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Okay.

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Uh I I am me and you are you.

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Yes, and that would work, except there's this thing David called uh common knowledge.

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You might I'll I'll tell you all about it later.

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Okay, so you might not know who me is.

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Exactly.

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There uh you are uh y yeah.

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Yes, you are not me is not sufficient.

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I'm the other David P David Pinsoff.

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I'm with uh my friend and co-host Dave Petrozowski.

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That is me, which in this case context is sufficient because it gets

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complicated.

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It takes a while to wrap your head around it.

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But anyway, we're here.

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Boy, this is really uh interesting conversation.

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People are gonna be turning podcast if they can't

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explain this, how are they going to explain like how the mind works, right?

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Which is actually a question I ask myself every day.

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So yeah.

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And we're doing the evolutionary psychology podcast.

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Even that I screwed up.

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Evolutionary psychology, the podcast.

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It was a good throwback to the first one.

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Yes.

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Um and uh we're doing a fantastic job introducing this episode.

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Hey Dave.

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Hey David.

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So we've done a few interviews now.

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Uh and this is the episode where we get back to just you and me, the Dave's putting

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their heads together.

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And I think this was a really fun, wide-ranging conversation.

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Yeah.

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This is uh instead of sort of being on our looking backwards, this is sort of looking

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forwards or positively saying, Well, what is evolutionary psychology and what are some

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examples of really great work that explain what it is and give meat

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to the idea that it makes predictions and gives people insights.

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And so I think if especially for those people listening who want some concrete examples

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of insight that can be provided from this perspective.

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And yes, and not just insight, but important, socially relevant insight.

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So we spend a good chunk of the episode talking about race and uh racial categorization,

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racial prejudice, and what evolutionary psychology can tell us about this uh important

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topic.

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Uh and we really get into the nuts and bolts of it in a in a fascinating and and

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mind-blowing way.

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Um from there we go go into anger, we go into happiness.

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We cover a lot of stuff in this episode.

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It was it was really fun.

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Yeah, absolutely.

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Yeah.

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And um and it was sort of fun because the some of the work is some of some of my empirical

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work that I do sort of in my day job.

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Um so um yeah so I'm the horse's mouth in that situation.

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Yeah.

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So without further ado, enjoy how to be a good evolutionary psychologist.

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David, good to see you today.

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Good to see you too.

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Excited to get into the nitty-gritty of how to actually be a good evolutionary

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psychologist.

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Yeah, that's right.

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We've had a couple guests on, but we haven't really talked about sort of what evps

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is positively per se.

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And I think it would be really helpful, especially for people who are listening who aren't

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part of the regular community of people, to just get a better idea of sort of what it is.

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Yes, I agree.

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There's plenty of discourse surrounding whether evolutionary psychology is good

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or bad, or whether we should take an evolutionary approach or what kind of evolutionary

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approach we should take.

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But there's very little discourse surrounding the very large difference between good

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evolutionary psychology and bad evolutionary psychology.

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And I think any person in the field would agree that there is plenty of bad stuff in there

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and plenty of good stuff in there.

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And I think the wider public has no way of telling the difference between those two things.

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Would you agree?

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I would agree, yeah.

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And I think also, I mean, this is the problem with the format of scientific dissemination

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is a lot of stuff is behind paywalls or it's in sort of boring journals.

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I think one of the things that is really cool that I hope people will start to get a sense

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of is what a treat it is to talk to people who are actually doing the science because

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they're really cool people.

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They have lots of cool experiences and they're studying really cool stuff.

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And I think one thing I tell people, like my students in classes, is that textbooks are

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usually anywhere from 10 to 20 years behind.

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Journal articles are, you know, three or four years behind.

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Because if you think about it, you know, you have an idea, you test the idea, you run the

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study, or you write the paper.

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It takes a while to then get accepted.

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Talking to people, you really catch up.

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And so, you know, if you're reading a popular book or a textbook, you're 20 years or 15

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years behind.

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If you're reading journal articles, you're three or four or five years behind.

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But if you're talking to people, you really get the update, up-to-date stuff.

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And that's a real treat to have.

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And so that's the other thing is so much of the empirical work and theoretical work is so

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new.

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Like David, your we'll talk about your humor work in some episode.

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I just saw that a couple months ago.

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I was completely blown away.

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Um, um, John Tuby, my uh recently um he passed away recently,

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but he was one of the founders of Ev Psyche, and he would famously sort of say you

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shouldn't study humor as your first project because it was such a trippy, tricky thing to

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do.

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Um, and I think uh humor's always been one of these sort of um things that are difficult in

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he thought it was it was tricky in the sense of mysterious or or um people won't take you

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seriously as an academic if you're no no no no no the first one he he said sort of you know

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you should start a project with clear selection pressures and an obvious design.

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So sort of sort of something like, you know, uh not starving to death, you know,

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reproducing clear survival, reproductive uh benefits, clear

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selection pressures, humor, things like that.

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He he put humor in this category of it's there's such a number of

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layers between clear design and the phenomenon that it would be very tricky,

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especially for an early career student, to do.

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And I think seeing your talk, you lifting the veil of actually, there's only a

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few straightforward designs involved.

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Uh, it was just to your credit.

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Uh I'm sorry, I sort of feel like I'm doing a teaser here.

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Uh so we should uh but anyway, yeah, no, it was uh really good and cool

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insight.

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But I think the point is that's an example of cool new work that

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it's exciting to talk about or share in this venue as well.

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Yeah, it's not very widely understood just how young the field of evolutionary psychology

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is.

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So it started in the 90s.

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Uh um, I mean, sociobiology was sort of the early beginnings of it.

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E.O.

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Wilson was beginning to bring ideas from evolutionary biology to study the social

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behavior of animals.

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And in his classic book, Sociobiology, he had a final chapter on humans, where he started

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to apply some of these ideas from evolutionary biology and the Neo-Darwinian synthesis to

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humans.

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And of course, it was extremely con controversial when he did that.

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But uh I think it took a couple decades to find the right way to apply

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evolution to human behavior.

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I mean, you know, Eo Wilson got some things right, But I think the the framework of

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sociobiology was not psychological enough.

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Um, and that is where Tubian Cosmodes came in in the nineties with evolutionary psychology,

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um, where the adaptation um in question was not behavior,

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but psychological mechanisms, cognitive systems.

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There are many ways to describe them, but the stuff in our head that takes in information

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and guides behavior, that is the appropriate target of scientific inquiry.

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That is where we should be looking for adaptations and for um functional

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organization.

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We should not be looking at the level of behavior per se.

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We should be looking at behavior regulation systems inside the nervous system.

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That's right.

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Yeah, the the level, the invariance is is the design.

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And a good example of that would be something like plants growing towards light.

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If you tried to have a science of describing where all the plants are growing, it would be

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complicated.

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Plants are everywhere, There's they're growing in all kinds of directions.

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The level of invariance is there's something phototropism, the auxins reduce the plant

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growth.

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And so that you can economically describe all plant behavior.

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I mean, there's other designs too, but in terms of photophotropism,

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the invariance is the underlying rule of you know, bend towards light

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and as you're growing.

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it's a beautiful analogy because if you were to try to study plant growth as the

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target of scientific inquiry, you'd be very confused.

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You'd have, you know, plants moving in uh this direction and that direction, uh to, you

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know, in this diagonal, that diagonal, and you would have no way of understanding why they

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were growing in which direction.

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And you could collect all this data about all the different trajectories of different

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plants, and you'd be incredibly confused as to what was going on.

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Uh And it is only when you realize the adaptive function of phototropism that you can

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organize all that data in an elegant and parsimonious way.

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And you can look at the at the at the level of the growth regulation system within the

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plant that was designed by natural selection to find sunlight.

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And I think a similar paradigm shift is needed for human psychology.

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We shouldn't be looking at the uh superficial level of behaviors.

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We should be looking deeper at what are the underlying systems that were selected for to

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generate the behavior.

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That's right.

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And it's also this is a point that Paul Smaldino makes.

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And before that, Noam Chomsky, which is that in just as a general point in science, and

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Noam Chomsky has a nice example of this uh, where you could set up a video camera and

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record a bunch of leaves falling outside of your window.

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Um, you could record that uh get a statistical analysis of how do those leaves

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behave.

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And one could probably get a better prediction of how those leaves will behave than even a

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physicist could do, right?

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Um, but the problem is that that sort of statistical description of those

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leaves is brittle and doesn't apply to new contexts.

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And this is Paul Smaldino's point, where if you have a mathematical description of behavior

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in a certain context, if a new context in a new context the behavior won't be

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the same, then you actually lose the predictive power of the model.

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So for example, those particular leaves falling in that particular place, you might have a

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good model of that, but you're not going to be able to model something else falling, right?

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Because it's just different.

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And there's nothing in the theory about coefficient, drag coefficients, or things like

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that.

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And so one of the reasons scientifically to have an underlying model that is

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causal is that it allows you to make inferences to

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new situations.

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And otherwise, you're sort of stuck with descriptions of a particular set of behaviors,

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but you lose the predictive power of a scientific theory.

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That's one of the main differences between just a description.

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And we talked with Dan Conroy Beam in a previous episode about there are a lot of

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theories in psychology that are descriptions of what happens either in a study or just

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general behavioral phenomenon.

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But if you don't unpack the underlying causal invariances like

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phototropism, then you're just stuck with statistical descriptions of those plants growing

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in those places, but you might not capture the right data in terms of like which direction

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does the light coming from.

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Same thing, the plants or the leaves falling and the video camera, if you uh

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extrapolate to a new context, that model might be useless.

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So it's very brittle.

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Um and so the point is a theoretical approach where

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the level of invariance is not behavior, but the underlying psychological design.

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I think this is sort of where we are as a field in psychology generally.

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And I think F-Psych was on the forefront in Lita and John's work in particular, really on

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the forefront of pushing that idea that the level of invariance is in the mind and the

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software and the mind, not at the level of behavior.

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Yes, absolutely.

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Um, and certainly psychology is stuck in this rut where there is a

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proliferation of endless biases and effects that pile up.

