in some cases. Your attention is spread over a wider variety of things, or, um, Yeah, that’s interesting the idea you might just have more of it in some situations. I mean, I guess having just more of it is compatible [00:43:00] with it still being kind of a nil some thing.

 you just have a larger quantity to distribute over the different things, but attention to one thing is still coming at the cost of attention to another thing. Um, but another thing we might want to include in here is maybe it matters. Um, Not just what you are attending to but what you’re kind of likely to attend to so you might think that attention Cut or salience at least certainly comes in degrees And you might think that sort of attention can do something similar.

So this is like a debate within people who work on um sort of attention within cognitive sciences, is it just like there is attention and there is not attention or can you also be doing something that’s like a bit of attending at any given moment, in which case maybe you could spread that bit of attending over multiple different stimuli, uh, in a way that kind of reflected a little bit what Perhaps you have in mind?

Another thing that might be happening in these very, like, informationally dense environments is just that we are switching our attention an awful lot. So at any given moment, we’re just switching between attending to these different stimuli. And then that creates a kind of effect where we [00:44:00] feel like, I mean, we are, in some sense, attending to a lot of things, but in a less sustained, a more fragmented way.

James Robinson: It’s one of the things. That probably illustrates why this is going to be so tricky to, to actually cast in mathematical terms. But I, I really like your idea of casting a bear trap, um, as I think for the right person, this would be a fascinating problem, but yeah, these networks seem so dense and, you know, possibly dynamic.

Um, and so there’s this kind of interaction with how long you attend to something as well. Um, Which, yeah, so they’re kind of, that might have some effect in terms of like how, what I’m trying to think is like how you could connect this to kind of outcomes in, in, in the real world. Like, um, you know, could you, you can certainly look at [00:45:00] the physical repositories of knowledge, like libraries and stuff, and, and even some of the kind of virtual ones, like the internet and so forth.

Like those things, you should be able to get some kind of model of how their structures much, much harder, obviously, to do the internal models. Um, but even those external models, like, I guess the problem is the external models kind of mean nothing unless you have, unless you mix in these internal models, because you know, one can go into a library and just ignore all the books and focus on the tables, right.

Or, you know, um, so yeah, it’s, yeah, it’s a really, it’s a really intriguing. And, uh, and tricky problem, I think.

Jessie Munton: Um, yeah, I think that’s right. And sometimes we might want to draw, um, so for the most part, I’ve just been amalgamating all the different causes that trigger your attention to go in one direction or another together.

But for certain purposes, we might want to separate those out. So you could have two people who just never, ever read, um, books by. Africana [00:46:00] philosophers, and in one case that might just be because there aren’t any in the library, and in the other it might be because there’s loads in the library, but they just don’t care, they’re not interested.

Those seem like significantly different states, and so for certain purposes we might want to say, what’s the subset of causes here, like is this something that’s Due to an environmental restriction that in some sense, we don’t want to include those nodes in the network. Um, or is it due to something that seems like it’s coming from some kind of internal motivation?

I think, I think there’s going to be all sorts of distinctions like that, which matter for various purposes, which aren’t immediately reflected just in the salient structure itself. Yeah,

James Robinson: I think that brings up an interesting question, which I know you’ve looked at, which is, you know, Well, to, to what extent we can change these salient structures, you know, particularly if, if one’s beliefs can all be correct and, and, and yet one’s still biased because perhaps, you know, it could just be simple, as simple as, uh, as your Africana suggestion, uh, or example suggests, it could be as simple as one having zero interest [00:47:00] in a particular cultural, um, group or, um, gender even, right?

Um, and Yeah, like, how do we, what do we say

Jessie Munton: about that? Yeah, it’s a good question, because a lot of this stuff feels like it’s very involuntary. And there’s a tension, I think, too, between recognizing the role that you know, social context play in determining what you attend to and then wanting the individual to take responsibility for some aspects of their salient structure, because you can’t control your physical and social environment always.

so in terms of how we change things, I mean, I, I think it, there is some stuff I think that the individual can do that you can try and become a bit more aware of how your attention goes and what you’re attending to. You can also be more, Mindful of what kinds of, um, material you’re kind of exposing yourself to and the ways in which that’s influencing how you’re then attending to people.

[00:48:00] So, um, You know, I grew up in an age where there were lots of magazines that had information about celebrities in where they’d like literally be kind of circling women’s cellulite in them. That’s definitely going to influence your salient structure. It’s going to influence how you attend to your own body and it’s going to influence how you attend to other people’s bodies.

So there’s probably a good reason to avoid exposing yourself to too much stuff of that sort. I mean, there’s probably lots of reasons to avoid it. But one reason is it is going to influence your salient structure and you can take some kind of responsibility for that. I think there is like lots of stuff that you can do at a broader social level that would influence people’s salient structures for good or for bad.

Um, I was really interested, you know, having come through well over half a decade now of reading a lot of children’s books. You can really see in that how we encourage certain patterns of salience by drawing children’s attention to certain basic aspects of families and how they’re set up. Children’s books are like massively, massively heteronormative.

Um, And also like in the kinds of [00:49:00] gender roles that are assigned to women and to men and lots of the books that you come across and, um, I think there’s lots of room to kind of be a bit more conscious about, you know, you might not think it’s something you’re explicitly telling a child, but you’re setting up a structure of kind of anticipations that they’re going to have when they encounter families in the real world when they encounter people in the real world and sorts of things that they do.

And it’s tricky because some of that stuff just just reflect. you know, true generalizations about how the world currently is. Some of it I think goes kind of beyond that, um, into, um, setting up these kinds of like very basic expectations or sort of sense of this being a fundamental kind of structure in the world.

I think there’s stuff to be done. to be done there. I also think it’s maybe something to think about when we are doing implicit bias training is it’s maybe helpful to talk explicitly in terms of salience and what’s going on at that level. Um, and also when it comes to thinking about what’s a [00:50:00] responsible way of communicating with statistics.

So your statistic might be accurate, but what What impact is it going to have beyond the accuracy of the statistics? And what stuff are you making salient by pulling out a particular statistic in a particular context? Um, there’s something that you need to be thinking about when you’re thinking about am I using this statistic?


James Robinson: Yeah, I think those are, those are lovely. Those are lovely examples. Um, I find it kind of ironic. This is the second, um, video. podcast that I’ve, I’ve, um, recorded. I mean, probably a lot of people will be listening to this just through headphones and not watching it. But, um, you know, one of the reasons I’ve decided to add video is just that, you know, it’s such a, people love YouTube.

It’s such a good way of finding podcasts. I kind of, in some ways, I like the purity of just speech. Because it’s removing some of that salience. Like you were saying, like, you know, the, the human body [00:51:00] is like a massive object of attention for every human. And, um, we just don’t seem to be able to get around that even often when we want to, right.

Even if we just want to listen to ideas, like we like to look at faces and. Uh, and you know, maybe that’s not a terrible thing, like the face does express some meaning, but I think it can often be a distraction. I’ve got thinking recently about on the augmented reality.

So we have the Apple vision pro, which is, you know, could be used to reinforce salient structures to, To calcify them, to use a term that you, you so aptly earlier. So for example, if someone’s really into football, like your son, right, he could just, he could wear an Apple vision pro and it could sort of football ify everything for him, right?

It could repaint the walls in Chelsea’s colors. He could, graft your, uh, you know, some famous [00:52:00] footballers. I don’t know enough about football. Let’s even mention a Chelsea player’s name, but you can graft their face onto his friends or something like this.

I have a vision. So, um, but these, these technologies could also be used in the other direction to correct for some of the, the things that we find too salient. this is like very sci fi. I don’t think. This is going to be an early use case of these technologies, but one can imagine people giving job interviews.

And, um, Kind of redrawing all the candidates to look the same. And, and so, um, we, we lose some of the biases that, that we, that we, we find so hard to shake off. And actually I think it is, you know, it does seem just very hard to shake off. So much of the, uh, or to, to, to adjust salient structures in so many ways.

I think there’s a kind of hysteresis firstly, like there’s lots of evolutionary reasons why we find certain certain things salient, [00:53:00] but it occurs to me that a chance comment can update one salience structure in a way that’s very difficult to update a friend of mine. Said, oh, high arched eyebrows, Joseph Fritzl’s got them, so has Gary Glitter.

And now, like, I don’t think he believed that they were, like, evidence of evil, and I certainly don’t.

Jessie Munton: Now when I look at high

James Robinson: arched eyebrows, they’re just slightly more salient for me because of that. Yeah. Yeah. And I can’t really unlearn that. Um, yeah.

Jessie Munton: Um, yeah, I mean, I think, I think, and you’re absolutely right about like, I dunno, philosophers have a long history of sort of denying our embodiment and because the framework that I’m offering is very much focused at the level of kind of information.

I worry that it feeds into that a bit and you’re right. They’re like our physical embodiment makes certain things salient to us. And it’s an aspect of other people that is inevitably salient to us. And. [00:54:00] Um, you know, you don’t want to end up in some situation where it feels like you have to bash yourself over the head with some hammer to change that in a way that you can’t.

I think one thing that’s really helpful is that you don’t necessarily have to change the salient structure, but you can have a metacognitive awareness of the role that it’s playing and how you’re thinking about things and what you’re absorbing from the situation. So, of course you’re going to notice what the people that you interact with look like, but maybe you can kind of challenge, you know, how you’re responding to that.

Um, thinking about your example of the, of the glasses, like, so I’m on Instagram and I follow like a bizarre selection of accounts. Some of them, I guess, are quite sports oriented, and there’s definitely a kind of presentation of the physical body there that, that is sort of valorizing in explicit and implicit ways of a kind of very athletic physique of a particular fairly circumscribed kind.

And then I follow some photography accounts at really push back against that and are quite invested in, encouraging and appreciation of the physical beauty of a much wider diversity of bodies. I think it’s really valuable following both of those. I think following both of them makes me [00:55:00] more aware of what’s going on in each of them.

 it’s interesting that I guess in that case, one thing I want to say is I feel like the ones which Encourage me to attend to the ways in which a wide diversity of bodies can be very beautiful. I feel like they’re putting me in touch with reality in some substantial way, but I don’t yet have a good way of saying, like, what, when does a salient structure do that?

And, you know, when does a salient structure, it feels like it’s akin to being misleading. But what do I mean by applying that term misleading in the context of a, of a salient structure?

James Robinson: Yeah. I, I think that’s a much healthier way. Uh, instead of trying to blinker ourselves with, um, apple Vision Pro or some other headsets.

Just to add some richness to our information diets, seems much more positive way of, of, um, uh, combating this. And as you say, just being aware of even having these salient structures, I think it’s really useful. And again, the, the physical embodiment of them, you know, changing the books that you have, or, we’re just being more mindful of [00:56:00] the programs that you watch.

I think those are all kind of useful learnings for me from this. I guess. You know, it’s nothing completely new, right? Everyone knows that it’s important to like, choose their information diet. , but, I think it, it does give, it does give an inkling of how,, the items in our diet connect to each other or the sort of the items in that our universe of information connect to each other.

Another thing I’m interested in is, search engines, which I know you’ve, you’ve looked at , and

one thing I like about search engines is that they’re these kind of public objects. So they’re pretty much the same for everyone. So they kind of create some. Baseline similarity in salience structures, sort of similar to how Walter Cronkite, everyone used to believe what he read on the news, right? At least [00:57:00] search engines, if I type in something and you type it in, we’ll probably get a similar set of results.

There’s some magic in the background, which may be depending on location and other things, it might, reorder. Or, or certainly if we were, we’re typing the same query in Spanish. We’d get a, a different set of results, but by and large, um, they’re fairly fixed structures. And they’ve had some demerits, but I think I’d overall say that they’ve brought benefits to society, search engines, social media I think is different because.

That is, targeted to each other very individually. So if I click on a link in Google, it doesn’t update its algorithm, for me alone. It doesn’t, I think, I’m not an expert in this, but I don’t think it’s more likely to, let’s suppose, I don’t know, I search for like fluffy dogs and I click on a poodle. I don’t think it’s more likely to think that I’m into poodles because of that.[00:58:00]

If I do the same in a social network, The algorithms do try to update and figure out what is the stuff that I’m really into and change my information diet, like tailoring it to me. And that seems like it would, have the effect of, I guess, kind of narrowing or reinforcing certain aspects of my salient structure.

Probably those aspects which, are Most attention grabbing in some way, or most easy to manipulate, I guess, like social media has these has this kind of meta goal of just making us all more manipulable, right? If it it’s primary goals are to, I know, sell stuff to, um, advertise things, etc. And to make us take certain decisions.

And it’s meta goal to do that is, Make us more easily to manipulate. So, um, encouraging us into a very, very kind of niche set of views makes it [00:59:00] easier to identify what things we will find salient. So yeah, I. I’m putting a lot of stuff on the table. I’m going to put one more thing, which is, I think the next evolution in the, the way that we access information is large language models like chat GPT.

,And I think that could go either the way of search engines or the way of social media. So again, they, there is for, for chatGBT, and similar, there are competing, , benefits or competing, how to put this,

, it gets points from us from tickling our, cognitive biases, right? And, like if it presents the information to us that we really find super salient and we just, really love digging into. [01:00:00] We’ll use more of that tool. On the other hand, it does also get points from us from, helping us develop better models of the world.

