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Oh, we got another comment.

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People hate this is interesting to the theory of humor.

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Some people hate our screwing up the intro.

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Like uh, like there's a comment on X where somebody's like, Well, what it's it's really

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interesting, actually.

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I don't know.

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I wonder why people get so pissed off about that.

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Yeah, I don't know.

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Yeah, I don't know.

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All right.

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Yeah.

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This is Evolutionary Psychology the Podcast.

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I'm David Pietrazuski.

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I'm David Pinsov, and this is actual evolutionary psychology.

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By actual evolutionary psychologists.

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David, I am really excited about this episode.

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Today we have two guests.

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Uh Christina Moya, who's returner, who is a guest co-host, and our

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guest proper is Rob Boyd.

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Yes.

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This was a really fun and interesting episode.

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Uh many tidbits about E.

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coli bacteria and Enola lizards and anecdotes from you know

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evolutionary biology, mathematics.

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What was so interesting about this is um there was some disagreements that we we navigated.

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Uh and we usually don't navigate too many disagreements on this podcast because um Dave and

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I are optimally rational agents who uh who cannot disagree on anything.

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Yes, and to the extent that we do we we we disagree, we we quickly realize largely that

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we're we're just exploring the larger space that we would both agree about from different

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perspectives.

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Yes, but uh Rob Boyd and Pete Richardson uh pioneered the study

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of cultural evolution, the the modeling of culture as its own kind of

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evolutionary process, and the story of how culture uh has been involved in the evolution of

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humanity and what role it has played uh in our preeminence

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on this planet.

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And I think we're still trying to reconcile how this analysis of

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culture can be fit into the Darwinian paradigm or the

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evolutionary behavioral sciences.

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I think Dave and I are of the camp that uh it can be reconciled, that this view of cultural

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evolution is compatible with even the most extreme Santa Barbara uh evolutionary

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psychology model of the mind.

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And we try to explore that, but at the end of the day, there may still be some

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disagreements, and that's part of what makes science fun and awesome is that we get to

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disagree with each other and do some research and get to the bottom of it.

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Yeah, I think I and I think this episode is a lovely example of Rob, is an incredibly

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brilliant.

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I mean, he is a giant whose uh shoulders we're all standing on.

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And a lot of what we take for granted, our our generation, meaning like David and I's uh

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generation, is because of John.

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Um, John and Lita and Rob and Joan and other folks like that.

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And I think Rob talked a lot.

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We talked also about that and just sort of the debates that were had um in their

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generation were sort of necessary for uh for coming to uh what you know uh

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you me and christina's uh view is now and not everybody agrees with us but that's that's

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part of the fun it's also a good example of uh not disagreeing to the point of vilifying

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but do the opposite of like we're all friends we can all be nice uh interpersonally but

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still disagree um uh or have debates we should that's the point of science yep absolutely.

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So it was it was a really fun time uh chatting with Rob and Christina about these big

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issues confronting the evolutionary social sciences and also the history of our field and

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how our field itself has evolved.

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Um I think you'll get a lot out of this conversation.

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Yeah, enjoy.

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Rob, it's really great to see you.

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Um thanks for being on.

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Um I wanted to start out by asking a simple question, which is um when

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I when I think of you and Pete's uh and other people's work, um the

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the sort of not by genes alone expression.

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Um so the idea of sort of uh biological evolution and gene uh gene

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selection um being adequate for an

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organism to be adapted or survive in an environment.

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My understanding is that one of the things that you did was

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to think about these other selective regimes that are on top of genetic

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selection, like cultural selection, as an additional mechanism.

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Is it accurate to say that that's something that you and the people around you really

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initiated and plugged in?

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Where did that idea come from?

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Um we Pete and I got started

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in the mid-1970s.

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And um it's hard to understand now, actually, um, or hard to

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behavioral ecology, um game theory, you know, evolutionary game theory was

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at best nascent.

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I mean, Hamilton had written these landmark papers in the 60s uh about

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kin selection, about senescence, um uh about sexual bunch of

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stuff.

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And and Maynard Smith had written, uh, and Parker and some other people had

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written these um taken basically the very surface ideas of

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game theory and and shown how they could be used to formalize the frequency dependent

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selection that arises when when you have social interactions of various kinds.

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But uh I mean the the textbook I went to graduate school in 1970 and

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the textbook that was the main textbook in ecology

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was a by a guy named Eugene Odom and it set out as its

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central premise that species evolve for the good of the species.

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And um and in the US, people just didn't think the

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same way that we do now about, you know, I mean, if you want to call it individual

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advantage or gene centered, there are various ways to think about it.

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But but and then in 1976 Wilson published sociobiology, which

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had a huge impact, uh, but was only sort of I mean, he

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never really completely understood, in my view, modern evolutionary theory.

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He was he kinda understood it, but you know, it he was

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still rooted, I think, in in to some degree in the older

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ecological, you know, Tinbergen style picture of things.

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Now things were somewhat different in Great Britain, where people were more centered in the

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in the modern way of thinking about things.

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Anyway, and then Dick Alexander, uh sort of, I think of Dick and

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and uh Wilson as kind of the fathers of American anyway, evolutionary

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thinking.

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And Dick wrote this long paper in uh the annual review of ecology

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and systematics.

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And unlike Wilson, it was completely rooted in the new way of thinking.

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And and was also full.

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I mean, Wilson famously had this last chapter where he said this is all going to change the

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social sciences.

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But it was kind of vague.

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And whereas Alexander got down to cases and I don't know if you ever met Dick but

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he was kind of a dark character in some ways but but very insightful

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guy and the the paper is just full of intriguing ideas about human

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evolution so people did the obvious thing they started thinking you know how how can we

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explain human evolution in evolutionary terms And there's a

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lot of enthusiasm.

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And both Pete and I, our initial reaction is yes, but

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it it doesn't, it's it's not enough that people are are as different from other

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vertebrates as you know uh multicellular organisms are from single cell.

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I mean it's and so anyway, that's why we started thinking about this.

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And so from the start, our idea was to try to understand.

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I mean, I mean, the obvious difference is different groups of people behave differently.

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It must have something to do with non-genetic transmission.

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Try to build a theory where that's something that could be favored by natural selection and

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at the same time lead to divergent results.

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And Mark Feldman and Luca Kowali-Sforza had written this book.

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Well, not a book yet, a bunch of papers in the early and mid-70s showing how you

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could use population genetic ideas, ideas from population genetics theories,

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to think about cultural transmission.

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They were not interested in the same questions we were.

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Mark was has been and still is very interested in genes and IQ and trying to make proper

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inferences from phenotypic variation, you know, amongst families and stuff.

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And only much later became interested in what I think of as the as the adaptationist

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questions, really not until the late 80s and 90s, but we were greatly

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benefited by what they taught, basically, in these papers about how you could use

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ideas in population genetics.

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And in our 84 book, I think what we mainly added was, well,

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two things.

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A bunch of ideas about directional processes that would lead to adapt culturally

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mediated adaptation.

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Because what it's got to be, you know, whatever it is, besides making things different,

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it's if it evolved, it's the system has to make has to be adaptive, the psychology has to

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pay.

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And also, uh, I think the thing that that we did that made people take

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notice was we said, okay, but yeah, how how can you make a system like that evolve

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from an organism that doesn't have a system like that?

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How can it produce fitness benefits?

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Um and then of course we're interested and at the same time you know lead to

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all the weird things that people do so that's uh we got started because we were interested

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in that question and uh we just kept plugging away uh what was the

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was the were the tools that these that was in the water that was new was it this

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frequency dependent the game theory or ESS analysis and then then that was

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the that was sort of the idea that was those were the tools.

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Is that correct?

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Or what would you say are were the well I think the the that was you needed those tools

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to do a proper job of asking what natural selection would do.

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You know, I mean you're making lots of simplifications like usual.

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But what Kavali Sforz and Feldman added and we added was seeing

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that uh once you have sufficiently accurate social

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learning, however that works, it creates another system which carries

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information through time, creates history.

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And in most organisms, I mean there are a bunch of things.

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There's succession and and you know all this extended evolutionary synthesis stuff.

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You know, so Pete Pete was raised on a farm and he likes farming examples.

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And uh if you think about transmitting farms, that's a kind of example of

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how you can have a non-genetic transmission.

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If you inherit a farm, your the behaviors that are good for you, everything else, is

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different than if you don't inherit a farm.

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But farms can't spread the way the idea about how to farm can spread.

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Because energetically small things, you know,

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knowing when to plant and knowing how to fertilize and stuff like that, they can spread

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extremely rapidly because they don't the the information itself doesn't count for much.

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Uh so I think that's personally, I think that's what makes culture different than other

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forms of.

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I mean, fins are a good example, but how you get from fins to legs, um

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uh knowing something about development and knowing something about

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homeobox genes and all these things that that encode developmental rules

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gives you a lot of purchase and understanding.

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So you know the story of TikTolic, this I think it's still the oldest fit, uh

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oldest land vertebrate.

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And this this guy whose work I'm uh what's his name?

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Uh your inner fish um I can't remember his name.

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This is a the hazard of old age.

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But anyway, I can't remember anything from the screen.

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My my proper noun module is failing on me.

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But but um so if you look at the you know, invertebrates, the uh uh

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landvertebrates, the you know, you get one bone in the upper arm, two bones in the next

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length, and then all kinds of little bones.

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You don't get any of that in fish.

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You just get this.

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and the question is, how do you get from fish to land

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vertebrates?

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And this guy whose name I will remember eventually, um he was

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he's a paleontologist.

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He worked on yep in North Greenland on these sediments that had um, you know, uh

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500 million year old um no, that's not right, must be more like 300 million year old,

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anyway, early land vertebrates, and um and he and he found these

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forelimbs of these early fishy um land vertebrates.

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And to understand how you got there from fins, you really do need to understand.

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Well, I don't know if you need, but it it's immensely it makes it much easier to understand

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what happens if you understand how limb development works.

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And so, you know, um, you know, the phenotypic

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gambit gets you why these organisms needed rigid forelimbs and and a bunch

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of other stuff, but it doesn't tell you why they're built the way they are.

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Yeah, no, no, no, for sure.

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It's not the whole picture and it's not satisfying for explaining what what which part of

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organism space to to use the talk.

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Exactly.

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It's yeah evolution is depends on where the variation is.

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And the phenotype gamba just essentially says, I don't know about that, so I'm not going to

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worry about it.

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Exactly.

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And I think this is actually something Christina and I have talked a lot about over the

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decades that that also, you know, you simplify what's not relevant for your particular

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um right goals.

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Right.

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Um and I think, you know, and one of the other things too is, you know, I uh obviously I

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was a student of Lita Cosby's and John Tube.

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Yeah.

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And I know there was a history of, you know, it was sort of uh love and conflict in the

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sense of you both had uh there were similar missions of evolutionizing the human behavioral

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sciences, using evolution to understand human behavior.

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But then there was um and yeah I know Rob, you and I have had conversations over the years

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too.

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Um uh yeah I mean maybe the well yeah and Christina no

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exactly.

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Um uh I mean do you I don't even know where to start with that.

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I don't I don't know if I even have a question, but like that might lead into um yeah I

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think it the contrast I think is um uh

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is useful.

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Uh I mean, and I wouldn't have said was, Lita's still around and right, still working, is

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that right?

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Yeah, no, Lita, yes, of course.

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Yeah, no, Lita's and we spent six months together at a

238
00:16:53,940 --> 00:16:59,940
institute in Germany and um and uh I would say we're

239
00:16:59,940 --> 00:17:05,370
friends, but um or were with John and but

240
00:17:05,690 --> 00:17:10,970
definitely pretty deep disagreements about uh how to think about

241
00:17:11,450 --> 00:17:17,290
both evolution and um and then about human evolution

242
00:17:17,290 --> 00:17:18,170
in particular.

243
00:17:18,410 --> 00:17:24,170
Um I was my evolution training came uh

244
00:17:24,730 --> 00:17:30,220
at UC Davis, which in those days was the

245
00:17:30,220 --> 00:17:33,180
heartland of selectionist biology.

246
00:17:33,740 --> 00:17:39,100
And then I did a postdoc at the University of Chicago, um, where

247
00:17:39,580 --> 00:17:42,700
the there was a renaissance.

248
00:17:42,940 --> 00:17:48,620
Uh it didn't last that long, but uh in uh monitative

249
00:17:48,620 --> 00:17:54,190
genetics and genetics of characters that are affected by genes at many loci.

250
00:17:54,750 --> 00:18:00,110
And and I would say that John and I had real disagreements about,

251
00:18:00,590 --> 00:18:03,790
forget about culture, about how evolution worked.

252
00:18:04,030 --> 00:18:09,710
And um, I mean, I still think I'm right or was right, but but I'm sure he thought the

253
00:18:09,710 --> 00:18:10,110
same.

254
00:18:10,350 --> 00:18:16,260
Uh he had a very fisherian view of of i and i don't really know i never talked to lead

255
00:18:16,420 --> 00:18:21,940
about this very much but s selection being acting on dragging

256
00:18:21,940 --> 00:18:27,940
genes slowly and he put a lot of emphasis on species as a real thing and i think

257
00:18:27,940 --> 00:18:33,620
they're at best an abstraction uh and the picture of evolution that that i think is

258
00:18:34,310 --> 00:18:39,830
is correct is that m most evolution now

259
00:18:39,990 --> 00:18:41,030
isn't always true.

260
00:18:41,190 --> 00:18:47,190
Sometimes it does work in a fisheron way, but but it's working on standing variation.

261
00:18:47,750 --> 00:18:53,510
So I don't know if you take uh so I mean there's been a lot of

262
00:18:53,510 --> 00:18:59,460
water under the bridge since, but um so this guy, John Losos, I don't know if you

263
00:18:59,460 --> 00:19:00,260
know his work at all.

264
00:19:00,420 --> 00:19:05,460
He works on anoles in in um the Caribbean.

265
00:19:05,700 --> 00:19:11,140
And um so it turns out that on each of the Caribbean islands there are

266
00:19:11,460 --> 00:19:15,700
a whole community of these lizards, anoless lizards.

267
00:19:15,860 --> 00:19:19,780
And there's big ones that live in the top of the trees and the little skinny ones that run

268
00:19:19,780 --> 00:19:25,230
along branches, and other ones that hold, you know, and And they've got typical

269
00:19:25,230 --> 00:19:29,710
phenotypic, these are mainly morphological color differences.

270
00:19:29,950 --> 00:19:33,710
And none of the of these guys on the different islands are related.

271
00:19:33,950 --> 00:19:39,630
On each island, these um morphs evolved from some

272
00:19:39,630 --> 00:19:44,430
generalist that made it to the island and then differentiated into all these things.

273
00:19:44,750 --> 00:19:48,120
Okay, not so radical already.

274
00:19:48,280 --> 00:19:53,400
They've done experiments where they in Loso says, and this is there's lots of work like

275
00:19:53,400 --> 00:19:58,600
this now, where they introduce lizards to islands with no lizards.

276
00:19:59,000 --> 00:20:04,520
And within five years, you begin to see

277
00:20:04,840 --> 00:20:10,760
these species first track the ones that run the little branches end up being having shorter

278
00:20:10,760 --> 00:20:14,440
legs, and the ones that live higher up in the trees have longer legs.

279
00:20:15,350 --> 00:20:16,470
but five years.

280
00:20:16,630 --> 00:20:22,470
This isn't gene new mutations happening and being dragged slowly across to fixation.

281
00:20:22,710 --> 00:20:28,630
This is taking standing variation that affects morphology and rapidly

282
00:20:28,630 --> 00:20:29,110
shifting.

283
00:20:29,190 --> 00:20:35,110
And there's lots and lots of examples like this coloration in deer mice, um

284
00:20:35,750 --> 00:20:41,500
uh coloration in guppies, life history variables in guppies.

285
00:20:41,660 --> 00:20:47,420
So you can so in Guppies, there are these

286
00:20:47,420 --> 00:20:49,900
rivers in Trinidad where all this work has been done.

287
00:20:50,060 --> 00:20:54,540
And as you go up the river, eventually you get to a pond above a waterfall where there are

288
00:20:54,540 --> 00:20:55,820
no predators.

289
00:20:56,060 --> 00:21:02,060
And the guppies up there are have slow life histories, and the guppies just below the

290
00:21:02,060 --> 00:21:04,140
waterfall have fast life histories, right?

291
00:21:04,220 --> 00:21:06,380
Because they got to get going before they get eaten.

292
00:21:06,700 --> 00:21:12,370
And so this guy Dave Resnick, who's at at Riverside,

293
00:21:12,530 --> 00:21:17,730
um put various predators, two different kinds of predators in these things above the

294
00:21:17,730 --> 00:21:18,130
things.

295
00:21:18,210 --> 00:21:23,250
And within three or four years, you've got faster life histories.

296
00:21:23,570 --> 00:21:29,250
And um so can I ask if if the implication of this difference

297
00:21:29,960 --> 00:21:35,880
in thinking is that evolution can happen much quicker if it's acting on standing

298
00:21:35,880 --> 00:21:36,520
variation.

299
00:21:36,840 --> 00:21:42,040
But is it also something about the nature of the variation, like that these are something

300
00:21:42,040 --> 00:21:46,680
like packages of traits, something going back a little bit to the phenotypic problems of

301
00:21:46,680 --> 00:21:48,040
the phenotypic gambit?

302
00:21:48,360 --> 00:21:48,600
Yeah.

303
00:21:49,470 --> 00:21:50,590
don't yeah.

304
00:21:50,750 --> 00:21:54,110
Are there constraints that you think are important to consider or no?

305
00:21:55,470 --> 00:21:58,670
There are, I'm certain, but I don't think we know what they are.

306
00:21:58,990 --> 00:22:04,750
I think um so resnik also, I mean, so these are all pretty simple

307
00:22:04,750 --> 00:22:09,230
changes, although life history, I don't think we really understand exactly what's going on

308
00:22:09,230 --> 00:22:09,550
there.

309
00:22:09,790 --> 00:22:15,560
Um but uh he he did uh in the same genus as guppies, but not

310
00:22:15,560 --> 00:22:16,200
guppies.

311
00:22:16,520 --> 00:22:21,480
Um he worked on um the evolution of live birth.

312
00:22:21,880 --> 00:22:26,360
So um uh a lot of fish have live birth.

313
00:22:26,440 --> 00:22:29,000
They retain the eggs inside their bodies.

314
00:22:29,320 --> 00:22:35,270
The the little developing embryos feed on the yolk, and then they have

315
00:22:35,270 --> 00:22:35,910
live birth.

316
00:22:35,990 --> 00:22:37,430
That's not such a big deal.

317
00:22:37,670 --> 00:22:43,030
But there are three species in this genus that have

318
00:22:43,030 --> 00:22:46,390
evolved placentas, basically.

319
00:22:46,550 --> 00:22:50,710
So they they lay eggs with hardly any yolk.

320
00:22:50,950 --> 00:22:56,710
And then they have uh an organ that uh it's not like our placenta

321
00:22:56,790 --> 00:23:02,390
particularly, it's designed differently, but still it's a complex organ whose job it is

322
00:23:02,710 --> 00:23:08,480
to provide nutrients to these little developing embryos

323
00:23:08,480 --> 00:23:10,640
that don't have any yolk to eat.

324
00:23:11,040 --> 00:23:16,080
And uh at a minimum, they've evolved that those have evolved in

325
00:23:16,080 --> 00:23:21,760
250,000 years in one of the species, maybe a million in the other two.

326
00:23:21,920 --> 00:23:22,800
And that's a minimum.

327
00:23:22,880 --> 00:23:27,760
That's from the last common ancestor that doesn't that doesn't have this tray.

328
00:23:28,160 --> 00:23:33,970
Um, So I don't think we really know about the evolution of I mean

329
00:23:34,130 --> 00:23:37,810
simple things like morphology, we know for sure that can evolve fast.

330
00:23:38,450 --> 00:23:44,130
And it it evolves fast, not because it's one gene, it evolves fast because it's many

331
00:23:44,130 --> 00:23:46,290
genes, each with small effect.

332
00:23:50,050 --> 00:23:54,610
You make a wolf into a Pekinese and you know, in hardly any time at all.

333
00:23:54,860 --> 00:24:00,860
And and I don't think we know about um but I do think it makes you think

334
00:24:00,860 --> 00:24:06,460
twice about the EEA and and th that our mind

335
00:24:06,780 --> 00:24:12,780
is a or our brain is a series of modules that were designed to deal

336
00:24:12,780 --> 00:24:16,460
with things ten thousand years ago and haven't changed since.

337
00:24:16,620 --> 00:24:22,470
Uh I actually think this is a problem that so my colleague here, um uh

338
00:24:22,630 --> 00:24:27,510
Kevin Langergraber has has argued that chimps have menopause.

339
00:24:27,590 --> 00:24:32,470
Uh and that's hugely controversial right this second, and people argue back and forth.

340
00:24:32,630 --> 00:24:34,710
I don't want to get in the middle of that one.

341
00:24:35,110 --> 00:24:40,550
But menopause, uh, people have measured the heritability of menopause.

342
00:24:40,820 --> 00:24:43,380
I had a student a long time ago, Jocelyn Pichet.

343
00:24:43,540 --> 00:24:44,820
You knew Jocelyn, didn't you?

344
00:24:45,060 --> 00:24:46,100
No, it was before my time.

345
00:24:46,420 --> 00:24:46,900
Before your time.

346
00:24:48,500 --> 00:24:51,620
She measured the heritability of menopause about 0.3.

347
00:24:52,180 --> 00:24:57,700
And her there were some problems with her work, but it's been done twice since,

348
00:24:58,020 --> 00:25:00,660
and estimates are about the same.

349
00:25:00,980 --> 00:25:06,340
So what that tells you is if there were a selected, so now you have peasant populations,

350
00:25:06,500 --> 00:25:11,370
agricultural populations, where, you know, women could keep having kids.

351
00:25:11,530 --> 00:25:13,450
Why aren't they keep having kids?

352
00:25:13,690 --> 00:25:18,330
Um and if you I mean the selective advantage ought to be pretty big.

353
00:25:18,570 --> 00:25:24,090
You could move menopause, this is the age of menopause, which in most populations is around

354
00:25:24,090 --> 00:25:27,290
50, pretty easily in a few thousand years.

355
00:25:27,450 --> 00:25:28,090
Not even that.