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I think Wikipedia has a list of biases that's like hundreds long.

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This is the sign of a field that is stuck in a cul-de-sac, I think.

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Um if you're just collecting biases and effects without a deeper theoretical framework to

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organize them, um, you're just you're butterfly collecting.

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Um, you're looking at the wrong thing.

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Um so I think that is one of the great benefits of evolutionary psychology

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is it causes you to look deeper into the underlying structure of the mind,

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into what we might call human nature, for lack of a better term, the reliably developing

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species typical uh developmental and psychological architecture um

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that uh has been produced by natural selection.

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That is the the place to look for adaptation, for function.

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Um and uh a science that doesn't look at that as

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the source of invariance, as you put it, is inevitably going to get lost

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um in descriptive cul de sacs and overfitting to data

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rather than finding the the underlying patterns.

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Yeah, I I I think that's right.

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I think you're what you're saying is that the

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evolutionary psychology is a kind of correction, and there are other ways to get there.

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Like I think there are areas of like AI or computer science or anywhere where people have

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there's sort of tasks that need to be solved that get at uh aside from just the

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behavior, what is the underlying design that I think is is sort of a crucial thing.

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And we're we're still not quite there.

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One one thing maybe to shift to to make this concrete for listeners, especially.

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Uh let me pose a question to you and you can you can uh take this question if you want.

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So one of the common misunderstandings of evolutionary psychology is that it's just so

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story.

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And I'm curious uh if in in well, yeah, what do you

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how do you typically explain why it isn't that?

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Or do you have an example of a study that you're aware of, or an example research project,

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either your own or someone else's, that's a clear example of why it isn't a just so story?

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I mean, uh, I've been I've seen this this idea over and over again.

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It's one of those zombie ideas that just won't die, no matter how much you correct it.

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Um so just so stories.

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The idea is that you take any human behavior and you spin a uh uh an

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evolutionary story about us as cavemen or whatever, um, and and you um

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make up some reason why it might have helped our ancestors survive and reproduce, and then

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your work is done.

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Uh and that's that's the criticism: is that evolutionary psychology does this.

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And I think it can be a fair criticism of some bad

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evolutionary psychology.

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So that's that's um a place uh where bad evolutionary psychology can go.

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If you don't uh have the right way of thinking and and and the right way of doing task

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analysis, you can sometimes get lost in this uh just so story trap.

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So I think it's it's it's a valid concern and something to look out for.

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Um but just as an empirical matter, um the idea that

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evolutionary psychology does not make testable predictions um is false.

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Um what I find ironic about the just so story idea um is that it itself is

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often unfalsifiable.

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Like a lot of people will just lazily say that some idea I present is unfalsifiable,

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and then I'll say, Well, actually, no, here's how you could falsify it.

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And I'll I list uh a number of empirical tests that you could falsify.

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And then I I often engage you know in petty debates with people on the internet when I

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blog, and and you know, when every now and then when someone says this is unfalsifiable,

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I'll say, No, here's how you can falsify it.

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And then what's funny is uh what I sometimes get is well, no, I don't believe you.

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Which which suggests to me that the idea that the hypothesis is unfalsifiable is itself

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unfalsifiable.

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Nothing could actually falsify it.

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No matter what I say, you know, the person will continue to believe that it's

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unfalsifiable.

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Um so uh I mean the best way to just dismiss this idea is just to

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like point to, say, the Journal of Evolution and Human Behavior, point to the latest uh,

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you know, two volume handbook of evolutionary psychology, uh, which I believe is uh over

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fifty chapters uh covering just an an enormous wealth of empirical research um that has

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been generated by evolutionary psychologists.

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Um so clearly they're not just sitting around telling stories.

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Clearly these people are doing research, they're testing hypotheses, they're doing

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statistical analyses, they're doing something.

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Yeah.

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Right.

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Um so that's one thing I might do is just point them to that stuff.

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I don't know.

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I mean, there are plenty of cases where evolutionary psychology hypotheses have been

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falsified.

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Perhaps the easiest one to wrap your head around is this hypothesis about homosexuality.

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So homosexuality is kind of mysterious from an evolutionary perspective, and that you would

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expect uh heterosexual uh mating to be selected for and homosexual mating to be

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heavily uh selected against, given that you're not uh reproducing and spreading your genes.

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So, one hypothesis for why genes for homosexuality might persist, despite their uh

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selective downsides, is that maybe it's a way, it's like a different fitness

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maximizing strategy.

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Maybe gay people are investing more in their kin, in their nieces and nephews.

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And because fitness isn't just about your direct reproduction, but about the reproduction

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of anyone who shares genes with you, maybe on net homosexuals are still doing okay

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evolutionarily evolutionarily if they're investing uh a lot in their nieces and nephews.

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Um the coin it's like helpers in the nest, I think.

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Helpers in the nest.

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No, as as a matter of fact, I don't think this is a very plausible hypothesis.

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Um but at the very least, it is falsifiable.

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It is very easy to test.

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It makes a very clear, bold prediction.

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And that prediction is that gay people should be absolutely effusive toward their

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nieces and nephews.

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They should just uh absolutely adore them and invest tons of time and energy into taking

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care of their nieces and nephews, enough to offset themselves not having kids of their own.

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And you can go out and you can run the tests.

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You can uh ask gay people how much time they spend with their nieces and nephews, you can

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compare it, you know, it to uh straight people, and uh the data has come in

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and the answer is no.

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Gay people are not particularly uh effusive toward their nieces and nephews relative to

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straight people.

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So that hypothesis has been uh falsified.

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Uh, that is uh no longer a viable hypothesis about the evolution of

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homosexuality.

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So that's one clear example of a hypothesis that was falsified.

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Right.

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And and I think there's also, I think this comes back to

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why people misunderstand evolutionary psychology and not only why, but how they

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misunderstand it, comes back to what we talked about, which is this idea of it's not about

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behavior but design.

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And where evolutionary psychology typically makes predictions is at the level of design.

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So what you just described was if this idea is right about that um if

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homosexuality, there should be design in this sort of type to

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be really strong and allo-parenting.

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And you don't see that.

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And other examples of design, a good example of this that

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is falsifiable but but turns out to be true.

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I, you know, I know this is just my own work, which is that one idea about like where it

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is, why do people categorize people by race?

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People had shown that people always categorize people by age, sex, and race.

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This was looked at um using a parallel.

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So let's we should probably unpack what it means to categorize someone by something,

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because a lot of people might not know what that what that means.

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Yeah, yeah, yeah.

339
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Great.

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So categorization is uh a process whereby when you're meeting somebody

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or you're judging somebody or evaluating somebody, you're not just treating their

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individual characteristics.

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Oh, this person is nicer or you know uh has this particular um

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attribute.

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They're also an instance of a broader category, which is a set of people.

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So they might be uh all this might be a woman, this might be

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somebody who is uh of a particular tribe or a race, like they might be

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black or white, whatever the local sort of cultural categories are,

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an old person, a young person.

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And this has been an important part of studying social cognition

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since the 20th century, especially in social psychology, because many bases of

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discrimination and unfair treatment are treating people not because of their individual

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attributes, but because of the category membership that they embody or people perceive them

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as embodying.

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So, for example, if you apply to my to to be

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a renter in my apartment, if somebody is using a social category as a

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basis to not allow them in, that's discrimination, right?

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And it's not that there's any problem with them as an individual, it's that because they're

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an instance of this category.

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So category based discrimination is a really important social

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phenomenon to understand.

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And categorizing people, that is, when a new person is encountered, the

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cognitive process whereby their Their cues that

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they embody in their face or the how they look or talk or whatever, because they can be

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verbal, they can like you know how they talk can be a category.

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Um, these all activate the representation of the category.

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And understanding that process is really important because it's the categorization process

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that's the first step prior to any discrimination.

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If people didn't never categorize people in the first place, there would be no racial

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discrimination, sexual discrimination, et cetera, because there wouldn't be categorization

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by this feature in the first place.

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So there was a long history of trying to understand not only the

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discrimination or the attitudes people held towards these categories, but starting around

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the 1960s and 70s in social areas of social cognition, people wanted

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to start to understand: well, what are the cognitive processes that cause people to

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categorize by social categories?

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In the first place, what are the social categories people use?

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And there were new methods to sort of study that.

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And one of the things I do in my day job as an empirical psychologist is study some of

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those cognitive processes.

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And one of the tools people use is something called the Who Said What paradigm, where

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people are shown photos of people along with a sentence.

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So it could be something like you're told, oh, you're going to see a bunch of people,

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they're just all having a conversation, and then you see a picture of like a person and

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there's text underneath, they say something, and then there's another person, and they say

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something else, like, hey, nice to meet you.

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Like, you know, what are you doing today?

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And then somebody says something else, and they just this sort of a conversation.

389
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Um, and usually participants or or people in a study would sort of see this on a computer.

390
00:25:22,450 --> 00:25:23,570
It's been done in real life.

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You get the same kind of result.

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And then at the end, there's a surprise recall task.

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So usually there's a long conversation.

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Usually it's between like eight people.

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You see about 24 statements, whatever.

396
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But at the end, there's a surprise recall task where all of a sudden you see all the faces

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or all the people that you had seen earlier, and then you're asked to try to remember who

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said which sentence.

399
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And it's a surprise task.

400
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And it feels really, really hard.

401
00:25:52,920 --> 00:25:58,920
Like shockingly, memory for what people have said or who have said what is quite

402
00:25:58,920 --> 00:25:59,240
bad.

403
00:25:59,400 --> 00:26:04,760
I actually make these stimuli, and I still, to this day, even the stimuli that I make, I'm

404
00:26:04,760 --> 00:26:05,560
like terrible at it.

405
00:26:05,640 --> 00:26:07,560
And I like it feels like random guessing.

406
00:26:07,720 --> 00:26:13,240
But the cool thing is that even though it feels like random guessing to the participants,

407
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their choices are not random typically.

408
00:26:17,950 --> 00:26:23,390
And what happens is that, so for example, if you present people in the conversation that

409
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differ in their sex, so half of them are male, half of them are female.