Cause at base, we are epistemic agents use a very philosophical term. We’re all interested in having a good, broad understanding of the world., At some level, it just may not be that in each individual task, that’s what we’re looking for. Like we, we might just be looking for fluffy dogs, right? , But.

They, they ought to see some benefits from encouraging us to broaden or, or, improve our salient structures in certain respects so that we do get better epistemic outcomes., so I guess, my, my feeling is like from an individual visit, one might like to have one’s cognitive biases tickled by an LLM from across lots and lots of different visits and lots and lots of different queries.

One might learn to appreciate that it’s actually better that sometimes the LLM throws in things that we hadn’t thought of at all, [01:01:00] that we’re just not aware of and kind of broadens our knowledge base. Um, but I don’t really have any intuitions on which of these models might win out. Um, so yeah, a lot of, I plunked a lot of ideas on the table.


Jessie Munton: Yeah. James, I’m interested in your confidence that search engines aren’t providing us with a more personalised service that might mean that individual’s experience of them differs. Do you have particular grounds for that?

James Robinson: Not very good grounds, um, but I would say that they’re less, certainly they’re less tailored than social media.

I definitely agree with

Jessie Munton: that, but I think it’s interesting that it’s, search engine companies are not very open about how much, you know, personalization there is at that level. And I suspect from the readiness with which Google gives me stuff to do with philosophy, That it’s not doing that for everybody.

But I might, maybe I’m wrong about that, but, but I think it’s significant and it’s something that there ought to be a lot more transparency around than there is. And in fact,, I think there ought not to just be transparency around it. I think you ought to be able [01:02:00] to just change settings or, you ought to have a slider that kind of says to how, how wide open do you want this set of results to be?

And how much do you want it to be tailored to the particular things that we think that you’re interested in at this given moment? So. In the context of search engines, so I said before that I think a really important thing we want from salient structures is we want flexibility. We want to be able to do lots of different things.

We want the information that we need in order to be able to do those things to be available to us. I kind of think the same about search engines that like, You want lots of different sorts of information to be available. We also intuitively want that to be information that is relevant to the thing that we’re searching for.

But there’s this big question, which is like, what does flexibility really involve in the context of, um, search engines and like, how open do we want that informational landscape to be? And I think my kind of judgments about this is a little bit all over the place. So part of me thinks with you that we want this landscape that’s quite open and we want this to be a shared tool that.

people are getting the same experience of, are getting the same [01:03:00] information from. That seems kind of like, well, transparency seems important here and that sort of seems like it’s part of transparency. At the same time though, I worry that that is going to flatten things out in a way that is to the disadvantage of people with more niche interests or whose informational concerns are not those of the majority.

So I feel like if you’ve got some very particular subset of interests and you’re going on Google, then Yeah. You want Google to give you stuff that’s relevant to that particular subset of interests. I also have the sense that we want, Google other search engines to make sure that we’ve got a really wide variety of information available that as you say, exactly my like challenge, the sorts of biases that we’re coming in with, all the kinds of views that we’re coming in with.

 then there’s another thing in the mix, which is like, to what extent do you also want it to make you aware? Not just of information that’s good and accurate, but information that’s not great, but the other people in your community are probably accessing because they find it a satisfying way of.

consuming the news and things like that. So I think that search engines have this kind of meta role to play a lot of the time where we don’t just want to know about the topic, but we want to know about [01:04:00] what kinds of information are available about the topic and who they’re available to. And again, that’s maybe a parameter that you should just be able to vary.

And that would be an amazing search engine. I think that it was like, do you just want the most accurate information or do you want to know what most people are learning about when they learn about this particular topic? So then when it comes to like large language models and what we want from them I guess like my ideal would exactly be that you give the user much more control and much more transparency by letting them vary those things to, to, to what they want to do.

I think there’s actually a particular Danger with large language models that I’m interested in at the moment, which is the way in which we’re encouraged to interact with them as though they’re people. Um, and so when I’ve thought about the epistemology of search engines, I’ve not thought about it in terms of testimony.

I don’t think that’s an appropriate model. So there’s all sorts of work in epistemology about, like, the appropriate norms around testimony. When you have one person who’s talking to another person and they tell that person some things, it’s like, your most basic interaction between two people.

That’s, that’s [01:05:00] testimony. And one thing that’s going on there that seems important is there’s this. interpersonal relationship there between two people. And part of what’s happening when I tell you something is I’m sort of telling it to you as me. And I’m saying, I’m telling this to you as one person to another, and that gives you some grounds to trust it because it’s that sort of an interaction.

I think large language models want us to think that we have that kind of a relationship with them. And I think it’s important that we don’t because that relationship is something that automatically kind of softens your skepticism or your wariness around certain things. Like we want to be, conversationally cooperative with the people that we talk to.

We don’t want to disagree with everything they tell us. We trust them to some minimal degree that just lets that conversation even get off the ground. And if we didn’t, you know, be hard to even do anything. But I don’t think we should have that trust in place with large language models. I think we should be very circumspect.

We should be thinking all the time about where they’re getting their information from and what kinds of things they’re not telling us. I think that’s crucial. It’s like, what information is missing from this conversation that I don’t know about? Um, and I think it’s helpful to not think of them [01:06:00] as kind of a person with the authority and the, and the moral significance that, uh, that, uh, that interacting with a person brings to a conversation.

James Robinson: Yeah, I completely agree with that. I think there is a, a lot of danger associated with the, anthropomorphization, if I can say that word of,, And even people who are very careful in their language, about them. So Steven Pinker, for instance, you’ll even manage to catch them out and find places where they refer to them. You know, it said this, right? I’m like, well, that’s not something that you’d say about a search engine, just the the saying of something is, is to us a very. Act. , so yeah, it’s, it’s really hard to catch them out. Incidentally, just one small thing I think they should do with LM’s is just like make them and I’ll put all the results in comic sans.

So we take it a little bit less seriously., I do think they, they do at least offer that offer that opportunity to tailor one’s results and say , you can just say, I am interested in these things, this is the kind of person I am. , [01:07:00] yeah. Tell me about X. Right. Explain, the theory of relativity as if I was a toddler.

Right. They will do a really, they will do a really impressive job at that and kind of drawing on what is salient to a toddler and reframing, something that you want to know in, in those terms. But I also wonder if they’re maybe too good at that because we might just all end up with this default setting, which is give me the information the way that I like it.

and, and even worse, give me only the kind of information, that I like., but yeah, yeah, completely remains to be seen how. How that plays out I

Jessie Munton: agree with that. And then it’s funny in a way that maybe we want to begin to build in, like we reach a point where these tools are very good at giving us information.

And part of what we want from them is occasionally to frustrate or annoy us by not quite giving us the information we want, but still to give us information that’s valuable.

James Robinson: Yeah. Another thing that came to my mind is I really like this idea of using search engines and also LLMs, actually even more LLMs as a way [01:08:00] of uncovering the kind of common.

Opinion in a certain way. Like, what is it? I think search engines are really good at capturing one’s, like societal level preoccupations. And so, we’re old enough, I think, to remember when Google introduced autocomplete. So you’d start typing something and then it would say, okay, you know, I am having problems with.

And then it comes up with a list of all the things that you could be having problems with. And that’s essentially a representation of the stuff that, that people most commonly type into Google and therefore the things that, people do have problems with, and that is like incredibly useful or yeah, really interesting information.

 and LLMs., also do this. There’s a good example from, uh, Isabel Boemeke, who’s, who’s this nuclear power, influencer, probably the only nuclear power influencer. On her blog recently, she looked at, she started asking chat GPT about nuclear power, nuclear power, and [01:09:00] it became really clear that all its answers were very biased against it.

It was like, oh, it’s really, you know, it’s pretty unsafe and so on. And it’s really hard to dispose of the waste. And it’s like, well, has any, you know. Has anyone ever died from, uh, nuclear waste disposal? Are there any deaths associated with that? Well, and it, and it answers no, but it can’t resist kind of imbuing the opinions, which is, are encoded into its training set, which are overwhelmingly, negative.

 even though like certainly within scientific communities, people are really keen on nuclear power., it’s, it’s very hard to get it to answer in a positive way about that.

Jessie Munton: Yeah. I think another thing that’s in the mix here with both search engines and LLMs is. And maybe this kind of comes back to the themes that we started with. So we naturally think of them as giving us information, and then there’s a question which is, well, what information do we want them to give us?

But I think that that process of giving us information can have these really broad ramifications that go sort of way beyond what we might ordinarily think is associated with it. So the [01:10:00] nuclear power example is nice in that respect, that I would say partly you might think, well, this is a slightly misleading subset of information.

There’s other information which we need in the picture to have a rounded impression of the, value and impact of nuclear power, but it also changes your concept of nuclear power. I mean, presumably part of this is happening because people do have a kind of bogeyman concept associated with it a bit in some contexts.

And then that’s further encouraged if you have these, tools for sorting and prioritizing information, which are prioritizing some misrepresentative subset of it, it’s not just that you end up not knowing the stuff you might want. to know, but your actual concepts that you’re using begin to change under this kind of an influence.

James Robinson: Yeah, there’s a very, uh, this is a

tangential example, but I think it Maybe illustrates again, how just the appearance of something on one’s cognitive landscape can have weird consequences. So in the paper that this morning was, [01:11:00] uh, headline Shakespeare expert overturns flytip a myth about playwrights father exclusive. John Shakespeare’s Muck Hill fine in 50 to 52 was a waste disposal toll rather than a punishment.

Research says, and, I, I noticed this today and I immediately thought about this conversation we’re going to have because I’m like, well, what is the point of that piece of knowledge, right? That Shakespeare’s dad was not a fly tipper, right? Is that even interesting to Shakespeare academics or Shakespeare aficionados?

Well, it is because it’s a headline and, and I read it and I, I was kind of like, oh, yeah, it’s sort of interesting, but it doesn’t, it’s not going to change my appreciation of his plays, but it does. Redraw my salient structure in a certain way. Like now I’m probably more inclined to think of the immortal bard when I go to the rubbish dump or even just take my bins out at night, right, even though there’s no kind of real justification for that.

Jessie Munton: Yeah, but yeah, I think it’s helpful you mentioning newspapers, because actually the sorts of things I’m interested in, of like, what information should be prioritised, that’s a question that’s been in newspapers since forever, they’re having [01:12:00] to make decisions all the time about what goes on the front page and what goes on all the other pages, and what even doesn’t get into the newspaper at all.

And I think another discipline where this stuff is there is also in library science and deciding how you organize libraries, like, what are the relevant categories and what are you promoting by having a category division between these two things rather than another two things. So I think these questions have been there all along, and we’ve tended to pursue them outside of the context of the mind directly, but I think it’s helpful to think about them more directly within the mind.

James Robinson: Yeah, yeah, I wonder if you have any, Ways in which this has kind of practically,, changed how you live your life. Has it made you more aware of what sources of information you take in? And, , or are you kind of like, like many philosophers I talked to you? Like, Oh, this is interesting stuff, but Uh,

Jessie Munton: no, I think it does impact me in certain ways.

I mean, I don’t know if this counts as an impact. I’m surprised [01:13:00] how much stuff I hear going on in the news. And I think there’s a problem with how this is being reported. And it’s not a problem that’s to do with the accuracy of it. It’s a problem to do with what we’re making salient by reporting it in this particular way.

So some of the coverage of stuff to do with trans women, I think, is like often making salient threats. that comes from a particular direction without like necessarily saying things that are inaccurate, but that’s having a really big impact on how that conversation goes. Or I think, coverage of immigration is often like very, very invested in making threat very salient, even when the groups concerned are extremely small.

 so, so, I mean, I, I guess I fall back on it increasingly as like a way of analyzing these things, I think is valuable, but that’s not really, I mean, an impact in sort of my, my particular life. I think, I think it has made me think. differently about how I use social media in various ways, or, yeah, what things am I passively letting just come into my informational environment in ways that are going to change my salient structure in ways that perhaps I don’t want.

 I guess I see it most broadly. I don’t know if this comes out of the stuff on salience or just how I’m thinking about epistemology in general. I think there’s [01:14:00] always a kind of mandate towards curiosity in all of this, like, a mandate towards trying to expand what you’re exposed to or the sorts of things that you consume., I, I think it, I hope it does make me more aware of that and more ready to invest in it in terms of perhaps buying books on weird subjects you might not have thought about or trying to think about what are the options that I’m not. Even engaging with it. I guess one thing that is important to all of this, I think, is that thinking in terms of salient structures lets us think more about the kind of negative space in our mental lives.

So what are the things that I’m not engaging with? What are the kind of lacuna that are there? I think that’s really crucial. Um, and, and so, you know, having just one ear listening out for some of those things and then trying to tune in when some of that’s coming onto your radar, I think is valuable.

James Robinson: Yeah, yeah.

I think that that’s spot on. I mean, certainly ignorance. If we, if we bring up the, if we prop up the straw man one more time, like ignorance has not really been studied [01:15:00] directly in, in, in epistemology, like where it’s come up is just where you have a belief, but it fails to be true, right? You, you believe something wrongly, but it’s not looked at all that negative space.