356
00:25:28,170 --> 00:25:33,480
I mean, and we know a thousand years, well, we know historical evidence, let's say, that

357
00:25:33,480 --> 00:25:37,800
suggests it hasn't changed much in the age of menopause in 2000 years.

358
00:25:37,960 --> 00:25:43,320
Now that's not very good data, but so anyway, I think there are I I don't have an answer to

359
00:25:43,320 --> 00:25:43,720
this question.

360
00:25:43,960 --> 00:25:49,720
I mean, in the end, uh I'm more of a agnostic about these things than than Lita and John

361
00:25:49,960 --> 00:25:50,200
were.

362
00:25:50,360 --> 00:25:52,250
And uh yeah, go ahead.

363
00:25:52,570 --> 00:25:55,450
Maybe like one of their arguments would be, or maybe not them.

364
00:25:55,530 --> 00:25:55,770
I don't know.

365
00:25:55,850 --> 00:26:00,810
I've seen Ed Hagen recently, like Yeah, it's a good good foil because he's so smart.

366
00:26:02,330 --> 00:26:03,530
Be so careful, right?

367
00:26:03,850 --> 00:26:03,930
Yeah.

368
00:26:04,090 --> 00:26:09,930
And I my understanding of some of their argument is that um complex adaptations, which is

369
00:26:10,170 --> 00:26:13,210
I mean, it is a complex adaptation because like now we're talking about, you know,

370
00:26:13,290 --> 00:26:19,050
quantitative traits that have multiple those sides, multiple phenotypes, but that um you

371
00:26:19,080 --> 00:26:24,440
know, I guess it's not arguable to say that the human brain is a complex adaptation, but

372
00:26:24,440 --> 00:26:25,800
there might be diff, you know, differences.

373
00:26:25,960 --> 00:26:31,480
Obviously, there's genetic variation in various cognitive, but I'm sure memory is I'm sure

374
00:26:31,560 --> 00:26:32,120
so so many things.

375
00:26:32,360 --> 00:26:32,760
Yeah, yeah, yeah.

376
00:26:33,320 --> 00:26:34,120
What isn't?

377
00:26:34,360 --> 00:26:40,120
Um, but that like the fundamental kind of um questions about human cognition that are like

378
00:26:40,360 --> 00:26:46,290
more species typical are unlikely to have changed as much in the last,

379
00:26:46,370 --> 00:26:48,610
I don't know, 10,000 years or something like that.

380
00:26:48,770 --> 00:26:49,730
Um, what do you make?

381
00:26:50,050 --> 00:26:56,050
I guess obviously it can't be any kind of um categorical

382
00:26:56,050 --> 00:27:02,050
break um in terms of what has and hasn't changed, but I guess there is,

383
00:27:02,210 --> 00:27:08,050
you know, there there's the equivalent of um biological anthropologists who look at kind

384
00:27:08,050 --> 00:27:14,000
of lumbar morphology and bipedalism and how it kind of works generally in humans.

385
00:27:14,320 --> 00:27:18,960
And I guess maybe their argument, but you guys might represent it better, would be

386
00:27:18,960 --> 00:27:22,560
something like there's the the equivalent attempt at doing something like that for the

387
00:27:22,560 --> 00:27:23,440
human mind.

388
00:27:23,760 --> 00:27:29,520
Um and and I think, you know, yeah, I there are things like lumbar morphology that are

389
00:27:29,600 --> 00:27:34,870
species typical in humans, but there's a lot of other stuff that's, you know, family

390
00:27:34,870 --> 00:27:40,630
typical and and uh you know so uh and and I don't think

391
00:27:40,870 --> 00:27:46,870
uh you know how much of I No what's exactly species also but

392
00:27:47,190 --> 00:27:52,230
yeah we are very, very you know uh living as I am living amongst

393
00:27:52,230 --> 00:27:56,160
paleoanthropologists these days, um uh No mess.

394
00:27:56,800 --> 00:28:02,640
Well, you know, I mean my my the director of the Institute of Human Origins, uh

395
00:28:02,720 --> 00:28:08,400
Johannes Heile Selassie, has just published in Nature a few weeks

396
00:28:08,400 --> 00:28:13,280
ago this species of Australopithecus uh

397
00:28:13,440 --> 00:28:14,560
Deridimata.

398
00:28:14,880 --> 00:28:16,080
Derridimata.

399
00:28:16,240 --> 00:28:18,480
When he first published it, I thought, ah, come on.

400
00:28:18,560 --> 00:28:19,840
You know, is that really that different?

401
00:28:20,000 --> 00:28:20,720
Is that as well?

402
00:28:21,120 --> 00:28:22,130
How the heck do we know?

403
00:28:22,290 --> 00:28:24,930
Living at exactly the same time as Aphorensis?

404
00:28:25,090 --> 00:28:29,010
And now he's got pretty good evidence that it had a significantly different mode of

405
00:28:29,010 --> 00:28:35,010
locomotion, that it had a opposable, semi-opposable toe and and um much

406
00:28:35,010 --> 00:28:36,290
longer arms.

407
00:28:36,530 --> 00:28:38,770
And you know, is that a species?

408
00:28:38,930 --> 00:28:43,490
Uh you know, I mean, all dogs are the same species, right?

409
00:28:43,570 --> 00:28:49,380
But if but if people found those fossils in the fossil record, Actually,

410
00:28:49,460 --> 00:28:54,500
this goes back to a story when Lyle visited Darwin in the

411
00:28:54,500 --> 00:28:55,940
mid-1850s.

412
00:28:56,020 --> 00:28:58,340
And you know, Darwin was a pigeon.

413
00:28:58,420 --> 00:29:04,020
He he kept pigeons of and and people had bred all these and you know, just as

414
00:29:04,020 --> 00:29:06,180
diverse as dogs, basically.

415
00:29:06,500 --> 00:29:12,070
And Lyle said, you know, shuddered that this

416
00:29:12,150 --> 00:29:17,030
basically wrecked everything because if we found these pigeons in the fossil record, they'd

417
00:29:17,030 --> 00:29:18,150
be different families.

418
00:29:18,310 --> 00:29:21,030
Yeah, more from based on their morphology.

419
00:29:21,270 --> 00:29:25,110
So you know, so I don't know how I got there exactly.

420
00:29:25,670 --> 00:29:29,910
As a very short person, oftentimes, like with towering people around me, I think how

421
00:29:29,860 --> 00:29:35,060
paleontologic would have surely classified as a but I'm not enough of a paleontologist to

422
00:29:35,060 --> 00:29:35,140
know.

423
00:29:35,460 --> 00:29:38,020
I mean maybe if they only got like my humorous or something like that.

424
00:29:38,260 --> 00:29:39,060
Yeah, exactly.

425
00:29:39,300 --> 00:29:45,060
Joan says that uh uh if you don't know David, Joan's about the same height

426
00:29:45,140 --> 00:29:47,860
as Christina, roughly, don't you think, Christina?

427
00:29:48,020 --> 00:29:49,380
I think maybe she has an inch on me.

428
00:29:49,460 --> 00:29:50,340
So I'm 4'11.

429
00:29:50,580 --> 00:29:51,460
Oh, she's five feet.

430
00:29:51,540 --> 00:29:51,700
Yeah.

431
00:29:51,940 --> 00:29:53,540
Those inches really make yeah, yeah.

432
00:29:54,100 --> 00:29:55,860
So she claims five feet.

433
00:29:55,940 --> 00:30:00,130
Uh and um she says all people are tall.

434
00:30:00,210 --> 00:30:05,970
You know, I can't tell a difference between okay.

435
00:30:06,050 --> 00:30:08,130
So I I don't know about John and Lita.

436
00:30:08,290 --> 00:30:14,290
I mean, I uh their method required them

437
00:30:14,450 --> 00:30:20,440
that there were these modules and by looking at contemporary behaviors, because they

438
00:30:20,440 --> 00:30:24,680
were the result of modules or some kind of enclosed I know you've written about modules.

439
00:30:24,920 --> 00:30:28,760
Yeah, but I mean but I mean it doesn't I don't mean modules in that technical psychological

440
00:30:28,920 --> 00:30:29,080
sense.

441
00:30:29,400 --> 00:30:35,400
Yeah yeah uh but that you could map particular input output relations back

442
00:30:35,560 --> 00:30:37,320
to some problem in the police.

443
00:30:38,120 --> 00:30:42,200
If you can't do that you've got problems, right?

444
00:30:42,360 --> 00:30:48,050
And I'm skeptical about that and uh you know uh and I'll I'll rat

445
00:30:48,610 --> 00:30:49,570
Pete out here.

446
00:30:49,650 --> 00:30:54,450
Uh Pete and I have ferocious arguments about this,

447
00:30:55,170 --> 00:30:56,130
basically.

448
00:30:56,290 --> 00:30:59,890
Um, he thinks there are none, no modules.

449
00:31:00,050 --> 00:31:04,450
And he bases this on, he's read a lot more than I have, of

450
00:31:05,250 --> 00:31:06,530
neurobiology.

451
00:31:06,770 --> 00:31:12,080
And um, there was a paper in Nature um some nature

452
00:31:12,080 --> 00:31:17,840
reviews a few a year or two ago uh which argued basically human brains

453
00:31:17,840 --> 00:31:23,760
just have more of the same they're just chimp brains with more of everything and no special

454
00:31:23,760 --> 00:31:29,760
f features i i can't i have no idea how to evaluate those kind of arguments

455
00:31:30,150 --> 00:31:32,870
And so I say, Pete, what about birds' nests?

456
00:31:33,030 --> 00:31:35,270
What about you know, beaver dams?

457
00:31:35,430 --> 00:31:37,270
Those look like modules to me.

458
00:31:37,510 --> 00:31:43,350
And you know, beavers, I've read quite a bit about beavers and uh little beavers.

459
00:31:43,510 --> 00:31:49,510
So beavers live in ponds where the everybody behind the dam is fairly closely

460
00:31:49,510 --> 00:31:49,990
related.

461
00:31:50,150 --> 00:31:56,070
The ecologists have studied them, you know, the averages are like 0.3 or 0.4 or

462
00:31:56,070 --> 00:31:56,630
something like that.

463
00:31:56,790 --> 00:32:00,680
So, and you know, pretty impressive, actually.

464
00:32:01,000 --> 00:32:06,760
But when the little beavers leave, they disperse, and they beavers build different

465
00:32:06,760 --> 00:32:12,040
kinds of structures and different kinds of aquatic environments.

466
00:32:12,280 --> 00:32:18,200
Sometimes they build little canals back to a pond they make for themselves.

467
00:32:18,280 --> 00:32:21,190
Sometimes they just build lodges on the side of streams.

468
00:32:21,270 --> 00:32:22,630
Sometimes they build dams.

469
00:32:22,790 --> 00:32:26,790
They build dams in different ways depending on how much water pressure there is.

470
00:32:26,950 --> 00:32:32,070
And those little beavers seem to know how to do that without ever having seen a dam being

471
00:32:32,070 --> 00:32:32,390
built.

472
00:32:32,550 --> 00:32:34,550
There's no social learning involved.

473
00:32:34,710 --> 00:32:36,790
And the same thing is true of birds' nest.

474
00:32:36,950 --> 00:32:42,630
Uh there uh so weaver birds, people have done raised weaver birds uh without

475
00:32:42,820 --> 00:32:46,900
any um exposure to nest building.

476
00:32:47,060 --> 00:32:50,100
And they build now, they don't do there is learning involved.

477
00:32:50,180 --> 00:32:55,620
So the first nest a weaver bird built is not as good as the second nest that he builds.

478
00:32:55,780 --> 00:33:00,260
And they are all the men or the males are building the nest, so he is okay.

479
00:33:00,420 --> 00:33:06,180
But um so there's some kind of information encoded in weaver

480
00:33:06,180 --> 00:33:09,940
bird brains and in beaver brains that tells them how to build a nest.

481
00:33:10,350 --> 00:33:16,350
Uh and so that makes me skeptical of the neurobiological arguments.

482
00:33:16,590 --> 00:33:20,350
Uh and I can't convince Pete.

483
00:33:20,430 --> 00:33:25,790
He's he's really really gone over to the everything is is um

484
00:33:26,030 --> 00:33:27,870
plastic kind of picture.

485
00:33:28,030 --> 00:33:30,190
And it's based on, you know, he's not stupid.

486
00:33:30,270 --> 00:33:34,430
He doesn't think it's a blank slate, but but he thinks it's there are these general

487
00:33:34,820 --> 00:33:38,660
motivational and embodied principles.

488
00:33:38,820 --> 00:33:41,060
And then that's where all the details come from.

489
00:33:41,220 --> 00:33:42,500
And I don't know.

490
00:33:42,740 --> 00:33:48,740
So I I just know that I'm I can't, I'm not convinced that anybody knows the answer

491
00:33:48,740 --> 00:33:49,140
to that.

492
00:33:49,300 --> 00:33:53,380
So do you think it's like an ontogenetic phylogenetic distinction?

493
00:33:53,460 --> 00:33:57,630
Like, I mean, do you think the people are saying it's just more of they're looking at the

494
00:33:57,630 --> 00:34:03,390
ontogeny and then the sort of to to to be really glossy about it, like John

495
00:34:03,630 --> 00:34:08,590
and Lita are thinking about sort of the the phylogenetic design on the developmental system

496
00:34:08,750 --> 00:34:10,830
to kind of bring it back to what we talked about before.

497
00:34:10,990 --> 00:34:15,150
But they weren't emphasizing that because they weren't studying the developmental system.

498
00:34:15,470 --> 00:34:16,430
Yeah, I don't know.

499
00:34:16,590 --> 00:34:22,380
I mean, uh uh every time I read neurobiology, I think, you know, they don't know what

500
00:34:22,380 --> 00:34:25,500
they're talking about, but at the same time they know a huge amount of stuff.

501
00:34:25,660 --> 00:34:27,660
And uh so I don't know.

502
00:34:27,820 --> 00:34:33,420
I just don't, you know, I I I never have had the enough background or

503
00:34:33,420 --> 00:34:39,340
ambition to um really and I don't think my own guess is I mean I bet

504
00:34:39,660 --> 00:34:43,180
my career on this kind of that it's not there yet.

505
00:34:43,260 --> 00:34:48,220
They don't know enough to know how it all works and um and uh

506
00:34:49,150 --> 00:34:54,590
and firm conclusions one way or the other, yeah, uh are dubious.

507
00:34:54,670 --> 00:35:00,350
But yeah, I I remember uh Randy Gallstell gave his talk because he's got that Gallastel um

508
00:35:00,590 --> 00:35:04,350
uh and I can't think of the other person's name because I can't think of nouns either.

509
00:35:04,510 --> 00:35:09,310
Um, but uh but they've got this book about you know memory requires addressable read write

510
00:35:09,470 --> 00:35:09,870
format.

511
00:35:10,030 --> 00:35:10,350
Yeah.

512
00:35:10,510 --> 00:35:15,550
And uh, you know, neural conductance changes don't doesn't buy you that.

513
00:35:15,820 --> 00:35:19,580
And I remember he gave a talk at Yale when I was a postdoc and he gave the talk in front of

514
00:35:19,580 --> 00:35:23,180
the neuroscientists at Yale and he gave this like hour long talk and they went crazy.

515
00:35:23,500 --> 00:35:25,980
And actually he was like the nobody had a good answer.

516
00:35:26,060 --> 00:35:31,100
And really when it came down to literally one of the people said, Yeah, but it's hard.

517
00:35:32,220 --> 00:35:34,380
So yeah, so I think your career is fine, Rob.

518
00:35:34,460 --> 00:35:35,260
I think they don't know.

519
00:35:35,900 --> 00:35:36,300
We don't know.

520
00:35:36,380 --> 00:35:37,260
No, we don't know anything.

521
00:35:37,340 --> 00:35:38,860
None of us know how this stuff works.

522
00:35:39,420 --> 00:35:43,610
I will tell you a Randy Gallstall anecdote, which is on the same theme.

523
00:35:43,770 --> 00:35:49,370
So I was at a conference in Paris, and and uh I was sitting next to Randy, who is a has a

524
00:35:49,370 --> 00:35:50,970
wicked sense of humor.

525
00:35:51,210 --> 00:35:54,890
And um uh and it's kind of a contrary, you know.

526
00:35:55,130 --> 00:36:00,730
And uh so this guy was giving this, you know, it was kind of a typical um

527
00:36:01,050 --> 00:36:02,410
neurobiology talk.

528
00:36:02,570 --> 00:36:07,160
He was an anatomist, and he was, you know, this is kind of like the old song, you know, the

529
00:36:07,160 --> 00:36:08,840
thigh bones connected to the neck bones.

530
00:36:09,000 --> 00:36:14,040
They have all these circuits in the brain and and different pieces are connected.

531
00:36:14,200 --> 00:36:19,240
And he had done a whole bunch of fancy work to to learn how, you know,

532
00:36:19,720 --> 00:36:24,680
information, we presume, is being transmitted between these uh

533
00:36:25,880 --> 00:36:28,520
uh anatomically different parts of the brain.

534
00:36:28,760 --> 00:36:34,450
And so somebody, and I don't know who raised their hand and said, Uh can you

535
00:36:34,450 --> 00:36:40,210
explain uh how the information that's transmitted all along these circuits is encoded?

536
00:36:40,770 --> 00:36:46,770
And Randy leaned over to me and he said, Now a glimpse into the abyss.

537
00:36:47,010 --> 00:36:52,880
And and and uh so uh

538
00:36:53,040 --> 00:36:54,160
and the guy had no answer.

539
00:36:54,240 --> 00:36:55,520
I said, We have no idea.

540
00:36:55,680 --> 00:36:58,640
And uh no, this is 20 years ago, but yeah.

541
00:36:59,280 --> 00:37:00,640
Well, at least it was an honest answer.

542
00:37:00,720 --> 00:37:04,480
Yeah, no, I mean, and that's yeah, I think that's I mean, I I appreciate that about all of

543
00:37:04,480 --> 00:37:09,920
us here is you know, I don't know, it's a good thing to Didn't you say I Rob, I feel like

544
00:37:09,920 --> 00:37:13,120
this is a story you told about John Maynard Smith where something somebody said something,

545
00:37:13,280 --> 00:37:14,400
Oh, you changed your mind once.

546
00:37:14,480 --> 00:37:15,600
And he said, Of course I did.

547
00:37:15,680 --> 00:37:16,560
I I knew the data.

548
00:37:16,640 --> 00:37:18,480
Like, is that no, I don't know that story.

549
00:37:18,720 --> 00:37:19,360
Okay, yeah, yeah.

550
00:37:19,440 --> 00:37:24,050
But I think that yeah, thinking that feeling like you have to know something is is a curse

551
00:37:24,050 --> 00:37:25,170
of the ac the account.

552
00:37:25,410 --> 00:37:25,730
Yeah, yeah.

553
00:37:25,810 --> 00:37:31,650
No, he was uh John is my intellectual hero and um and uh

554
00:37:32,610 --> 00:37:35,090
he was an honest guy that way.

555
00:37:35,330 --> 00:37:35,570
Yeah.

556
00:37:35,810 --> 00:37:36,850
Did you know him?

557
00:37:37,170 --> 00:37:38,690
Um kind of.

558
00:37:38,930 --> 00:37:44,780
Uh I uh I met him at various conferences and then we we got

559
00:37:44,780 --> 00:37:47,580
invited to this, both got invited to this.

560
00:37:47,980 --> 00:37:53,820
Uh that it's in Steyr, um, Austria, every year they

561
00:37:53,820 --> 00:37:59,820
have a kind of a school on on um some topic.

562
00:38:00,140 --> 00:38:06,140
And uh uh the I got invited to give a bunch of lectures on, and and they invite a

563
00:38:06,140 --> 00:38:09,810
bunch of students for a week, and then the last day a bunch of big shots show up.

564
00:38:10,050 --> 00:38:15,890
And uh so I wasn't a very big shot, but I they talked me into giving lectures

565
00:38:15,890 --> 00:38:21,810
about game theory and kin selection to all these students, you know, four

566
00:38:21,810 --> 00:38:24,850
days, hour and a half lecture every day.

567
00:38:25,170 --> 00:38:30,210
And uh so I get there, and who's in the audience but John Maynard Smith?

568
00:38:30,290 --> 00:38:31,490
Holy crap!

569
00:38:31,730 --> 00:38:37,540
And uh and um so unlike the other big shots, he showed up the

570
00:38:37,540 --> 00:38:41,780
first day, listened to the whole thing, talked to the students.

571
00:38:42,100 --> 00:38:43,540
Uh, he was great.

572
00:38:43,700 --> 00:38:47,460
And it turned out that like me, he's an early riser.

573
00:38:47,620 --> 00:38:53,460
So, you know, at 6 30 every morning, he and I were there at the beginning of the line to

574
00:38:53,460 --> 00:38:53,940
get breakfast.

575
00:38:54,020 --> 00:38:56,180
And so I had breakfast with him every morning for the week.

576
00:38:56,260 --> 00:38:57,300
And I hung out with them.

577
00:38:57,380 --> 00:39:00,950
We got to be, you know, we were hanging out together a lot.

578
00:39:01,110 --> 00:39:01,270
Yeah.

579
00:39:01,430 --> 00:39:03,510
And then I met him some other times.

580
00:39:03,670 --> 00:39:09,510
And I I mean, he was a prickly guy, but I thought great.

581
00:39:09,750 --> 00:39:15,510
And um and um you know, not a modest fellow,

582
00:39:15,590 --> 00:39:18,950
but but uh I don't think he probably had good reason not to be honest.

583
00:39:19,430 --> 00:39:20,470
That's that that is true.

584
00:39:20,710 --> 00:39:26,000
Um I I wanna see if I could so uh it'll probably be um of interest to our listeners to see

585
00:39:26,000 --> 00:39:31,360
if we could really nail down on what the disagreements are between uh you and Lita and

586
00:39:31,360 --> 00:39:31,520
John.

587
00:39:31,680 --> 00:39:35,120
So in discussing these differences about how evolution works, it's gonna really make me

588
00:39:35,120 --> 00:39:35,840
fess up here now.

589
00:39:35,920 --> 00:39:36,720
But okay sorry.

590
00:39:38,000 --> 00:39:42,000
No I think it's important for us to get a handle on precisely what the disagreements are

591
00:39:42,000 --> 00:39:43,040
and whether they even exist.