410
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When people are given that sentence and they look at it and they're like, Hi, how are you

411
00:26:33,470 --> 00:26:33,630
doing?

412
00:26:33,790 --> 00:26:34,670
Like, what are you doing today?

413
00:26:34,750 --> 00:26:37,470
And they're like, Man, I don't remember at all who said this.

414
00:26:37,630 --> 00:26:40,350
And you just click on one of the faces you saw randomly.

415
00:26:40,590 --> 00:26:41,950
Feels like random guessing.

416
00:26:42,030 --> 00:26:43,630
You're not conscious of anything.

417
00:26:43,870 --> 00:26:49,840
But it turns out that, and this is a very reliable, replicable finding, is

418
00:26:49,840 --> 00:26:54,880
that what ends up happening in people's cognitive processing is that they're

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00:26:54,880 --> 00:26:59,760
categorizing the statement not as just coming from an individual, but also a social

420
00:26:59,760 --> 00:27:00,320
category.

421
00:27:00,480 --> 00:27:04,480
So for example, this is a statement coming from a woman or a man.

422
00:27:04,720 --> 00:27:10,610
And what will happen is in the guessing process, the fact that that

423
00:27:10,610 --> 00:27:16,050
statement was said by a man or a woman will cause them to be more likely to

424
00:27:16,050 --> 00:27:21,170
choose one of the men or one of the women, even if they don't remember the correct speaker.

425
00:27:21,410 --> 00:27:26,450
So, in other words, like if there's four male speakers, even if they get the male speaker

426
00:27:26,450 --> 00:27:31,970
wrong, the actual particular individual one, they'll be more likely to attribute it to

427
00:27:31,970 --> 00:27:32,850
another one of the men.

428
00:27:33,010 --> 00:27:38,100
So if you and I were talking to somebody and they forgot which one of us said it.

429
00:27:38,500 --> 00:27:39,220
Which David, yeah.

430
00:27:39,940 --> 00:27:40,660
Yeah, exactly.

431
00:27:41,220 --> 00:27:43,460
They'd be like, well, one of the Davids said it, right?

432
00:27:43,620 --> 00:27:46,100
Um and Or one of one of the men said it.

433
00:27:46,500 --> 00:27:47,060
Exactly.

434
00:27:47,220 --> 00:27:53,060
And and so, and it turns out then you can quantify for each participant the

435
00:27:53,060 --> 00:27:58,980
degree to which their errors cluster non-randomly, and to the degree that a statement that

436
00:27:58,980 --> 00:28:04,830
had come from a man was attributed to other men, a statement that had come from a woman is

437
00:28:04,830 --> 00:28:10,190
attributed to other women, that quantifies in a very precise way to the degree to which

438
00:28:10,190 --> 00:28:13,470
that particular participant categorized by sex.

439
00:28:13,950 --> 00:28:19,230
And it's good because it allows you to measure categorization by, for example, sex in a way

440
00:28:19,230 --> 00:28:20,270
that's non-conscious.

441
00:28:20,430 --> 00:28:22,270
So there's no social desirability things.

442
00:28:22,350 --> 00:28:25,710
Because if you ask somebody like, oh yeah, no, are you categorizing people by like, you

443
00:28:25,710 --> 00:28:27,630
know, race, the people are like, no, no, no, no.

444
00:28:27,700 --> 00:28:31,780
but like they might be right they just know that you know that you're I'm not supposed to

445
00:28:31,860 --> 00:28:36,020
so you just sort of are you are you likely to confuse what one black person said with what

446
00:28:36,020 --> 00:28:39,860
another black person said oh no of course not no exactly but and but if you look at the

447
00:28:39,860 --> 00:28:44,100
data they're they're actually doing that yeah exactly and so this is in this this who said

448
00:28:44,260 --> 00:28:49,300
what paradigm was used for basically 40 years and what people found was that

449
00:28:49,540 --> 00:28:54,980
categorization by many categories like social class, like

450
00:28:56,070 --> 00:29:00,790
sort of more arbitrary things, like maybe if they're a university student or a teacher,

451
00:29:01,430 --> 00:29:06,790
even visible things like clothing, styles, these were things that would sometimes be

452
00:29:06,790 --> 00:29:11,110
categorized as measured by this paradigm, but sometimes not.

453
00:29:11,270 --> 00:29:11,510
Yeah.

454
00:29:11,670 --> 00:29:14,790
So like it would just sort of depend on is it relevant or not?

455
00:29:15,750 --> 00:29:20,260
You know, like in we all have this experience of like, you know, sometimes we categorize

456
00:29:20,260 --> 00:29:26,260
people by like whether or not they are a supporter of a particular team or of a political

457
00:29:26,260 --> 00:29:30,500
party or something, and maybe not other times, you know, like it's just not relevant.

458
00:29:31,460 --> 00:29:37,140
But um, but there were certain categories that people always use, um, regardless of whether

459
00:29:37,140 --> 00:29:38,820
or not it was relevant to the context.

460
00:29:38,900 --> 00:29:44,500
And one of those was um, well, one of them was sex, as we talked about,

461
00:29:44,740 --> 00:29:50,110
one of them was age, um, you know, usually broad, broad strokes of age, like old, young,

462
00:29:50,190 --> 00:29:51,470
um, kind of thing, you know.

463
00:29:51,710 --> 00:29:53,790
And then the third one was race.

464
00:29:54,990 --> 00:30:00,030
And uh, especially for race, people were interested in seeing if there was a way to reduce

465
00:30:00,030 --> 00:30:01,470
categorization by race.

466
00:30:02,030 --> 00:30:07,840
Because again, uh, for something that is socially problematic, like racism, uh

467
00:30:08,000 --> 00:30:13,280
changing categorization would be a way to change discrimination by race.

468
00:30:13,440 --> 00:30:18,320
And so people immediately, once they discovered people seem to always categorize people by

469
00:30:18,320 --> 00:30:18,640
race.

470
00:30:18,800 --> 00:30:23,040
And this is usually like black versus white, like that, that broad stroke.

471
00:30:23,280 --> 00:30:29,200
There, there have been other um other kinds of categories that you find similar

472
00:30:29,200 --> 00:30:29,360
things.

473
00:30:29,520 --> 00:30:35,280
So, for example, um uh an analogous category sort of in Germany is um

474
00:30:35,600 --> 00:30:41,530
people who are um sort of a Middle Eastern or particular Turkish descent and that has been

475
00:30:41,530 --> 00:30:41,770
found.

476
00:30:41,930 --> 00:30:46,570
So like people will categorize by like sort of white European German versus Turkish in

477
00:30:46,570 --> 00:30:47,530
Germany, for example.

478
00:30:47,690 --> 00:30:53,530
So like visible, physically visible sort of like racial categories in a local

479
00:30:53,530 --> 00:30:54,090
context.

480
00:30:54,410 --> 00:30:57,290
This is sort of a what people have typically meant by race.

481
00:30:57,610 --> 00:30:57,770
Okay.

482
00:30:57,850 --> 00:31:03,020
I just want to lay the groundwork for the discovery that I think you're about to get to,

483
00:31:03,100 --> 00:31:05,820
which was made uh by an evolutionary psychologist.

484
00:31:06,060 --> 00:31:10,220
So th i i i in this context of when when was this research being done?

485
00:31:10,300 --> 00:31:11,500
Like 80s, 90s?

486
00:31:12,460 --> 00:31:16,220
The first Who Said What paradigm was done in uh 78.

487
00:31:17,660 --> 00:31:23,020
And then from then on uh in up and through early 2000s.

488
00:31:23,340 --> 00:31:28,010
So this is two or three decades of research on this paradigm.

489
00:31:28,250 --> 00:31:34,010
And people are are finding that that the mind is intuitively categorizing people by

490
00:31:34,010 --> 00:31:34,650
race.

491
00:31:34,970 --> 00:31:35,370
Correct.

492
00:31:35,610 --> 00:31:41,450
And the holy grail that everyone in this field is looking for is how to we how do

493
00:31:41,450 --> 00:31:44,490
we get people to stop categorizing by race?

494
00:31:44,810 --> 00:31:45,050
That's right.

495
00:31:45,770 --> 00:31:50,730
The thought is if we can cut this at the root, and if we can stop people from

496
00:31:50,730 --> 00:31:56,020
categorizing by race at the beginning, then it will solve this

497
00:31:56,020 --> 00:32:01,780
downstream problem of people discriminating or treating

498
00:32:01,780 --> 00:32:03,140
black people unfairly.

499
00:32:03,380 --> 00:32:07,860
All of these social problems that we as social scientists are trying to solve, we can cut

500
00:32:07,860 --> 00:32:13,140
them at the root by trying to eliminate this bias in the human mind to categorize by race.

501
00:32:13,300 --> 00:32:18,580
So everybody is looking for the holy grail of how do we get people to stop

502
00:32:18,580 --> 00:32:20,170
categorizing by race.

503
00:32:20,250 --> 00:32:21,850
Is that a fair characterization?

504
00:32:22,090 --> 00:32:22,490
That's right.

505
00:32:22,570 --> 00:32:26,810
And I think I don't, I'm not even sure they had that, uh, all of that in mind.

506
00:32:26,970 --> 00:32:32,170
I think it was some of it was just at the level of well, we're finding it is always a basis

507
00:32:32,170 --> 00:32:36,490
of categorization, and it would seem like a good idea to get it to not be.

508
00:32:36,570 --> 00:32:38,090
So let's figure out a way to do it.

509
00:32:38,250 --> 00:32:43,130
And people sort of stood on their head, I think, as a care a fair characterization.

510
00:32:43,290 --> 00:32:46,650
Um, they would tell they would change the relevance of race.

511
00:32:46,810 --> 00:32:52,740
Many theories in social categorization were theories that predicted roughly

512
00:32:52,900 --> 00:32:58,100
that if a context is relevant to the category, then it should be categorized.

513
00:32:58,340 --> 00:32:58,580
Yeah.

514
00:32:58,820 --> 00:33:00,260
So relevance, yeah.

515
00:33:00,420 --> 00:33:02,660
Um, or stereotypicality.