I guess, just for many evolutionary reasons, we’re not very good at looking at negative space. We fixate on things. I find it so fascinating that you can put a tiny dot in a huge canvas, and although the space is eclipsed. Right? Um, you will spend almost all your attention on that dot, right? It’s not even that your space is like slightly unequally, your attention is slightly unequally weighted across the space.

Like it’s, it’s completely like overwhelmed by that. And that’s just so, um, yeah, it’s so fascinating. Um,

Jessie Munton: and I think, I mean, I, yeah, and I don’t want to downplay the extent to which there has been work on. ignorance, [01:16:00] or it is there to some extent. But I think it’s true that there is this aspect of traditional epistemology that to the extent that you’re interested in applying terms like justification and knowledge, you need something there to apply those terms to.

And with a canvas, like you say, we don’t tend to notice the negative space, but the problems Much more acute in our own minds insofar as the negative space is exactly the stuff that you don’t know. And there’s a kind of, you know, meta negative space. You know the negative space is there in some ways because it’s not, it’s, it’s the stuff that you don’t know or that you’re not thinking about or that’s not making its way into your mind.

So I think that’s like a point at which thinking in terms of structures is really helpful that they will reveal to you where you have negative space a bit more potentially.

James Robinson: Yeah, I think it’s, it seems to me like it’s another lens on a very old problem of exploration and exploitation, um, which is, yeah, I don’t know originally where that, that, that term or that, that phrasing has come up, but I know it’s popular within the kind of machine learning.

[01:17:00] community, like should your models , really focus in on certain features that they, they think are improving their predictivity, um, or like versus the kind of compute time that you could spend on looking at entirely. different features, which, initially may not really seem to be doing much.

 But, but perhaps we, you know, just need a little bit more information. And I mean, that’s such a hard problem, right? Why, what books to read, like what blogs, what people to listen to. We’re in such a rich. Informational landscape. We carry around these devices, which kind of potentially give us access to all the world’s knowledge. , But we can only take such a thin slice of that. But maybe, maybe the answer is we do need to take. Slices across various different dimensions, discard some, but, you know, nonetheless don’t just lean into the things that we, [01:18:00] we naturally inclined to.

Jessie Munton: And it is tricky, like, you know, our time is limited.

There’s way more books already probably that I would like to read than I’ll ever get to read in my lifetime. and so, you know, that can feel like a mandate towards exploiting the stuff that you enjoy rather than exploring. On the other hand, I think there’s all these ways in which we’re fairly. Um, it’s kind of spend thrift with our mental resources and I don’t know, I consume a lot of stuff passively or that I’m not that invested in.

And maybe if I thought a bit more about it, I could make better use of those resources.

James Robinson: Yeah, absolutely. Um, yeah, I don’t know if you have any kind of final thoughts. I, I know there’s like. There’s, there’s a lot more of your work, which is really fascinating. I advocate people to, to look up, you know, you’ve looked at, um, perception and, um, kind of optical illusions and how we learn from, from those.

 and all of this does overlap, I guess, with, with your work here on, on, on salience as well, which is really fascinating. Um, so. [01:19:00] I don’t know if you want to add either on that topic or, or anything else as a kind of final, final

Jessie Munton: thought. I don’t know. I feel like talking about perception might get us into a whole, a whole nother substantial conversation.

 So I, I think I’ll, I’ll leave that there for the moment. Brilliant.

James Robinson: Yeah, this has been such a, such a lovely conversation. I, I do concur that this model does actually unusually for a, Philosophical thesis, change my way of thinking about not, not just change my way of thinking in philosophy, but actually change, the way that I go about and generally consider things.

So I find it a really useful framework. So thank you. Oh,

Jessie Munton: good. Yeah. And maybe if any, network scientists are listening, who wants to help me out, they can, get in touch. Yeah,

James Robinson: I hope so.

Jessie Munton: Brilliant. Yeah. Thanks James.

Geoffrey West: Networks, Heartbeats & The Pace of Cities

While physics is incomplete there is relatively little we don’t understand when it comes to particle or planetary motions. But physics is incapable of telling us much about life in cities, the beating of our hearts or whether society will implode.

And yet, the techniques of physics have been used to powerful effect in unraveling emergent laws which explain why:

  • Whales live longer than hummingbirds
  • Megacities are more energy efficient than towns …
  • … but the growth of cities fuels unsustainable growth

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 mathematically derive 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 that optimal space-filling networks are fractal-like in nature and scale as if they have an extra dimension. A 3D fractal network scales as if it is 4D. It’s a lot to take in, which is why this conversation felt short for me, even though it was 2 hours.


Geoffrey West: Scale

James Robinson: [00:00:00] All right, Geoffrey West, thank you for joining me.

Geoffrey West: Yes, pleasure, James. Thank you for inviting me. I’m looking forward to our conversation.

James Robinson: You started your career looking at the tiniest of things, at quarks and so forth, and, and, and very far away project, uh, problems like the, the origin of the universe. but you’ve, Ended up in a very different place looking at enormously large systems composed of lots of little things and speaking to the issues that concern us every day.

Um, can you tell us how you went about, how did that

Geoffrey West: journey happen? Oh boy, let’s see if I can keep it brief. Well, first of all, of course, I don’t suppose any of it would have happened had I not had a sort of natural predilection, , wanting to Sort of, I mean, it sounds, sounds arrogant, but understand everything, you know, as a boy, you know, I was always asking questions.

I was interested in everything, as one does when is, you [00:01:00] know, as a young boy and even in high school and so forth. Um, and, I, I always harbored a sort of romantic image. Of what being an academic would be, and I, and that was sort of enhanced by being an undergraduate at Cambridge, just the, the physicality of it, I mean, and, uh, sort of romantic, totally romantic and unrealistic image, and, and, and I sort of had this image that, I’d always be around people asking questions across the entire spectrum of life, so to speak.

Um, but I was also very good at mathematics. And, uh, but what I think happened was that, um, that led me naturally to physics because physics seemed to be the only science that actually answered questions. , it was the, they pose them, these, these deep questions and they answer them, but they not only answered, [00:02:00] they answered them.

In a rather precise, quantitative fashion with an analytic, deductive strategy, and that was very appealing. So I ended up doing, as you said, high energy physics, so quarks and gluons and string theory and dark matter and all these wonderful questions. But then, um, but I always sort of was slightly frustrated, um, that I, I was being forced into this box.

even though I had a rather, um, you know, very eclectic group around me, uh, nevertheless, um, uh, so that kept going. And then, um, in the, I guess it must have been the, um, late 80s, 90s when this superconducting supercollider was being proposed and being built, you know, you know, this huge accelerator, um, that, uh, was going to cost at the beginning of the order of [00:03:00] 10 billion and, uh, uh, we were all very excited about it and so on.

And then it was canned in the early 90s. This is

James Robinson: a big facility in the, in the That was going to happen in the USA, right? Yes, in


Geoffrey West: It was much bigger than the Large Hadron Collider, now at CERN. Um, and, uh, it got canned, uh, and, uh, so it was kind of a, obviously a crisis in the field. And I, like many others, uh, were, went into a kind of depressed mode.

But I also went into a mode of, you know, oh, oh, so part of it was It also coincided that, um, cancellation of the superconducting supercollider, the SSC, coincided with one of those waves of, um, anti science that comes to fore every once in a while, and it. It focused [00:04:00] primarily on physics and the comment that was always around was physics was the science of the 19th and 20th century centuries.

The science of the 21st century will be biology. And, uh, well, it’s hard to argue with that in many ways, but it was, but I reacted. You know saying yes, that’s very likely but biology will not be a real science Until it somehow integrates And absorbs the culture and some of the techniques of physics doesn’t have to have physicists necessary But it needs to think more like physics now By the way This was total arrogance and total ignorance because I knew no biology and it was coming out of pure defensiveness and reaction to this SSC thing.

Um, but you know, we heard that all the time, but there was also a corollary to that that was either left unsaid, but sometimes said, um, uh, and [00:05:00] that was, there’s no need to do any more fundamental physics, we know all the fundamental physics we need to know, let’s devote our resources to other things. And I felt that was completely mistaken.

Um, so, uh, sitting around one day, I thought, you know, that, that I keep saying this statement that biology won’t become a real science that does physics, you know, it’s sort of stupid, but maybe I should try to put money where my mouth is and try to think of doing some biology of my own. Well, that happened to coincide also with some concerns.

Obviously initiated to some extent by the collapse of the SSE that I was getting old. I was in my mid fifties at the time, uh, and, uh, I come from a very short lived line of males. Most of us die in our fifties and sixties. And so I [00:06:00] realized that, you know, if, if genetics play a role, I probably don’t have more than about 10 more years.

And I started thinking about it. I thought, why is that? You know, what is it that’s. that is the origin of aging. And, um, I thought that’s an interesting problem to think about, but no doubt there must be tons of work been done in biology on this and in medicine. Um, and, um, so I said, but I started thinking about it and then I started.

thinking a little more seriously by going to the library and actually reading about it. And one of the things I discovered was that in fact, it was a total backwater, that despite the fact that at least, at least the way I think about it, it’s the second most death is the second most important event in the life of an organism.

Birth being the most important, but death is, you know, that’s it. And yet here you found, you know, here it was a backwater. I looked in these big fat books, um, you [00:07:00] know, that they teach, uh, elementary biology and that covers all of biology. And you look in the index, nothing about aging and death. Everything else is covered.

So I thought, Ooh, that’s good because that means that maybe this is something I can think about. But then another thing I realized was that I had set myself not just the question, why do we age and why do we die, but why do we live a hundred years? So I’d put it in a physicist terms, simplistically, where in the hell does the scale of life come from?

You know, why a hundred years? Why not a thousand years? You know, what are the knobs that you can turn to make us live a thousand years or what knobs have been turned by natural selection and so on. So, um, I started thinking about that, and, um, the, the first thought that I had to start, you know, actually deriving, quote, a theory, [00:08:00] was, look, if the system is going to age, decay, and eventually decay, Disappear, um, obviously you have to understand what it was in the first place that was keeping it alive, you know, because obviously something has gone wrong.

I mean, it’s produced too much entropy or whatever. So, uh, and that’s called metabolism in biology. So I didn’t know much about that. So I started reading about metabolism and I learned about these extraordinary scaling laws. In biology, that is, that, um, we will hopefully talk a little bit about that later on, but I discovered, I discovered, I learned, reading, that there was this famous law discovered in the 1930s by a man named Max Kleiber that said that metabolic rate, from a physicist’s viewpoint certainly, but maybe also a biologist, the most fundamental quantity of life, the How much energy does the organism need to stay alive?

How much [00:09:00] food does it need to eat per day to stay alive? If you asked how did that scale with the size of an organism, that scaled in an extraordinarily simple mathematical way. There’s a so called power law. Um, uh, and, and the way that’s represented is if you plot, The metabolic rate logarithmically that is going up by factors of 10, um, on the vertical axis against weight plotted logarithmically on the horizontal axis, all the points fitted on a straight line.

And that blew my mind because I was a great subscriber, as we, most of us are, to the idea of evolution by natural selection, and this kind of naive idea. It’s all historically contingent. Everything depends on what’s happened before, and the frozen accidents that have happened, and the kind of environmental niches think organisms evolved in.

Not just the organism, but every component of the [00:10:00] organism. Therefore, You would have expected, if you plotted anything as complex as metabolic rate versus size, there would be, you know, there might be some correlation, but the points would be all over the graph, reflecting historical contingency. This was quite the contrary.

And I thought, my God, you know, there must be an explanation for this. Well, it turned out there wasn’t a satisfactory one, there was no, and by the way, this was true across all of life, wasn’t just sort of mammals and birds or fish, but everything Straight line. Not only that, the slope of this straight line, Max Kleiber had learned, was three quarters, very close to three quarters.

So I thought, and, and so I first thought, that’s great, um, I’ll use this to learn about aging. But I first better understand where this law comes from, myself. Uh, and so I started [00:11:00] biology. And I, I learned, I derived. that law from some fundamental principles. Um, I hooked up with some extremely good biologists and we eventually published.

A paper in science that got a lot of publicity and, uh, you know, I was still running a big high energy group, by the way, I mean, it was sort of weird, it was sort of a hobby still, but it became very clear that this was much more exciting than the epsilon progress I was making in string theory, that anyway, no one was paying much attention to anyway, whereas here I was getting accolades for doing this, this work in biology.

serendipitously led to my sort of adiabatically slowly moving into becoming a kind of pseudobiologist. Yeah, I think,

James Robinson: and in a moment we’ll, I want to go into the details [00:12:00] of where that three, three quarters scaling law comes from and what it means because that’s That’s so fascinating, but I do want to pause here because it’s such an extraordinary story.

This arc going from, you know, being quite a eminent theoretical physicist running a group at Los Alamos in one field, and then, you know, fairly late for most people in their career at least, you, you, you take a completely different track in some ways. We’ll find out that you actually use the tools. of a theoretical physicist, but you know, it’s an extraordinary, it’s, it’s an incredibly ambitious program to say, Oh, no one’s, no one’s figured out why animals, why, why, why humans live for a hundred years.