592
00:39:43,120 --> 00:39:45,790
Because I think there are some people who think that we can all just get along and these

593
00:39:45,790 --> 00:39:49,710
disagreements are just kind of narcissism of petty differences.

594
00:39:49,950 --> 00:39:55,710
Um but uh so in

595
00:39:55,710 --> 00:40:00,430
talking about your your differences between Lita and John, you mentioned rapid evolutionary

596
00:40:00,430 --> 00:40:02,110
change and guppies and lizards.

597
00:40:02,190 --> 00:40:05,950
You talked about uh the evolution of menopause, how it has surprisingly low heritability

598
00:40:06,030 --> 00:40:08,750
and how there may have been surprisingly high heritability.

599
00:40:08,990 --> 00:40:09,470
Oh, you think?

600
00:40:09,630 --> 00:40:09,710
Okay.

601
00:40:09,960 --> 00:40:10,520
Regardless of the thing.

602
00:40:10,760 --> 00:40:16,760
0.3 means that if you get a one standard deviation change due to selection, you get

603
00:40:16,760 --> 00:40:20,600
a three tenths of a standard deviation change per generation.

604
00:40:20,840 --> 00:40:21,720
Do the math.

605
00:40:21,880 --> 00:40:23,640
You get Yeah, that's true.

606
00:40:24,760 --> 00:40:29,640
Um but nevertheless, uh I I believe the suggestion was that um, you know, there could have

607
00:40:29,640 --> 00:40:33,800
been selection for uh increased menopause in recent human evolutionary history, but the

608
00:40:33,800 --> 00:40:37,750
fact that we didn't see that suggests that there's some kind of constraint to um to

609
00:40:37,990 --> 00:40:38,630
adaptiveness.

610
00:40:38,790 --> 00:40:39,430
Is that the same thing?

611
00:40:39,590 --> 00:40:44,870
No, or that, or that for some reason a 50-year-old menopause is is fitness

612
00:40:44,870 --> 00:40:45,830
maximized.

613
00:40:45,990 --> 00:40:47,110
Uh okay.

614
00:40:47,430 --> 00:40:47,750
All right.

615
00:40:47,910 --> 00:40:51,190
Um well so the I I'm still trying to nail down what the disagreement is then.

616
00:40:51,270 --> 00:40:56,710
Is it just that um uh there's been more recent uh evolution than perhaps Tubian

617
00:40:56,790 --> 00:40:57,590
Cosmodies think?

618
00:40:57,750 --> 00:41:02,070
That uh maybe the EEA is more recent than they they might have thought, or is it is the

619
00:41:02,070 --> 00:41:06,960
point that there are constraints on optimality that limit the utility of adaptationist

620
00:41:06,960 --> 00:41:07,360
analysis.

621
00:41:07,520 --> 00:41:13,120
What what what is Yeah, no, I uh all this is secondary.

622
00:41:13,280 --> 00:41:18,800
Uh um uh the real disagreement between John,

623
00:41:19,360 --> 00:41:25,200
Lita, Pete and I uh is I think about

624
00:41:25,920 --> 00:41:31,360
um cultural evolution and its role in explaining

625
00:41:31,600 --> 00:41:32,480
behavior.

626
00:41:33,040 --> 00:41:38,830
Um Pete and I think that uh, well, to put it

627
00:41:38,830 --> 00:41:44,270
as bluntly as possible, that in humans, selection has favored a

628
00:41:44,270 --> 00:41:50,190
psychology that does stuff that causes people to do stuff that they

629
00:41:50,190 --> 00:41:55,000
see people around them doing, even though they have no uh

630
00:41:55,480 --> 00:41:59,080
adaptive reason to think that's the correct thing to do.

631
00:41:59,800 --> 00:42:03,480
And uh I've got models, of course, that show that's possible.

632
00:42:03,720 --> 00:42:09,560
Now that's you know, why maybe as as Pete's kid used to say.

633
00:42:09,800 --> 00:42:13,400
Um and uh uh uh

634
00:42:14,920 --> 00:42:20,680
philosophers use talk about why possibly, that's what models but I like why maybe better.

635
00:42:20,840 --> 00:42:26,770
Um and uh I mean I think, I mean, I've talked to

636
00:42:26,770 --> 00:42:27,890
John about this.

637
00:42:28,050 --> 00:42:33,810
Uh he just I had never talked to Lita about this, but uh uh

638
00:42:34,050 --> 00:42:39,810
he thought that was impossible, that our psychology couldn't be

639
00:42:39,810 --> 00:42:45,560
built in a way that uh you would learn to be

640
00:42:45,560 --> 00:42:51,560
celibate, or you would learn to risk your life climbing mountains, or you would learn all

641
00:42:51,560 --> 00:42:57,080
those things would have to arise from motivations and information

642
00:42:57,080 --> 00:43:02,360
processing that would have been favored by selection in a

643
00:43:02,360 --> 00:43:04,360
hunter-gatherer existence.

644
00:43:04,680 --> 00:43:08,040
Um small bubble bands, et cetera, et cetera.

645
00:43:08,200 --> 00:43:13,630
And I just think that's wrong that that selection has created a

646
00:43:13,630 --> 00:43:18,270
psychology that causes us to be susceptible to

647
00:43:19,630 --> 00:43:24,350
the social environment, informational environment in which we live.

648
00:43:24,830 --> 00:43:30,510
And because it it it's so social

649
00:43:30,670 --> 00:43:32,670
learning is a two-edged sword.

650
00:43:33,340 --> 00:43:39,100
It gives us immense adaptive power, much greater adaptive power

651
00:43:39,100 --> 00:43:41,020
than any other vertebrate.

652
00:43:43,580 --> 00:43:48,140
Since now I'm giving a speech, but I'll give the speech anyway.

653
00:43:53,500 --> 00:43:57,260
It depends who you listen to, emerged from Africa.

654
00:43:57,580 --> 00:44:02,390
And they spread across the world in a few thousand years.

655
00:44:02,790 --> 00:44:07,190
So this is a a um a

656
00:44:08,310 --> 00:44:14,070
vertebrate uh a tropical forager living

657
00:44:14,390 --> 00:44:19,910
in warm environments with a particular mix of of adaptations that are

658
00:44:19,910 --> 00:44:20,470
necessary.

659
00:44:20,710 --> 00:44:26,320
And it looks like within a few thousand years they're living north of the Arctic

660
00:44:26,320 --> 00:44:32,000
Circle, and in which the suite of adaptations

661
00:44:32,240 --> 00:44:36,800
necessary to make a living is immensely different.

662
00:44:37,680 --> 00:44:42,720
And you need clothing, you need housing, you need all kinds of stuff.

663
00:44:43,040 --> 00:44:48,970
And uh this people were able to acquire all these adaptations for

664
00:44:48,970 --> 00:44:54,810
all the different parts of the world they lived in because they could evolve

665
00:44:54,810 --> 00:45:00,250
culturally and acquire inf so it's not

666
00:45:00,250 --> 00:45:03,290
individual humans that adapt.

667
00:45:03,690 --> 00:45:09,120
Human populations adapt because they can share information

668
00:45:09,680 --> 00:45:13,520
and they can it only works if you

669
00:45:15,120 --> 00:45:21,040
adopt adaptations that you don't understand why they're

670
00:45:21,040 --> 00:45:22,240
the way they are.

671
00:45:23,680 --> 00:45:25,360
Credulity, yeah, like the kayakism.

672
00:45:26,080 --> 00:45:27,600
Yeah, so you have to be credulous.

673
00:45:28,320 --> 00:45:32,170
And what you get for that is this

674
00:45:33,770 --> 00:45:39,690
huge adaptive machine that gives you things that individual

675
00:45:39,690 --> 00:45:44,250
cognition, as smart as we are, is grotesquely

676
00:45:45,210 --> 00:45:47,370
underpowered to acquire.

677
00:45:47,690 --> 00:45:53,620
And uh but that means that you're prone to picking up ideas that

678
00:45:53,700 --> 00:45:55,860
you know aren't that sensible sometimes.

679
00:45:56,020 --> 00:46:01,060
And so I think it's a it's like lots of stuff in evolution, there's a trade-off.

680
00:46:01,140 --> 00:46:06,500
There's a trade-off between having cultural adaptation, and I'll say just as an aside,

681
00:46:06,740 --> 00:46:12,340
David, uh I think selection's important, but so are non-selective processes.

682
00:46:12,580 --> 00:46:16,580
So it it it it it cultural selection is only part of the story.

683
00:46:16,820 --> 00:46:22,690
Um I mean transformative processes like spurber and all those guys

684
00:46:22,850 --> 00:46:24,610
are are for sure important.

685
00:46:25,410 --> 00:46:31,250
And um uh uh and we can talk about that if you want.

686
00:46:31,410 --> 00:46:36,690
But but so uh and I think I mean maybe I'm

687
00:46:36,690 --> 00:46:42,530
caricaturizing caricaturing um uh John and Lita, but

688
00:46:42,530 --> 00:46:47,540
I I think and I've talked more to John about this than Lita.

689
00:46:47,860 --> 00:46:49,540
He just thought that was nonsense.

690
00:46:49,780 --> 00:46:55,380
That uh that um um people were smart.

691
00:46:55,460 --> 00:46:59,700
They had all these domain-specific adaptations and

692
00:47:01,220 --> 00:47:07,220
um it it seems like though that there's a compatibility between the two

693
00:47:07,220 --> 00:47:07,620
views.

694
00:47:07,700 --> 00:47:12,990
I the only disagreement that I can pick up on is on the extent of of credulity about this

695
00:47:12,990 --> 00:47:14,110
cultural information.

696
00:47:14,270 --> 00:47:19,230
But it seems like you could get that kind of cultural adaptation with a fair amount of

697
00:47:19,230 --> 00:47:23,550
credulity and a fair amount of scrutiny of the different cultural variants and a fair

698
00:47:23,550 --> 00:47:28,110
amount of sensitivity to, say, the success of a particular hunting practice or a particular

699
00:47:28,110 --> 00:47:31,550
person who's adopting that practice or the particular social benefits.

700
00:47:31,710 --> 00:47:35,870
You know, all of these, the psychology could be sensitive to all of these variables, and

701
00:47:35,870 --> 00:47:37,630
you could still get this cultural adaptation.

702
00:47:37,710 --> 00:47:41,300
And in fact, it could even facilitate this cultural adaptation if you have these

703
00:47:41,300 --> 00:47:42,580
psychological sensitivities.

704
00:47:42,900 --> 00:47:43,300
Of course.

705
00:47:43,460 --> 00:47:43,780
Yeah.

706
00:47:43,860 --> 00:47:48,500
I mean, this is um, you know, what people say about scientific theories.

707
00:47:48,580 --> 00:47:52,580
Um uh the first the first reaction is well, that's complete nonsense.

708
00:47:52,660 --> 00:47:54,020
How could that possibly be?

709
00:47:54,180 --> 00:47:58,980
The second reaction is, well, maybe under particular circumstances, and the third reaction

710
00:47:58,980 --> 00:48:00,660
is that's what we thought all along.

711
00:48:01,140 --> 00:48:07,110
And um, and uh, you know, uh I maybe I think maybe

712
00:48:07,110 --> 00:48:11,990
there's a sociological pr point here to make which is that like I think for the point of

713
00:48:12,230 --> 00:48:16,630
showing the novelty and the of of being able to make new predictions.

714
00:48:16,790 --> 00:48:22,070
Um I think you know culturalists have often pointed to really amazing things that are weird

715
00:48:22,070 --> 00:48:27,680
in humans, like you mentioned celibacy, like sacrificing for and Kind of the

716
00:48:27,680 --> 00:48:28,400
in-group.

717
00:48:28,640 --> 00:48:32,080
And I do bet that like some people don't think that that's, you know, there are different

718
00:48:32,080 --> 00:48:35,680
explanation people propose different explanations for those extreme examples.

719
00:48:35,840 --> 00:48:41,440
Um, but I think that that has maybe sometimes lended to be characterized as like uh people

720
00:48:41,440 --> 00:48:47,360
are dumb perspective, or that like the the credit like that's the extreme

721
00:48:47,360 --> 00:48:48,560
level of credulity, right?

722
00:48:48,720 --> 00:48:51,200
Like that is credulous, yeah.

723
00:48:51,520 --> 00:48:51,760
Right.

724
00:48:51,840 --> 00:48:57,590
I I I mean, um so if you think people are endowed with a

725
00:48:57,910 --> 00:49:03,510
so the thing is well, I mean, celibacy is an interesting one

726
00:49:03,670 --> 00:49:06,070
because people obviously like sex, right?

727
00:49:06,310 --> 00:49:10,630
And um and so the question is, how could it be?

728
00:49:10,790 --> 00:49:16,580
I mean, I've not just from John Alita, I mean Dick Alexander and all

729
00:49:16,580 --> 00:49:17,060
those people.

730
00:49:17,140 --> 00:49:21,700
Come on, you know, I mean try to find an adaptation like people know what they're doing

731
00:49:21,860 --> 00:49:27,380
right now that it's worth and the thing is uh the

732
00:49:28,020 --> 00:49:33,460
selection can't I mean in my view, selection can't endow us with you know have sex no

733
00:49:33,460 --> 00:49:37,700
matter what, because uh there are always trade-offs.

734
00:49:38,020 --> 00:49:43,730
So um it I mean uh to take an example,

735
00:49:43,890 --> 00:49:49,730
uh in in uh the Maasai, um young

736
00:49:50,050 --> 00:49:55,650
men, Maran E, uh are the warriors were supposed to be

737
00:49:55,650 --> 00:49:56,530
celibate.

738
00:49:57,010 --> 00:50:02,900
And um when they graduated from that age set, then they could get married

739
00:50:02,900 --> 00:50:03,700
and have sex.

740
00:50:03,860 --> 00:50:09,300
And of course, big surprise, sometimes they had sex, but you know, as Murani,

741
00:50:09,700 --> 00:50:11,860
not as as as seniors.

742
00:50:12,180 --> 00:50:14,180
But it was costly, right?

743
00:50:14,260 --> 00:50:17,940
There were norms in place that people imposed costs.

744
00:50:18,100 --> 00:50:23,780
And so people, sure, they like sex, but they're also sensitive to, you know.

745
00:50:23,940 --> 00:50:26,100
And so where do the norms come from?

746
00:50:26,580 --> 00:50:32,450
The norms on John Alita's account, I would say, have to come from some module

747
00:50:32,530 --> 00:50:33,010
somewhere.

748
00:50:33,570 --> 00:50:39,570
And um on my account, they can evolve all over the place because we don't know.

749
00:50:40,050 --> 00:50:44,450
It we're not very good at figuring out how society should be organized.

750
00:50:44,770 --> 00:50:47,810
That's another thing we don't understand very well.

751
00:50:48,290 --> 00:50:52,520
I mean, I I've argued sort of endlessly that

752
00:50:53,800 --> 00:50:59,000
selection of cultural differences between groups is one force that shapes norms.

753
00:50:59,160 --> 00:51:02,680
I am surely that can't be the only thing.

754
00:51:02,840 --> 00:51:04,520
It doesn't explain a lot of change.

755
00:51:04,680 --> 00:51:05,480
It's too slow.

756
00:51:05,640 --> 00:51:10,120
There are a lot of reasons why it can't be the main, the only main process, and I don't

757
00:51:10,120 --> 00:51:15,810
think we're very good at at there's some papers by Lehman and Powers and some other people

758
00:51:15,810 --> 00:51:17,410
about bargaining.

759
00:51:17,970 --> 00:51:22,850
I I think there are problems with that way of looking at it, but I think within group

760
00:51:22,850 --> 00:51:25,170
processes uh must be important.

761
00:51:25,490 --> 00:51:28,210
And um and so we got to figure that out.

762
00:51:28,370 --> 00:51:34,370
But it's I I think that the fact that these things are heritable at the group level,

763
00:51:34,530 --> 00:51:40,240
that they meaning that groups persist, you ship shift environments

764
00:51:40,400 --> 00:51:44,240
and and they'll shift eventually, but there it often is quite slow.

765
00:51:44,400 --> 00:51:49,680
And you can predict a lot about what people's norms are from what language they speak.

766
00:51:50,000 --> 00:51:55,680
And all these things are not the signatures of a

767
00:51:55,680 --> 00:52:01,520
universal psychology mapping environment, meaning the ecological

768
00:52:01,680 --> 00:52:05,770
physical environment, onto social behavior.

769
00:52:05,930 --> 00:52:10,650
It's there's some history and and um if

770
00:52:11,290 --> 00:52:15,050
evolutionary psychologists want to th say that's what we believe, fine.

771
00:52:15,930 --> 00:52:16,810
I've won.

772
00:52:18,490 --> 00:52:21,050
But uh and I think that's right.

773
00:52:21,130 --> 00:52:24,170
I mean to just put it like you know like I think Christina and I have these conversations.

774
00:52:24,330 --> 00:52:27,930
I think I like you know I wonder when you and John were talking, I think we're we're

775
00:52:28,090 --> 00:52:32,330
hindsight is 2020 and I think we wouldn't have the understanding we have if you and John

776
00:52:32,490 --> 00:52:36,660
hadn't had that debate, but I mean one thing I appreciate as a John Lita student was you

777
00:52:36,660 --> 00:52:42,580
know the kayak example where you don't just to to caricature the the

778
00:52:42,660 --> 00:52:48,420
the the the the john and leita uh my training would be sort of there's no account of

779
00:52:48,420 --> 00:52:53,460
kayak design right in the mind right that that there's you can have to explain that

780
00:52:53,460 --> 00:52:59,110
complexity and that adaptation and why that kayak does so well what I like about this.

781
00:52:59,510 --> 00:53:00,230
Or bicycle.

782
00:53:00,390 --> 00:53:01,510
Yeah, or bicycle or anything.

783
00:53:01,590 --> 00:53:01,910
Exactly.

784
00:53:01,990 --> 00:53:02,150
Yes.

785
00:53:02,230 --> 00:53:03,270
I prefer bikes as we know.

786
00:53:03,350 --> 00:53:03,430
Yeah.

787
00:53:03,590 --> 00:53:03,990
Yeah, exactly.

788
00:53:05,990 --> 00:53:11,750
But um, yeah, no, I I mean I like that there's an extra thing to explain, which is

789
00:53:11,750 --> 00:53:15,830
this uh shorter time span, the trial and error.

790
00:53:15,990 --> 00:53:19,110
Everything is trial and error, you just don't see the error all the time, but it's you

791
00:53:19,110 --> 00:53:24,870
know, just variance in the world, and there's selective retention of variation in the

792
00:53:24,870 --> 00:53:25,350
design.

793
00:53:25,510 --> 00:53:30,920
And I think, you know, Christina and I, my feeling is that now evolutionary

794
00:53:30,920 --> 00:53:36,760
psychologists are often thinking about like, what's the EEA of the class of things

795
00:53:36,760 --> 00:53:41,800
that are like kayak design, exactly in the day way that David's talking about it, where

796
00:53:41,800 --> 00:53:47,640
there's sort of there are entries for I'm gonna accept something with credulity,

797
00:53:47,880 --> 00:53:48,200
right?

798
00:53:48,600 --> 00:53:54,310
Um because this has been an aspect that has recurrently been so I actually think

799
00:53:54,310 --> 00:54:00,070
we've come, I believe we've come to completely both both being

800
00:54:00,070 --> 00:54:04,070
integrated, but I think we didn't we couldn't have gotten there if you guys hadn't had that

801
00:54:04,390 --> 00:54:06,630
argument because I do think it was missing.

802
00:54:06,710 --> 00:54:10,920
You know, I will say that as a student of John Leader, like I do think that the extra um I

803
00:54:10,920 --> 00:54:12,360
mean, I think the the idea was there.

804
00:54:12,440 --> 00:54:17,080
I mean the true to be DeVore paper had that idea, but I don't I do think it was under

805
00:54:17,480 --> 00:54:18,120
emphasized.

806
00:54:18,200 --> 00:54:20,520
And I do think you we needed to have that argument.

807
00:54:20,680 --> 00:54:25,320
Maybe that's maybe that's my buffalo everybody can get along upbringing, but I but that's

808
00:54:25,320 --> 00:54:25,800
my opinion.

809
00:54:25,880 --> 00:54:26,920
That's my two cents about it.

810
00:54:27,080 --> 00:54:29,480
I don't know what Christina uh thinks about it.

811
00:54:29,640 --> 00:54:35,110
Um I think that there's a method I'm not we've been skirting around like the methodological

812
00:54:35,110 --> 00:54:35,830
difficulty of it.

813
00:54:35,990 --> 00:54:39,190
I mean I I generally agree that they're compatible, Rob, for what it's doing with.

814
00:54:39,590 --> 00:54:42,310
And I don't, and maybe historically they weren't.

815
00:54:42,470 --> 00:54:48,470
Um but there's a methodological difficulty as well in like parsing out, you

816
00:54:48,470 --> 00:54:53,800
know, no, if we all agree that the kayak isn't the EEA, but there's like a kayak-like

817
00:54:54,760 --> 00:54:54,920
things.

818
00:54:55,320 --> 00:54:59,720
There's no kayak module, but there's maybe is like, you know, a cock, there has to be a

819
00:54:59,720 --> 00:55:03,240
cognition that's capable of accepting and processing kayak-like things.

820
00:55:04,120 --> 00:55:06,280
And what is the category of kayak-like things?

821
00:55:06,520 --> 00:55:11,720
The difficulty is that, like, I'm not sure that we the kayak is a is a good or bicycle is a

822
00:55:11,720 --> 00:55:15,080
good example of that because we know it's like technological evolutionary history.

823
00:55:15,320 --> 00:55:19,160
But things like kinship structures or social systems, we have no idea.

824
00:55:19,320 --> 00:55:24,930
And then it becomes, I think, a much harder process of like disentangling of like,

825
00:55:25,090 --> 00:55:29,890
well, you know, is the reason that we have these kinds of like intuitions about kinship or

826
00:55:29,890 --> 00:55:34,050
about um, I don't know, maybe reciprocity or maybe about fatherhood?

827
00:55:34,210 --> 00:55:35,810
Like, is that like a kayak?

828
00:55:36,050 --> 00:55:36,370
I see.

829
00:55:36,450 --> 00:55:36,610
Yeah.

830
00:55:36,690 --> 00:55:42,210
So you're just don't have like the the historical knowledge of when this kind of fatherhood

831
00:55:42,210 --> 00:55:45,010
institution or this social system evolved?