516
00:33:02,820 --> 00:33:07,540
So is the context one where race is relevant for stereotypes, or is it counter

517
00:33:07,620 --> 00:33:08,740
stereotypical?

518
00:33:09,140 --> 00:33:12,350
All of these things telling people attend to race.

519
00:33:12,430 --> 00:33:15,230
So that part of the instruction would be attend to the race.

520
00:33:15,550 --> 00:33:18,830
One instrument another a different set of instructions was don't attend to race.

521
00:33:18,990 --> 00:33:22,830
Um you know the default is not nothing nothing changed.

522
00:33:22,910 --> 00:33:28,750
So so everything that the current theories of categorization uh were

523
00:33:28,750 --> 00:33:31,310
predicting uh weren't working.

524
00:33:31,470 --> 00:33:31,710
Yeah.

525
00:33:32,030 --> 00:33:32,270
Yeah.

526
00:33:32,430 --> 00:33:37,720
And I also wanted to add that at this point, you can correct me if I'm wrong, people were

527
00:33:37,720 --> 00:33:43,560
starting to grow rather pessimistic about the possibility of eliminating this tendency to

528
00:33:43,560 --> 00:33:44,840
categorize by race.

529
00:33:45,080 --> 00:33:50,280
There was even some talk of maybe this is just a part of human nature, maybe this is just

530
00:33:50,280 --> 00:33:54,200
in our DNA, we're innately racist because of our evolutionary heritage.

531
00:33:54,280 --> 00:33:58,280
There was some bad evolutionary psychology coming out of social psychology at this time

532
00:33:58,440 --> 00:34:02,760
that maybe this stuff is just is hopeless and that we're just uh we're innate racists.

533
00:34:02,870 --> 00:34:03,030
right?

534
00:34:03,350 --> 00:34:09,270
Yeah, I th I think the the I think the that that um innate racist was sort of

535
00:34:09,270 --> 00:34:12,390
outside the professional vein of research.

536
00:34:12,550 --> 00:34:18,230
The professional vein of research, however, did was as you it's correct what you're saying,

537
00:34:18,310 --> 00:34:21,430
it was not just resigned to it would be inevitable.

538
00:34:21,670 --> 00:34:25,110
They were to their credit trying to make claims about the underlying design.

539
00:34:25,190 --> 00:34:30,420
And so one of those claims was well maybe it's built into our psychology.

540
00:34:30,580 --> 00:34:35,460
I don't think they were claiming we're sort of innate racist, but um, but it it it sort of

541
00:34:35,460 --> 00:34:40,740
amounts to the same thing, which is that race, age, and sex are all really important.

542
00:34:41,700 --> 00:34:47,620
And they may be primitives to the human mind and sort of built-in

543
00:34:47,620 --> 00:34:49,540
categories to the human mind.

544
00:34:49,780 --> 00:34:55,590
And that was the conclusion, reluctantly, uh particularly in the case of race,

545
00:34:55,830 --> 00:35:00,710
based on these decades of failures to change categorization by race, correct?

546
00:35:01,590 --> 00:35:01,910
Okay.

547
00:35:02,310 --> 00:35:02,950
Yeah.

548
00:35:03,830 --> 00:35:04,150
All right.

549
00:35:04,230 --> 00:35:07,670
Now should we should evolutionary psychology enter the stage?

550
00:35:07,990 --> 00:35:08,310
Yeah.

551
00:35:08,470 --> 00:35:13,590
So uh and this is where this is a really nice example of two principles.

552
00:35:13,750 --> 00:35:17,670
One of evolutionary psychology not just being a just so story.

553
00:35:17,830 --> 00:35:23,320
And the second thing is that having an idea of an ancestral environment

554
00:35:23,640 --> 00:35:29,400
as different than modern circumstances, both of these principles

555
00:35:29,400 --> 00:35:34,840
are really useful for what we're about to say and were really necessary for what we're

556
00:35:34,840 --> 00:35:35,400
about to say.

557
00:35:35,640 --> 00:35:41,310
So what ended up happening was, um, and so so Lita

558
00:35:41,470 --> 00:35:46,110
Cosmeties, John Tuby, um at the time Rob Kurzman had did some work, and then I've done a

559
00:35:46,110 --> 00:35:46,910
lot of this work as well.

560
00:35:46,990 --> 00:35:51,470
So sort of all of us as a team are are sort of responsible for this work.

561
00:35:51,630 --> 00:35:54,190
Um, and we're just talking about it because I know it so well.

562
00:35:54,350 --> 00:36:00,190
Um but but basically um what what especially I think Lita Lita

563
00:36:00,350 --> 00:36:06,240
and John um sort of did in Rob were to was to look at

564
00:36:06,240 --> 00:36:10,400
this phenomenon of people always categorize people by race in particular.

565
00:36:10,640 --> 00:36:15,600
And then this additional claim of there's sort of software in the mind for categorizing

566
00:36:15,600 --> 00:36:16,720
people by race.

567
00:36:17,040 --> 00:36:19,280
This idea is a functional claim.

568
00:36:19,440 --> 00:36:24,800
This is saying there is a system in the mind that is well designed to categorize people by

569
00:36:24,830 --> 00:36:25,470
race.

570
00:36:25,790 --> 00:36:31,470
A claim about what the function of a particular piece of software is in the mind has to be

571
00:36:31,470 --> 00:36:34,590
consistent with the way natural selection works.

572
00:36:35,790 --> 00:36:41,710
And uh and this is just simply because this is the only way that you get complexity,

573
00:36:41,790 --> 00:36:45,870
as you put very uh eloquently in previous episodes, David.

574
00:36:46,270 --> 00:36:51,640
The only way that complex, non-entropic

575
00:36:52,200 --> 00:36:58,200
structure can get built into the mind, just like as in the body, is if that structure

576
00:36:58,520 --> 00:37:04,200
is based around features of the environment that would have been present over evolutionary

577
00:37:04,200 --> 00:37:04,520
time.

578
00:37:05,320 --> 00:37:10,920
And those structures would have responded to those features that would have been present

579
00:37:10,920 --> 00:37:16,440
over evolutionary time in a way that would have been fitness benefiting, i.e.,

580
00:37:16,850 --> 00:37:22,050
would have generated differential reproductive success on average over

581
00:37:22,050 --> 00:37:23,330
evolutionary time.

582
00:37:23,970 --> 00:37:29,330
So the idea is that if we think of human software as sort of a bunch of

583
00:37:29,330 --> 00:37:34,770
complicated input-output processes, the claim that the social

584
00:37:35,170 --> 00:37:41,010
psychological literature was making was that there is a system in the mind that

585
00:37:41,010 --> 00:37:44,290
is for categorizing people by race.

586
00:37:44,740 --> 00:37:48,340
And this is precisely where an evolutionary approach comes in handy.

587
00:37:48,740 --> 00:37:54,420
And I want to interject, this is also precisely the point where bad evolutionary

588
00:37:54,420 --> 00:37:56,100
psychology could have been done.

589
00:37:56,500 --> 00:38:01,780
So if I see this pattern of people are naturally categorizing people by race, I could very

590
00:38:01,780 --> 00:38:07,590
easily tell a just-so story about how uh in the ancestral environment there was

591
00:38:07,590 --> 00:38:13,430
lots of intergroup warfare, intergroup competition, and categorizing people by you know of

592
00:38:13,430 --> 00:38:17,750
a different race would have been adaptive in the ancestral environment when we were cavemen

593
00:38:17,830 --> 00:38:22,150
and we were encountering people from different regions, and we would it would have been it

594
00:38:22,150 --> 00:38:26,070
would have benefited us to go to war with those other tribes that we encountered.

595
00:38:26,230 --> 00:38:28,630
So and and that I would end the analysis there.

596
00:38:28,790 --> 00:38:30,070
No further empirical work.

597
00:38:30,150 --> 00:38:32,150
That's my untestable just so story.

598
00:38:32,320 --> 00:38:33,040
my work is done.

599
00:38:33,200 --> 00:38:36,160
So that's an example of where you could do very bad evolutionary psychology.

600
00:38:36,400 --> 00:38:36,720
That's right.

601
00:38:36,800 --> 00:38:40,080
And you could look across cultures and then say, sort of, look, these people, this is the

602
00:38:40,080 --> 00:38:41,120
group basis here.

603
00:38:41,200 --> 00:38:44,720
And you say, well, yeah, that's because that's, you know, that's activates their tribal

604
00:38:44,720 --> 00:38:45,440
psychology, whatever.

605
00:38:45,600 --> 00:38:46,320
Yeah, no, exactly.

606
00:38:46,480 --> 00:38:46,800
That's right.

607
00:38:46,880 --> 00:38:47,040
Yeah.

608
00:38:47,440 --> 00:38:51,680
But but you and and Rob and Leda and John did not do bad evolutionary psychology.

609
00:38:51,760 --> 00:38:53,040
You did good evolutionary psychology.

610
00:38:53,360 --> 00:38:54,160
Better, yes.

611
00:38:55,120 --> 00:38:56,160
It's it's still oversimplified.

612
00:38:56,400 --> 00:38:56,960
But yeah, yeah, yeah.

613
00:38:57,600 --> 00:39:03,390
So I mean, but but it's so the the claim there's sort of um so yeah, let's

614
00:39:03,390 --> 00:39:04,510
just so thank you.

615
00:39:04,670 --> 00:39:10,590
The claim then is all right, let's look at the claim from uh this functional perspective.

616
00:39:10,750 --> 00:39:16,750
So the claim is that evolutionary um over well, the

617
00:39:16,750 --> 00:39:20,590
claim is there's a system in the mind for categorizing people by race.

618
00:39:21,070 --> 00:39:23,470
There's two parts to any evolutionary account.

619
00:39:23,630 --> 00:39:29,220
One is is the feature of the world present, And then two is

620
00:39:29,700 --> 00:39:34,180
would there have been selection for dealing with that feature of the world in a way that

621
00:39:34,180 --> 00:39:35,940
would have been fitness relevant?

622
00:39:36,980 --> 00:39:42,740
And if you look at race, even on just the first criteria of would this have been a feature

623
00:39:43,220 --> 00:39:46,020
of around which our minds could have evolved?