There’s nothing in the literature on this. I’m quite intrigued about that problem. So I’ll, I’ll go and I’ll go and find a solution. Um, And, you know, one wouldn’t expect a lot of [00:13:00] progress, uh, you know, that doesn’t sound like it’s going to be a fruitful start of a research program, but it, it really was. Um, I, I just love these kind of two act books, you know, and, uh, this seems like one

Geoffrey West: of them.

Yeah. So yeah, so of course, by the way, just to repeat what I said earlier, it was a, um, a product of arrogance, ignorance, and naivete. Um, and, and it’s true, I did not expect That this would have, you know, that I better solve the problem, frankly, and I didn’t expect that, you know, that this would lead to a change in direction of my career, but I was very open to it.

That’s why I told the SSC. I was very open to it because it was for two reasons. One was because the field I was in was going through a crisis. And stagnation. And also I realized that some, at some semi-conscious level, I had felt constrained or claustrophobic. [00:14:00] Somehow surprising in a way when you think about it, because I was working in string theory, which I think maybe not by then, maybe it had, it had already been dubbed this ridiculous term theory of everything.

Um, and, and here I was feeling claustrophobic to work and one of the things I realized later, by the way, was, um, I had. Also, part of that arrogance was that, um, part of the culture of physics, but particularly high energy physics and theoretical high energy physics, um, was and is still to some degree that all you need to know is the fundamental equations.

You know, if you knew, you know, if string theory is it, and it is beautiful, by the way, I’m not putting any of that down, quite the contrary, um, if it is it. Um, um, that [00:15:00] all you got to do, you have the theory, you have the equation, and then you solve it, and you keep turning the crank, and out come, you know, uh, the origins of the universe, and the big bang, and then come galaxies, and then planets, and then you have the earth, and then there’s life, and then there’s, you know, automobiles, and then there’s iPhones, and it all comes from, you know, just turning the crank, and, uh, because once you have that equation, In a certain sense, it’s all engineering.

So that was sort of, I mean, I’m exaggerating and making a total cartoon version, but that was sort of the mindset. And the, the, the thing that I learned of was the obvious that. Equally challenging and even more exciting in some ways is the messy stuff that exists on this planet. As far as we know, this is the only place in the universe, as far as we know, some probably are other places, this is it.

This, [00:16:00] this complete mess that we live in on this planet and all these extraordinary processes that take place, um, called life or complex systems, um, are even more challenging, remarkably, than understanding the origins of the universe. Which is weird, you know, because physics has built into it, the culture is that there is an equation, a fundamental equation, and from that follows everything.

Well, one thing will follow is the evolution of the universe, and we’ve done an incredible job. I mean, the progress in cosmology, astrophysics, astrobiology even, has been fantastic in the last 25, 30 years. Um, but It’s, it’s all, you know, what, what some of us call simplicity. That’s not, you know, that because [00:17:00] you can write an equation and try and solve it and continue.

I mean, it’s a linear, almost linear process, whereas trying to understand what’s going inside your head at the moment, you know, we’re probably never under, I mean, that’s not, that’s not a passion statement, but you know, understanding our brains and consciousness and, you know, What the stock market is going to do and, uh, you know, are we going to solve all the problems of the future of the planet?

Those are a completely different category of problems. That’s right. You can’t write an equation. Yeah.

James Robinson: I think we’re not saying that in principle. There’s some kind of new non physical behavior that emerges, right? In principle, if you could crank that equation, it would produce, or it does indeed, if we had the equation, a theory of everything, that is, you know, the underlying dynamics that governs everything.

And in principle, it could be cranked perhaps, but in [00:18:00] practice it can’t. And even if it could, I’m not sure that that cranking would produce understanding. It might produce. You know, the right outcomes, but would it actually explain anything to you in a, in a human sense? Probably

Geoffrey West: not. Um, yes. I mean, we don’t learn anything about life from the fact that, uh, you know, uh, the nuclei of.

of atoms are made of protons and neutrons, or well we do from that, but the protons and neutrons are made of quarks and gluons and so on. It doesn’t, you know, so there is this, which physicists recognize, there’s this level structure and those levels are to varying degrees uncoupled. In some cases they’re highly coupled, and the trouble in, for life on earth, for the stuff on earth, all the various levels are very closely coupled, and they’re all interrelated.

You can’t do that separation, and that’s what makes, that’s what [00:19:00] allows us to do physics in a way. Is that, uh, especially fundamental physics, because levels tend to get separated from each other. And you can consider them, um, autonomously. Yeah.

James Robinson: Let’s come back to these remarkable scaling laws, which we should say Max Kleiber discovered almost a hundred years ago, I think.

Um, in the 1930s. So it was, you know, it’s incredible that they, they were sort of laid to one side for so long. Um, and. You know, what they say is truly remarkable, that if you double the mass of a, of an organism, uh, so if you go from one animal that weighs half of a, half of another species, that heavier species doesn’t need twice as much food per day.

It needs about 75 percent more. So that’s the three quarters of the, of the exponent that you mentioned. And this is, [00:20:00] this three quarters is remarkably consistent across species. Um, And across kingdoms, it’s not just animals, it’s plants as well. That, that same exponent turns up if you’re looking at, um, like the number of leaves in, in trees, it doesn’t double as you, um, double the mass of the tree.

It again, only goes up by three quarters. That’s an incredibly striking thing. How does one go from seeing that relationship in the data to then figuring out an explanation for

Geoffrey West: that? So, first of all, I want to just, um, continue with the phenomenology of it. That is, it’s not just metabolic rate, but you already said it, number of leaves.

It’s almost anything. You can make what is extraordinary. And the thing that really got me wasn’t, I mean, the metabolic rate got me. But then when I learned very quickly that, uh, almost any physiological [00:21:00] quantity trait of any kind of organism Obey similar laws, as does any life history event. So a physiological trait would be like number of leaves or the length of your aorta and so on.

And life history would be, you know, how long you live, in fact, um, uh, or how many offspring you have, or how long do you take to mature, you know, all these kinds of, they’re all scary about them. They all have these straight lines. And the, the thing that is so striking is that the slopes of those lines.

Always simple multiples of one quarter. So there’s this extraordinary universality and first discovered by Clymer. But, um, the, the, during the, uh, 30s, 40s and into the 50s even, um, people just added to this so that there’s, you know, huge amounts of data that can be collapsed onto these [00:22:00] scaling curves. And one of the things that helped me in my work was it just so happened to then be.

late 80s, in the early 80s, two or three books had been written summarizing all of this data basically. And so it was already there ready to be explained, if you like. I mean, so, um, uh, but There was interest in these laws, they weren’t sort of put aside then quite, and in fact, you know, many of the most distinguished biologists, Huxley, Hordain, uh, and so forth, um, Darcy Thompson, all were intrigued by these things.

Um, but what killed it, of course, was the molecular revolution. I mean, uh. The realization that we can really understand very important, powerful aspects of life from a molecular viewpoint and with the discovery of the structure of DNA, [00:23:00] etc. And that completely dominated biology and to varying degrees still does.

I mean, that viewpoint, much like high energy physics. Has the viewpoint that everything can be, you know, if you know the fundamental laws of quarks and gluons, you get everything. There’s sort of this naive view in biology, if I, I mean, in fact, it was in the Human Genome Project, it was basically said. Once I’ve mapped the human genome, everything follows, you know, we know everything, which was, you know, even I, who knew very little about it, thought that was absurd.

Um, but anyway, that’s, that’s beside the point. Um, so here were these, so they went into sort of, onto a back burner, um, known mostly only to ecologists because for obvious reasons in an ecology, you need to know when you’re talking about interaction of species, um, how their metabolic rates change [00:24:00] with their size and so on.

So many ecologists knew it. And my, my major collaborator, Jim Brown, was a very distinguished ecologist. And he, we came together because he was very. Intrigued as to what the hell the origin of these laws were that he was using, you know, where the hell did they come from? Um, so now let me try to answer your question, uh, indeed, where do they come from?

So the thing that got me, uh, immediately when I realized that, um, uh, that, that these laws were ubiquitous and had this universality to them, was that obviously whatever The underlying principles were had to transcend the, uh, sort of in evolved engineered design of life. That is, you just, you know, if it applies to trees and to mammals, it has to be something that is independent.

Of, uh, [00:25:00] the, the, you know, what makes you a mammal and what makes a tree a tree. And, um, so one of the things that is common, of course, and that’s why the molecular revolution was so powerful, was, of course, genes. Um, and, and you could say, well, it’s encoded in the genes. That doesn’t explain anything, of course.

It just sort of puts it back one step. Um, uh, and so I sort of dismissed that. I didn’t, that was not a very satisfactory answer. And then I thought, well, there is one thing. that is common to all of these, um, first of all, it’s obvious that a lot of these are to do with the use of energy in some form or another, uh, metabolism being the most obvious example.

But, um, you have to distribute energy and maybe all these laws are simply A reflection of the mathematical and physical constraints on the networks that had to [00:26:00] evolve in order to distribute energy. So natural selection, as it evolved multi, especially multicellular organisms, but even, you know, unicellular ones with huge numbers of components.

It had to evolve networks that distributed energy and information to all the various components in a roughly, Let’s say democratic, efficient way. You know, just thinking in a very coarse grained way of thinking about it. So I thought, well, maybe that’s the origin of it. Um, let me try and see if it works for mammals.

Just that idea, take that idea for mammals. So, um, I started to look at the structure of networks, and I wrote down the mathematics of these networks, and wrote down some generic universal principles that I thought might apply to them. Like, for example, one is obvious. One is that, um, the [00:27:00] network, say your circulatory system, it’s terminal units, it’s in by the capillaries, have to end up feeding all the cells.

So the network has to be what’s mathematically called space filling. It has to go everywhere, I mean, otherwise it doesn’t make any sense. But you have to put that into mathematics. The, the, uh, the second most important one. was that, um, if you look at all mammals, that, um, natural selection, when it evolved different species, uh, uh, uh, than a, than a mammalian, um, did not reinvent all the fundamental components, you don’t start, you know, from the beginning again, it, um, it used the same fundamental units, same, basically the same cells, the same capillaries and so on, so the idea was, That this network ends at a capillary [00:28:00] and then feeds a cell, but the capillary is the same in the mouse as it is in the whale.

That is, and the idea being also that, look, um, if you, um, in your house, the end of a terminal unit is your, is an electrical outlet, plug in the wall. Now you live in a, I don’t know where, well, Let’s say you live in a modest size building, but I don’t know in Edinburgh, but in London and certainly in New York, there are skyscrapers.

When they scale up to a skyscraper from your house, they don’t scale up the electrical outlets. The outlets stay the same. And so it is, you know, all the outlets, the faucets, the taps on your, um, on your sinks and so forth, all these outlets. So I said, okay, that’s almost certainly true of the sorts of systems that have evolved biologically.[00:29:00]

So that’s another one. But the last one, the last. sort of speculative principle was that, and this is the most important one, was that, um, of all the possible networks that could have evolved, uh, that even if they’re space filling and have these invariant terminal units, the ones that actually have evolved by the process of natural selection, and this is where natural selection really comes in, are the, are, um, the ones that have minimized the amount of energy.

That is needed in order to keep, sustain the system. Namely, the idea being, so let’s take the circulatory system again. We all have a circulatory system that is evolved to minimize the amount of energy our hearts have to do. To pump blood through it to supply the cells to keep you alive, um, so that you can [00:30:00] maximize the amount of energy you can devote to sex and reproduction and the rearing of offspring.

So that was my, in the end, our translation. of Darwinian fitness. That is more pretty pushing your genes forward, so to speak. Um, that was the translation of that into a physical framework. It comes very

James Robinson: naturally from a physics y way of thinking, I guess, as well. You’ve got to minimize some quantity.

Geoffrey West: And you know something, I, I did that and I just sort of did, you know, we did it and so on.

And it was only much later I realized. Shit, you know, that’s really, I mean, I hate to say this sounds that’s quite profound actually, you know, that, that, that natural select the, the survival of the fittest, so to speak, the continuous feedback, positive feedback in competition in the environment has led to [00:31:00] those.

That can maximize their Darwinian fitness by minimizing the amount of energy they need to devote to keeping themselves alive, that mundane part. So it’s a whole different, it’s a sort of a different view of, or a different rephrasing. Of natural selection. And it’s sort of interesting because it’s only in the last couple of years, I thought, it’s so weird we never emphasize that in our work.

I mean, we taught we say it, but it deserves, I’ve often thought it deserves a little essay or something that sometimes I should write, trying to promote that as a just, you know, a different way of thinking about it. It’s, from my viewpoint, it’s equivalent. It’s not a It’s, uh, anyway, but the point about that is that physics operates by optimization.

All the fundamental laws of physics are derived from optimization principles, everything from general relativity to [00:32:00] Newton’s laws. And so, you know, we’re, that’s the way many of us like to think about systems is what is being optimized. And then we have the apparatus. I mean, much of the apparatus of mathematical physics.

Is related to optimization problems and, um, and constraints. Newton’s bead

James Robinson: on a wire was sort

Geoffrey West: of Yeah, that’s right. Exactly. Exactly. That was the

James Robinson: beginning of calculus, um, differential. Exactly.

Geoffrey West: It was very much in that spirit. And so, um I started working out on that, working on that, at first on my, totally on my own, and I made what I thought was progress.