832
00:55:45,250 --> 00:55:49,860
Or is that really a deep seated part of human cognition?

833
00:55:50,420 --> 00:55:51,860
Well, I mean, kinship.

834
00:55:52,020 --> 00:55:55,300
We know that there's a lot of cultural variation in kinship, yeah.

835
00:55:55,460 --> 00:56:00,580
And and we've got some idea of the timescales on which um

836
00:56:01,460 --> 00:56:02,340
those systems are.

837
00:56:02,820 --> 00:56:06,660
I guess with like phylogenetic kind of from Ruth Mace kind of stuff.

838
00:56:06,900 --> 00:56:07,060
Yeah.

839
00:56:07,220 --> 00:56:07,540
Yeah.

840
00:56:07,780 --> 00:56:12,990
And so I mean, throughout Western

841
00:56:13,710 --> 00:56:18,830
central Australia, all the dry bits basically, people had these

842
00:56:18,910 --> 00:56:23,230
incredibly complicated eight-section kinship systems.

843
00:56:23,310 --> 00:56:24,350
Do you guys know about those?

844
00:56:24,830 --> 00:56:26,030
Yeah, Christina knows.

845
00:56:26,110 --> 00:56:26,590
She's around.

846
00:56:27,710 --> 00:56:28,670
Yeah, exactly.

847
00:56:28,910 --> 00:56:33,230
And uh there's I tried to learn that it's really complicated.

848
00:56:34,190 --> 00:56:39,960
And and you know, that's evolved on something like 10,000 year timescales,

849
00:56:40,120 --> 00:56:40,280
right?

850
00:56:40,440 --> 00:56:46,040
Um and well we know from the geographical extent, I think, that

851
00:56:46,360 --> 00:56:48,920
and linguistic correlation that we don't really know.

852
00:56:49,080 --> 00:56:54,920
But but I mean it's not like bicycles,

853
00:56:55,000 --> 00:56:56,440
it's not the last hundred years.

854
00:56:56,520 --> 00:57:01,110
It's it's uh and kayaks we don't really know.

855
00:57:01,350 --> 00:57:07,190
I mean, I wish we did, but we the history of kayaks, there's some toy kayaks from about

856
00:57:07,190 --> 00:57:08,150
4,000 years ago.

857
00:57:08,230 --> 00:57:11,910
They look like the modern ones, but and that's about all we have.

858
00:57:11,990 --> 00:57:14,550
Uh, and then some that are a few hundred years old.

859
00:57:14,790 --> 00:57:18,230
Um, so we don't really know very much about the time scale.

860
00:57:18,550 --> 00:57:24,320
Um and surprisingly, people on the north coast of Asia

861
00:57:24,880 --> 00:57:30,720
and Kamcheka and places like that, which you'd think present pretty similar

862
00:57:30,720 --> 00:57:32,080
ecological problems.

863
00:57:32,240 --> 00:57:36,880
They do build skin boats, but they're really crude compared to the skin boats of people in

864
00:57:36,880 --> 00:57:37,680
North America.

865
00:57:37,840 --> 00:57:40,400
So I wish we knew more about that.

866
00:57:40,560 --> 00:57:46,550
And um the only good examples I think we really have are

867
00:57:46,710 --> 00:57:49,670
uh pretty recent um things.

868
00:57:49,830 --> 00:57:55,670
Uh there's a gor there's this guy whose name I forget again, sorry, who English guy who

869
00:57:55,670 --> 00:57:59,510
um studies the evolution of looms in East Asia.

870
00:57:59,750 --> 00:58:01,510
Uh they're fantastic.

871
00:58:01,750 --> 00:58:07,190
He really understands the history and the phylogenetic patterns, and there's a bunch of

872
00:58:07,190 --> 00:58:12,780
horizontal transmission, which makes, I mean, horizontal not in the between group

873
00:58:12,780 --> 00:58:14,060
transmission of ideas.

874
00:58:14,140 --> 00:58:15,180
And anyway.

875
00:58:15,740 --> 00:58:17,580
So I don't think we know.

876
00:58:17,980 --> 00:58:22,940
But I guess what I was trying to argue, Rob, is that like we know that we we we have good

877
00:58:22,940 --> 00:58:26,860
reason to believe that like 50,000 years ago we didn't have kayaks everywhere.

878
00:58:27,020 --> 00:58:28,540
Uh I don't buy that.

879
00:58:29,580 --> 00:58:29,740
Okay.

880
00:58:29,820 --> 00:58:29,900
Okay.

881
00:58:30,220 --> 00:58:31,100
No, I don't buy that at all.

882
00:58:31,260 --> 00:58:33,980
So so there could have been like we could have, I mean, I know there's debate about like

883
00:58:33,980 --> 00:58:39,180
Neanderthals also doing some level of like seafaring or Oh, I think the evidence evidence

884
00:58:39,180 --> 00:58:45,010
for seafaring uh and the first people who got to actually of all people, Kristen Hawks

885
00:58:45,090 --> 00:58:48,370
has a paper, uh, Kristen and Jim O'Connell.

886
00:58:48,690 --> 00:58:54,130
Um, quite good, I think, for my taste, quite good evidence that the earliest

887
00:58:54,130 --> 00:58:57,650
settlers of Australia had ocean-going boats.

888
00:58:57,810 --> 00:58:58,610
Oh, wow, okay.

889
00:58:58,850 --> 00:59:04,660
Um they get this from the settlement of offshore islands, which are which

890
00:59:04,980 --> 00:59:08,500
would have been you know 50 or 100 kilometers.

891
00:59:08,900 --> 00:59:11,140
Or maybe there is a kayak module.

892
00:59:11,700 --> 00:59:13,780
No, but they weren't the same boats.

893
00:59:13,860 --> 00:59:17,780
You know, the uh all the details about how to make the kayak.

894
00:59:18,100 --> 00:59:18,820
No, I agree.

895
00:59:19,140 --> 00:59:25,060
You know, it it's there may be some boat module, possibly.

896
00:59:25,140 --> 00:59:30,990
I I'm skeptical actually, but but um uh But more more plausibly there

897
00:59:30,990 --> 00:59:32,990
are folk physics modules.

898
00:59:33,150 --> 00:59:36,670
I mean, I don't like the term module, but there are systems that have intuitions or

899
00:59:36,750 --> 00:59:40,830
expectations about the physical world and how objects interact.

900
00:59:41,150 --> 00:59:46,030
Surely there are there are probably uh you know folk engineering or tool use modules where

901
00:59:46,030 --> 00:59:49,070
we have a concept of what a tool is and that it has a specific function.

902
00:59:49,630 --> 00:59:53,390
That's what this guy uh o Suriak, this French guy.

903
00:59:53,550 --> 00:59:55,060
Uh Anyway, sorry to interrupt.

904
00:59:55,300 --> 01:00:00,580
Yeah, no, and and Clark Barrett has argued this in his book Um Uh The Shape of Thought.

905
01:00:00,820 --> 01:00:06,660
So it seems to me that even the extreme uh Santa Barbara

906
01:00:06,660 --> 01:00:11,700
school picture of the mind, which is filled with these context sensitive, specialized

907
01:00:11,700 --> 01:00:12,740
modules, right?

908
01:00:12,980 --> 01:00:17,060
Is totally compatible with cultural evolution and cultural adaptation.

909
01:00:17,620 --> 01:00:19,460
Do you see any kind of incompatibility there?

910
01:00:19,540 --> 01:00:22,710
Because it seems like those those two pictures of the mind could both be true.

911
01:00:22,870 --> 01:00:27,990
We could both have really sophisticated minds with complex specialized adaptations, and we

912
01:00:27,990 --> 01:00:32,070
could have cultural evolution and culturally adaptive processes at the same time.

913
01:00:32,150 --> 01:00:36,230
And it may be even be the case that the two complement each other, that you're more likely

914
01:00:36,230 --> 01:00:40,390
to get cultural evolution in a more adaptive direction if you have the the the

915
01:00:40,550 --> 01:00:43,910
sophisticated mind to evaluate the different outputs of culture.

916
01:00:44,310 --> 01:00:48,800
But then you can't Yes, I agree with everything you just said.

917
01:00:49,040 --> 01:00:49,360
Okay.

918
01:00:49,520 --> 01:00:53,200
Um, but that's not what John Alita said.

919
01:00:53,440 --> 01:00:53,760
Okay.

920
01:00:54,000 --> 01:00:59,680
Uh they wanted to go from stories about I

921
01:01:00,000 --> 01:01:01,760
that's pejorative, I shouldn't say that.

922
01:01:02,640 --> 01:01:08,480
They wanted to go from hypotheses about uh life

923
01:01:08,480 --> 01:01:13,840
in mobile foraging bands in um the late Pleistocene,

924
01:01:14,400 --> 01:01:20,270
and make inferences about how people should behave now.

925
01:01:21,070 --> 01:01:26,670
And that means that there's a direct correspondence between some

926
01:01:26,750 --> 01:01:32,270
adaptive, I mean, I'm quoting them now almost, some adaptive problem that people

927
01:01:32,590 --> 01:01:38,030
faced in these Pleistocene societies and how

928
01:01:38,190 --> 01:01:41,870
behavior is expressed now in response to cues that people get.

929
01:01:42,430 --> 01:01:45,940
And uh I'm sure that's true to some extent.

930
01:01:46,100 --> 01:01:51,620
I mean, but um I also think there's a huge range of

931
01:01:51,620 --> 01:01:55,220
behavior, which that doesn't help you with.

932
01:01:55,380 --> 01:01:59,140
But John John, I think, thought that got you the whole package.

933
01:01:59,620 --> 01:02:03,940
I mean it well, it could it could well get you the whole like what if some of those modules

934
01:02:03,940 --> 01:02:09,810
involve evaluating potential uh tools or uh uh potential uh foraging strategies

935
01:02:09,970 --> 01:02:13,810
or potential social norms in terms of whether they advocate for one's interests or through

936
01:02:13,970 --> 01:02:19,570
the norm or the tool should be like correct they don't but they could nevertheless

937
01:02:20,130 --> 01:02:21,570
right I think that's that's true.

938
01:02:21,730 --> 01:02:23,090
That that's the key difference, right.

939
01:02:23,330 --> 01:02:27,730
But it seems like i if if we're assuming that they don't tell you the content of the norms

940
01:02:27,810 --> 01:02:32,100
or the content of the tool, then it seems like they're entirely compatible perspectives

941
01:02:32,100 --> 01:02:36,740
that you could yeah yeah but we got to fill in the details and you know uh

942
01:02:39,060 --> 01:02:42,740
yeah I don't think we're very close to that actually and I think Christina's point I mean

943
01:02:42,900 --> 01:02:47,780
just want to echo Christina's point it also then means that there is this issue of at what

944
01:02:47,780 --> 01:02:53,380
level of abstraction and the the concern would be that you're looking at um something

945
01:02:53,700 --> 01:02:58,410
that so just to be clear, like we were talking about like where does the evolved psychology

946
01:02:58,410 --> 01:03:02,170
end and where does the information stored in the environment begin?

947
01:03:02,970 --> 01:03:08,970
And Christina's point, if I understood it, was that you it's hard to know, and there may

948
01:03:08,970 --> 01:03:14,490
be cases where we think something is so well designed that uh

949
01:03:14,650 --> 01:03:19,770
we're really looking at it as like this is something that's in the phenotype, that's you

950
01:03:19,770 --> 01:03:25,440
know, reliably developing, and that's why it has the problem-solving and form

951
01:03:25,680 --> 01:03:27,600
fit relationship we do.

952
01:03:28,080 --> 01:03:33,840
But then there's this other thing of once we once we accept that cultural

953
01:03:33,840 --> 01:03:39,280
selection can create form-fit relationships, then we might be

954
01:03:39,280 --> 01:03:45,280
inferring, for just for lack of a better way of putting it, like genetic selection

955
01:03:45,600 --> 01:03:50,250
systems, where in fact it's more cultural selection systems.

956
01:03:50,410 --> 01:03:53,930
It's oh when we know the clear distinction, like Christina always talks about like reading,

957
01:03:54,010 --> 01:03:57,530
I think is a good example where you know if we didn't know about the history of reading, we

958
01:03:57,530 --> 01:03:59,450
might think it's just it's a module.

959
01:03:59,770 --> 01:04:00,330
It's a module.

960
01:04:00,410 --> 01:04:01,450
I mean maybe not.

961
01:04:01,530 --> 01:04:02,170
I don't I don't know.

962
01:04:02,250 --> 01:04:04,010
Like 'cause the fact that not everybody learns to read.

963
01:04:04,090 --> 01:04:07,210
Like I I I you know like any example has its issues.

964
01:04:07,370 --> 01:04:09,050
But I think that's a fair point, Christine.

965
01:04:09,130 --> 01:04:11,720
I want to make sure like that like is that fair, Christina?

966
01:04:11,960 --> 01:04:16,360
Yeah, and I think that so I was trying to also I not to be like material versus social is

967
01:04:16,360 --> 01:04:21,160
like a clear distinction, but I think that the social world is fuller of that ambiguity.

968
01:04:21,320 --> 01:04:24,200
Like we don't know very much about about Paleolithic social life.

969
01:04:24,280 --> 01:04:25,880
It probably was super diverse.

970
01:04:26,040 --> 01:04:31,080
Um we don't know what it was like two million years ago, three million years ago, like

971
01:04:31,330 --> 01:04:32,610
forget it, right?

972
01:04:32,850 --> 01:04:38,690
Um, and like to to do a parallel to the reading example, like almost every society has

973
01:04:38,690 --> 01:04:39,410
marriage today.

974
01:04:39,570 --> 01:04:41,010
I know there are exceptions.

975
01:04:41,410 --> 01:04:46,610
Um, and so we might infer that there's like a marriage-like modular world cognition that

976
01:04:46,610 --> 01:04:50,210
really favors marriage when you know we have good theoretical reasons to believe that

977
01:04:50,210 --> 01:04:51,890
that's probably a cultural institution.

978
01:04:52,050 --> 01:04:56,450
Like, yes, you know, partly driven by like psychological motivations that are patent human

979
01:04:56,530 --> 01:05:02,260
and so forth, but I think it's a real challenge to disentangle those, and more so when we

980
01:05:02,260 --> 01:05:07,700
don't have like a good paleontology or archaeology to kind of help with our intuition about

981
01:05:07,860 --> 01:05:07,940
it.

982
01:05:08,100 --> 01:05:08,660
Yeah, yeah, yeah.

983
01:05:08,900 --> 01:05:13,700
The idea that our brain is just uh you know a shapeless mass with no

984
01:05:13,700 --> 01:05:17,860
predispositions, that's just obviously stupid.

985
01:05:18,180 --> 01:05:24,100
And um I you know, Steve Pinker's book, The Blank Slate.

986
01:05:24,790 --> 01:05:29,750
I mean, I know there are lots of social scientists who believe in the blank slate, but

987
01:05:30,630 --> 01:05:33,110
they're just not thinking hard about things.

988
01:05:33,270 --> 01:05:33,910
It can't be.

989
01:05:34,070 --> 01:05:38,790
It just it just no matter what, they can't be, you know,

990
01:05:39,910 --> 01:05:43,830
and so it's always about how does it work exactly.

991
01:05:44,150 --> 01:05:50,140
And um or I completely agree with you Christina maybe exact we're never

992
01:05:50,140 --> 01:05:55,260
going to get to exactly but maybe a little bit of structure uh and um

993
01:05:56,140 --> 01:06:02,140
and uh I so what I would say is questions

994
01:06:02,140 --> 01:06:07,870
are not about whether there's evolved stuff in the human

995
01:06:07,870 --> 01:06:12,270
brain that shapes the way we respond to cues in the environment.

996
01:06:12,350 --> 01:06:13,790
That's gotta be, right?

997
01:06:14,110 --> 01:06:19,550
But there are questions about, you know, quantitative questions about where we sit on

998
01:06:20,030 --> 01:06:21,150
a kind of continuum.

999
01:06:21,230 --> 01:06:27,150
And my picture is um, because we're predisposed strongly to

1000
01:06:27,150 --> 01:06:32,960
think what people around us do must be sensible, um uh uh we

1001
01:06:32,960 --> 01:06:38,800
get a lot of stuff from that and um and i i

1002
01:06:38,800 --> 01:06:44,160
if that's the way that evps psych is going i'm pleased i mean that's um

1003
01:06:44,720 --> 01:06:49,600
uh uh you know you know when there's gonna be disagreements you know we're scientists right

1004
01:06:49,680 --> 01:06:55,650
that's the business we're in but but uh but on the other side of things coming from like

1005
01:06:55,810 --> 01:07:01,650
what um what questions might have influenced cultural evolutionary theorists

1006
01:07:01,730 --> 01:07:06,930
um coming from like the more cynical like economists or of psych side, do you think that

1007
01:07:06,930 --> 01:07:12,450
there's been any shift in like thinking about what that credulity has to look like?

1008
01:07:12,770 --> 01:07:15,090
Or like what the limits of that credulity are?

1009
01:07:15,410 --> 01:07:16,850
Yeah, it's a good question.

1010
01:07:17,090 --> 01:07:22,580
Um I mean I think of it more uh I

1011
01:07:22,580 --> 01:07:28,180
mean so so I talk to Sarah Matthew quite a bit, and

1012
01:07:28,740 --> 01:07:34,580
she and I differ about um how likely it

1013
01:07:34,580 --> 01:07:40,370
is that evolved motivations, I would call them about kinship and

1014
01:07:40,370 --> 01:07:44,850
stuff, structure, cultural evolution.

1015
01:07:45,890 --> 01:07:48,290
And, you know, she could be right.

1016
01:07:48,450 --> 01:07:50,770
I mean, um, I could be right.

1017
01:07:50,850 --> 01:07:53,090
Uh these are things that we're gonna learn.

1018
01:07:53,170 --> 01:07:59,010
But I wouldn't say uh I I think of it as a bunch of specific stuff, not

1019
01:07:59,010 --> 01:08:04,610
some general limitation about how credulous we are, but how

1020
01:08:04,610 --> 01:08:10,480
strongly we're motivated in by different kinds of things we experience in

1021
01:08:10,480 --> 01:08:15,760
the environment to to um to think well no yeah

1022
01:08:16,960 --> 01:08:22,720
uh there's this xkcd cartoon that that um the

1023
01:08:22,720 --> 01:08:28,530
mother is asking the kid you know um Are you, you know, the

1024
01:08:28,530 --> 01:08:32,290
kid says, I I'm, you know, you you're doing this just because all your friends are doing

1025
01:08:32,290 --> 01:08:32,370
it.

1026
01:08:32,450 --> 01:08:37,970
And the kid says, is, yeah, that would what would I I I always succumb to kin pressure.

1027
01:08:38,130 --> 01:08:40,130
And the mother says, why would you do that?

1028
01:08:40,210 --> 01:08:43,250
You know, suppose you were on a on a burning bridge.

1029
01:08:43,410 --> 01:08:49,170
And uh, and the kid says, Well, if 50 of my friends, well informed,

1030
01:08:49,330 --> 01:08:51,640
jump off the bridge, who am I?

1031
01:08:51,800 --> 01:08:56,120
You know, what's the newspaper the next day gonna say about the people who stayed on the

1032
01:08:56,120 --> 01:08:56,680
bridge?

1033
01:08:56,920 --> 01:08:59,320
And but that depends on the cue.

1034
01:08:59,480 --> 01:09:02,280
It depends on what inferences you can make from the environment.

1035
01:09:02,440 --> 01:09:04,120
You know, maybe all those people were stupid.

1036
01:09:04,280 --> 01:09:08,840
They jumped off the bridge, and you're the smart person who who made the calculation to do

1037
01:09:08,840 --> 01:09:09,880
it correctly.

1038
01:09:10,120 --> 01:09:15,790
Um something that makes me super anxious about our enterprise here

1039
01:09:15,950 --> 01:09:20,190
is that I think I think we can largely agree that there about like certain basic

1040
01:09:20,190 --> 01:09:21,310
motivations that we have, right?

1041
01:09:21,390 --> 01:09:25,390
Like motivations like hunger is motivating, um, sex is motivating, so forth.

1042
01:09:25,870 --> 01:09:29,550
And you know, you might think on a good day, like, okay, we just need to find like the

1043
01:09:29,550 --> 01:09:33,950
order in which the prior like the algorithm that prioritizes some motivations or the other,

1044
01:09:34,030 --> 01:09:37,230
including the motivation to conform to others, might be like, I think there might be a

1045
01:09:37,230 --> 01:09:42,940
little bit of a debate about how much that's in an uh bit of motivation to conform to what

1046
01:09:42,940 --> 01:09:43,500
others do.

1047
01:09:43,740 --> 01:09:44,060
Yeah.

1048
01:09:44,220 --> 01:09:49,820
Um but on my nihilistic days, I think what's crazy is that those motivations themselves

1049
01:09:49,820 --> 01:09:50,940
culturally evolve.

1050
01:09:51,260 --> 01:09:51,740
For sure.

1051
01:09:52,060 --> 01:09:57,900
So that makes kind of coming up with like a well, but look, I

1052
01:09:57,900 --> 01:10:00,220
mean motivations to conform, culturally.

1053
01:10:00,460 --> 01:10:04,620
You're prone to these kinds of motivated by hunger, right?

1054
01:10:04,780 --> 01:10:10,350
Or like how much you should be motivated by yeah but you're prone to these depressive uh

1055
01:10:10,670 --> 01:10:16,510
uh uh feelings Christine I've known you this long uh think of where we've come in the last

1056
01:10:16,830 --> 01:10:22,110
75 years even 50 years you know I wouldn't we're much less confused now.

1057
01:10:22,270 --> 01:10:22,830
I'm sorry.

1058
01:10:22,990 --> 01:10:28,750
Yeah yeah I I wouldn't frame that as the motivation to conform evolving itself.

1059
01:10:28,910 --> 01:10:30,430
That doesn't really make a lot of sense to me.

1060
01:10:30,510 --> 01:10:35,560
What might make sense is that the costs of not conforming might vary from place to place.

1061
01:10:35,720 --> 01:10:39,560
Well, I think the power imbalances and the alliance structure might be such that there are

1062
01:10:39,560 --> 01:10:42,840
really powerful people who are really going to do bad things to you if you violate the

1063
01:10:42,840 --> 01:10:43,080
norms.