624
00:39:46,180 --> 00:39:51,860
Because something has to be a stable feature of the environment for our minds to uh

625
00:39:52,180 --> 00:39:54,420
to have some structure to represent it.

626
00:39:54,580 --> 00:39:56,850
A good example is like a mother.

627
00:39:57,090 --> 00:39:58,610
Mothers are always present.

628
00:39:58,690 --> 00:40:04,290
That's a stable, enduring feature of the sexually

629
00:40:04,290 --> 00:40:05,810
reproducing organisms.

630
00:40:06,050 --> 00:40:11,730
And especially where your mother is investing in you, there's really good

631
00:40:11,970 --> 00:40:14,450
ideas that like you always had a mother.

632
00:40:14,530 --> 00:40:17,010
And so that's a stable feature of the world.

633
00:40:17,090 --> 00:40:21,890
And that feature of the world, given that you have a mother who has an identity who's

634
00:40:22,050 --> 00:40:27,260
individual, that's an enduring feature that can create selection pressures and mental

635
00:40:27,260 --> 00:40:30,060
machinery for identifying who your mother is, right?

636
00:40:30,380 --> 00:40:32,140
Which is of critical adaptive importance.

637
00:40:32,380 --> 00:40:32,620
Exactly.

638
00:40:32,700 --> 00:40:35,820
And that's the so it's a feature of the environment.

639
00:40:36,060 --> 00:40:39,100
One, two, it would have fitness relevance, right?

640
00:40:39,260 --> 00:40:44,860
A robot, a squishy robot that doesn't identify its mother versus one that does.

641
00:40:45,260 --> 00:40:51,180
There's clear, straightforward logic to why one design would do well

642
00:40:51,420 --> 00:40:52,380
versus another.

643
00:40:52,670 --> 00:40:52,990
right?

644
00:40:53,390 --> 00:40:56,350
And um so that so that's that.

645
00:40:56,670 --> 00:41:02,590
In the case of race, even the first criteria, was it present over

646
00:41:02,590 --> 00:41:03,790
evolutionary time?

647
00:41:04,030 --> 00:41:09,950
Already we're in tricky uh tricky ground, uh shaky ground, let's put it that way.

648
00:41:10,190 --> 00:41:15,790
Um so race as we talk about it, if you look uh just from an objective biological

649
00:41:15,790 --> 00:41:21,700
perspective, um, you know, human beings have uh superficial

650
00:41:21,700 --> 00:41:27,060
variation in response to like climactic um exposure.

651
00:41:27,220 --> 00:41:31,700
So what we think of as race is sort of very skin-deep superficial differences

652
00:41:32,900 --> 00:41:35,460
between populations of people.

653
00:41:36,100 --> 00:41:41,940
Um but the degree to which those physical features track

654
00:41:41,940 --> 00:41:47,490
ancestry is actually quite weak because um different

655
00:41:47,490 --> 00:41:52,770
populations of people who have different recent common ancestry um can look similar because

656
00:41:52,770 --> 00:41:57,890
they've been exposed to similar climates or uh it's sort of you know um things like how

657
00:41:57,890 --> 00:42:02,690
much melanin people have, like what their um what their eye shapes are, things like that.

658
00:42:02,850 --> 00:42:08,450
A lot of these things are very superficial um adaptations and they're very recent too.

659
00:42:08,690 --> 00:42:12,960
Um white skin evolved something like shockingly recently.

660
00:42:13,040 --> 00:42:15,440
I think it's even less than 5,000 years ago.

661
00:42:15,520 --> 00:42:16,400
There's actually really good.

662
00:42:16,560 --> 00:42:17,200
Yeah, it's incredible.

663
00:42:17,520 --> 00:42:18,400
That's that's not enough time.

664
00:42:18,640 --> 00:42:19,120
No, no, no.

665
00:42:19,280 --> 00:42:21,520
Modern humans, you know, we're 60,000 years ago.

666
00:42:21,600 --> 00:42:25,920
A 60,000-year-old, well, not year old, but like, you know, if in a time machine, if you if

667
00:42:25,920 --> 00:42:30,960
you met a uh a person from 60,000 years ago, they'd be a much better hunter and runner and

668
00:42:31,040 --> 00:42:32,560
et cetera, than you.

669
00:42:32,800 --> 00:42:38,710
Um, But they would be different in certain ways, but they're still us, right?

670
00:42:38,870 --> 00:42:43,590
So, you know, our current brains were around 60,000 years ago.

671
00:42:44,870 --> 00:42:47,670
And, you know, human beings don't come into subspecies.

672
00:42:47,990 --> 00:42:52,710
Like even chimps, for example, have five to six times more genetic variation than we do.

673
00:42:52,870 --> 00:42:54,950
And even chimps don't have subspecies.

674
00:42:55,510 --> 00:42:59,670
And so we're really related, which is consistent with, you know, there's more recent

675
00:42:59,670 --> 00:43:05,300
genetic evidence that there were really uh tight bottlenecks in our ancestral populations.

676
00:43:05,380 --> 00:43:10,420
So like as a as a from a biological perspective, we are extremely similar to one another,

677
00:43:10,580 --> 00:43:12,020
humans as humans are.

678
00:43:12,340 --> 00:43:18,100
So um so the idea that sort of race as we talk about it would have been a feature over

679
00:43:18,100 --> 00:43:19,380
evolutionary time.

680
00:43:19,620 --> 00:43:25,220
Number one, um very racial quote unquote what we count what the physical features that we

681
00:43:25,220 --> 00:43:29,430
think of as race are very recent um things.

682
00:43:30,230 --> 00:43:36,230
Also, it's only with recent transportation technology that you would people

683
00:43:36,230 --> 00:43:40,230
would have encountered sort of large-scale systematic differences among these things

684
00:43:40,310 --> 00:43:43,350
because otherwise everyone's traveling on foot or even by boat.

685
00:43:43,510 --> 00:43:46,870
You're meeting people, you're mating with them, you're, you know, like it's just

686
00:43:47,750 --> 00:43:53,280
ecologically valid or non-modern technologically

687
00:43:53,280 --> 00:43:59,280
mediated social world is one where basically as the scale of social interaction,

688
00:43:59,840 --> 00:44:05,600
whatever scale that is, people are sort of blending together in terms of what they look

689
00:44:05,600 --> 00:44:05,840
like.

690
00:44:05,920 --> 00:44:08,160
Um just by virtue, yeah.

691
00:44:08,640 --> 00:44:12,880
Very unlikely for an ancestral hunter-gatherer to be doing intercontinental travel.

692
00:44:13,360 --> 00:44:14,320
Exactly, yes.

693
00:44:14,560 --> 00:44:19,210
Um and and even if they were, it would be just them, and then they're just part of that

694
00:44:19,210 --> 00:44:21,770
community, and their children look like the community, right?

695
00:44:21,850 --> 00:44:27,850
So it's not uh this this large scale, large numbers of groups that are socially isolated

696
00:44:28,010 --> 00:44:33,690
remain so distinct for multiple generations, is really a modern phenomenon,

697
00:44:33,770 --> 00:44:34,090
right?

698
00:44:34,570 --> 00:44:39,210
And and so race as we think about it, you know, it's it's it would have not have been an

699
00:44:39,210 --> 00:44:40,410
enduring feature.

700
00:44:40,490 --> 00:44:44,060
Um, And even what counts as a race varies historically, right?

701
00:44:44,140 --> 00:44:47,580
So, like, you know, in the United States, being Irish was literally a race.

702
00:44:47,660 --> 00:44:48,940
It wasn't figuratively a race.

703
00:44:49,100 --> 00:44:54,940
You know, you can if you look across places, you know, Rwanda, Hutu, uh, Twitsi, you know,

704
00:44:55,020 --> 00:45:00,940
this was a uh we know the history of this was a hallucinated racial distinction

705
00:45:00,940 --> 00:45:02,620
that had no objective basis.

706
00:45:02,940 --> 00:45:03,100
Right.

707
00:45:03,180 --> 00:45:08,010
And I'm sure if you brought people into the lab at that time period and showed them some

708
00:45:08,010 --> 00:45:12,410
Irish people and some they would say, Oh, it was one of the Irish people said that.

709
00:45:12,650 --> 00:45:15,610
And they would have you would have seen categorization by Irishness.

710
00:45:15,930 --> 00:45:16,330
That's right.

711
00:45:16,970 --> 00:45:21,610
The idea that we have inbuilt software for detecting Irishness is preposterous.

712
00:45:22,250 --> 00:45:23,450
So something something has gone wrong here.

713
00:45:23,770 --> 00:45:23,930
Yeah.

714
00:45:24,170 --> 00:45:27,690
If you showed the same thing to ancient Greeks or Romans, the racial categories would have

715
00:45:27,690 --> 00:45:28,330
been different.

716
00:45:28,490 --> 00:45:30,570
But the same idea, right?

717
00:45:30,700 --> 00:45:34,300
Um, and this is sort of a part of what we talked about, instinct blindness, right?

718
00:45:34,380 --> 00:45:38,700
This idea that if we experience something vividly, and we do, like there's a pop-out

719
00:45:38,860 --> 00:45:39,420
effect, you know.

720
00:45:39,580 --> 00:45:45,500
Like one analogy I like to use is something like you can see

721
00:45:45,500 --> 00:45:51,260
the clothing color of people or what a car looks like, but there's a pop-out effect if you

722
00:45:51,260 --> 00:45:56,940
see a police officer or uh an EMT or an ambulance or a

723
00:45:56,940 --> 00:45:59,260
police car or military uniform.

724
00:45:59,690 --> 00:46:05,130
And it's not just a consequence of the color, but it is something about there's this

725
00:46:05,130 --> 00:46:05,850
additional inference.

726
00:46:05,930 --> 00:46:08,810
Or another example of this would be like sort of gang colors, right?

727
00:46:09,130 --> 00:46:10,330
Or team colors, right?

728
00:46:10,410 --> 00:46:12,170
There's just like this additional inference.