Well, it was progress, I thought I derived, it wasn’t. But I then was hooked up with Jim Brown, a biologist who had been thinking about this as a biologist, as an ecologist. And, uh, He and his student, a man named Brian Enquist, who is now himself a, a [00:33:00] highly established, well known ecologist, uh, we started meeting as, uh, discussing it, and I was telling him what I had done, and they were telling me what I’d done wrong, or what was not right biologically, and getting it straight.

And it took a year for what I had thought I’d derived. And it was basically, I mean, 90 percent was well, maybe 80 percent was basically right, um, to, um, getting it in, in, uh, in shape to write a paper that then was published eventually in science. Um, but it took a year and by the way, it was a real year. I mean, we, we made a commitment at the beginning.

It was kind of an interesting, um, uh, something I’d never done. Um, we met, we were two different institutions and, uh, it turned out. For various reasons, it was very convenient to meet in the middle at the Santa Fe Institute. And that began my association with the Santa Fe Institute. But we [00:34:00] made a commitment that we would meet every Friday morning, beginning about, between 9 and 10, and they would hang around until about 2 or 3, and we would just stay together with a blackboard, and battle things out.

And, you know, I knew no biology. And they were, how should I say, um, challenged, mathematically challenged, I don’t know if that’s a term. Uh, you know, so it took, it took a bit. It was, it was sort of like, often likened it to a marriage, you know, where you, It’s beautiful and wonderful, and then other times you think, Jesus Christ, what am I doing with this, they’re driving me nuts, they don’t understand, you know, this and that, and I’m sure they felt exactly the same.

But it was a wonderful, it was a tremendous collaboration which lasted for about 15 years, actually. But having got that paper, [00:35:00] by the way, the important thing was having done that work, it opened up. Everything. Because metabolism underlies so many things, and so the network theory underlies so many things, you could just sort of apply the same kinds of ideas to, you know, a whole plethora of subjects across biology.


James Robinson: I just want to say, I think I feel like a year doesn’t seem that long, given that you’re just spending your, your Friday mornings on it. So it’s a reminder how much one can accomplish if you, if the time is set aside and the right collaborators are found.

Geoffrey West: You know, I, uh, it’s a good point because I mean, the, the thing was Jim was running a big ecology group.

I mean, if they work in the field, um, and I was running, still running high energy physics up at Los Alamos. So, uh, you know, both of us were working. In our spare time kind of thing on it, but it was became very clear. [00:36:00] Maybe it was more than it was probably a year and a half as I think about it. But anyway, it became very clear to all of us that this was one of the most exciting things.

Not only we were doing then, but we had, we’d ever been doing, I mean, I know my love of high energy physics and all the work that I. was quite proud of. Um, this, this was really exciting. I mean, first of all, to go from a totally abstract world of quarks and strings to a world where, you know, you, real thing, you know, vascular systems and metabolic rates and growth rates and cancer and so on was Um, it was very exciting.

James Robinson: Yeah. It’s not, it’s not easy to crank through from the, you know, string theory to figure out why a whale lives so much longer [00:37:00] than a mouse. Um, and I want to, let’s, let’s, let’s go a little bit more into the details on, on this, um, three quarter power. So, so we said that nature is, or evolution is trying to optimize for something and it’s, you know, it’s keeping the energy cost.

Down. So I guess what the networks are trying to do is deliver stuff to the cells, the terminal units as efficiently as possible. Um, and in my mind, at least, it seems like what they need is as large a surface to do that as possible. It’s sort of like if you’re trying to push a lot of water through a a liter of water through a straw, you’re going to have to work pretty hard.

But if you want to push it through a big fat pipe, it’s very easy. Um. Is that sort of the bones of what needs to be maximized, as it were, kind of a surface area that, that you’re touching all the

Geoffrey West: cells with? If you put it that way, [00:38:00] um, and indeed that’s one way you can look at it, because, um, let me just back off a second to the network and I will come back to that.

Mm hmm. Because you’ve got to examine, it’s right, I mean What you said is correct, but I want to put it in a slightly different form. Um, so, uh, you know, when you grind through the mathematics of, uh, so you have to do the mathematics of a network, as you said, a heartbeat. So the complication here, which is not true for trees, that’s the trees and plants, is you have a beating heart, you know, you don’t have a pump and it’s just pushing like, like a straw, you know, it’s a suck.

You’re going, you’re, you’re beating hard, so it’s pulsatile, um, so, uh, that complicated things, um, but, um, so, uh, but you, nevertheless, it’s the same idea that you’re pushing blood, uh, through the network [00:39:00] down to the cells, and, um, when you do the mathematics of that, what you discover is that, um, um, um, Where that three quarters comes from is that the three, is it actually, it’s not three quarters, what the result is, is three divided by three plus one, which is of course three quarters.

But the three in that, in those, is the dimension of space you’re in. So If you were in five dimensions, it would mean five over five plus one. Okay. So, um, and that’s natural that that three would occur somewhere. Um, the dimension of space you have to fill, you have to supply. Um, the plus one is. Subtle, but it’s to do with your statement about maximizing surface area effectively because what it is, it reflects the fractality of the network.

That is what you [00:40:00] discover is when you try to, when you optimize this system, the network, um, uh, the network structure that does that is, is a fractal one, namely it’s self similar. Um, that is, it just keeps repeating itself over and over again. So that if you cut one, you go down the network and you cut a little piece out and you removed it from the network and then you blew it up, it would look just like the old network.

So it’s, uh, you have to blow it up in a nonlinear fashion given by the equations, but there is a operation. that just reproduces the old network. So it just sort of repeats itself non linearly, but nevertheless, it’s, it’s repetitive. And that minimizes. the, um, energy needed to push through the network. It could also be, it is also, um, if you think of that network as a [00:41:00] surface, I’m sorry, if you think of the capris, all the capris you could lay and they form some weird surface.

Um, what you’re saying is exactly right. It’s the, it’s that, that surface. is effectively maximized with respect to all the changes you can make in the network. So, um, the, the, the trick for mammals with a beating heart that is at first a problem is, you know, you got to push it, you got to, you know, your blood comes out of your heart at a very, I’ve forgotten the numbers and it’s been too long since I’ve looked at this, but it comes out very fast.

You know that if you cut an artery, You don’t live very long, you know, less than a minute, or the blood rushes out. But if you touch a capillary, break a capillary, just scrape your finger, it just oozes out. And so the system [00:42:00] is a part of that fractal nature is extraordinary. That it arranges so that the pressure drop from the very high pressure of the heart comes to almost nothing at the bottom.

So that when the capillary reaches the cell, blood can efficiently diffuse across the cellular membranes. to feed the cell. Otherwise, if it’s rushing by, if you’re just like a straight image of a straw, that’s why I’m addressing the question, your image of the straw. If you push, it’s the same velocity at the end as it is at the beginning.

James Robinson: That’s a beautiful explanation of why blood comes out so slowly, because clearly it makes sense. It would be a waste of energy if your blood was delivered with a high speed to their end units right they just need to, it’s the very last, you know, centimeter or millimeter they need to travel. So they’ve kind of [00:43:00] like all the all the energy is being used up.

delivering to, um, things further up the chain, I suppose.

Geoffrey West: Absolutely. I must say, um, independent of anything else, uh, when I, um, when, when, when I put it all together and had now this, um, this model, this theory of the cardiovascular system, um, and how it worked. It was quite beautiful. I mean, most, by the way, one of the things, of course, I discovered a lot of this needless to say was known.

I mean, in one form or another, put it, it was this context that was not known and putting it all together. in this form. Much of this has been worked out, um, in various parts, um, much earlier. Even back to, I think, the famous Thomas Young, who was the first to get the speed of blood through, um, you know, through your artery, through your main artery.

Um, but, uh, anyway, that [00:44:00] was the beginning. It turns out Trees, of course, and then you have this is this interesting question. Trees don’t have, um, beating hearts. Plants are quite different. So how does it work there? So you have to do that. In fact, they’re not, it’s not a bunch of pipes joined together. You know, like we are, we’re not the, we’re not like the, the, the plumbing system in your house.

Um, where that’s, that’s who we are, but plants, that plant above you there, um, is a bunch of fibers joined together, you know, like an electrical cable and it sprays out those branches are just the spraying out of the fibers into different branches. And so you have to do that, you know, that, that’s a whole different calculation.

James Robinson: You, you mentioned that it’s 3 plus 1 and, uh, you also talked about the, the fractal nature of these networks. And, and those two points are, [00:45:00] are, are highly related. And I think this comes across beautifully in your book, uh, Scale, that when you have. The way that something scales can add an extra dimension to its behavior, as it were.

So if you, if you just draw a line on a piece of paper and you double the, the piece of paper, uh, if you’ve drawn a straight line, well, you’ve used, you know, that would require twice as much ink. You’ve drawn a line, which is twice as long. There are these, you can draw a very special space filling curve on a piece of like paper, which is when you double a piece of paper, you’re gonna double the ink.

And that’s kind of obvious because if you space filled the paper with ink, you’ve covered the entire area. Um, but that It takes a little bit of, uh, I guess, mathematical imagination, but that trick works all the way up in any dimension. So where we have these, these, um, networks with our bodies filling three dimensional space, um, [00:46:00] the way that they scale up is, is to the fourth power in a, in a certain sense, or at least the, yeah, this, this kind of critical surface area that they can

Geoffrey West: reach.

Yes, so they behave as if we’re in four dimensions, and that’s what’s incredible, the fractal, so you know, I don’t know, I don’t know if we want to have a little tangential conversation about fractals and the wonders of fractals, but we are fractals, I mean, that is, you know, the essential part of us, everything from our.

You know, what I just talked about our circulatory system to our brains that we have this kind of self similar property approximately, obviously. Um, and, um, and, and of course, maybe we will talk about that maybe a little bit later that, that permeates nature. And this was the great discovery of, um, Benoit Mandelbrot.

Um, you know, who then showed us some of the mathematics of [00:47:00] fractals. The curious thing about Mandelbrot, if he was a mathematician, and he showed no interest in why it was like that. That was most peculiar, actually. I knew Mandelbrot, and I used to, in fact, I once had a big argument with him about that. He showed no interest in why would they be like this.

It was very strange. Anyway, that’s beside the point maybe, but, um, but it, but his discovery was fantastic. I mean, his promotion of it and discovery and looking across the breadth of science to show examples of it, I think, uh, was, was fantastic. Because it is, it is extraordinary that, um, we were dominated by Euclidean geometry.

Um, up for almost 2000 years, even though, uh, you know, we got out of Euclidean geometry with, uh, you know, differential geometry and Einstein and general [00:48:00] relativity and so on. But this other kind of geometry and, and the point that Mandelbrot of course kept making is there aren’t right angles and straight lines in nature.

I mean, that’s not how nature works, and I think that’s, you know, it’s a very simplistic cartoon kind of statement, but it’s of course mostly right, and that’s true, and in fact nature is dominated by these self similar fractal quantities, and the curious thing about them is, in terms of their dimensionality, as defined by how they scale.

Um, they can have, uh, dimensions that are not integers, as you said, you have a line and you double its size, it’s twice the length, I mean, almost by definition, you think, um, but these kinds of things, you can double the size, and in fact, uh, all kinds of weird things happen, you know, you get more [00:49:00] or you get less sometimes, so,

James Robinson: uh, The Cox Loaf Lake, I was looking this up, um, which is this, you know, it looks like a kind of classic.

Snowflake. Um, and if you, if you double the size of that, you get, um, not double, but, um, you know, 26 percent extra on top. So it’s factual, a factual dimension is, is 1. 26.

Geoffrey West: Yeah. 1. 26. And that’s true of us. I mean, we’re not 1. 26, but our system, you know, that’s why you have these, the kind of Kleiber’s law and all these quarter powers, um, but it’s all dominated by four.

It’s, it’s the, it’s, it’s. As if we’re in four dimensions because the fractal dimension, we have evolved to essentially maximize. I mean, we could have had a fractal dimension of 3. 7 or 3. 2, which would have been still fractal. But we actually maximized it and you [00:50:00] can’t go beyond one, it turns out. So three plus one gives you the four.

But the mathematics do that. I mean, you know, I mean, I, I, the way this happened. Historically for me was it’s very typical, you know, I did the calculation and it was, you know, it was a complicated mathematical physics calculation, not, uh, you know, good mathematical physicists would be anyone could be able to do it, but setting up solving it, you get the result.

And you say, wow, that’s great. The degree is fantastic. Now let me try to understand it. You know, where was, you know, what were the essential features through all that hieroglyphics that gave rise to this very simple result? That was because I think that was particularly the startling thing. Um, because when I started that calculation, I said, there’s no way this is three quarters.

I mean, Kleiber fitted it to three [00:51:00] quarters, but it’s probably Point seven three eight And that’s what I’m going to show that it’s point, whatever it is. And I showed him his three quarters. So I spent a lot of time trying to figure out what the hell was going on here. That it’s such a simple result. Yeah.

James Robinson: It’s not like any of the numbers you tend to get in physics, which is just like, you know, the gravitational constant is some very long, complicated number.

Geoffrey West: So wait a minute, what happened here? So that’s why, but it’s very typical in physics. You get a result. Um, especially if it turns out to be, you know, much simpler than you thought.