1064
01:10:43,240 --> 01:10:47,400
And in some environments the power structure is different and those costs aren't as high.

1065
01:10:47,640 --> 01:10:50,680
But I wouldn't explain that as culture shaping the motivation to conform.

1066
01:10:50,840 --> 01:10:55,080
I would just explain that in terms of, you know, the mind making cost benefit calculations

1067
01:10:55,080 --> 01:10:58,600
about what what is going to be the likely course of action in this particular social

1068
01:10:58,600 --> 01:10:58,920
context.

1069
01:10:59,160 --> 01:10:59,320
Yeah.

1070
01:10:59,400 --> 01:11:01,560
You're a real evolutionary psychologist.

1071
01:11:01,960 --> 01:11:06,990
Uh uh there's quite a bit of evidence that in other

1072
01:11:07,150 --> 01:11:12,030
creatures that uh there's an innate conformist propensity.

1073
01:11:12,110 --> 01:11:16,270
It's got nothing to do with norms or other people's punishments.

1074
01:11:16,430 --> 01:11:21,710
Uh some evidence in people, it's somewhat conflictual, conflicting, um,

1075
01:11:22,190 --> 01:11:27,440
but models show that in the right kind of environment, having an

1076
01:11:27,440 --> 01:11:32,880
intrinsic motive to conform can make you better off.

1077
01:11:32,960 --> 01:11:33,280
Yeah.

1078
01:11:33,520 --> 01:11:35,760
And uh in the fitness sense.

1079
01:11:36,000 --> 01:11:40,080
And uh now it hangs on being hard to figure out what the right answer is.

1080
01:11:40,320 --> 01:11:46,080
And um and uh so and I think I mean

1081
01:11:46,160 --> 01:11:52,030
now this is I won't live long enough to find out what

1082
01:11:52,030 --> 01:11:57,710
the answer to this question is, but uh I think we are innately

1083
01:11:58,030 --> 01:12:03,470
predisposed, or innately, we have, you know, reliably developing whatever you want to call

1084
01:12:03,470 --> 01:12:08,590
it, uh um propensity to obey social norms.

1085
01:12:09,230 --> 01:12:15,150
Um we don't do a cal well, we do do calculations, but we don't need to.

1086
01:12:15,470 --> 01:12:21,340
We're we uh all other things being equal

1087
01:12:21,740 --> 01:12:27,340
if if the norm is to um you know

1088
01:12:27,580 --> 01:12:33,580
play the game a particular way lime in the corn sure yeah so you know these these

1089
01:12:33,580 --> 01:12:39,500
experiments that Mike Tomasalo has done i watch the videos he te they teach

1090
01:12:39,500 --> 01:12:45,340
some little German kid a new game Daxing and um and then the

1091
01:12:45,430 --> 01:12:51,190
kid learns how to play the game, and then they have a f a Schill who then

1092
01:12:51,190 --> 01:12:52,950
plays the game wrong.

1093
01:12:53,190 --> 01:12:58,710
And the kids, Nick, not not not Daxing, he says in German, you know, he gets gets really

1094
01:12:58,710 --> 01:12:59,190
agitated.

1095
01:12:59,430 --> 01:13:00,310
That's his verboten.

1096
01:13:00,470 --> 01:13:00,550
Yeah.

1097
01:13:02,310 --> 01:13:07,750
And uh you know, I don't think uh evolutionary

1098
01:13:07,750 --> 01:13:13,180
psychology um i i think our

1099
01:13:13,660 --> 01:13:19,340
our sense that some things are right and some things are wrong there's morality and uh

1100
01:13:19,580 --> 01:13:24,860
and we feel intrinsically motivated about uh moral

1101
01:13:24,860 --> 01:13:30,780
violations that's not in my view now this is a hypothesis not a fact

1102
01:13:31,020 --> 01:13:36,350
uh uh a calculation based on the cost and benefits of powerful people.

1103
01:13:36,590 --> 01:13:42,590
It's something we feel and I can make models that show how such a thing

1104
01:13:42,590 --> 01:13:43,230
could evolve.

1105
01:13:43,390 --> 01:13:44,990
Doesn't mean evolve that way.

1106
01:13:46,430 --> 01:13:52,190
And it again depends on uh on the difficulty

1107
01:13:52,190 --> 01:13:54,270
of doing the calculations.

1108
01:13:54,350 --> 01:14:00,180
Uh and um um so uh I think uh

1109
01:14:00,420 --> 01:14:03,620
that one is one which we're gonna make progress on, actually.

1110
01:14:03,780 --> 01:14:06,500
That uh uh yeah, totally.

1111
01:14:06,580 --> 01:14:07,780
You you you may be right there, Rob.

1112
01:14:08,020 --> 01:14:12,740
There may be a real disagreement here, but I want to push you and and uh to acknowledge

1113
01:14:12,740 --> 01:14:14,180
that maybe there is no disagreement.

1114
01:14:14,260 --> 01:14:18,980
We're just talking past each other because even your model of norms is built on the

1115
01:14:18,980 --> 01:14:20,020
foundations of punishment.

1116
01:14:20,180 --> 01:14:24,710
What a norm is is something that people are punished for doing and the non-punishers are

1117
01:14:24,710 --> 01:14:25,750
punished, right?

1118
01:14:26,070 --> 01:14:29,910
And so the the punish the idea of punishment, the infliction of costs, is built into the

1119
01:14:29,910 --> 01:14:30,150
model.

1120
01:14:30,390 --> 01:14:35,590
That's it's built into the evolutionary model, not the contemporary why people do it model.

1121
01:14:36,150 --> 01:14:40,230
So that explains why we have a norm psychology.

1122
01:14:40,390 --> 01:14:46,230
Once you've got a norm psychology, you know, the reason that you're outraged that oh, what

1123
01:14:46,390 --> 01:14:49,910
it was some outrage at the Olympics recently about uh some rule.

1124
01:14:49,990 --> 01:14:53,900
But anyway, um uh or I mean seriously.

1125
01:14:54,380 --> 01:14:58,460
But doesn't it presuppose that you have to know what's being punished and what's not being

1126
01:14:58,460 --> 01:14:58,700
punished?

1127
01:14:59,020 --> 01:14:59,580
No, no, no.

1128
01:14:59,660 --> 01:15:01,180
You just need to know what the norm is.

1129
01:15:01,500 --> 01:15:05,420
But then how but how do you know what what the norm is if unless you're observing because

1130
01:15:05,660 --> 01:15:07,660
people teach you, because you see what everybody does.

1131
01:15:07,980 --> 01:15:08,860
How are they teaching you though?

1132
01:15:08,940 --> 01:15:13,100
Presumably they have to, you know, threaten you with punishment or actually punish you,

1133
01:15:13,180 --> 01:15:13,260
right?

1134
01:15:13,580 --> 01:15:14,300
No, no.

1135
01:15:14,540 --> 01:15:17,820
Uh so I I don't even think you believe this.

1136
01:15:17,980 --> 01:15:23,150
Um uh uh so uh is it okay to beat your wife?

1137
01:15:23,550 --> 01:15:24,670
I mean, obviously not.

1138
01:15:24,750 --> 01:15:26,350
And well, some I call it.

1139
01:15:26,430 --> 01:15:27,310
I think it's fine.

1140
01:15:27,550 --> 01:15:31,470
Uh yeah, when we did this fieldwork in Fiji, um

1141
01:15:33,310 --> 01:15:39,230
uh Fijian norms uh uh have it that if you don't beat your wife when she's

1142
01:15:39,550 --> 01:15:45,460
talks back or does some uppity thing, uh you're a not just that

1143
01:15:45,460 --> 01:15:47,700
you don't get what you want, you're a bad person.

1144
01:15:48,100 --> 01:15:53,860
And uh okay, so one of our field assistants was a

1145
01:15:53,860 --> 01:15:55,940
couple, a married couple.

1146
01:15:56,260 --> 01:16:01,780
And um uh the guy, you know,

1147
01:16:02,100 --> 01:16:05,140
beat his wife pretty severely one night.

1148
01:16:05,460 --> 01:16:07,060
So what do you do about that?

1149
01:16:07,220 --> 01:16:12,610
Uh you're living in a culture where um that's the right thing to do.

1150
01:16:12,850 --> 01:16:15,410
Uh we told him he couldn't do it.

1151
01:16:15,490 --> 01:16:20,930
And so these moral beliefs, by the time you get to be mine, sure are strongly held.

1152
01:16:21,010 --> 01:16:26,770
And they've got nothing to do with the calculation of of my long-term

1153
01:16:26,770 --> 01:16:27,410
benefit.

1154
01:16:27,570 --> 01:16:29,330
Uh I I might disagree there.

1155
01:16:29,490 --> 01:16:34,960
I mean, like uh it I think if you ask anyone, you know, uh what will happen if you are seen

1156
01:16:34,960 --> 01:16:39,200
as a domestic abuser, they will say that you will you will suffer horrible reputational

1157
01:16:39,200 --> 01:16:39,760
consequences.

1158
01:16:40,240 --> 01:16:45,840
But we pay we took this guy who was our field assistant and we paid a

1159
01:16:45,840 --> 01:16:51,840
substantial cost to yell at him and tell him he couldn't do that in a culture where

1160
01:16:51,840 --> 01:16:54,320
everybody thought what he was doing was fine.

1161
01:16:54,930 --> 01:16:59,330
I think there may be presumably people understand that there are reputational costs for

1162
01:16:59,330 --> 01:17:00,770
engaging in certain behaviors.

1163
01:17:00,850 --> 01:17:04,210
And that was where was the reputational cost to me?

1164
01:17:04,610 --> 01:17:10,450
Uh I I don't uh I mean maybe to be super cynical, maybe you know it was

1165
01:17:10,450 --> 01:17:13,570
gonna get back to your colleagues that you had a wife beater already.

1166
01:17:13,890 --> 01:17:15,890
Yeah I mean that's the argument you'd have to make.

1167
01:17:16,690 --> 01:17:18,690
But can I subject I don't believe that argument.

1168
01:17:18,850 --> 01:17:23,170
I I I I mean to give you another example from my

1169
01:17:24,760 --> 01:17:30,760
failed field work um uh uh in Fiji there's a very strong norm

1170
01:17:30,920 --> 01:17:36,600
that women must be covered from head to toe in the village and uh

1171
01:17:36,680 --> 01:17:42,600
and Fijian guys gossip endlessly about shoulders and ankles uh and uh

1172
01:17:42,760 --> 01:17:48,360
uh you know they never see anything else young guys that is and uh so

1173
01:17:48,600 --> 01:17:54,010
we spent three months in this village and we went to the um to um

1174
01:17:54,810 --> 01:18:00,730
uh we got at the village boat, took us you know several hours down

1175
01:18:00,730 --> 01:18:06,570
the archipelago and dropped us at this beach where a tourist boat would come and pick us

1176
01:18:06,570 --> 01:18:06,890
up.

1177
01:18:07,210 --> 01:18:12,250
And so we're sitting on the beach having lunch, and a tourist walks by, a woman, and she's

1178
01:18:12,250 --> 01:18:13,290
in a bikini.

1179
01:18:13,370 --> 01:18:19,220
And I had this overwhelming that woman needs to put

1180
01:18:19,220 --> 01:18:20,340
some clothes on.

1181
01:18:20,660 --> 01:18:23,780
She is not dressed properly.

1182
01:18:24,180 --> 01:18:29,700
And um there you did adapt to the local circumstances.

1183
01:18:30,260 --> 01:18:31,460
I did, absolutely.

1184
01:18:31,540 --> 01:18:34,340
Uh but it was, I didn't realize that adapted.

1185
01:18:34,820 --> 01:18:40,420
You know, it was um this is not science, this is you know, it's my I'm giving

1186
01:18:41,540 --> 01:18:46,330
anecdot that living in a place where

1187
01:18:47,610 --> 01:18:52,170
people thought it was wrong for women, and this is all brand new in Fiji.

1188
01:18:52,410 --> 01:18:54,170
This is only 150 years old.

1189
01:18:54,330 --> 01:19:00,090
Uh um, and she was dressed completely fine by

1190
01:19:00,250 --> 01:19:05,050
you know, we got on this boat and it's covered with college age tourists, all of them

1191
01:19:05,290 --> 01:19:09,530
bikinis, and in 45 minutes I didn't feel that way anymore.

1192
01:19:09,770 --> 01:19:15,740
But uh uh um but I speak to like three different timescales at least at

1193
01:19:15,740 --> 01:19:19,820
which like things like punishment and I mean we could there's a whole debate about what

1194
01:19:19,820 --> 01:19:22,380
kinds of social costs these are might be acting.

1195
01:19:22,540 --> 01:19:24,300
So mainly not punishment, I think.

1196
01:19:24,460 --> 01:19:26,620
Mainly loss of social standing.

1197
01:19:26,700 --> 01:19:26,940
Yeah.

1198
01:19:29,420 --> 01:19:31,420
That's a kind a kind of p a kind of cost, yeah.

1199
01:19:31,740 --> 01:19:34,790
Well, but it doesn't it's not costly punishment, it doesn't cost right.

1200
01:19:34,950 --> 01:19:39,670
If if you deprive people of costly services, you'd have to give them with because they were

1201
01:19:39,670 --> 01:19:42,550
good people, then it actually pays you to punish them.

1202
01:19:42,630 --> 01:19:47,190
But so there are models that are like this is about intergenerational evolutionary

1203
01:19:47,190 --> 01:19:48,390
timescales that we're talking about.

1204
01:19:48,470 --> 01:19:54,310
And this endowed us with some sort of like genetically evolved intuition for conforming to

1205
01:19:54,310 --> 01:19:59,110
whatever we see other people around us to do in order to avoid those social costs.

1206
01:19:59,270 --> 01:20:02,540
Then there's a possibility and these are not mutually exclusive because it seems like even

1207
01:20:02,540 --> 01:20:04,540
your experiences are at different timescales, right?

1208
01:20:05,100 --> 01:20:05,820
Two different timescales.

1209
01:20:06,140 --> 01:20:06,940
Two different timescales.

1210
01:20:07,180 --> 01:20:11,980
Another one is that like you in you like currently there are institutions that ostracize

1211
01:20:11,980 --> 01:20:14,860
you, punish you, whatever, for not conforming.

1212
01:20:14,940 --> 01:20:20,220
And so you learn about that early in childhood, let's say, and you kind of develop these in

1213
01:20:20,220 --> 01:20:23,650
internalized ideas about what is morally right and wrong.

1214
01:20:23,810 --> 01:20:27,490
And then like if the social environment changes for you like in adulthood, it's not going

1215
01:20:27,490 --> 01:20:30,130
to change very quick like those intuitions aren't going to change very quickly.

1216
01:20:30,530 --> 01:20:33,010
They're shallow, the diff the the things yeah.

1217
01:20:33,170 --> 01:20:36,850
I I think the only thing there is a third there is a third though, just to be complete.

1218
01:20:37,010 --> 01:20:40,050
Like there is a third possibility, I don't know if anybody believes this, but that it's

1219
01:20:40,130 --> 01:20:42,050
like very much in the moment, right?

1220
01:20:42,130 --> 01:20:47,250
That like the current incentive structures shape in the moment throughout your life.

1221
01:20:47,410 --> 01:20:48,770
Like what is right and what is wrong.

1222
01:20:48,930 --> 01:20:50,640
And I don't know how credible that is.

1223
01:20:51,280 --> 01:20:53,280
I mean this is these are questions, right?

1224
01:20:53,360 --> 01:20:54,080
Good questions.

1225
01:20:54,320 --> 01:20:59,840
Uh um I mean the only thing I would add to to the to the

1226
01:21:00,800 --> 01:21:06,720
is that once you've internalized that beating your wife is wrong, then when

1227
01:21:06,720 --> 01:21:11,280
you do the calculation about should I beat my wife?

1228
01:21:11,520 --> 01:21:17,190
Um uh I mean on David's account, and I I certainly think

1229
01:21:17,190 --> 01:21:22,230
that's part of it, is I'm thinking about what'll happen to me if I get caught beating my

1230
01:21:22,230 --> 01:21:22,710
wife.

1231
01:21:23,030 --> 01:21:29,030
But I'm also have feelings that affect my trade-off that that

1232
01:21:29,030 --> 01:21:30,390
this is not the right thing to do.

1233
01:21:30,470 --> 01:21:36,470
I I I I get negative, you know, displeasure, whatever it is, um

1234
01:21:37,720 --> 01:21:43,720
Because I grew up in a society and and so that tips, that changes the

1235
01:21:43,720 --> 01:21:46,280
way I do the the the calculation.

1236
01:21:46,600 --> 01:21:51,400
And um you know, I so anyway.

1237
01:21:51,560 --> 01:21:55,720
So yeah, I think some of the issue too is I think with all of these conversations, one of

1238
01:21:55,720 --> 01:22:01,650
the problems is uh the entire conversation we've had, natural selection or

1239
01:22:01,650 --> 01:22:05,570
selective selection based thinking of cultural things.

1240
01:22:05,890 --> 01:22:11,410
We we lack a good nat, we don't have a natural vocabulary of what are the entities, right?

1241
01:22:11,490 --> 01:22:17,010
Like, is it a piece of um culture design, uh

1242
01:22:17,330 --> 01:22:18,290
a module?

1243
01:22:18,610 --> 01:22:22,690
And now we're talking about sort of emotions, and you know, there's sort of well, like cost

1244
01:22:22,770 --> 01:22:23,330
benefit.

1245
01:22:23,410 --> 01:22:26,120
There's a sense in which I can calculate the cost benefit.

1246
01:22:26,200 --> 01:22:30,200
Like Rob, I think the other thing I do is I get really angry when people cross uh

1247
01:22:30,360 --> 01:22:33,560
pedestrian no walks now after living in Germany.

1248
01:22:33,880 --> 01:22:34,280
Exactly.

1249
01:22:34,520 --> 01:22:38,120
And that's like a very that's like how many times do you get yelled at in Germany from

1250
01:22:38,600 --> 01:22:40,040
violating some rule you didn't know?

1251
01:22:40,680 --> 01:22:42,600
Which I yeah, I I I loved it actually.

1252
01:22:42,760 --> 01:22:44,840
I was dispositionally German.

1253
01:22:44,920 --> 01:22:49,930
Uh but anyway, um but uh uh but but then like there, but there's another sense of which

1254
01:22:50,010 --> 01:22:51,770
David, you know, even the emotions, right?

1255
01:22:51,850 --> 01:22:55,290
Like maybe the emotions baked into the emotions are cost benefit.

1256
01:22:55,450 --> 01:23:00,170
But of course, there's a difference between the kind of rational cost benefit that sort of

1257
01:23:00,170 --> 01:23:05,450
like goal or planning systems are considering in this very short time scale versus maybe

1258
01:23:05,450 --> 01:23:07,770
these longer timescale emotional systems.

1259
01:23:08,010 --> 01:23:13,820
So I think in a lot of ways, um what typically is failing us is that there's

1260
01:23:13,820 --> 01:23:19,580
just distinctions that are not made in the natural language that we all sort of have as

1261
01:23:19,580 --> 01:23:23,500
organisms or just as cultural beings in the 21st century now.

1262
01:23:24,220 --> 01:23:25,500
English speakers in the 21st century.

1263
01:23:25,820 --> 01:23:26,780
Exactly, yeah, precisely.

1264
01:23:26,860 --> 01:23:27,500
Yeah, exactly.

1265
01:23:27,580 --> 01:23:31,830
And that's uh yeah, we had Clark on recently and he was making a point that um, you know,

1266
01:23:31,990 --> 01:23:35,670
it that's is also useful to talk to other people from different cultural backgrounds

1267
01:23:35,750 --> 01:23:39,990
because they'll make different distinctions that we might be able to use, you know, or or

1268
01:23:39,990 --> 01:23:41,590
at least see like our cultural bias.

1269
01:23:41,750 --> 01:23:47,350
But I think, like for me at least, uh there there's a sense in which all of these

1270
01:23:47,670 --> 01:23:53,670
debates can be resolved, but they really hang on making more distinctions, and

1271
01:23:53,670 --> 01:23:57,430
you can't start to make those more distinctions till you maybe you have the debates to

1272
01:23:57,430 --> 01:23:57,910
begin with.

1273
01:23:58,150 --> 01:23:59,110
Yeah, I agree with that.

1274
01:23:59,190 --> 01:24:04,880
Yeah, I think um uh you know we've made

1275
01:24:04,880 --> 01:24:05,280
progress.

1276
01:24:05,600 --> 01:24:06,240
That's good.

1277
01:24:06,400 --> 01:24:11,520
Uh and science is the you know series of

1278
01:24:11,520 --> 01:24:13,680
hypotheses now refuted.

1279
01:24:13,840 --> 01:24:18,560
And also, you know, Mox Planck said science progresses one funeral at a time.

1280
01:24:18,800 --> 01:24:21,680
Um, and I think there's some truth to that too.

1281
01:24:21,920 --> 01:24:27,710
Um Rob just to push on like I mean for Pete's argument that it's sort of

1282
01:24:27,710 --> 01:24:33,630
all very general he'll allow motivations yeah but no

1283
01:24:33,790 --> 01:24:39,390
that can be quite specific motivations but there aren't any um

1284
01:24:40,430 --> 01:24:46,270
I'm not actually sure how he parses this out but but uh uh there's

1285
01:24:46,270 --> 01:24:52,220
nothing in there that tells you um what would be good examples I mean, obviously

1286
01:24:52,380 --> 01:24:53,500
technological examples.

1287
01:24:53,580 --> 01:24:56,620
There's nothing we're you know, like birds' nests.

1288
01:24:56,860 --> 01:25:02,780
Uh and um maybe like no propensities

1289
01:25:02,780 --> 01:25:05,980
to think about taxonomic categories in a yeah, yeah, exactly.

1290
01:25:06,060 --> 01:25:07,580
That'd be a good thing.

1291
01:25:07,740 --> 01:25:13,490
Uh uh that we don't we aren't innately Linnaean in our taxonomic

1292
01:25:13,570 --> 01:25:16,050
um right way of thinking.

1293
01:25:16,130 --> 01:25:19,170
Uh and I think the evidence is pretty good we aren't.

1294
01:25:19,410 --> 01:25:25,170
Uh uh the Fijians put dolphins and and fish in the

1295
01:25:25,170 --> 01:25:31,010
same category, but um uh yeah, and

1296
01:25:31,010 --> 01:25:35,420
they don't and you know so they don't have any animals they care about.