729
00:46:12,250 --> 00:46:13,690
And that I think is the idea.

730
00:46:13,850 --> 00:46:16,730
There's sort of pop-out for these for these categories.

731
00:46:16,890 --> 00:46:22,860
But anyway, getting back to this idea, race would not have been a feature in which

732
00:46:22,860 --> 00:46:24,300
our minds evolved.

733
00:46:24,460 --> 00:46:30,220
What counts as a race is really different and volatile across historical time and even

734
00:46:30,220 --> 00:46:32,540
within historical time across cultures.

735
00:46:32,780 --> 00:46:37,980
And so the idea that the mind has software for this particular

736
00:46:37,980 --> 00:46:41,260
category is sort of seems strange.

737
00:46:41,660 --> 00:46:47,020
And then the logic of an evolutionary approach or adaptationism is that you take the

738
00:46:47,020 --> 00:46:52,970
behavior, but then you say, look, any outcome is either a product of adaptations, or it's

739
00:46:52,970 --> 00:46:56,330
a byproduct of adaptations, or it's noise, right?

740
00:46:56,810 --> 00:47:02,170
And it's some combination of those three things underlie any behavior.

741
00:47:02,330 --> 00:47:06,410
Now it might be multiple adaptations, it might be multiple combinations of these, but just

742
00:47:06,410 --> 00:47:10,010
by virtue of the logic of how natural selection works, it has to be one of these three

743
00:47:10,010 --> 00:47:10,730
categories.

744
00:47:10,970 --> 00:47:11,530
Yep.

745
00:47:12,020 --> 00:47:16,980
And one question then, and this is part of doing a task analysis, which we may or may not

746
00:47:16,980 --> 00:47:22,420
get to here, is then you look at a certain behavioral phenomenon or a particular phenomenon

747
00:47:22,420 --> 00:47:23,380
you're interested in.

748
00:47:23,460 --> 00:47:29,060
And then you say, well, you know, what kind of an adaptation or sets of

749
00:47:29,060 --> 00:47:34,180
adaptations does this look like it might be either a result of or a byproduct of?

750
00:47:34,660 --> 00:47:40,010
And so when looking at how people were treating race, what

751
00:47:40,010 --> 00:47:43,530
inferences follow, what kind of thing does it look like?

752
00:47:43,770 --> 00:47:47,850
This led to an idea, and this is called the alliance hypothesis of race.

753
00:47:48,010 --> 00:47:53,290
So the idea is that there would not have been selection pressures on the mind for

754
00:47:53,290 --> 00:47:55,450
categorizing people by race.

755
00:47:56,170 --> 00:48:00,730
In contrast, there would have been selection pressures on the mind for

756
00:48:01,370 --> 00:48:03,530
tracking alliances.

757
00:48:03,840 --> 00:48:09,600
So an alliance is uh people joining together

758
00:48:09,920 --> 00:48:11,760
to cooperate.

759
00:48:12,000 --> 00:48:14,720
That cooperation can also involve antagonism.

760
00:48:14,800 --> 00:48:19,120
So then an alliance can be who's on whose side in a conflict.

761
00:48:19,360 --> 00:48:22,800
It can involve coordination, so who's coordinated with who.

762
00:48:23,280 --> 00:48:29,130
And there's a lot of evidence, a lot of theory, a lot of modeling, what we know from

763
00:48:29,130 --> 00:48:34,490
the hunter-gatherer literature, and just deductive logic is that

764
00:48:35,050 --> 00:48:39,370
and even you know comparative evidence of from other primates, chimpanzees also have

765
00:48:39,370 --> 00:48:40,250
intergroup differences.

766
00:48:40,650 --> 00:48:40,810
Right.

767
00:48:41,050 --> 00:48:41,290
Right.

768
00:48:41,450 --> 00:48:47,450
So the idea is that cooperation, competition, coordination are

769
00:48:47,450 --> 00:48:52,220
really important, deep principles of our evolutionary past.

770
00:48:52,700 --> 00:48:58,380
The ability to negotiate these relationships is super important for

771
00:48:58,380 --> 00:49:01,340
fitness, meaning the designs that are successful or not.

772
00:49:01,500 --> 00:49:06,540
Designs that could negotiate these relationships will do better than those that cannot.

773
00:49:06,700 --> 00:49:12,700
A concomitant of doing well or navigating these relationships is

774
00:49:12,700 --> 00:49:17,180
the ability to track who is affiliated with who.

775
00:49:17,790 --> 00:49:19,630
This is a complicated problem.

776
00:49:19,870 --> 00:49:25,630
I mean, most of my empirical work is on this problem, and we know very

777
00:49:25,630 --> 00:49:28,510
little about how the software for this works.

778
00:49:28,910 --> 00:49:32,110
But what the idea is that we have this software.

779
00:49:32,190 --> 00:49:34,830
This is a clear set of adaptive problems.

780
00:49:35,310 --> 00:49:40,180
The ability to identify who is allied with who is important.

781
00:49:40,340 --> 00:49:44,500
It's important for predicting when you see two people come together.

782
00:49:44,820 --> 00:49:46,900
Can you predict what their relationship will be?

783
00:49:47,060 --> 00:49:51,380
If you see another person, can you predict what their relationship will be towards you?

784
00:49:52,100 --> 00:49:56,340
And part of the way that the system would work is

785
00:49:57,860 --> 00:50:03,570
just like who your mother is, the groups that exist, the alliances that exist

786
00:50:03,810 --> 00:50:05,970
are dependent on local circumstances.

787
00:50:06,130 --> 00:50:09,170
So it's a learning system, it's a learning adaptation.

788
00:50:10,370 --> 00:50:15,810
There would have been no consistent way in which groups demarcated themselves throughout

789
00:50:15,810 --> 00:50:17,330
our evolutionary history.

790
00:50:17,730 --> 00:50:18,050
That's right.

791
00:50:18,290 --> 00:50:19,810
In the same way it would be a good idea.

792
00:50:19,890 --> 00:50:19,970
Yeah.

793
00:50:20,130 --> 00:50:24,690
You have to learn exactly how groups are being differentiated, what the what the markers

794
00:50:24,690 --> 00:50:24,770
are.

795
00:50:25,280 --> 00:50:25,600
Exactly.

796
00:50:25,760 --> 00:50:29,680
In the same way that who your mother is always varies over every generation.

797
00:50:29,760 --> 00:50:35,120
And therefore, it's a learning system that has an open parameter that says there are a set

798
00:50:35,120 --> 00:50:41,040
of cues that are reliably present that tell you who your mother is,

799
00:50:41,200 --> 00:50:46,770
but the system doesn't develop to create an identity Ahead of time.

800
00:50:46,850 --> 00:50:49,650
It's not innate, yes, quote unquote, in the system.

801
00:50:49,810 --> 00:50:52,050
The identity itself is not in the system.

802
00:50:52,930 --> 00:50:58,850
The rules for identifying the identity that exists in the world is in

803
00:50:58,850 --> 00:50:59,490
the system.

804
00:50:59,650 --> 00:51:05,010
And that's the same principle in the alliance system, which is

805
00:51:05,490 --> 00:51:11,280
what the basis of group interaction or treat social interaction

806
00:51:11,280 --> 00:51:16,880
will be will vary, but then you can use cues to learn

807
00:51:16,880 --> 00:51:18,880
who's affiliated with who.

808
00:51:19,120 --> 00:51:24,960
And the idea is that so there's software in the mind for tracking alliances, and part

809
00:51:24,960 --> 00:51:30,640
of that design is a learning system that is looking out in the world for reliable

810
00:51:30,640 --> 00:51:32,960
patterns of cooperation and competition.

811
00:51:33,120 --> 00:51:35,280
You could do a task analysis of what those are.

812
00:51:35,360 --> 00:51:41,030
It might be when you see two people physically hurting one another, encode not only their

813
00:51:41,030 --> 00:51:46,390
individual identities, but any any category level features that they have, and see if that

814
00:51:46,390 --> 00:51:51,030
category level predicts future conflict.

815
00:51:51,110 --> 00:51:55,670
So, for example, like if if the people who live on this side of the river versus who live

816
00:51:55,670 --> 00:52:00,950
on this side of the river or who have this tattoo versus have this other tattoo, it's

817
00:52:00,950 --> 00:52:05,540
basically this learning thing of there's the software that's looking out in the world for

818
00:52:05,540 --> 00:52:10,100
who's cooperating with who, who's fighting with who, and then what are the cues that are

819
00:52:10,100 --> 00:52:14,500
correlating in thus predicting those relationships.

820
00:52:15,460 --> 00:52:21,300
All of this has very clear selection pressure advantages, to just put

821
00:52:21,300 --> 00:52:22,020
it that way.

822
00:52:22,660 --> 00:52:23,780
Would have been enduring.

823
00:52:23,860 --> 00:52:27,940
We're talking about it at a fairly abstracted level, but it's the it's the level of

824
00:52:27,940 --> 00:52:28,820
invariance, right?

825
00:52:28,900 --> 00:52:30,980
We're not talking about what the particular cue is.

826
00:52:31,190 --> 00:52:35,590
We're not talking about the particular relationship, but it's the abstract, relevant

827
00:52:35,590 --> 00:52:36,630
categories, right?

828
00:52:36,710 --> 00:52:37,990
Of that's constant.

829
00:52:38,230 --> 00:52:38,710
And the idea of the question is.

830
00:52:53,300 --> 00:52:53,540
Right.

831
00:52:53,620 --> 00:52:53,780
Yeah.

832
00:52:54,020 --> 00:52:57,700
Um, and what you're saying here throws a wrench into that whole dichotomy because what

833
00:52:57,700 --> 00:53:00,740
you're talking about is an evolved learning system.

834
00:53:01,060 --> 00:53:01,380
That's right.

835
00:53:01,460 --> 00:53:01,620
Yes.

836
00:53:01,700 --> 00:53:02,900
And there's been yeah, yeah.

837
00:53:03,780 --> 00:53:04,100
Yeah, yeah.