And then you have to go back and think through what were, what, what was the essential feature? What were the essential features that gave rise to the simplicity that I should have seen a priori?

James Robinson: , So we’ve got to the three quarter law, and it is a genuine three quarters, it’s not an approximation.

Geoffrey West: Well, that’s the thing, yes, I mean, that’s, and the [00:52:00] data does You know, , I mean, that was the original proposal of, of, um, Kleiber and indeed the data certainly, you know, it hovers around that. We’ve done a lot of analysis and of course there’s all kinds of controversies about the data and about this and that, which I find somewhat tedious.


James Robinson: one final comment on the fractal, um, point, uh, we were talking earlier about, um, Sean McMahon, who I interviewed not so long ago, the astrobiologist and his whole thing is looking for bio signatures and it does. I do wonder if, if. You know, if we see some fractal patterns with the right dimension on another planet, would that constitute a biosignature, at least, or a technosignature?

Geoffrey West: So that’s interesting. So, um, I was, funnily enough, the Astrobiology Institute. [00:53:00] Um, they, when it was set up at NASA, I was one of the people they brought in right at the very, very beginning. This is, this has got nothing to do with anything. But in fact, I wrote a, and so they, you know, we were involved in the early discussions of what it should be doing and so forth and so on.

And then they invited proposals. And I wrote, this is, this is quite funny in a way. I wrote a proposal with myself, Murray Gell-Mann. And, you know, the famous physicist, right, and someone else who’s now, um, at Harvard, Juan Pérez-Mecader. And we just assumed, you know, that, um, we would get funded, and it got rejected, so I never became, so I got so pissed off, I didn’t, I sort of withdrew from the Astrobiology Institute, whole thing.

Juan is a major member of it now. But anyway, that’s got nothing to do with anything other than my own memories of that. Because at that time, I was [00:54:00] thinking exactly about this. I mean, that’s the relevance of this. In fact, part of that proposal was, could you use any of this? This was just one part of the proposal.

Could you use any of this work, this, um, scaling work, the fractal like behavior? It’s nature and so on to, um, say, yes, there must have been life or at least there must have been, uh, this is evidence that there could have been life here. Now, the real problem with that is obvious that fractals, I mean, just as Sean, point Sean was making and his seems to be, uh, his mission is to look for non bio, non, non biological things, abiotic processes that sort of mimic life.

And of course, you know, obviously the most obvious one here is rivers. I mean, you know, if there’s been water and rivers, obviously, you know, so the question then is, [00:55:00] can you have enough data that you can distinguish the fractal dimension of those for a biological one? And is that meaningful? And so on. So we, you know, I played around with that for a bit.

It was a, you know, it’s a long shot, but, um, certainly if you saw, you know, if you saw things that had other potential, uh, biological features, This would be evidence that, um, you should add to that, for sure, that if you did see any kind of, um, either remnant or if the thing was actually still, supposedly still alive, that it had this kind of structure, because I did, oh, so one of the things I did believe in all that was that, um, because it was also part of the astrobiology thing, is that if life exists elsewhere, where?

It will have this kind of structure. It will have to be networked and it will try to [00:56:00] optimize and it will have evolved. Therefore, it will have quarter powers. So that was sort of the, uh, the speculative argument. Maybe this is a

James Robinson: good segue onto. cities, because I think if we, if we were to look up through a telescope and look at a city on, you know, discover an alien city, it would probably have some very similar properties to, um, the cities here on earth as well.

Um, because as you found cities also behave remarkably similarly in many ways to, to, to organisms. So perhaps take us through, well, You know, how did that next leap in your career come about?

Geoffrey West: Yeah. So that was, um, so it was pretty clear once, you know, one of the things we didn’t talk about yet, and we may or may not come back to, is that this work, I did say it applied to many things.

We took it into many different areas of biology, understanding growth, [00:57:00] understanding, um, some aspects of cancer.

James Robinson: Perhaps we can talk about that first if, yeah, I’m,

Geoffrey West: well, it might be good to talk about growth actually briefly, because there’s a big contrast with cities there. So growth in this works in a very simple way.

You, you, um, take in food and nutrition, you metabolize, you send the metabolic energy through the networks, networks goes to the cells and it, um, maintains them. Um, and replaces ones that have died, and in a growing phase it adds new cells. So that’s, so you can write that down as an equation, it’s controlled by the network, and so on.

But here’s the point, the network, the network that is controlling as the system is growing, That is the supply. The supply is growing in what we call a [00:58:00] sublinear fashion. The three quarters is less than one. And one of the things also didn’t say that that implies that the energy needed to support a cell.

Is less, the bigger you are, it decreases systematically the bigger you are, according to this quarter power law. So, um, you know, your cells are working, uh, less hard than your dogs, but your horse is working less hard than you. Um, so going back to the growth that’s supplying the cells, but the supply is decreasing.

As the system gets bigger because it’s only decreasing per cell as it’s getting bigger because you’re adding in a linear fashion, you just keep adding cells. So you’re adding the demand is growing faster than the supply, because the supply is growing in the sublinear, [00:59:00] the demand is growing approximately linear, linear always beats sublinear, therefore you stop.

So you can derive the equation, it says, and the solution says you grow quickly at the beginning, and then gradually as the, um, uh, the, the supply Beats out the demand as the, the, uh, the demand beats the supply. Uh, you stop, that’s why you stop and derive. And it’s quite beautiful actually. And you can see that if you rescale accordingly.

All organisms can be, and you look through the right lens, all organisms grow following the same curve. And, uh, so that’s great. And that stability, that, that stable configuration that we end in, that most organisms end in, not all, um, plays obviously a hugely important role. In the long term [01:00:00] sustainability of the biosphere, because you’re spending most of your time in a kind of meta stable state, rather than continually changing.

So, um, and I’m gonna, I’m, I’m, so we needed to go through that because when we come to cities, you’ll see it’s not like that. So here’s what cities, so cities, so we got into this because I moved to the Sanofi Institute because of this work and the Sanofi Institute is this extraordinary place where people from all disciplines, all backgrounds, all stages of their career are all together in one place and all kinds of.

interesting collaborations, interactions, integrations take place. Um, so, I was giving a talk on some of this, and, uh, in the audience were two visitors, um, on sabbatical. One was a well known anthropologist, Sander van der Leuuw [01:01:00] from Paris, and the other was a well known economist, statistician, David Lane.

And they said what I’d already thought about. I brought it up in the talk, actually. I said, you know, It would be really interesting to take this paradigm, as a physicist, it would be really interesting to take this paradigm and apply it to other systems, like companies, I said, and possibly cities, I said, you know, because they’re networks, they’re sort of organismic in some way, and these guys, Went sort of bonkers and said, fantastic.

That’s what we should be doing. You know, so we put together a proposal, which was funded. That one was fun. Jen very generously, may I say, and, uh, it got me working on, oh, I was going to work on companies because I thought they were, they were much more interesting than cities. I thought cities were boring, but it turns out I, in my naivete, I hadn’t realized that you couldn’t get.

data on companies without buying it, [01:02:00] you know, that is most of it is, well, it’s almost all proprietary and, uh, um, various, uh, companies have assembled data sets, but you had to pay, I think it was 40, 000 at the time, I should get some large amount of money that we did not have at our disposal. So I said, okay, look.

What we have to do is we have to prove the whole concept of all this by working on this boring problem of cities. Uh, we’ll look at cities and then we’ll motivate that to get funding so we can buy data and do the real problem of companies. So I put together a different collaboration, a lovely bunch of young people who at that, so as the thing from biology where the scaling laws were known here, they basically were not known.

So these guys had to go out, scrape around for the data. [01:03:00] Discovered, to my amazement that uh, indeed, well I was sur well, I wasn’t so surprised that they scale. I was surprised. at the exponent, the analog to the three quarters, because the first work that we did, actually the first work. was with a colleague at, uh, the, um, ETH in Zurich, the, uh, it’s like the MIT of Switzerland, um, Dirk Helbing, and he and his student, and, and, uh, we, we put together, he, we put together some data that showed that cities do scale.

in terms of their, um, infrastructure, just like biology. So that was just biology. You know, if you looked at the roads and various things, um, which are very similar to your cardiovascular system, and you plot various things, they scale in the same way when you plot logarithm against logarithm, they’re nice straight lines.

Um, the only difference being that the [01:04:00] slope It was 75. Okay. So we need to understand that. But then the collaboration grew and it expanded into socioeconomic quantities. And there was the big surprise, uh, and the surprise was that not, well, first of all, it confirmed that things scale. Socioeconomic means things like wages, number of patents.

Um, not a crime, uh, not a flu, you know, anything that’s involving interaction of human beings directly. And all those scaled, but they scaled instead of sub linearly, less than one, super linearly, bigger than one. So. And I’m embarrassed to say I was surprised when I first saw that, in fact, I said something must be wrong.

It took me, it took me a good 20 [01:05:00] minutes to realize that I was completely wrong. And I completely switched and said, my God, of course, I’m, that’s, it’s, it’s exactly right. That things that are socioeconomic should scale. Bigger than one because the bigger you are, what bigger than one means, the bigger you are, the more you have per capita.

So the bigger the city, the higher the wages, the more restaurants per capita, um, the more inventions, the more patents per capita, and so on. So I said, it’s obvious, that’s right. We should have guessed that a priori. And I was really, I still kick myself that I hadn’t thought of that and written it into the proposal, written it somewhere because I can’t claim I predicted it.

That’s for sure. So, um, so the sum total of all this was something that was really, um, very satisfying. We looked at [01:06:00] data across the globe. So that meant North America, Central America. Oh no. Hilarious. Sorry. Central America, North America, South America, Europe, Asia, that means China, Japan, let’s see where else, I don’t know, wherever we could find data.

And what we found was the same scaling everywhere for the same thing. And that was kind of mind blowing. That was great. But we discovered that all infrastructure, roughly. That means roads, electrical lines, water lines, scaled with the same exponent, which was about 0. 85, um, across the globe, the same way, roughly speaking, um, but all socioeconomic quantities, whether, as I say, good, bad, or ugly, namely wages.

Crime, [01:07:00] disease, all scaled with the same exponent of about 1. 15. So there was, like biology, a kind of universality, um, even though here now it was bifurcated. It was a, you know, it was a dual universality. The infrastructure behaved differently than the, uh, socioeconomic. But the fact that it’s scaled meant that there were universal principles constraining.

The structure, organization, and growth of cities across the globe. So it was almost as if, it was almost as if, uh, you know, in the industrial revolution came and people realized cities. We’re going to grow, they were growing, and a big international convention was gathered and all the countries came together and said, how are we going to design cities?[01:08:00]

And they said, well, we have to do it according to these scaling laws. So it was almost, you know, and of course, it’s all happened organically. And the question is, how, what, what is the organic principles? What are the organic constraints that have led cities, despite the fact that they’re different geographies, different cultures, different histories, the time and energy that went into the politics and the planning individually of each of these places, they all end up sort of lying close to these scaling curves.

So these huge constraints obviously are at work and what are Well, um, uh, I would say that our work and can we derive, of course, A comparable theory that we did, as was done in biology to derive the 0. 85 and 1. 15 and so on. Well, the answer is that we’ve made progress, but it’s still a work in [01:09:00] progress. We understand, we’re very sure of the underlying dynamics, but it’s extremely hard to derive a really fundamental theory that unambiguously gives these answers.

So the idea is the following. The infrastructure is like biology and it’s to do with, again, an optimization. And the idea there is that maybe it’s to do with You know, cities evolved via, you know, they, what is, what is the point of a city? The whole point of a city is to bring people together in order for them to interact, to facilitate interaction, to increase wealth, to have more ideas, to innovate, to increase quality and standard of life.

It’s this incredible machine that we have evolved in the last, you know, several thousand years. So, um. [01:10:00] But as it evolved, um, and people came together, they need to interact. So maybe one of the optimization principles is you try to, uh, the city evolved for people to try to get from point A to point B in the quickest way.

You can get to various, centers in the quickest way. So that was even though the streets are all going, you know, especially, you know, in Europe, I mean, the streets don’t, it’s not a grid. But nevertheless, when people try to go, even now, when you try to go to pick up your kid at school, that’s what you’re doing.

You try to go roughly speaking, the quickest way, maybe it’s the cheapest way. But something is that is an optimization that’s very analogous to the um, kind of optimization that takes place in biology that we talked about earlier. Now, for the socioeconomic, something different, a little bit [01:11:00] different, and that is that you want to optimize, and that’s part of that infrastructure thing, the number of interactions, the rate of interactions, you want to optimize number of interactions, and at the same time, and here’s the kicker, and this is totally speculative, Everybody wants more, everybody wants more of everything, including, you know, everything from material well being to even interaction, you know, they want to go to the theater, they want it and so on.

So that’s sort of the idea. And it’s, and, and the hard part of this is not just putting those into mathematical terms, which you can do, but is integrating these two networks. You can’t talk about them truly separately because. You can’t have a network of interaction. So, by the way, the socio economic interaction.

The flow in the network is really information that’s being exchanged [01:12:00] and in the infrastructural network, it’s energy and resources. So in the bigger picture, a city is the interface and integration between on the one hand, it’s physicality. It’s energy, it’s thermodynamics, if you like, with the exchange, with information exchange in social networks, which are tied to that infrastructure.