1297
01:25:35,500 --> 01:25:40,860
They're pigs and chickens and and you know and they just don't think about

1298
01:25:40,860 --> 01:25:44,380
vertebrates very much, but I mean land vertebrates, but anyway.

1299
01:25:44,620 --> 01:25:44,780
Yeah.

1300
01:25:44,940 --> 01:25:49,420
But do you think I mean I do the I mean like we all I think we all do this, and I think

1301
01:25:49,420 --> 01:25:54,940
this is something I learned from Christina, which is this notion of you make the

1302
01:25:54,940 --> 01:26:00,550
tentative Almost like a gambit or like a assumption that's

1303
01:26:00,550 --> 01:26:03,270
helpful for your own carving up the world, right?

1304
01:26:03,350 --> 01:26:08,710
So, like I, as a as a John and Lita adaptationist, I don't want to study the

1305
01:26:08,710 --> 01:26:13,590
complexities of like developmental programs or like genetic pleotropy.

1306
01:26:13,830 --> 01:26:15,510
Like, I want to I want to assume that away.

1307
01:26:15,590 --> 01:26:16,550
And so I do.

1308
01:26:16,790 --> 01:26:21,190
And there's an argument in sense which like that's fair of me because of what I'm studying.

1309
01:26:21,350 --> 01:26:26,880
Somebody else later, even though I'm wrong about saying it doesn't matter if I say that, it

1310
01:26:26,880 --> 01:26:31,680
does matter, I can assume it away because for what the slice of the world is that I'm

1311
01:26:31,680 --> 01:26:35,120
studying, I have to assume it away at least for now.

1312
01:26:35,360 --> 01:26:39,360
Does is Pete what is is Pete assuming he's a hundred percent with that?

1313
01:26:39,520 --> 01:26:44,950
I mean I I mean I we think of ourselves as com full adaptationists.

1314
01:26:45,030 --> 01:26:45,350
Yeah.

1315
01:26:45,510 --> 01:26:51,430
And and uh but we just see the adaptive problem as different

1316
01:26:51,510 --> 01:26:56,630
than I see it differently than than maybe John and Lita did.

1317
01:26:57,430 --> 01:27:03,350
And uh you know in our in Nobajin Salon we have this example of the

1318
01:27:03,350 --> 01:27:09,340
avocado slicer that uh I was, you know,

1319
01:27:09,580 --> 01:27:15,340
the the adaptationist paradigm is uh it's not a paradigm,

1320
01:27:15,420 --> 01:27:16,540
it's a heuristic.

1321
01:27:16,780 --> 01:27:22,460
And uh it is an extremely powerful heuristic, which sometimes leads you

1322
01:27:22,460 --> 01:27:23,260
astray.

1323
01:27:23,580 --> 01:27:29,100
And um uh and depends on a bunch of ancillary

1324
01:27:29,410 --> 01:27:34,290
hypotheses about trade-offs and costs and benefits and a bunch of other stuff.

1325
01:27:34,450 --> 01:27:39,970
And um uh and I, you know, I have no time whatsoever

1326
01:27:40,290 --> 01:27:46,130
for Goodian or or um uh the guy

1327
01:27:46,130 --> 01:27:52,050
that studied Tiktalic, this fish, he's a big believer in, you

1328
01:27:52,420 --> 01:27:53,620
developmental constraints.

1329
01:27:53,780 --> 01:27:55,860
I I don't think they're constraints.

1330
01:27:56,020 --> 01:28:01,860
I think there are developmental pathways that affect the

1331
01:28:01,860 --> 01:28:07,780
patterns of variation that can that do exist now and that will exist

1332
01:28:07,940 --> 01:28:11,460
in the future if we make if we make some changes.

1333
01:28:11,700 --> 01:28:13,380
And they're obviously important.

1334
01:28:13,460 --> 01:28:17,860
And the extent that they're important, they make the adaptation as paradigm.

1335
01:28:22,570 --> 01:28:26,170
Because if you don't know what those developmental um

1336
01:28:29,850 --> 01:28:34,090
couldn't is this a I'm thinking something about why you wouldn't call this a constraint.

1337
01:28:34,570 --> 01:28:37,610
Um like a pathway versus a constraint.

1338
01:28:38,330 --> 01:28:44,220
Um maybe it comes from my background is doing I did for three years did

1339
01:28:45,180 --> 01:28:51,100
optimization mathematics as a you know to design things like power plant systems and stuff.

1340
01:28:51,260 --> 01:28:57,260
And a constraint is something is a relationship between variables that you're trying to

1341
01:28:57,260 --> 01:28:58,860
adjust that is fixed.

1342
01:28:59,660 --> 01:29:05,490
So either, you know, temperature is related to volume and there's a curve and

1343
01:29:05,490 --> 01:29:11,090
then you have to travel along that curve or um or

1344
01:29:11,330 --> 01:29:17,250
uh there's a constraint the you know something can't be greater than uh less than zero,

1345
01:29:17,410 --> 01:29:18,210
say or something like that.

1346
01:29:18,450 --> 01:29:18,610
Right.

1347
01:29:18,690 --> 01:29:23,250
If you make the the smokestack higher with less concrete, it would be better, but it's not

1348
01:29:23,250 --> 01:29:24,130
gonna stay up to the state.

1349
01:29:24,370 --> 01:29:25,250
There is no smokestack.

1350
01:29:25,520 --> 01:29:25,840
Yeah.

1351
01:29:25,920 --> 01:29:26,560
It's a constraint.

1352
01:29:26,720 --> 01:29:26,880
Yeah.

1353
01:29:27,040 --> 01:29:32,080
And I think most of the things we ha we see in biology are

1354
01:29:32,640 --> 01:29:38,480
things that shape the patterns of variation that selection can work

1355
01:29:38,480 --> 01:29:38,800
on.

1356
01:29:38,960 --> 01:29:44,160
They don't say it can't go there, but they affect the

1357
01:29:44,320 --> 01:29:49,650
likelihood that new variants um are produced.

1358
01:29:50,050 --> 01:29:53,570
And so sometimes it can be absolutely crucial, you know.

1359
01:29:53,730 --> 01:29:58,370
So do you guys know the Lensky experiments with with um E.

1360
01:29:58,530 --> 01:29:58,850
coli?

1361
01:29:59,650 --> 01:30:02,050
Yeah, like lots of different evolutionary trajectories, right?

1362
01:30:02,210 --> 01:30:02,450
Yeah.

1363
01:30:02,610 --> 01:30:04,450
So Lensky did experiments.

1364
01:30:04,530 --> 01:30:10,130
I think he's got 14 replicants now 65,000 plus

1365
01:30:10,370 --> 01:30:11,010
generations.

1366
01:30:11,410 --> 01:30:17,090
Uh in the same it puts them in a new environment 65,000 generations ago and

1367
01:30:17,880 --> 01:30:19,240
watches what happens.

1368
01:30:19,560 --> 01:30:22,680
At first, um, they diverge.

1369
01:30:22,840 --> 01:30:28,440
Some of them uh they go in the same average direction, they get bigger, the individual E.

1370
01:30:28,600 --> 01:30:34,360
coli get bigger, uh, they do a bunch of other things, but some lines are

1371
01:30:34,360 --> 01:30:35,960
doing better than other lines.

1372
01:30:36,040 --> 01:30:39,770
So, and he can prove this because he he's got them in the freezer.

1373
01:30:39,930 --> 01:30:41,050
He's got fossil E.

1374
01:30:41,210 --> 01:30:42,490
coli in the freezer.

1375
01:30:42,650 --> 01:30:47,610
And he creates competition experiments between a thousand generations ago and now.

1376
01:30:47,930 --> 01:30:51,370
And sure enough, the new ones always beat the old ones.

1377
01:30:51,610 --> 01:30:52,970
Okay, so this is all great.

1378
01:30:53,050 --> 01:30:58,730
And then after 20 or 30,000 generations, a lot of that variation disappears.

1379
01:30:59,130 --> 01:31:04,730
And they are all pretty much on the same, not quite, but almost on the same trajectory.

1380
01:31:05,050 --> 01:31:08,280
And now these are not eukaryotes, right?

1381
01:31:08,360 --> 01:31:11,640
So they don't have full-blown recombination.

1382
01:31:11,800 --> 01:31:13,080
They have some recombination.

1383
01:31:13,240 --> 01:31:15,160
But so it takes a while.

1384
01:31:15,320 --> 01:31:20,520
My picture of this and his picture is that it takes a while for you know the order in which

1385
01:31:20,520 --> 01:31:22,760
mutations occur matters, right?

1386
01:31:22,920 --> 01:31:28,040
Both because mutations potentiate other mutations and all this kind of stuff.

1387
01:31:28,440 --> 01:31:33,720
But then at like 50,000, I don't know the exact number, but in about 50,000 generations,

1388
01:31:34,200 --> 01:31:37,210
all of a sudden, one of the lines

1389
01:31:40,090 --> 01:31:42,970
just beats the crap out of everybody else.

1390
01:31:43,690 --> 01:31:46,010
So the typical, you know, how this experiment works?

1391
01:31:46,170 --> 01:31:51,210
He puts he puts in some glucose in the morning.

1392
01:31:51,530 --> 01:31:55,290
The population expands to carrying capacity, then they shut down.

1393
01:31:55,450 --> 01:31:57,530
The next morning gives them more glucose.

1394
01:31:57,610 --> 01:31:59,770
And that goes on for 40,000 generations.

1395
01:31:59,850 --> 01:32:01,770
And they get better at that environment.

1396
01:32:01,900 --> 01:32:07,660
Now there's citrate in the medium, and it's very well known in E.

1397
01:32:07,820 --> 01:32:09,820
coli biology that E.

1398
01:32:09,980 --> 01:32:14,060
coli cannot digest citrate in the presence of oxygen.

1399
01:32:14,300 --> 01:32:19,580
The enzyme that's necessary to do the job is inactivated in the presence of oxygen.

1400
01:32:19,740 --> 01:32:24,930
This is something that people who do, It was thought to be true of all E.

1401
01:32:25,170 --> 01:32:27,810
coli, but not at 50,000 generations.

1402
01:32:29,250 --> 01:32:35,090
A series of neutral mutations had occurred, and then eventually, and those are

1403
01:32:35,090 --> 01:32:40,610
all improbable that they drift to high enough frequency, and then a new

1404
01:32:40,610 --> 01:32:45,740
mutation that Coupled with those neutral ones,

1405
01:32:46,380 --> 01:32:47,180
allowed the E.

1406
01:32:47,260 --> 01:32:50,540
coli to digest citrate in the presence of oxygen.

1407
01:32:50,940 --> 01:32:54,140
And all of a sudden, all bets are off.

1408
01:32:54,220 --> 01:32:58,940
It completely annihilated the the previous um

1409
01:32:59,900 --> 01:33:01,740
50,000 generations.

1410
01:33:01,820 --> 01:33:07,630
You know, in humans, that goes back, you know, to the Mesozoic practically,

1411
01:33:07,710 --> 01:33:07,950
right?

1412
01:33:08,030 --> 01:33:13,630
I don't know exactly how far, but but 60,000 times 10 is

1413
01:33:13,630 --> 01:33:18,110
600,000 gen uh uh no 600,000 years.

1414
01:33:18,590 --> 01:33:23,710
Yeah, so it doesn't go back to the Mesozoic, but it goes back well before people, and um,

1415
01:33:24,030 --> 01:33:29,320
so there is this kind of stuff you would never have predicted that on an

1416
01:33:29,320 --> 01:33:34,520
adaptationist program if you took this

1417
01:33:34,840 --> 01:33:36,840
species-specific property of E.

1418
01:33:37,000 --> 01:33:43,000
coli, namely they can't digest citrate in the presence of oxygen as a fix as a

1419
01:33:43,000 --> 01:33:44,040
constraint, right?

1420
01:33:44,200 --> 01:33:49,800
And um, and it wasn't a constraint, there just wasn't any variation in the necessary

1421
01:33:51,530 --> 01:33:56,490
genes which gave rise to the necessary phenotypic variation for that to happen.

1422
01:33:56,650 --> 01:34:02,490
And the series of mutations and events, namely drift, that had to occur for that to

1423
01:34:02,490 --> 01:34:06,090
happen, um are very improbable.

1424
01:34:06,570 --> 01:34:12,320
So I you know I think you know the

1425
01:34:12,320 --> 01:34:18,000
adaptation is it hypothesis extremely powerful, but sometimes it gets you the wrong

1426
01:34:18,000 --> 01:34:18,400
answer.

1427
01:34:18,560 --> 01:34:19,040
Yeah.

1428
01:34:19,360 --> 01:34:24,960
So what do you make of some people are really um kind of concerned about making equilibrium

1429
01:34:25,200 --> 01:34:29,280
type arguments, which is kind of maybe another version of the phenotypic gambit?

1430
01:34:29,520 --> 01:34:29,920
I don't know.

1431
01:34:30,080 --> 01:34:36,000
Just that um even if we're adaptations, like the world is constantly changing and no time

1432
01:34:36,160 --> 01:34:37,360
more than today.

1433
01:34:37,600 --> 01:34:42,670
Um, does this I think Pete has actually made some arguments to this effect and some of his

1434
01:34:42,670 --> 01:34:47,310
students that like equilibrium thinking is just at odds with what we know about the human

1435
01:34:47,310 --> 01:34:47,950
experience.

1436
01:34:50,110 --> 01:34:54,910
Does this give us pause for making adaptationist kinds of we should think about the

1437
01:34:54,910 --> 01:34:57,310
timescale on which variation takes place?

1438
01:34:57,470 --> 01:35:01,710
And and I know Pete knows all about this, but he likes to argue.

1439
01:35:02,030 --> 01:35:04,830
I have not argued with Pete about this particular item.

1440
01:35:05,070 --> 01:35:09,240
Uh I mean there's variation on all kinds of timescales, right?

1441
01:35:09,400 --> 01:35:15,160
And um and uh on some time scales, I

1442
01:35:15,160 --> 01:35:19,800
think you know that technically, so if we have variation on

1443
01:35:20,920 --> 01:35:26,440
um say we have an organism that has a one-year generation time and and we have

1444
01:35:27,110 --> 01:35:29,910
temporal variation on 100-year timescales.

1445
01:35:30,230 --> 01:35:36,070
Um, it's never going to reach an equilibrium, but uh, but there'll be a

1446
01:35:36,070 --> 01:35:38,950
stationary distribution of types, right?

1447
01:35:39,190 --> 01:35:45,190
And um it'll respond to some temporal average or in spatial, you know,

1448
01:35:45,270 --> 01:35:48,150
it's all these averages in population genetics.

1449
01:35:49,360 --> 01:35:55,280
I think that's clearly of great importance to get the right timescale on which you

1450
01:35:55,280 --> 01:35:58,240
think adaptation is responding.

1451
01:35:58,560 --> 01:36:00,320
But it's not an imprinciple thing.

1452
01:36:00,400 --> 01:36:05,040
It's just one of the things you have to take into account when it's, you know, it's there

1453
01:36:05,040 --> 01:36:06,160
are trade-offs, right?

1454
01:36:06,240 --> 01:36:09,840
And and um if only we knew.

1455
01:36:10,400 --> 01:36:15,680
Well, I think, yeah, uh I I'm more of an optimist than you are, Christina.

1456
01:36:18,590 --> 01:36:18,910
Yeah.

1457
01:36:19,950 --> 01:36:25,790
I think so Pete and I have argued that agriculture didn't evolve uh during

1458
01:36:25,790 --> 01:36:31,790
the Pleistocene because not because you couldn't grow plants, because you know, wheat was

1459
01:36:31,790 --> 01:36:32,830
growing somewhere for sure.

1460
01:36:32,910 --> 01:36:35,870
It didn't just appear magically 10,000 years ago.

1461
01:36:36,110 --> 01:36:41,700
Um uh but because the timescale of fluctuations during the last

1462
01:36:41,700 --> 01:36:47,380
glacial was too short for the and I, you know, we would

1463
01:36:47,380 --> 01:36:52,580
support that with so if you look at the spread of agriculture across the world,

1464
01:36:53,140 --> 01:36:56,260
agriculture didn't spread, agriculturalists spread.

1465
01:36:56,500 --> 01:37:02,100
So, um, and so populations which already had the norms, you know,

1466
01:37:02,340 --> 01:37:07,950
women's roles, you have to be willing when you're an agriculturalist, you've got to be able

1467
01:37:07,950 --> 01:37:08,910
to save stuff.

1468
01:37:09,070 --> 01:37:11,230
And so sharing norms have to change.

1469
01:37:11,390 --> 01:37:14,670
There's a whole bunch of stuff that has to change.

1470
01:37:15,470 --> 01:37:20,030
And our argument would be that that doesn't change on 500-year timescales.

1471
01:37:20,270 --> 01:37:25,230
And um, you know, um, now that might be wrong.

1472
01:37:25,390 --> 01:37:29,870
Um I have to say, archaeologists haven't taken it very seriously.

1473
01:37:30,030 --> 01:37:35,720
Um, but uh but um that's a case where

1474
01:37:35,720 --> 01:37:41,240
our picture of the temporal scale on which norms evolve is

1475
01:37:41,480 --> 01:37:46,680
related to the temporal scale on which the environment's evolving.

1476
01:37:46,760 --> 01:37:51,320
And if you you know, I mean I could go on and on, but but the the the environmental

1477
01:37:51,320 --> 01:37:56,680
variation in the Pleistocene was staggering compared to the to the Holocene.

1478
01:37:56,920 --> 01:38:02,910
I mean, um, you know, you could be a hunter-gatherer living in what would

1479
01:38:02,910 --> 01:38:08,590
be now the south coast of France, and 500 years later you're living in northern Norway

1480
01:38:08,670 --> 01:38:10,990
someplace without having moved at all.

1481
01:38:11,150 --> 01:38:17,070
That was this that was the scale and and the amplitude and timescale of and now

1482
01:38:17,070 --> 01:38:21,390
the place, the Holocene is this happy, warm, stable world.

1483
01:38:21,550 --> 01:38:26,060
Uh, and um, I really think we really ought to think about that.

1484
01:38:26,140 --> 01:38:30,060
And and uh uh Eric Smith thinks.

1485
01:38:30,380 --> 01:38:35,340
So I Pete and I published this paper, this shows you, you know, how you get hoisted on your

1486
01:38:35,340 --> 01:38:36,220
own petard.

1487
01:38:36,620 --> 01:38:42,140
Um uh we published this paper a couple years ago about large-scale cooperation in

1488
01:38:42,140 --> 01:38:43,740
Holocene Hunter-gatherers.

1489
01:38:43,820 --> 01:38:49,420
That I would argue shows there's plenty of large-scale cooperation in,

1490
01:38:49,580 --> 01:38:55,030
and we argue, see, These ethnographic studies of the Kung and the

1491
01:38:55,030 --> 01:38:58,870
Hadza and so on are not good models for the Pleistocene.

1492
01:38:58,950 --> 01:39:04,790
That um that uh if you think about Pleistocene cooperation, you could you should think

1493
01:39:04,790 --> 01:39:08,070
about large-scale cooperation amongst non-relatives.

1494
01:39:08,230 --> 01:39:12,150
And Eric said, Oh yeah, but uh

1495
01:39:13,500 --> 01:39:18,940
Pleistocene climate variation was so great that the social institutions necessary to

1496
01:39:18,940 --> 01:39:24,460
support large-scale cooperation couldn't have evolved, so they were just like the Hodsa.

1497
01:39:26,860 --> 01:39:28,380
I thought that was mean.

1498
01:39:29,900 --> 01:39:30,940
Full circle, yeah.

1499
01:39:31,420 --> 01:39:33,100
At least he cited you, right?

1500
01:39:33,740 --> 01:39:35,180
He was one of the reviewers.

1501
01:39:35,260 --> 01:39:36,060
That's how I know.

1502
01:39:36,140 --> 01:39:37,900
It wasn't that he wrote a paper about this.

1503
01:39:37,980 --> 01:39:43,710
It's that so we we quoted him in the paper and and uh

1504
01:39:44,110 --> 01:39:49,950
and we got permission to use his name because Eric is a very smart guy and thoughtful.

1505
01:39:50,030 --> 01:39:50,430
But yeah.

1506
01:39:50,910 --> 01:39:54,670
Rob, this is a slight change of or topic, just methodological for a second.

1507
01:39:54,750 --> 01:39:58,030
I know uh like do you what is your opinion about sort of computer technology?

1508
01:39:58,110 --> 01:40:01,550
Because a lot of the stuff we're talking about is also like there's you can do if you

1509
01:40:01,550 --> 01:40:06,160
understand the concepts, you can do the math, but then there's also a lot of computational

1510
01:40:06,160 --> 01:40:07,360
modeling of things.

1511
01:40:07,680 --> 01:40:13,040
Do you view the sort of analytic or you know math um thinking about

1512
01:40:13,040 --> 01:40:16,240
ESSs versus modeling and simulations?

1513
01:40:16,800 --> 01:40:20,480
Do you view that as still separate?

1514
01:40:20,720 --> 01:40:26,720
And is there a cost of losing the first to the second with all the technology?

1515
01:40:26,800 --> 01:40:28,640
Or what's your st what's your take on that?

1516
01:40:28,960 --> 01:40:29,280
You know?

1517
01:40:29,680 --> 01:40:32,400
I I I think they've always been complementary.

1518
01:40:32,720 --> 01:40:38,390
Um I think they're the the you know the cheapness and

1519
01:40:38,390 --> 01:40:44,230
speed of of computing has made agent based simulations better and more

1520
01:40:44,230 --> 01:40:45,110
practical.

1521
01:40:45,350 --> 01:40:51,030
Um I think that agent based simulations uh there's a temptation to over

1522
01:40:51,430 --> 01:40:57,040
specify uh that people because it's easy, people have a

1523
01:40:57,040 --> 01:41:02,160
tendency to to build what they think of as realism into the models.

1524
01:41:02,400 --> 01:41:05,600
And you know, all models are wrong, some are useful.

1525
01:41:05,680 --> 01:41:07,600
That's a famous aphorism.