838
00:53:04,180 --> 00:53:08,900
And Annie Wirtz has another great we will have her on too, uh, where this is exactly her

839
00:53:08,900 --> 00:53:14,740
point where there's another context where just like learning who your mother is, when the

840
00:53:14,740 --> 00:53:16,580
invariance is variance, right?

841
00:53:16,660 --> 00:53:20,490
The invariance is uh you can't build this in.

842
00:53:20,650 --> 00:53:26,170
You can't build in what David Pinsoff mother David Pinsoff's mother looks like to every

843
00:53:26,170 --> 00:53:30,570
human being because except for you, David, or your siblings, that will be wrong.

844
00:53:30,730 --> 00:53:36,650
Um and so when the invariance is uh is variation, it

845
00:53:36,650 --> 00:53:38,250
builds a learning system, right?

846
00:53:38,490 --> 00:53:38,730
Yes.

847
00:53:39,050 --> 00:53:40,250
This is Annie's point as well.

848
00:53:40,330 --> 00:53:40,490
Yeah.

849
00:53:40,730 --> 00:53:45,290
So I just wanted to quickly interject that you're talking about an evolved learning system.

850
00:53:45,620 --> 00:53:47,300
So continue with with what you're doing.

851
00:53:47,460 --> 00:53:47,620
Yeah.

852
00:53:47,860 --> 00:53:48,500
Yeah, thank you.

853
00:53:48,580 --> 00:53:52,020
It's good to dispel these sort of simple misunderstandings as we go.

854
00:53:52,260 --> 00:53:52,580
Yeah.

855
00:53:52,660 --> 00:53:54,900
So this is an evolved learning system.

856
00:53:55,140 --> 00:54:01,060
And the idea is that this description of the software, even at this basic level, the idea

857
00:54:01,060 --> 00:54:07,060
is that that software could be an explanation for why we see

858
00:54:07,060 --> 00:54:08,660
categorization by race.

859
00:54:08,980 --> 00:54:14,910
And the argument for that was that in a place where certain physical

860
00:54:14,910 --> 00:54:18,750
features become correlated with how people interact and treat one another, and there's a

861
00:54:18,750 --> 00:54:24,670
clear history about what that is in our culture and many cultures and in m most of our

862
00:54:25,390 --> 00:54:28,190
current milieus.

863
00:54:29,790 --> 00:54:34,910
So certain physical features become associated with how people treat one another, interact,

864
00:54:34,990 --> 00:54:35,950
and get along.

865
00:54:36,190 --> 00:54:41,700
So this software, this alliance tracking software, and that's just the label for it, When

866
00:54:41,700 --> 00:54:47,380
it grows up in a society or a social world in which certain physical features

867
00:54:48,020 --> 00:54:53,700
are picked up by this alliance tracking system, the idea is that those

868
00:54:53,700 --> 00:54:56,420
physical features are predicting these relationships.

869
00:54:56,580 --> 00:55:00,420
The evolved learning system is picking up on those physical features.

870
00:55:00,820 --> 00:55:04,100
It's not designed to pick up on physical features per se.

871
00:55:04,260 --> 00:55:06,420
It doesn't care if they're physical or not.

872
00:55:06,660 --> 00:55:10,890
The idea is that it's learning which physical or which features.

873
00:55:10,970 --> 00:55:16,330
I'm sorry, I don't mean physical features, any cues that predict how people interact or get

874
00:55:16,330 --> 00:55:17,690
along with one another.

875
00:55:17,930 --> 00:55:23,130
It picks up on those and then it stores those as being

876
00:55:23,130 --> 00:55:27,210
relevant for predicting other people's behavior, but then also how they're going to

877
00:55:27,210 --> 00:55:29,770
interact with me and how I should interact with them.

878
00:55:30,010 --> 00:55:35,940
And the idea is that that such that kind of software could

879
00:55:35,940 --> 00:55:41,620
explain why people are categorizing people by race, which has nothing to do with there

880
00:55:41,620 --> 00:55:45,300
being a dedicated system for categorizing people by race in the in their heads.

881
00:55:45,540 --> 00:55:45,700
Yeah.

882
00:55:46,100 --> 00:55:46,260
Yes.

883
00:55:46,420 --> 00:55:49,940
And I want to add one more thing that people get caught up on.

884
00:55:50,020 --> 00:55:54,980
So a common criticism of evolutionary psychology is that they think everything is an

885
00:55:54,980 --> 00:55:55,620
adaptation.

886
00:55:55,940 --> 00:56:00,930
They think our belly buttons are adaptations that so that we could, you know, put nuts and

887
00:56:00,930 --> 00:56:02,130
small pieces of food there.

888
00:56:02,450 --> 00:56:07,570
They think that, you know, our uh the the ridge of our nose is an adaptation to hold up our

889
00:56:07,570 --> 00:56:08,050
glasses.

890
00:56:08,210 --> 00:56:11,330
They see adaptations everywhere, even where they don't exist.

891
00:56:11,650 --> 00:56:16,530
So here we have a very clear um rebuttal to that criticism.

892
00:56:16,770 --> 00:56:22,370
We have a an instance where the hypothesis is specifically a byproduct hypothesis.

893
00:56:22,610 --> 00:56:28,500
You are not claiming that we have specific adaptations for categorizing by race.

894
00:56:28,660 --> 00:56:34,580
By contrast, you are claiming that we have adaptations for detecting alliance membership.

895
00:56:34,820 --> 00:56:40,500
And in the modern world, race becomes a cue of alliance membership.

896
00:56:40,660 --> 00:56:46,260
And so we categorize by race as a byproduct of adaptations for

897
00:56:46,260 --> 00:56:49,150
categorizing by alliance membership.

898
00:56:49,310 --> 00:56:53,950
So this is a byproduct hypothesis, not an adaptationist hypothesis.

899
00:56:54,030 --> 00:56:56,190
I just wanted to state that for the record.

900
00:56:56,510 --> 00:56:56,910
Yeah, yeah.

901
00:56:57,070 --> 00:57:02,990
And I would even say further: the idea is that what race is is

902
00:57:02,990 --> 00:57:08,270
a hallucination in the sense of race doesn't exist objectively.

903
00:57:08,590 --> 00:57:11,680
It's that it's a social convention.

904
00:57:12,080 --> 00:57:16,400
And the physical features that we think of as race get picked up on.

905
00:57:16,480 --> 00:57:22,080
And why they become race is because they're those things that have been picked up by

906
00:57:22,320 --> 00:57:27,280
this alliance tracking machinery because of the way that these features have been used

907
00:57:27,280 --> 00:57:30,800
historically and as a basis of discrimination.

908
00:57:31,280 --> 00:57:36,640
Um, and I mean that in the precise sense, I mean, uh, you know, discrimination, it could be

909
00:57:37,010 --> 00:57:42,850
treating other people better, you know, for example, like, you know, um uh white people um

910
00:57:43,090 --> 00:57:46,530
discriminating towards on behalf of other white people.

911
00:57:46,690 --> 00:57:52,450
Um, but the idea is that like these categories, again, like the Hutu Tutsi thing, can

912
00:57:52,770 --> 00:57:57,250
be uh not based on a sort of objective uh features, right?

913
00:57:57,330 --> 00:57:59,900
It's just uh coordination uh hallucination.

914
00:57:59,980 --> 00:58:05,660
It's could you speak if everyone has shares this uh is coordinated around this, um, that's

915
00:58:05,900 --> 00:58:08,380
that's where you get the category race appearing.

916
00:58:08,540 --> 00:58:14,380
It's it's after it has become socially predictive and people are acting as if

917
00:58:14,380 --> 00:58:15,340
it's socially predictive.

918
00:58:15,580 --> 00:58:20,700
That's that's it's it's it's a social construct in the in the precise meaning of that word.

919
00:58:21,180 --> 00:58:27,070
Um So, this explanation of being a byproduct, and thank you for emphasizing that.

920
00:58:27,310 --> 00:58:31,230
Um, what's crucial about it is this makes predictions.

921
00:58:31,870 --> 00:58:37,070
And it makes predictions because the claim is there's a well-designed system for tracking

922
00:58:37,070 --> 00:58:38,110
alliances.

923
00:58:38,670 --> 00:58:43,800
And part of that includes then that it should be sensitive to what uh

924
00:58:44,360 --> 00:58:48,120
who's cooperating with who, who's competing with who.

925
00:58:48,440 --> 00:58:54,360
And the job of this system is to track these relationships, keep track of

926
00:58:54,360 --> 00:58:59,560
the cues that predict them, and then use these cues to generate inferences about who will

927
00:58:59,560 --> 00:59:02,520
cooperate with who, who will compete with who, et cetera.

928
00:59:02,920 --> 00:59:08,200
So the paradigm that had shown that people always categorize by race this who said what

929
00:59:08,360 --> 00:59:14,230
paradigm, what Rob and Lita and John and myself have done, and we've really

930
00:59:14,870 --> 00:59:18,630
tested the heck out of this, and I'm quite confident in it.

931
00:59:18,710 --> 00:59:23,190
Um, and I was a bit skeptical at first, um, you know, but I convinced myself, and that was

932
00:59:23,190 --> 00:59:29,030
a good um, you know, that was a good, you know, 10 or 15 years of running lots of

933
00:59:29,030 --> 00:59:34,950
different studies trying to falsify it, um, was that this system,

934
00:59:35,430 --> 00:59:41,180
what it should be designed to do is to track the validity of a cue.

935
00:59:41,660 --> 00:59:47,500
So if race is being treated as an alliance cue, in the

936
00:59:47,500 --> 00:59:53,500
old studies, there was nothing in the stimuli that told

937
00:59:53,500 --> 00:59:56,460
people that there was some other alliance cue present.

938
00:59:56,700 --> 01:00:01,820
So even though the conversation wasn't about race or relevant to race, the idea is that

939
01:00:01,850 --> 01:00:07,050
alliances, especially alliances that have to do with like people treating each other, you

940
01:00:07,050 --> 01:00:12,010
know, at the level of like, you know, conflict, strong levels of

941
01:00:12,010 --> 01:00:17,610
discrimination that are valid across situations, people's lives, um,

942
01:00:17,930 --> 01:00:21,930
there's no better cue of alliance in the stimuli except for race.