And it’s hard to put that into mathematics and it’s still ongoing, but we’re pretty sure. You can show, for example, one of the things that, uh, I, I’m, I’m confident of is that, um, You notice the superlinear is 1. 15, which is 0. 15 above linear, and the 0. 85 is 0. 15 below linear, and that is no accident. That the, you can show that if you do, if you have these [01:13:00] networks integrated, one sort of compensates the other.

And it’s almost as if, The saving that you’re making as the city grows or as you make a bigger city goes into making the city more productive, more exciting, have more interactions, produces more patents, has more crime, is, you know, is more, more opportunities and so on. I mean

James Robinson: intuitively that that feels right like if I can get to the if it’s that much easier to get to a restaurant because it’s that much closer I’m going to go there and you know I’m going to have more interactions um yeah it’s Again, it’s, it’s worth just pausing for a minute to cash out some of the implications of this, just crunching the numbers that firstly as cities get bigger in a way they get more efficient, just like [01:14:00] organisms.

So you double the size of, um, a city and it’s only consuming 75 percent more. Resources. Um, and I’ve heard you say New York is the greener city. 85. Sorry. 85. Yes. 85. The wrong. I was still still on the biological. Yeah, yeah. Uh, yeah. So you, so you, you’re making a 15%

Geoffrey West: saving. Yeah. Which is huge, enormous. I mean, you don’t have many doublings to do your.

Way ahead. So the curious thing about this was that, you know, so much. So during COVID during a pandemic, um, much better be in a small town because the interactions are much less and you’re much less likely. to have catch COVID in a small town than you are in a big city. So that’s obvious in a certain way, but you can put numbers to that actually.

It’s much faster in [01:15:00] a big city. So that’s the point. You’re going to get it much faster than you are in a small town. You know, if you want to sort of buzzier, sexier life, better be in a big city.

James Robinson: Yeah, and that’s, you know, it’s almost paradoxical that the energy uses is lower, but it is the pace of life is, is faster.

And I do want to comment here as well, that it’s so intriguing that for the longest time people have talked about cities in this anthropomorphic or maybe biomorphic way, um, I was thinking of the, uh, there’s that last line of Wordsworth’s, um, poem on, on West, on Westminster Bridge where he says, he’s looking at London from Westminster Bridge and he says, um, You know, all that mighty heart is lying still.

So that’s London at night in, um, 18, the 19th century, uh, 1802, um, so there is this intuition that cities are lively cities, never sleep, you know, all [01:16:00] these kinds of attributions of, uh, animal characteristics to them. And it turns out that in a certain sense, they, they do behave something like. Organisms and, and not following exactly the same scaling laws.

Um, but

Geoffrey West: nonetheless, But there’s this super linearity.

James Robinson: And that’s very

Geoffrey West: different. So that’s the point of departure. Yeah. Where, and that comes about. So how does that, that comes about because the city brings people together. And so you have a situation that A talks to B, B talks to C, C talks back to A. And you build on each other.

You’re continually having positive feedback in those interactions, and, you know, you’re creating ideas all the time. Now, all those ideas are useless and pointless to anybody else, mostly, and they die very quickly. But the whole point is that. The spirit of that dynamic has led to the theory of [01:17:00] relativity.

It led to Amazon, and it led to, you know, General Motors, and so on. That’s, that’s the process. The city does that. That’s why universities mostly are in big cities.

James Robinson: Yeah, I think, I do find the, the Einstein example interesting because I’m always struck that, that he was, you know, a patent clerk in, in Bern, which I went to once and it seemed like a very sleepy city.

Oh, it’s

Geoffrey West: still a city, it’s still a city. And, you know, it’s, it’s, it’s that the ideas around that now Einstein, of course, made a, you know, phase transition, a huge, enormous leap, but you know, it’s like, it’s sort of like the Newtonian, if I’ve seen further, it’s because I stood on the shoulders of giants, it’s not like Einstein did it totally in a vacuum, he had all that stuff behind him, which came out of it.

Urban living, you know, I mean, I mean, places, I mean, Oxford and [01:18:00] Cambridge have this sort of ivory tower image, but they’re actually cities and of themselves, they are cities. I mean, you bring people together and that’s what, and so city, you know, I think you have to extend even the, um, the idea of a city, you know, it’s, um, it’s really the network of people that are connected, uh, it’s, it’s the network of people that are interacting.

James Robinson: Yeah. It’s, it’s, um, Yeah, and it’s curious, I guess, even if Einstein wasn’t actually the greatest physicist, he had access to all the resources. It made me think of you going to the library to get those books on biology, you know, that’s one of the complicated things that the city

Geoffrey West: discuss with other people, you know, including his wife, of course, who didn’t get credit.

But, uh, so who was a physicist, but anyway, yeah, that’s a, [01:19:00] that’s a deep, those things are urban, you know, come out of Some urban kind of environment. One thing I’m

James Robinson: intrigued about is how much of the additional productivity that can be measured is in some ways, firstly, possibly an accounting trick in that, you know, I can tell you a joke now.

And if you find it funny, you might laugh, but you’re not going to pay me for it. But if I go across the road and I go to this, the stand, this, this famous comedy club, and I tell a joke that I might just get paid. I mean, it’s unlikely, but you know, I’m not consuming any more resources or doing anything different really.

Um, but I, you know, something that is economically measurable results there. And I think there’s like a, there’s a motivating effect of living in cities to do that because everything’s so. Everything is so expensive and perhaps there’s also some social competition going on as well. So what I wonder is [01:20:00] how much of it is to do with us producing more ideas through interactions and how much of it is the capture, commercialization and dissemination of ideas and products based on ideas that is motivated by this kind of boiler room of a city.

Geoffrey West: Well, I think it’s both, of course. It is both, but you know, both of them are requiring enormous resources. You know, it’s not like, I mean, there’s this image, you know, when you, when you say thoughts, for example, your first way you think, well, thought doesn’t cost anything. Of course it does. I mean, first of all, it costs a little bit of metabolic energy, but that’s, but what it does, it costs in your head, you have to be there.

You have to be in that house. You have to heat the house. You have transportation. You have entertainment. You have all of Edinburgh there. And that all goes into producing that thought. I mean, that thought [01:21:00] costs actually a lot of money, and it’s much more expensive, that thought. than a thought that took place 200 years ago, actually, because the infrastructure needed to keep you here and doing that is much higher.

So it’s quite complex, all of that. I mean, so you’re right. I mean, and that’s what makes trying to really have a. You know, what kind of universal theory of how this all works. I mean, after all, what we’re getting into here is almost socioeconomics. You know, we’re sort of crossing into other boundaries, other fields here, of course, where people try to think of these things.

But, um, it’s, it’s highly non trivial. And, uh, but the scaling laws, to me, are, were a window onto opening up some of this territory to try to understand what that dynamic is. And why cities are so important and, uh, and, and I see them [01:22:00] as almost obviously, it seems to me, the whole future of the planet depends on what happens in cities.

Um, that’s primarily because, first of all, more than half the globe lives in cities. Um, it’s going to be more like. 75 percent before too long, um, and that’s where almost all the ideas are created, you know, the image, the image of the, you know, the guru going on top of the mountain, or even that image of Einstein, who’s the nearest we have to it, um, is, you know, is very misleading, I think.

The vast majority of ideas and things do occur in an urban kind of environment. And, you know, it wasn’t like, um, you know, as we’ve already, you know, I’m maybe beating a dead horse here. Einstein didn’t come out of nowhere. Yeah, yeah, yeah. There was a whole century of puzzlement, [01:23:00] yeah, yeah. Yeah, he had all that stuff behind him.

But anyway, um, but what I wanted to do was, uh, to now really distinguish. a really important part between cities and organisms. As I said, there’s this positive feedback. So you have the superlinear, you get bigger you are, the more you have per capita, rather than in biology, the bigger you are, the less you need per capita.

Um, so, uh, in terms of growth, because When you go to growth and you have the same idea, you know, you take that same, um, structure that you have in, in biology, it was you have the metabolic rate that gets apportioned between maintenance on the one hand and growth on the other. Here you have to invoke something called social metabolic rate.

So you could imagine we’ve sort of implicitly been talking about it, the sort [01:24:00] of energy, including the information, and the information translated to energy units, if you’d like the energy. That is coming in to say let’s just just take a city for the moment coming into the city that’s driving everything and what it’s doing on the one hand is maintaining the city as it is.

And it’s repairing the roads and the buildings and repairing the people with doctors and hospitals and so on. So it’s doing all that maintenance work. But then of course, um, uh, part of it is being a portion to growing new stuff, growing new buildings, roads, developing different areas, adding new people and so forth.

Well, the difference here now is that the driving force, the supply. Is now growing with size as distinct from decreasing with size on a per capita basis. Uh, but the, um, the, the demand is still [01:25:00] sort of just adding. So what happens is that the supply completely outruns the demand. So instead of growing and then stopping, you just continually grow.

Not only do you grow faster and faster and faster. Which is what we see. In fact, you end up growing faster than exponential. Yeah. And that’s because

James Robinson: That’s pretty much what happened. I guess, the reason you’re growing faster than exponential is that for a city of a given, as you double a city, it, it It more than doubles the, um, the, the sort of creativity, the buzz and so on.

Um, and well, that on its own is exponential, but that is then compound that leads to attracting more people into the city. It’s

Geoffrey West: a positive, it’s a. It’s a very fast positive feedback [01:26:00] phenomenon. Yeah. And that’s been the history from, especially since the Industrial Revolution, of course. Um, that has been the history of cities in, in almost across the globe, but certainly in all industrialized nations.

And um, and that’s what we’ve seen. And so actually the theory. As it stands is very satisfying because we say look we have at the basis we have social networks where we have this positive feedback which gives rise to super linear scaling and the super linear scaling then gives rise to super exponential growth and that’s what we see so it’s actually it’s a it’s a nice theory it’s got still as I say work in progress to really get to the fundamentals but um It’s a, it’s a very complete picture.

Um, but it has some weird consequences and some very disturbing consequences. And that is that, that, that open [01:27:00] ended growth. Which we love and which is the paradigm, you know, since the, uh, industrial revolution and the, um, discovery of fossil fuels and their exploitation and capitalism and entrepreneurship and all these marvelous things that allow us to do what we’re doing now.

Um, that, um, so that’s the result of all that, but unfortunately the mathematics of it has built into it something that’s called a finite time singularity. This word singularity now comes in and what that means in English is simply that that growth curve going up reaches an infinite number in a finite time.

So, um, what it’s so that, you know, you’ll have the number of, uh, of, of patents or the number of AIDS cases will become infinite. in some finite time. Finite time could be [01:28:00] 10 years, 50 years, 100 years, whatever. We don’t, but in some fine, not infinite time. And that’s obviously crazy. It can’t obviously, it doesn’t make any sense.

But the theory tells you what happens. It says that as you go up and you approach the singularity, um, what happens is that you would then. Um, sort of stagnate and then collapse. So it’s sort of a sophisticated Malthusian argument that you can’t, it’s, you can’t sustain that kind of growth. Now Malthus got it wrong and he got it wrong for good, for good reasons.

I mean, he was attacked and I think for the right reasons, namely that, um, uh, you didn’t take into account that people are going to innovate. You know, and it gets you out of that, you know, he said that agriculture, agriculture could not keep up with the increase in population because population increases [01:29:00] exponentially and agriculture was linear and he was wrong.

Um, but so taking that idea to this theory, and this now is based on, you know, this agrees with data, so it has some, some serious credibility. So as. As this thing goes up and, uh, reaches a singularity, what it, what you realize is that that, what I told you is sort of assuming that, you know, in the big picture, nothing has changed, you know, uh, we’re in some major paradigm that, uh, like the industrial revolution or going way back the bronze age or the stone age, you know, something that dominated somehow The way people structured society and the tools they used and so on.

Uh, in modern times that would be, you know, the computer and most recently the internet. [01:30:00] You know, that’s sort of a, so these big paradigm shifts, these huge innovations, which, um, set the tone and the culture of the way that growth takes place. They sort of fix the parameters in a certain sense. So that gives you a hint as to how you get out of this.

What it says is you do what we’ve done, namely, as you grow this, this very fast, super exponential way. Before you reach the singularity, you better make a major innovation, a major paradigm shift. You better reinvent yourself. You better reset the boundary conditions, start over again, which is effectively what we’ve done.

So we go along these curves, you’re approaching a singularity, you discover, I don’t know, coal. Boom. Then you discover, well, more recently, You invent computers, as I say, [01:31:00] then you invent the internet and so on. And so that’s great. That’s what we’ve done. The hitch to this is that, uh, something I haven’t talked about.

And that is that as the system grows, the pace of life increases, things get faster. Yeah. Everything gets faster. The, um, and, um, in fact, we’ve looked at data and the data supports that in agreement with the predictions. Um, so, um, and indeed, one of the things that has to get faster is you have to innovate faster and faster.

So an innovation that might have taken, you know, 50 to 100 years to really develop 1, 000 years ago, make this up, uh, now would only take 10 or 15 years, but you have to do a new one, you know, how long has it been, you know, the internet age is what, 20 years old, [01:32:00] maybe, I don’t know, um, we’re going to have to do another one like it, maybe in 15 years, or we’re going to have to do one soon, I don’t know.