1526
01:41:10,640 --> 01:41:16,400
And I think that done right, um analytic

1527
01:41:16,400 --> 01:41:22,290
models and um Computer simulations should be used

1528
01:41:22,290 --> 01:41:27,570
together to understand things, especially things where random

1529
01:41:27,570 --> 01:41:33,410
factors are important, like climate change or small population effects, or any of

1530
01:41:33,410 --> 01:41:34,210
those things.

1531
01:41:36,290 --> 01:41:42,050
I will say that for kind of sociological reasons, I think, or

1532
01:41:42,050 --> 01:41:47,600
maybe cultural evolutionary reasons, when I publish an

1533
01:41:47,600 --> 01:41:53,440
analytical result, the the uh I put nowadays, I didn't used to, but all the math

1534
01:41:53,440 --> 01:41:57,440
is in the, you know, the the uh what do they call that?

1535
01:41:57,520 --> 01:42:01,680
The supplementary the supplementary material, but somebody can follow it.

1536
01:42:01,840 --> 01:42:02,000
Yeah.

1537
01:42:02,240 --> 01:42:02,880
That's not true.

1538
01:42:03,200 --> 01:42:08,400
There's no, you know, people always say I put my code in the in you know the supplementary,

1539
01:42:08,480 --> 01:42:14,160
but it might as well be on the moon because we don't have any conventions about how to

1540
01:42:14,400 --> 01:42:17,910
to to and I will tell you a story.

1541
01:42:18,150 --> 01:42:24,070
Um uh I like stories, but um uh Herb Gintis and I, this

1542
01:42:24,070 --> 01:42:29,910
2001 paper that's been cited more than any other paper I've ever written, and I actually

1543
01:42:29,910 --> 01:42:35,190
think is maybe not such a great paper, um where we looked at uh

1544
01:42:35,430 --> 01:42:37,270
cultural group selection.

1545
01:42:37,590 --> 01:42:42,880
Um uh Well, the details are important.

1546
01:42:43,200 --> 01:42:48,800
But for reasons I don't really remember, Herb and I decided to do um

1547
01:42:49,680 --> 01:42:52,560
uh uh clean room simulations.

1548
01:42:52,880 --> 01:42:58,800
So we both wrote simulations, we clearly specified what the model should be

1549
01:42:58,800 --> 01:43:04,570
like, and then we wrote the simulations and they did completely different things

1550
01:43:05,130 --> 01:43:10,570
and um uh it took us a month of hard work to

1551
01:43:10,810 --> 01:43:16,250
find out where they diverged and why they diverged and it was all

1552
01:43:16,250 --> 01:43:20,890
stupid reasons none of it had was conceptual and

1553
01:43:21,900 --> 01:43:23,340
nobody does that, right?

1554
01:43:23,420 --> 01:43:27,500
The only people who do that are people writing programs to fly airplanes and stuff like

1555
01:43:27,500 --> 01:43:27,740
that.

1556
01:43:28,060 --> 01:43:33,980
And um uh I think this is a big problem actually, that that the

1557
01:43:34,060 --> 01:43:39,020
the reliability of analytical stuff is better than the

1558
01:43:39,020 --> 01:43:44,780
reliability of simulations because you know I write

1559
01:43:44,780 --> 01:43:47,180
simulations and I, you know, I've never done that since.

1560
01:43:47,340 --> 01:43:53,030
It took and uh so I don't know how we're gonna solve that, uh,

1561
01:43:53,190 --> 01:43:54,150
but we will, I think.

1562
01:43:54,230 --> 01:43:59,750
We'll we'll come up with and it's gonna make simulations a lot harder, uh, I think uh to to

1563
01:43:59,750 --> 01:44:01,030
to make sure they're right.

1564
01:44:01,190 --> 01:44:06,870
And um you might be able to ask AI today what's the difference between those and herbs.

1565
01:44:07,510 --> 01:44:12,950
Maybe maybe I I I ask AI to look at I I've been doing some simulation so

1566
01:44:13,510 --> 01:44:16,550
Moshi and I, you remember those conversations we had.

1567
01:44:16,710 --> 01:44:22,620
Moshi and I got in this argument about um uh the the

1568
01:44:22,620 --> 01:44:28,300
paper that minwa and i and christin and uh about continuous

1569
01:44:28,300 --> 01:44:33,660
norms and uh so mo she said well blah blah blah blah and

1570
01:44:34,060 --> 01:44:40,060
uh i couldn't the um the uh programming that minwa

1571
01:44:40,220 --> 01:44:45,420
had written couldn't be modified very easily to to address most these questions so i

1572
01:44:45,420 --> 01:44:51,150
rewrote an agent based model which fortunately produced the same results that

1573
01:44:51,150 --> 01:44:56,990
Benoit's produced, um, and was way faster, and so I'd forced Benoit to do all

1574
01:44:56,990 --> 01:44:59,870
this work because I thought the other way it'd be faster.

1575
01:45:00,110 --> 01:45:05,870
Anyway, uh and so then I I thought, well, I should ask

1576
01:45:05,870 --> 01:45:11,820
Chat GPT to look at this code, and and and and it had

1577
01:45:11,820 --> 01:45:13,740
all kinds of stupid suggestions.

1578
01:45:13,980 --> 01:45:19,980
Uh uh, so I I this was now t how long ago was it that we were arguing

1579
01:45:19,980 --> 01:45:20,540
with Moshi?

1580
01:45:20,780 --> 01:45:22,060
Two or three years ago, something like that.

1581
01:45:22,380 --> 01:45:23,020
Two years ago.

1582
01:45:23,180 --> 01:45:23,740
Yeah.

1583
01:45:23,980 --> 01:45:26,140
Uh and it may be that it's a lot better.

1584
01:45:26,220 --> 01:45:31,340
I mean, they're making and I know that from my daughter that that it is getting better.

1585
01:45:31,420 --> 01:45:32,860
So maybe it would work now.

1586
01:45:33,020 --> 01:45:38,730
But then it just had uh I thought it it it

1587
01:45:38,970 --> 01:45:44,890
it made a bunch of suggestions that would have made the code five percent faster and

1588
01:45:46,410 --> 01:45:49,130
a thousand percent harder to understand what it did.

1589
01:45:49,850 --> 01:45:55,130
And uh um so anyway, that's my anecdote about

1590
01:45:55,130 --> 01:45:56,410
ChatGPT.

1591
01:45:57,050 --> 01:45:58,810
It has no conceptual understanding.

1592
01:45:58,890 --> 01:46:04,060
Yeah, just do you think that's Yeah, it doesn't it at least then it didn't care about how

1593
01:46:04,060 --> 01:46:05,100
expressive the code was.

1594
01:46:05,420 --> 01:46:05,660
Right.

1595
01:46:05,740 --> 01:46:05,980
Yeah.

1596
01:46:06,540 --> 01:46:12,380
Do do you think we ought to be using more just basic analytic models, basic

1597
01:46:12,380 --> 01:46:15,740
algebra relative to agent based simulations?

1598
01:46:16,380 --> 01:46:18,380
Is that part of the the argument you're making?

1599
01:46:18,460 --> 01:46:21,420
That that that way of thinking is kind of underplayed?

1600
01:46:22,060 --> 01:46:27,970
It's harder and um uh I think, yeah, I do think it's not

1601
01:46:27,970 --> 01:46:29,090
enough of it being done.

1602
01:46:29,250 --> 01:46:35,170
And I think part of the problem is, I mean, this is another cultural evolutionary thing.

1603
01:46:37,250 --> 01:46:42,290
The people who do it, analytical work, are mainly

1604
01:46:42,930 --> 01:46:47,570
physicists and mathematicians that are looking for another job.

1605
01:46:47,890 --> 01:46:53,540
And they place a big store on the you know my

1606
01:46:53,540 --> 01:46:56,980
equations are longer than your equations kind of competition.

1607
01:46:57,220 --> 01:47:01,860
And uh and so this is really clear in reciprocity theory.

1608
01:47:02,020 --> 01:47:07,620
So um Rus I I just Sarah and I have just written a review of

1609
01:47:07,620 --> 01:47:12,100
reciprocity theory for um for um ticks.

1610
01:47:12,660 --> 01:47:18,310
And um I would say since 2005, maybe

1611
01:47:18,470 --> 01:47:24,470
somewhere in there, 95% of modeling and reciprocity

1612
01:47:25,030 --> 01:47:28,790
is responding to previous models of reciprocity.

1613
01:47:29,190 --> 01:47:34,550
And almost none of it is in

1614
01:47:34,550 --> 01:47:39,720
response to questions about observed behavior.

1615
01:47:39,960 --> 01:47:45,720
And that's because I work with a mathematician, Bertha Schoenmann, who was a

1616
01:47:45,720 --> 01:47:50,360
wonderful person and a good colleague, but too sensitive to work in the evolutionary

1617
01:47:50,360 --> 01:47:51,080
biology world.

1618
01:47:51,160 --> 01:47:53,080
He quit because we were so mean.

1619
01:47:53,800 --> 01:47:55,320
Reviewers were so mean.

1620
01:47:55,560 --> 01:48:01,550
Anyway, uh, he said mathematicians, to be a successful mathematician, you have to find

1621
01:48:01,550 --> 01:48:07,390
a problem that is not too easy, so anybody

1622
01:48:07,390 --> 01:48:10,670
could do it, and not so hard, so you can't do it.

1623
01:48:10,910 --> 01:48:14,670
But this sweet spot in between is something you can make progress on.

1624
01:48:14,830 --> 01:48:18,990
There's a lot of interesting developments, and that's what reciprocity theory is.

1625
01:48:19,150 --> 01:48:24,780
It's a really nice problem, a lot of possibilities, and I think mainly a waste of time.

1626
01:48:25,180 --> 01:48:31,100
Uh um uh and this is uh oh what few friends I have left in that field

1627
01:48:31,180 --> 01:48:33,580
I'm not gonna have any more after we publish this paper.

1628
01:48:33,740 --> 01:48:39,580
But um that's why John Minor Smith is my my intellectual hero.

1629
01:48:40,060 --> 01:48:42,700
Um he never did anything complicated.

1630
01:48:43,020 --> 01:48:43,260
Yeah.

1631
01:48:43,580 --> 01:48:47,100
Look at the f the classic, you know, Hamilton's rule, the classic Trevor's paper.

1632
01:48:47,180 --> 01:48:49,980
This is all this is just basically has no math in it.

1633
01:48:50,060 --> 01:48:52,150
But but there's a little bit of a little bit of it.

1634
01:48:52,230 --> 01:48:57,990
But yeah, I I well he he says Bill Hamilton told me that that you could represent this as

1635
01:48:57,990 --> 01:48:59,270
a prisoner's dilemma.

1636
01:48:59,510 --> 01:49:00,790
Here's what Hamilton said.

1637
01:49:01,030 --> 01:49:07,030
I just you know I've read that paper recently so I'm it's easy for me to be an expert here.

1638
01:49:07,110 --> 01:49:13,000
But but um uh uh and that paper is full of bad

1639
01:49:13,000 --> 01:49:15,080
confusions, the Tververs paper.

1640
01:49:15,240 --> 01:49:21,240
But uh you know, he he well, I won't go into that, but but you know we should have a

1641
01:49:21,240 --> 01:49:22,360
two hour episode about Trivers.

1642
01:49:22,840 --> 01:49:27,400
He's one of our you know powerful ancestors, but he's not a clear thinker.

1643
01:49:27,560 --> 01:49:33,400
He he's uh he's uh extremely brilliant, intuitive thinker, but you

1644
01:49:33,800 --> 01:49:35,240
you gotta check, right?

1645
01:49:35,400 --> 01:49:41,210
I mean um you know the key is to find simple

1646
01:49:41,210 --> 01:49:46,410
enough representations of some problem that you can make analytical progress.

1647
01:49:46,570 --> 01:49:49,050
And there are some problems you just can't do that way.

1648
01:49:49,210 --> 01:49:54,810
I mean, you know, uh anything involving random drift-like features.

1649
01:49:54,970 --> 01:49:59,210
I mean, there is analytical stuff, but it's hopelessly complicated and it can't do

1650
01:49:59,210 --> 01:49:59,690
anything.

1651
01:49:59,850 --> 01:50:03,370
Well, there's lots of interesting stuff it can't do very easily.

1652
01:50:03,530 --> 01:50:09,240
Uh Anything, any model in which selection varies in

1653
01:50:09,240 --> 01:50:12,280
time or space, and it isn't white.

1654
01:50:12,440 --> 01:50:18,280
So if there's any correlations in time and space, there's no analytical method to deal with

1655
01:50:18,280 --> 01:50:18,440
that.

1656
01:50:18,520 --> 01:50:22,760
That's completely opaque to analytical approaches.

1657
01:50:22,840 --> 01:50:24,280
And it's quite easy to deal with.

1658
01:50:24,360 --> 01:50:26,440
John Gillespie did a lot of work on that.

1659
01:50:27,000 --> 01:50:29,400
And so, and that's obviously a question of importance.

1660
01:50:29,480 --> 01:50:31,240
So we ought to do a lot of simulations.

1661
01:50:33,090 --> 01:50:35,810
but if we can do the analytical stuff, it's very powerful.

1662
01:50:35,890 --> 01:50:39,730
It gives you intuitions that are hard to get out of the simulations.

1663
01:50:39,890 --> 01:50:45,650
You can get them, but it's harder because the equations talk to you.

1664
01:50:45,730 --> 01:50:50,290
You know, they when you look at the equations, they tell you things without actually having

1665
01:50:50,290 --> 01:50:51,410
to solve them.

1666
01:50:51,810 --> 01:50:57,540
And um And as yet, I think we'll fix this, but as

1667
01:50:57,540 --> 01:51:03,380
yet, our simulation tools don't do this.

1668
01:51:03,540 --> 01:51:09,380
Um I've been working with a couple of Spaniards uh uh uh economists

1669
01:51:09,620 --> 01:51:15,620
who do simulations of repeated prisoners' dilemma of all things, but I just

1670
01:51:15,620 --> 01:51:17,060
got done criticizing.

1671
01:51:17,300 --> 01:51:22,950
And um they use this thing that's often thought of as kind of a

1672
01:51:22,950 --> 01:51:25,910
child's play programming language, net logo.

1673
01:51:26,550 --> 01:51:32,310
And um I'm really impressed to the extent to which they're able to get

1674
01:51:32,950 --> 01:51:38,470
intuitions out of the way how easy it is.

1675
01:51:38,920 --> 01:51:44,280
It's very slow and a kind of stupid language and as a computer science kind of project.

1676
01:51:44,520 --> 01:51:49,080
But in terms of teaching stuff, I'm very impressed.

1677
01:51:49,160 --> 01:51:50,280
I'm gonna try to learn it.

1678
01:51:50,360 --> 01:51:53,560
And anyway, so I think this is technological, a lot of it.

1679
01:51:53,640 --> 01:51:56,840
We just haven't we haven't been doing it long enough to to be good at it.

1680
01:51:57,000 --> 01:52:02,970
And um the the Asian-based simulation says, But

1681
01:52:02,970 --> 01:52:08,810
the idea is that uh the anal the analysis so far or the formulas are

1682
01:52:09,050 --> 01:52:15,050
you're forced to know what your the concepts and the relationships in a way that you could

1683
01:52:15,050 --> 01:52:18,810
sort of be agnostic um about in a simulation.

1684
01:52:18,890 --> 01:52:23,130
Like you might run a simulation where like, well, yeah, I don't know what that I don't know

1685
01:52:23,130 --> 01:52:25,080
why, I don't know what the relationship is.

1686
01:52:25,240 --> 01:52:26,680
I just know I got an outcome.

1687
01:52:26,920 --> 01:52:30,360
And I don't really know what all the things that I fit into what mattered or didn't.

1688
01:52:30,440 --> 01:52:36,440
It's just in in compared to the analysis or the formula where or the analytic math, you

1689
01:52:36,440 --> 01:52:42,360
have to know what the entity is and what the relationships are,

1690
01:52:42,440 --> 01:52:44,200
or otherwise you're not able to do that.

1691
01:52:44,360 --> 01:52:45,560
Oh, I I I disagree with that.

1692
01:52:45,720 --> 01:52:46,040
Okay, yeah.

1693
01:52:50,650 --> 01:52:52,410
Asian-based simulation.

1694
01:52:52,810 --> 01:52:56,490
So, in an analytical model, typically you've got a bunch of state variables, you know,

1695
01:52:56,570 --> 01:52:58,970
frequencies of genes or whatever it is.

1696
01:52:59,210 --> 01:53:05,210
And you write down a dynamical system in which you posit relationships based on some in my

1697
01:53:05,210 --> 01:53:08,250
way of thinking, and Christina was forced to go through all this.

1698
01:53:08,410 --> 01:53:13,370
In my class, you write down a life cycle and you ask what happens to individuals, and you

1699
01:53:13,530 --> 01:53:19,100
and then you use the law of large numbers to then ask to create

1700
01:53:19,100 --> 01:53:21,420
relationships for the state variables.

1701
01:53:21,740 --> 01:53:27,580
Um I think agent-based simulations are exactly the same in the sense you have to

1702
01:53:27,580 --> 01:53:31,740
write down a life cycle, you have to write down state variables, but now the state

1703
01:53:31,740 --> 01:53:36,780
variables aren't these aggregate ones, they're ones at the individual level, you know, what

1704
01:53:36,780 --> 01:53:39,020
it knows, how big it is, whatever it is.

1705
01:53:39,340 --> 01:53:44,870
And so your space of possibilities is much bigger.

1706
01:53:45,510 --> 01:53:51,510
But I think in at least the way I think about things,

1707
01:53:51,750 --> 01:53:56,950
uh there's a quantitative difference between them, but

1708
01:53:56,950 --> 01:53:59,430
conceptually they're exactly the same.

1709
01:54:00,150 --> 01:54:06,080
There's nothing uh you have to specify ahead of time

1710
01:54:06,640 --> 01:54:08,800
what the possibilities are.

1711
01:54:09,280 --> 01:54:10,560
Uh you can't have unknown.

1712
01:54:10,800 --> 01:54:16,080
And I there was a physicist at S of I when I was there who went on and on about what was

1713
01:54:16,080 --> 01:54:21,120
wrong with evolutionary theory, is that it specified the possibilities in advance, and

1714
01:54:21,120 --> 01:54:23,360
evolution really didn't do that.

1715
01:54:23,520 --> 01:54:28,450
It could go, and I think this is really an argument about how big the space is.

1716
01:54:28,610 --> 01:54:32,290
And if the space gets big enough, then um

1717
01:54:34,850 --> 01:54:39,810
yeah, that lends itself to I think I have seen agent-based models that don't give a good

1718
01:54:39,810 --> 01:54:44,930
intuition at the end, even in the article of or have I I have seen articles where they

1719
01:54:44,930 --> 01:54:47,890
don't give a good intuition of why it resulted the work that they did.

1720
01:54:48,050 --> 01:54:53,250
And I do think that's rare in analytical models because I mean I think it could still

1721
01:54:53,250 --> 01:54:53,490
happen.

1722
01:54:53,890 --> 01:54:56,770
It happens, but it's much I agree, it's much rarer.

1723
01:54:56,900 --> 01:55:02,660
It it it um there's like a they because part of the process of publishing the analytical

1724
01:55:02,660 --> 01:55:08,100
model is like walking you through why the next thing right and and and also the analytical

1725
01:55:08,100 --> 01:55:14,100
model because the intern internal works of the um of

1726
01:55:14,100 --> 01:55:19,860
the simulation model aren't visible to you in the same way, uh it's much harder to

1727
01:55:19,860 --> 01:55:21,780
figure out what's happening.

1728
01:55:22,100 --> 01:55:27,730
And um and I think we need to do I mean

1729
01:55:29,010 --> 01:55:34,770
we we need to do a lot more exp of experimentation with with agent

1730
01:55:34,850 --> 01:55:40,050
based models you know go in and do experiments look at intermediate values uh

1731
01:55:41,490 --> 01:55:47,410
and I you know my bet is that over time referees and

1732
01:55:47,410 --> 01:55:50,850
the scientific process will force people to do that.

1733
01:55:51,010 --> 01:55:54,720
Uh Now I teach a version of that class, Rob T.

1734
01:55:54,960 --> 01:55:55,360
Oh, do you?

1735
01:55:56,960 --> 01:55:59,440
But I think that most of them don't want to be modelers.

1736
01:55:59,520 --> 01:56:05,520
And so mo a lot of the time is spent just like so their final project is reading a model

1737
01:56:05,680 --> 01:56:10,480
and making sure that they can understand why the results are the way that they are.

1738
01:56:10,960 --> 01:56:13,600
It could be a simulation, it could be a mathematical one.

1739
01:56:13,760 --> 01:56:18,030
Um, because that's what I think a lot of us well, a lot of the evolutionary social

1740
01:56:18,030 --> 01:56:21,070
scientists who are not going to be modelers themselves still need that practice to be able

1741
01:56:21,070 --> 01:56:25,550
to read that literature and understand why the results turn out that way, as opposed to

1742
01:56:25,550 --> 01:56:27,950
take it for granted that there's going to be this relationship.

1743
01:56:28,270 --> 01:56:34,030
I think that's actually led to a lot of confusion or taking at face value um kind of

1744
01:56:34,030 --> 01:56:34,590
conclusions.

1745
01:56:34,750 --> 01:56:35,150
Yeah.

1746
01:56:35,470 --> 01:56:39,790
Without thinking about the conditions under which or the assumptions that allow those

1747
01:56:39,790 --> 01:56:40,990
patterns to arise.

1748
01:56:41,310 --> 01:56:41,470
Yeah.

1749
01:56:41,710 --> 01:56:46,380
I think the I mean this is a problem with not just evolutionary social science but

1750
01:56:46,380 --> 01:56:52,380
evolutionary biology more generally is that it's not a norm

1751
01:56:53,020 --> 01:56:58,780
that practitioners understand the mathematical

1752
01:56:58,780 --> 01:56:59,420
theory.

1753
01:56:59,820 --> 01:57:05,820
Um and um it's not a norm that mathematical theorists are

1754
01:57:05,820 --> 01:57:09,420
well versed in the empirical facts.

1755
01:57:09,820 --> 01:57:15,170
And I mean, so if you interact with physicists or to a lesser extent with

1756
01:57:15,170 --> 01:57:16,290
economists.

1757
01:57:18,050 --> 01:57:22,610
Every empiricist knows the theory, at least at some level.

1758
01:57:22,690 --> 01:57:27,010
I mean, really knows it in a in a substantial way.

1759
01:57:27,570 --> 01:57:33,570
And um in economics, now economics has become very empirical.

1760
01:57:33,730 --> 01:57:36,370
I mean, much more than it used to be.

1761
01:57:37,330 --> 01:57:41,160
And you know, and it's deeply rooted in game theory.

1762
01:57:41,320 --> 01:57:47,320
Now, my my own personal opinion is most of it is kind of crazy that it it's not

1763
01:57:47,640 --> 01:57:53,000
very well coupled to anything about real humans, the game theory that, but anyway, be that

1764
01:57:53,000 --> 01:57:58,890
as it may, when you talk to economists and you they're talking about econom uh I

1765
01:57:58,890 --> 01:58:04,010
go three times a year to this group of listen, I'm part of this network, which has got, you

1766
01:58:04,010 --> 01:58:09,770
know, Samoglu and Robinson and Myerson and all these Nobel Prize winning economists and

1767
01:58:09,770 --> 01:58:15,370
various students and stuff, and they really understand exactly what

1768
01:58:15,690 --> 01:58:21,080
how the models work, what they say, and they're not doing modeling themselves at all, the

1769
01:58:21,080 --> 01:58:22,440
people that I'm listening to.

1770
01:58:22,520 --> 01:58:26,920
They're doing, you know, mainly these big regression kinds of studies.

1771
01:58:27,160 --> 01:58:30,520
And um, so that's their version of empiricism.

1772
01:58:30,760 --> 01:58:36,760
Um, and it is, and then if you listen to biologists, let's forget about

1773
01:58:36,760 --> 01:58:41,880
evolution or self-c, but they kind of pick and choose theory the way they want.

1774
01:58:42,040 --> 01:58:44,200
They don't really understand the models that well.

1775
01:58:44,490 --> 01:58:50,170
you know there this obviously varies from person to person but um um

1776
01:58:51,130 --> 01:58:56,970
I think you know it's because when you teach this course you

1777
01:58:56,970 --> 01:59:01,930
don't you can be a nobody's requiring this course whereas if if you're in physics or con

1778
01:59:02,170 --> 01:59:07,210
economics you take a year in graduate school where they teach you all the same stuff you

1779
01:59:07,210 --> 01:59:13,180
learned in undergraduate school all over again you know, theory of the firm, game theory,

1780
01:59:13,260 --> 01:59:14,300
all this stuff.

1781
01:59:14,860 --> 01:59:17,340
So they really got it deep.

1782
01:59:17,980 --> 01:59:22,940
And um, you know, I think what a biologist would say, that's all a waste of time.

1783
01:59:23,020 --> 01:59:26,620
We don't have enough theory to make that worthwhile.

1784
01:59:26,780 --> 01:59:31,660
And I think there's some truth to that because the system hasn't developed, so that the

1785
01:59:31,660 --> 01:59:36,300
theory and the empiricism is inextricably linked together.

1786
01:59:36,540 --> 01:59:42,230
And um you know it's better integrated in economics the

1787
01:59:42,470 --> 01:59:43,190
Oh yeah, much better.

1788
01:59:43,430 --> 01:59:48,470
But like so, but is it inherent to the body of theory that they've developed that it's no,

1789
01:59:48,550 --> 01:59:51,030
it comes it's it's just cultural evolutionary.

1790
01:59:51,590 --> 01:59:51,990
Yeah, right.

1791
01:59:52,230 --> 01:59:54,870
It's it has to do with the way the institution evolved.

1792
01:59:55,430 --> 02:00:00,260
Um the it was so theoretical when I took graduate economics in

1793
02:00:00,260 --> 02:00:02,580
1971, there was hardly any.

1794
02:00:02,820 --> 02:00:06,420
I mean, empiricism was kind of like biology, this casual empiricism.

1795
02:00:07,060 --> 02:00:12,660
And um then in the 90s uh and knots,

1796
02:00:13,220 --> 02:00:18,340
uh, economics did this big shift to um

1797
02:00:19,060 --> 02:00:24,820
so now hardly anybody gets a PhD um doing

1798
02:00:24,820 --> 02:00:25,380
theory.

1799
02:00:25,590 --> 02:00:29,910
The way you get a PhD is is, you know, it's like a biologist.

1800
02:00:29,990 --> 02:00:35,830
You find some system that allows you to to test something, but you do that having

1801
02:00:35,990 --> 02:00:41,910
you're absolutely deeply knowledgeable about game theory, but not game theory the way

1802
02:00:41,910 --> 02:00:46,550
we do it, game theory the way economists do it, which I think is, well, you don't care what

1803
02:00:46,550 --> 02:00:52,220
I think about it, but it it's kind of yeah it's you know

1804
02:00:52,540 --> 02:00:53,420
wacky basic.

1805
02:00:53,660 --> 02:00:55,660
I shouldn't say that on a podcast.

1806
02:00:55,980 --> 02:00:56,940
It's a technical term.

1807
02:00:57,020 --> 02:00:57,660
Yeah.

1808
02:00:58,540 --> 02:01:03,260
You know, I mean their equilibrium concepts are not evolutionary.

1809
02:01:03,340 --> 02:01:08,540
They're about you think that I think that you think that I think uh and um

1810
02:01:09,490 --> 02:01:12,690
uh and they're deeply committed to those.

1811
02:01:12,850 --> 02:01:18,610
And if you uh you know, I go to these meetings and I voice mild skepticism in people

1812
02:01:19,010 --> 02:01:22,370
and they're very very ethnocentric about economics.

1813
02:01:22,450 --> 02:01:26,850
They don't think the rest of the social sciences is worth listening to, except history,

1814
02:01:26,930 --> 02:01:28,370
maybe hardly at all.

1815
02:01:28,610 --> 02:01:33,980
And um, but you know I I figure I'm doing missionary work on yeah and uh

1816
02:01:34,380 --> 02:01:35,900
fighting the good fight, yeah.

1817
02:01:36,940 --> 02:01:40,380
You know, missionaries end up in the stewpot sometimes.

1818
02:01:42,540 --> 02:01:47,100
Uh yeah, but I think I think the connection, I mean theory, I think theory to sort because

1819
02:01:47,100 --> 02:01:52,220
we're wrapping up here, theory and empirics, I think, is a theme of sort of Rob, your

1820
02:01:52,220 --> 02:01:57,470
contribution, and I think all the evolutionary sciences is that we've sort of, you know,

1821
02:01:57,710 --> 02:02:00,670
for a while there was a lot of theory, not a lot of empirical work.

1822
02:02:00,830 --> 02:02:04,750
Maybe we've swung to there's lots of empirical work, but not enough theory.

1823
02:02:04,990 --> 02:02:10,830
But I think, I don't know, I mean, I think uh um I'm I'm at least heartened that

1824
02:02:10,830 --> 02:02:16,830
we're we compared to a lot of human psychology, for example, and and uh I'm

1825
02:02:16,990 --> 02:02:18,990
I'm speaking as a psychologist, yeah, yeah.

1826
02:02:19,230 --> 02:02:24,580
Um, you know, there's a lot more theory we have at our disposal as a fish and and a lot of

1827
02:02:24,580 --> 02:02:25,620
psychologists per se.

1828
02:02:25,860 --> 02:02:31,620
Yeah, I think I mean Joe and Michael have written this paper about that and yeah and uh

1829
02:02:31,780 --> 02:02:37,540
when I interact with the social psychologists here, Doug Kenrick and and uh

1830
02:02:37,780 --> 02:02:40,020
um oh gosh.

1831
02:02:40,180 --> 02:02:43,220
Anyway, um and Steve Newberg.

1832
02:02:43,300 --> 02:02:46,660
Uh yeah, really smart, accomplished people.

1833
02:02:46,820 --> 02:02:46,980
Yeah.

1834
02:02:47,140 --> 02:02:49,930
But they they would do better if they had more theory.

1835
02:02:50,010 --> 02:02:50,650
Yeah, I think.

1836
02:02:51,050 --> 02:02:51,290
Yeah.

1837
02:02:51,370 --> 02:02:51,530
Yeah.

1838
02:02:51,770 --> 02:02:52,410
Different histories.

1839
02:02:52,490 --> 02:02:52,650
Yeah.

1840
02:02:52,730 --> 02:02:55,530
Different so as you said, different, different different institutions.

1841
02:02:55,850 --> 02:02:58,170
Different institutional selection, different histories.

1842
02:02:58,410 --> 02:02:58,890
Absolutely.

1843
02:02:58,970 --> 02:02:59,450
Yeah.

1844
02:02:59,690 --> 02:03:03,690
Um uh Christina, do you have any uh final questions?

1845
02:03:03,930 --> 02:03:07,690
Uh oh, that's a really tough spot to put.

1846
02:03:08,170 --> 02:03:08,730
Yeah.

1847
02:03:09,050 --> 02:03:11,850
I mean we can always ask Rob if we should have asked him anything.

1848
02:03:11,930 --> 02:03:12,970
That also is a tough before.

1849
02:03:13,930 --> 02:03:19,620
I wanted to ask if there's anything that you've changed your mind about like over the last

1850
02:03:19,620 --> 02:03:20,900
several decades.

1851
02:03:21,620 --> 02:03:24,340
Um maybe based on the empirics or maybe better theories.

1852
02:03:24,660 --> 02:03:29,460
Yeah, uh I used to be more gung-ho about cultural group selection than I am now.

1853
02:03:29,700 --> 02:03:35,220
Um I'm more aware of the empirical um

1854
02:03:36,230 --> 02:03:41,030
I mean a lot of the criticism of cultural group selection has kind of been in principle

1855
02:03:41,190 --> 02:03:44,710
group selection can't work and that's wrong, right, for sure.

1856
02:03:45,030 --> 02:03:50,950
But the problem is there are well, first of all, I worry a

1857
02:03:50,950 --> 02:03:51,110
lot.

1858
02:03:51,270 --> 02:03:57,190
I have been worried ever since 1985 about how fast it is and can

1859
02:03:57,190 --> 02:03:58,550
it explain enough?

1860
02:03:58,710 --> 02:04:02,630
Uh you know, it's a lot of norms we've got evolved, and is there enough cultural group

1861
02:04:02,630 --> 02:04:03,030
selection?

1862
02:04:03,190 --> 02:04:06,640
And um, And I worry about that actually.

1863
02:04:06,880 --> 02:04:12,080
And I have come to think that within group processes

1864
02:04:13,200 --> 02:04:18,960
have got to be more important, both based on that and based on lots of empirical

1865
02:04:18,960 --> 02:04:22,960
examples, which just there's no there's no group selection involved, and yet there's lots

1866
02:04:22,960 --> 02:04:23,920
of change.

1867
02:04:27,330 --> 02:04:31,650
I am bothered by the fact that I can't think of a good theory.

1868
02:04:31,890 --> 02:04:37,650
I I think the bargaining theories don't make sense because, or at least they can't

1869
02:04:37,650 --> 02:04:43,490
explain the variation we see, because um the scale on which

1870
02:04:44,370 --> 02:04:50,130
I mean small scale people can bargain on the scale of a few thousand people, maybe,

1871
02:04:50,340 --> 02:04:56,100
and we see norms on the scale of continents and and so there has to be something else that

1872
02:04:56,100 --> 02:04:58,980
causes successful norms to spread from one group to another.

1873
02:04:59,140 --> 02:05:01,220
It can't all be within group bargaining.

1874
02:05:01,300 --> 02:05:03,220
And I've got some ideas about that.

1875
02:05:03,300 --> 02:05:06,020
But and Sarah has got some ideas about that.

1876
02:05:06,180 --> 02:05:10,820
And I'm less convinced about conformism than I used to be

1877
02:05:13,210 --> 02:05:14,970
as a learning strategy.

1878
02:05:15,210 --> 02:05:19,850
Um is that because there are better ones out like basically we're gonna be able to do that.

1879
02:05:20,010 --> 02:05:25,930
No, just because uh because the the the the data are ambiguous is what I

1880
02:05:25,930 --> 02:05:27,210
would say mixed.

1881
02:05:27,450 --> 02:05:33,210
Um uh the data for other animals surprisingly stronger are much stronger

1882
02:05:33,290 --> 02:05:38,170
yeah so these wonderful experiments that Lucy Applin has done uh on

1883
02:05:38,730 --> 02:05:43,360
bird learning, or you know, they're they they are conformists for sure.

1884
02:05:43,600 --> 02:05:49,120
Um and interestingly, so the the the so a kind of

1885
02:05:49,120 --> 02:05:54,320
psychology you might think, well, the number of instances is what people would respond to.

1886
02:05:54,480 --> 02:05:58,800
But the theory tells you it's the number of individuals, not the number of instances,

1887
02:05:58,960 --> 02:06:04,230
because that's well because that's what generates adaptive information and sure enough

1888
02:06:04,310 --> 02:06:09,510
those birds don't care about instances they care about the number of individuals and can I

1889
02:06:09,510 --> 02:06:13,590
can I put a pause and just say something that is like common knowledge according to like

1890
02:06:13,590 --> 02:06:17,910
the rest of the social sciences if you repeat something more people will believe it.

1891
02:06:18,070 --> 02:06:23,350
Yeah and that is that doesn't make sense to me like why but what are the what is the

1892
02:06:23,510 --> 02:06:27,880
radical side but is the empirical side true As far as I'm aware, at least in humans, the

1893
02:06:27,880 --> 02:06:29,640
empirical side hasn't been holding up on that.

1894
02:06:30,200 --> 02:06:31,560
This is what they call it.

1895
02:06:32,120 --> 02:06:32,360
Yeah.

1896
02:06:32,600 --> 02:06:32,920
Yeah.

1897
02:06:33,080 --> 02:06:38,600
And uh I think they need a theory to tell them what

1898
02:06:39,080 --> 02:06:41,880
you know what kinds of repeats are important.

1899
02:06:42,840 --> 02:06:46,600
And repeats across individuals are important.

1900
02:06:47,000 --> 02:06:51,800
Repeats within individuals will matter in an environment which is changing on time scales

1901
02:06:52,040 --> 02:06:53,240
that are fast enough.

1902
02:06:53,480 --> 02:06:57,010
But anyway, um, so what else have I changed my mind about?

1903
02:06:57,170 --> 02:07:02,930
Um and just to be clear, the the um slight increased skepticism about

1904
02:07:02,930 --> 02:07:07,090
cultural group selection is just that it doesn't account for as many norm changes as you

1905
02:07:07,090 --> 02:07:11,570
might have thought that they did because that um change is happening too quickly, culture

1906
02:07:11,730 --> 02:07:12,530
change is happening too quickly.

1907
02:07:13,090 --> 02:07:13,970
Too quickly.

1908
02:07:14,210 --> 02:07:19,560
And you know, so the shift in norms about tobacco smoking in the US.

1909
02:07:19,800 --> 02:07:19,960
Right.

1910
02:07:20,120 --> 02:07:21,080
No group selection there.

1911
02:07:21,160 --> 02:07:22,280
There, you know, it's, you know.

1912
02:07:22,680 --> 02:07:25,320
They're running migrants to like the no smoking zone.

1913
02:07:25,640 --> 02:07:25,800
Right.

1914
02:07:25,880 --> 02:07:26,120
Right.

1915
02:07:26,280 --> 02:07:28,760
It's it's it's it it's not that.

1916
02:07:29,160 --> 02:07:35,160
Um and um uh now, well, I don't want to go in

1917
02:07:35,160 --> 02:07:40,040
all the details, but this is an area which I thought when I first started, I thought I had

1918
02:07:40,040 --> 02:07:41,000
the answer.

1919
02:07:41,320 --> 02:07:43,640
Now I think it's part of the answer.

1920
02:07:43,800 --> 02:07:45,400
Uh how big a part?

1921
02:07:45,670 --> 02:07:46,390
I don't know.

1922
02:07:46,630 --> 02:07:50,950
Um uh uh Joe gets really mad when I say that.

1923
02:07:51,190 --> 02:07:55,430
But um uh at least I think he does.

1924
02:07:55,590 --> 02:07:57,270
Um I mean it could be faster.

1925
02:07:58,150 --> 02:07:59,030
You don't want to hear all this.

1926
02:07:59,350 --> 02:08:02,710
It might have mattered more historically than it does now, like when there was so much lots

1927
02:08:02,710 --> 02:08:04,230
of sort of variation.

1928
02:08:04,470 --> 02:08:04,710
Yeah.

1929
02:08:04,870 --> 02:08:08,310
Well, I think the main form is gonna be differential spread.

1930
02:08:08,550 --> 02:08:08,790
Yeah.

1931
02:08:09,040 --> 02:08:14,880
So I groups imitating successful other groups, individuals in imitating people and

1932
02:08:15,040 --> 02:08:16,400
successful neighbors.

1933
02:08:17,040 --> 02:08:19,600
But I still don't think that explains a lot of stuff.

1934
02:08:19,760 --> 02:08:24,320
And um I don't know.

1935
02:08:24,400 --> 02:08:26,160
I can't think of anything else off the top of my head.

1936
02:08:26,240 --> 02:08:27,840
I've been right about so many things.

1937
02:08:31,120 --> 02:08:34,160
You can't show that you're a good scientist if you're just right all the way.

1938
02:08:34,560 --> 02:08:36,480
I have to I have to think of something.

1939
02:08:37,910 --> 02:08:41,590
But I do think I mean Rob, just to say like as we're closing up too, like I do appreciate

1940
02:08:41,590 --> 02:08:45,670
that, you know, as a student of John Alitas, like you've been very gracious over the years.

1941
02:08:45,830 --> 02:08:51,750
And and I think talking about the evolved psychology explicitly, and I do think that you

1942
02:08:51,750 --> 02:08:57,590
are part of the reason why for people like Christina and David,

1943
02:08:57,830 --> 02:09:03,510
that the the the gap between sort of cultural evolution and evpsych, uh at least in

1944
02:09:03,510 --> 02:09:08,940
principle, and maybe a lot of times in practice is very narrow and and and and nowadays

1945
02:09:09,020 --> 02:09:11,980
this I don't even think most people I don't even I don't know.

1946
02:09:12,140 --> 02:09:17,820
I mean I'm in my experience it's it's more in Christina language sort of people's uh

1947
02:09:17,980 --> 02:09:23,660
um emphasis in terms of their methods, less thus than their sort of deep

1948
02:09:23,660 --> 02:09:28,550
commitments um you know where I think somebody who's an evolutionary psychologist like yeah

1949
02:09:28,630 --> 02:09:31,590
there's cultural evolution and somebody who's cultural evolutionist like oh yeah there's

1950
02:09:31,590 --> 02:09:36,470
evolved psychology I may not use it in my model but you know that yeah yeah I unfortunately

1951
02:09:36,470 --> 02:09:41,110
have another thing that I need to get to yeah so um but yeah it was this was great thank

1952
02:09:41,110 --> 02:09:46,550
you Rob thank you for my pleasure yeah this was a lot of fun yeah thank you

1953
02:09:48,070 --> 02:09:52,220
you never know what to say for the outro Thanks for listening.

1954
02:09:52,460 --> 02:09:53,420
Yeah, this was great.

1955
02:09:53,580 --> 02:09:55,180
Uh everybody have a good week.

1956
02:09:55,260 --> 02:09:57,900
You know, do the usual Patreon um show.

1957
02:09:58,380 --> 02:10:00,940
Patreon, social media, kind review, you know the drill.

1958
02:10:01,100 --> 02:10:01,340
Yep.

1959
02:10:01,420 --> 02:10:02,780
We should get t shirts, David.

1960
02:10:03,100 --> 02:10:04,380
T shirts, fanny packs.

1961
02:10:04,860 --> 02:10:06,220
Can I say our logo?

1962
02:10:06,380 --> 02:10:07,580
I don't love our logo.

1963
02:10:07,740 --> 02:10:12,060
In terms of like I I like our logo for the purposes of a podcast, but I don't know if I

1964
02:10:12,060 --> 02:10:14,220
would want the brain on a shirt for me.

1965
02:10:14,300 --> 02:10:15,340
What do you think?

1966
02:10:15,630 --> 02:10:16,190
Hmm.

1967
02:10:16,910 --> 02:10:18,350
Yeah, I don't know.

1968
02:10:18,430 --> 02:10:23,390
I don't really have any aesthetic taste or fashion sensibility.

1969
02:10:23,870 --> 02:10:25,710
Here's my vision of a t-shirt.

1970
02:10:25,870 --> 02:10:30,510
A black t-shirt that says nothing except the podcast in parentheses.

1971
02:10:30,910 --> 02:10:33,070
Oh, that like kind of a minimalist direction.

1972
02:10:33,470 --> 02:10:34,670
It's like you gotta be on the end.

1973
02:10:34,910 --> 02:10:36,270
It's sort of like you know, bank.

1974
02:10:36,670 --> 02:10:39,790
Ah, sort of small small dino in covert signal.

1975
02:10:40,030 --> 02:10:40,590
Exactly.

1976
02:10:40,830 --> 02:10:41,470
Oh, okay.

1977
02:10:41,550 --> 02:10:42,110
I like that.

1978
02:10:42,350 --> 02:10:42,670
Yeah.

1979
02:10:42,830 --> 02:10:43,230
All right.

1980
02:10:43,390 --> 02:10:44,830
Well, maybe that's what we'll do.

1981
02:10:45,160 --> 02:10:45,560
All right.

1982
02:10:45,640 --> 02:10:45,960
Yeah.

1983
02:10:46,120 --> 02:10:46,440
Cool.

1984
02:10:46,600 --> 02:10:49,960
Well, we can't do it w unless you um support us.

1985
02:10:50,040 --> 02:10:50,280
Yeah.

1986
02:10:50,440 --> 02:10:53,880
And, you know, maybe give us some some money on Patreon for the t shirts.

1987
02:10:54,120 --> 02:11:00,040
If you if you run a a t shirt concern and have the ability to silk screen

1988
02:11:00,200 --> 02:11:03,560
um, you know, however many of those, let us know.

1989
02:11:03,960 --> 02:11:04,600
Yeah.

1990
02:11:04,910 --> 02:11:05,470
Totally.

1991
02:11:05,710 --> 02:11:05,790
Okay.

1992
02:11:06,110 --> 02:11:06,430
All right.

1993
02:11:06,750 --> 02:11:07,390
See you next week.

1994
02:11:07,950 --> 02:11:08,110
Bye.

1995
02:11:08,190 --> 02:11:09,630
Have a good week, everybody.