In fact, you can fill the air, the world, you know, so the pace of life is increasing. We have to do things faster and faster. You have to innovate faster and faster. If you don’t, you’ll collapse. And we’re now approaching such a point again, a singularity, and we have to make some major shift, maybe in the next, you know, 10 to 20 years.

And we don’t know, of course, can’t predict what that is. We can guess, we can speculate as to what that is. But the point is, that a major people were right in criticizing Malthus and people like the club of Rome and people like Paul Ehrlich who all predicted collapse because none of them seriously took into account innovation.

The things change that you’re going to make a [01:33:00] major innovation. This does take that into account and it says Yes, you can postpone the collapse, but you can’t stop it because you’re just putting off to the next time and you got to do it again, you got to make another innovation, but you have to do it quicker than you did the last one and so on and so forth.

So if you took a sort of reductio ad absurdum view of this, um, you’d have to end up making a major innovation, you know, sort of every month, which is ridiculous. So, um, so this has built into it. It’s the collapse of the system and the question is how do you get out of that and I’m happy to speculate. But my goodness,

James Robinson: it is a big question.

I wanted to comment just on the, um, I mean, another interesting point of departure between Malthus and. Your ideas is that they were looking at exponential growth, [01:34:00] which is only going to become infinity and infinity and infinity. I mean, that wasn’t the essential problem with their ideas because sure enough, like once you have enough consumption, it doesn’t have to be infinite consumption before it out, it outstrips, um, your production, but as you say, they, they ignored the, yeah, the, the innovation that has happened in cycles and.

And it seems is happening in quicker and quicker cycles. What comes to my mind is chat GPT claiming to be the most quickly adopted tool in history and getting to a hundred million users within weeks, which, um, I have no reason to disbelieve them. In fact, I have more reason to believe them, you know, looking at the history of, of, of product adoption.

Um, But it does seem that at some point, just biological limits are going to call a halt to this. I mean, several things come to mind. In your book, you have this wonderful example of walking pace, [01:35:00] which increases, um, frustratingly at the, you know, uh, not with the 1. 15 exponent, but it gets 10 percent faster every time you double the size of a city, which just one is wonderful.

But clearly, you know, if, if you. I, I did the maths just earlier, and if you put the whole of me, the whole of the U S in, um, New York, I’m just trying to look up my calculation. It was, what was it? I think, I think then that came out to maybe. 12 miles an hour, which wasn’t too bad. It’s like jogging. But then if you put the whole of China into one city, you get, you get like 350 miles an hour and maybe that’ll happen.

Maybe we’ll sort of turn ourselves into cyborgs or we’ll be going around with roller skates or something, but I don’t, I don’t think that’s going to happen. Um, and you know, one can get even more fundamental and say, look, well, the density of cities increases with, with, with size, but presumably we’re not going to create black holes [01:36:00] because, you know, before we get to that point, we’re just going to say, this is too cramped.

I don’t like it.

Geoffrey West: But you’ve raised a really important point because, uh, which I’ve pondered. Um, and that is that, um, all this has changed. You know, since, since we formed cities, this whole dynamic has been in place. It was very slow until the industrial revolution, and now it’s gone bonkers, you know, in the last 200 years.

And, um, it’s, it’s accelerated in a kind of uncontrolled way. Yet, we are the same biology. We’re the same, not only as we were when we were hunter gatherers. and started becoming sedentary 10, 000 years ago, but 100, 000 years ago or longer with basically the same, the same brain. And yet we’ve adapted extraordinarily to this.

So that’s, first of all, brings up an interesting question of itself, which I find intriguing. [01:37:00] How, you know, how, how has our brain been able to adapt so extraordinarily quickly? To this fast changing environment that we’re in, I mean, that of itself, but then the follow up question, which is the one that I find most intriguing is what is the limit to that?

You can’t have, I mean, it’s, it’s the same thing as, you know, um, in the physical world. As a thing from the neural world, you know, someone could run 100 meters in 9. 8 seconds. Someone may well run it in 9. 7 or 9. 6, and even conceivably in 9, but what about 5 seconds or 2 seconds? Or one second. Well, it’s obviously ridiculous.

You can’t, wouldn’t be a human being, in fact. So there is a limit. We don’t know quite where it is. It’s probably a close city approaching it for running, [01:38:00] but maybe that’s true of our neurological capacity. When is it, and already you can feel that, you can feel that with the extraordinary changes that are taking place with the, you know, the new gadgets and new inventions and every year there’s another bloody new iPhone that you have to adapt to or whatever, and I, you know, I’m 83 and I have to adapt to it.

Suddenly, my colleagues decide we’ve got to use Overleaf, so I have to learn Overleaf. Oh no, now we’re going to do a Google Docs. Now, it sounds trivial, but you know, these things are, and I’m, you know, I’m reasonably smart. You know, a lot of people Have a struggle with that and they have the equivalent of that um, and they feel disenfranchised almost and uh, and so my conclusion is if you’re like that you vote for trump [01:39:00] because He provides a simple solution, whereas all this other stuff is so complex.

So that is my, that

James Robinson: is a theory of everything, you know,

Geoffrey West: my point there is I’m being totally sarcastic and silly, but my point there is, are we approaching a time? When our brains, our neurology simply cannot adapt to the technology we’re creating. And it may well be that we’ve solved the problem with GPT.

I don’t know, maybe that, that will do it. Or maybe chat GPT is the next major AI. Looks like it may well be the next huge paradigm shift. Just like the internet was may not be it’s too it’s well, I mean despite all the hype. I think it’s way too early to tell It certainly is extraordinary. [01:40:00] I gave you a little problem the other day, very simple problem, and it got it completely wrong, by the way.

You know, as, as it does, I mean, inevitably it’s very human, I have to say. Yeah,

James Robinson: I think, I think it’s extraordinarily good at, um, particular fields of programming and quite broad ones. And, and so I, I, I know I’m convinced that in certain places it is going to. Accelerate production of things and it will be a paradigm shift for the development of software.

Geoffrey West: Absolutely. My fear is mostly that it’s, um, we’re going to give so much, I mean, I already hear it, of course, so much over to it, AI and machine learning. Um, that, um, all kinds of terrible things are going to happen. Um, that, uh, you know, because people are so naive. Because most of the people that do this, that make these decisions, have absolutely no idea how this thing works, and what it is, and what its consequences might be.

I mean, it’s quite [01:41:00] irresponsible, but you know, that’s the way of the world.

James Robinson: Well, we’re, we’re running up against time. Um, and that’s another constraint that, that seems very human. We’re probably not going to be speaking at a million words per minute in the year 2100 unless we have interfaced with chat, GVT and so forth.

But, um, But I do, yeah, this throws up so many questions and I just wonder, do you, have you pondered what the answers might be? It seems like we can’t carry on speeding up. Perhaps there’ll be a natural biological break that’s applied, but one has to fear that perhaps that would come too late. Yes.

Geoffrey West: So I don’t know.

I, I, you know, obviously it’s all spec. I mean, by the way, needless to say. A large part of what I, the last, you know, I don’t know, even half hour, 20 minutes, [01:42:00] is speculative, clearly. It’s a different character than the first part of the discussion, but a part that’s very extremely interesting and enjoyable and should be, one should participate in, I think.

Um, but, um, so my, So I got very despondent with some of this, you know, I mean, that is that I couldn’t see how we’re going to get out of this. It looks like the system’s doomed to collapse eventually. Um, that, uh, even, you know, and that may be wrong now. I didn’t, I must admit, I was, like many others, taken by surprise.

by how powerful ChatGBT was. I mean, I knew a lot about AI because Center for the Institute has been involved in AI since its beginnings. I mean, AI has been around for 50 years in various forms. Um, but that was a very serious breakthrough. Um, and as you say, will have profound effects in various [01:43:00] parts of, um, you know, productivity, culture and so on.

But, um, so maybe that, That qualitatively also will change things, I don’t know. I sort of think not, that we’ll still run into the same kinds of problems, um, because one of the things that you realize in all this, so it doesn’t matter how much science one does, the future of the planet lies with politicians.

You know, that is policy makers anyway, people, I mean, they make the decisions, they do it. So, you know, I mean. Global warming is a classic example. I mean, only a minority of people really pay serious attention to it. And, uh, you know, we’re not really addressing the problems. Um, so it needs that. So that led me to the crazy idea maybe that, um, well, first of all, a paradigm shift when I, when you [01:44:00] use the word paradigm shift or major innovation, what immediately comes to mind Is a new technology, you know, that’s, that’s the way we’ve talked about it in the past, especially in more recent years, that’s been the way we talk about it.

And we just talked about another one, AI, but, um, innovation and paradigm shifts, of course, in no way connotes that has to be technological. Um, it, it could be cultural or political and so forth, who knows. And so, um, it led me to this really, I’m almost embarrassed to bring it up, but the idea that, you know, what we really need is an, is what I call an anti Trump.

You know, you need someone with the charisma and apparent attraction of, uh, of a Donald Trump, namely someone that can change people’s, what we [01:45:00] presume to be fundamental views in one year. That is, you know, they don’t have to believe in truth. They don’t need evidence. They can discard science if they wish, and so on.

We need someone that does exactly the opposite. That sort of promotes, sort of a Jesus Christ, or a Martin Luther King, or, I don’t know, Nelson Mandela. That somehow, instead of tapping in to some of the darker sides that we all have, Uh, somehow it, um, taps into, is the spark that sets off a coherent collective effect of the good in people.

I know this sounds all very naive, and 1960s, maybe that’s what I’m influenced by, but that It’s not. You know, that, that promotes love, love thy neighbor, that, uh, connotes the idea [01:46:00] of collective behavior, that we don’t have to continually want everything and have everything, that, you know, that, I mean, it is weird.

I mean, roughly speaking, the quality and standard of life probably has monotonically increased, maybe at a slower rate, for the last, I don’t know how many years, you know, I mean, when you think of the things around you, I mean, I don’t know how old you are, but certainly at my age, if I think of life now compared to 20, 40, 60, 80 years ago, the change is absolutely extraordinary.

And it has been going on. But so why is it? That with that happening, people are so unhappy and so disgruntled and want to have authoritarian rule. Why could, how can that be? I mean, do you think, I mean, the assumption would be the opposite. We want to reach out to more and be more [01:47:00] giving and less wanting.

So it needs someone that does that, that can somehow articulate that. And, uh, somehow re, re, re center the direction and focus of human beings, because it’s fairly universal. What a wonderful note to end on. It’s all flaky, you better not show any of that, it’s all a bit,

James Robinson: it’s all rather flaky. But I think what, what is fascinating to me is that, you know, while you’ve studied these Networks and found what seems to be almost inevitable laws.

They’re clearly not that we have a means of pushing back against these dynamics and deciding the networks that we have around us and how we interact with them. And, you know. It does come down to individuals and maybe one person [01:48:00] convincing the collective to behave differently. But, uh, yeah, one can’t, it doesn’t seem, it doesn’t seem clear that we can engineer our way out of this solution with a new technology.

But as you say, maybe the paradigm shift is not a technological one, but a shift of

Geoffrey West: perspective. By the way, I’m glad you said something I should have said much earlier. You know, the nature of these laws. These are not like Newton’s laws, you know, or Maxwell’s equations, or theory of relativity, or quantum mechanics.

First of all, these laws are stochastic, meaning there’s lots of variance. That’s one of the big questions, how much variance in all these laws, in the biology, or the social ones. So, um, there’s that. And then there’s the other, that To what extent can you, you know, if you believe everything I’ve talked about, [01:49:00] then the problems we’re facing, and it’s sort of obvious, and we are rooted in our social networks.

And the question is, are they a given? Have they, you know, are they so ingrained in our DNA that we can’t change them? Or are they quite cultural? And actually with great effort, We can change things in the city. You know, is it, is it like we can stop smoking or wear seatbelts or is it sort of like, you know, this is who we are.

Don’t know if anyone knows the answer to that. Well, I think

James Robinson: anyone can stop smoking if they, you know, if the cigarettes go away and it might be similar to. You know, if we, perhaps that technology does have something to answer for here. The, the way that technology has been developed has been growth focused, but not direction focused, I think.

Um, [01:50:00] and social media has, has been developed to capture our attention, but not direct our attention where it ought to go. I suppose. That’s right.

Geoffrey West: And it goes for, and it tends to go to the odds, whatever the metric is least common denominator. Right. Well, I hope we’ve Yes, I have to go, actually.

James Robinson: I think with this podcast, we’re sort of doing our bit to push back against that.

Geoffrey West: Maybe.

James Robinson: Thank you so much. This has been, yeah, such a, such a tour de force, just like your book. So, um, thanks again. Thank you so

Geoffrey West: much. Appreciate it.

Peter Nixey: AI — Disruption Ahead

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. … Read more

David Papineau: How Philosophy Serves Science

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 … Read more

Moral philosophy as puzzles of daily life — Paulina Sliwa

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 equally enjoyed seeing how Paulina thinks, it’s a wonderful example of philosophical tools at work.

(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

Astrobiology: what is life & how to know it when we see it — Sean McMahon

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.


(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)

How & why do animals play? — Gordon Burghardt

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.


Gordon Burghardt — Multiverses Podcast


(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