943
01:00:22,170 --> 01:00:26,570
And so the reason why people were categorizing people by race is because this software

944
01:00:26,570 --> 01:00:32,320
system, this alliance tracking system, was looking at the people, detected this relevant

945
01:00:32,320 --> 01:00:36,320
cue and it wasn't detecting any other countervailing information.

946
01:00:36,560 --> 01:00:41,760
And the idea is that the alliance tracking system, if it's well designed, should be able to

947
01:00:41,760 --> 01:00:46,000
pick up on which cues are relevant for the current situation.

948
01:00:46,960 --> 01:00:51,680
And so the idea is that a well-designed alliance tracking system, it has to, as part of its

949
01:00:51,680 --> 01:00:57,650
job, juggle multiple alliances and be able to inhibit when a current alliance,

950
01:00:57,730 --> 01:01:02,530
uh a particular alliance is not relevant and activate one when it is and learn about new

951
01:01:02,530 --> 01:01:02,850
ones.

952
01:01:03,170 --> 01:01:06,530
These are just the con the implications of a well-designed system.

953
01:01:06,930 --> 01:01:07,090
Yes.

954
01:01:07,170 --> 01:01:12,770
It would be disastrous if you were to use an outmoded alliance category and

955
01:01:12,770 --> 01:01:16,450
mispredict who is going to come to your aid or fight with you.

956
01:01:17,170 --> 01:01:21,480
This would be dis a disastrous outcome uh from a Darwinian perspective.

957
01:01:21,640 --> 01:01:27,400
We would expect uh design for getting the answers to these questions right

958
01:01:27,480 --> 01:01:31,960
of what is the most relevant alliance uh in in the current social environment.

959
01:01:32,040 --> 01:01:32,840
Aaron Powell That's right.

960
01:01:32,920 --> 01:01:33,640
Yes, exactly.

961
01:01:33,800 --> 01:01:39,320
It needs to be a flexible, nimble system that's really sensitive to like what is

962
01:01:39,320 --> 01:01:41,640
currently organizing the conflict.

963
01:01:41,800 --> 01:01:44,760
And if you get it wrong, uh you're in trouble.

964
01:01:44,840 --> 01:01:50,550
Um And this prediction then is that so you so that's the

965
01:01:50,550 --> 01:01:52,230
idea of how the software works.

966
01:01:52,390 --> 01:01:57,830
So then what you do is then you think, okay, the software is an input-output system.

967
01:01:57,990 --> 01:02:00,310
Current humans have this software.

968
01:02:00,630 --> 01:02:06,630
How can we test to see if that's the design underlying racial categorization?

969
01:02:06,920 --> 01:02:07,080
Yes.

970
01:02:07,320 --> 01:02:12,120
And then you just you take, then say, well, what are the class of inputs that this thing

971
01:02:12,120 --> 01:02:13,240
should be sensitive to?

972
01:02:13,480 --> 01:02:18,680
And so we've conducted studies where we show people in this who said what paradigm just

973
01:02:18,680 --> 01:02:23,240
social groups that are a basis of cooperation.

974
01:02:23,400 --> 01:02:26,920
So we tell people, like, look, this is a group of people, they're all working together,

975
01:02:27,080 --> 01:02:30,520
traveling, they they really trust and count on one another.

976
01:02:30,680 --> 01:02:36,510
And you show them having a conversation where one group is talking about how they all

977
01:02:36,510 --> 01:02:41,550
work together, spend a lot of time together, trust one another, have had difficult,

978
01:02:41,870 --> 01:02:44,110
dangerous experiences together.

979
01:02:44,350 --> 01:02:48,190
And then there's another group who also is similarly like that.

980
01:02:48,350 --> 01:02:54,030
And so you're basically showing people the system cues of

981
01:02:54,350 --> 01:02:57,550
this set of people are all highly cooperative.

982
01:02:57,820 --> 01:03:00,460
This other set of people are all highly cooperative.

983
01:03:00,620 --> 01:03:05,180
And it's, you know, with like text, but you know, the presumably there's like any number of

984
01:03:05,180 --> 01:03:06,700
cues that you could use.

985
01:03:07,020 --> 01:03:07,660
Yeah.

986
01:03:07,980 --> 01:03:13,900
Um, but this was a first-pass test of like if there is an alliance tracking system, these

987
01:03:14,220 --> 01:03:19,340
cues of a history of deep engaged cooperation

988
01:03:20,220 --> 01:03:23,740
for each group with one group, group A and group B, right?

989
01:03:24,610 --> 01:03:27,810
this should satisfy the input conditions of the system.

990
01:03:28,770 --> 01:03:34,770
And then the idea is that if this alliance tracking system is good at not only picking up

991
01:03:34,770 --> 01:03:40,690
on new group memberships, it should also be able to deactivate

992
01:03:40,690 --> 01:03:46,530
or inhibit the use of cues that are no longer relevant, then the simple way to show that

993
01:03:46,530 --> 01:03:52,340
is we show people that race is no longer predictive of who's in group

994
01:03:52,340 --> 01:03:53,620
A or who's in group B.

995
01:03:53,780 --> 01:03:58,660
So concretely, there's an equal number of black and white people in group A and an equal

996
01:03:58,660 --> 01:04:00,740
number of black and white people in group B.

997
01:04:01,060 --> 01:04:06,260
And so as the people are shown having this conversation, so basically there's somebody in

998
01:04:06,260 --> 01:04:08,500
group A and they're like, Hey, nice to meet you.

999
01:04:08,660 --> 01:04:12,900
And the groups are having a friendly conversation, but the people are getting a window

1000
01:04:12,900 --> 01:04:14,980
into, oh, there's one group here.

1001
01:04:15,390 --> 01:04:19,870
they're all uh I think it was something like Habitat for Humanity and like partners in

1002
01:04:19,870 --> 01:04:21,630
health, like they were charity groups.

1003
01:04:21,790 --> 01:04:26,910
Um each charity group, those groups really work together.

1004
01:04:27,230 --> 01:04:31,710
And the people who are in that group are all in alliance, basically, is the idea.

1005
01:04:31,870 --> 01:04:32,110
Yeah.

1006
01:04:32,270 --> 01:04:32,910
Yeah.

1007
01:04:33,870 --> 01:04:39,640
And then that idea then is that there's two important

1008
01:04:39,880 --> 01:04:42,440
cues in that stimuli, in those stimuli.

1009
01:04:42,680 --> 01:04:48,600
One is that race is no longer predictive of who's on who who's allied with whom.

1010
01:04:49,080 --> 01:04:53,880
And then there's a new basis of alliance, which is this team membership.

1011
01:04:54,120 --> 01:04:59,790
And basically, when you do that and you show people the same

1012
01:04:59,790 --> 01:05:04,590
stimuli that in the past studies had always found categorization by race.

1013
01:05:04,990 --> 01:05:10,590
In fact, you get categorization by the new team membership, by charity group

1014
01:05:10,590 --> 01:05:16,510
membership, and you get people decreasing, strongly decreasing

1015
01:05:16,510 --> 01:05:18,350
their categorization by race.

1016
01:05:18,590 --> 01:05:23,220
And we vary how strong the cues are to charity group membership.

1017
01:05:23,380 --> 01:05:28,740
And in the conditions where it's very strong, people are often not categorizing by

1018
01:05:29,140 --> 01:05:30,020
race at all.

1019
01:05:31,140 --> 01:05:31,780
Say that again.

1020
01:05:31,860 --> 01:05:32,740
Not categorized by race.

1021
01:05:32,900 --> 01:05:34,180
Not category by race at all.

1022
01:05:34,580 --> 01:05:37,140
So you have accomplished the holy grail.

1023
01:05:37,300 --> 01:05:41,780
You have done what social psychologists have been trying to do, have been hoping they could

1024
01:05:41,780 --> 01:05:46,340
do, which is to eliminate categorization by race.

1025
01:05:46,580 --> 01:05:51,150
And how you got there was by doing good evolutionary psychology.

1026
01:05:51,310 --> 01:05:55,630
And it's hard to see how you could have gotten there without doing that kind of

1027
01:05:55,870 --> 01:05:57,710
evolutionary psychology.

1028
01:05:57,950 --> 01:05:58,270
Right?

1029
01:05:58,590 --> 01:05:59,870
Yeah, I mean I think that's fair.

1030
01:05:59,950 --> 01:06:02,430
I mean it's it's a uh yeah I'd say that's fair.

1031
01:06:02,510 --> 01:06:07,790
Aaron Powell So I I I consider that a big win for evolutionary psychology.

1032
01:06:07,950 --> 01:06:12,590
It is an empirical discovery that we did not know existed.

1033
01:06:13,000 --> 01:06:16,600
Doing this kind of evolutionary thinking resulted in this new discovery.

1034
01:06:16,680 --> 01:06:19,000
And it's an extremely important discovery.

1035
01:06:19,240 --> 01:06:24,200
We basically learned that this thing that we thought was an ineradicable part of the human

1036
01:06:24,200 --> 01:06:29,320
condition, which is racial categorization, uh, we we thought it was uh uh impossible to get

1037
01:06:29,320 --> 01:06:29,640
rid of.

1038
01:06:29,800 --> 01:06:34,650
And then here come the evolutionary psychologists saying, wait a second, the idea that we

1039
01:06:34,650 --> 01:06:38,890
would have uh evolved software for categorized by race makes no sense.

1040
01:06:38,970 --> 01:06:42,970
If you know anything about human evolutionary history, what makes way more sense is that we

1041
01:06:42,970 --> 01:06:45,290
would have alliance detection systems.

1042
01:06:45,530 --> 01:06:51,370
If you uh give cues of uh alliances that are more relevant than race,

1043
01:06:51,690 --> 01:06:55,290
we would expect the mind to categorize by alliance and not by race.

1044
01:06:55,370 --> 01:06:57,450
And lo and behold, we run the test.

1045
01:06:57,690 --> 01:07:00,730
Humans categorize by alliance and not by race.

1046
01:07:00,970 --> 01:07:05,140
We have eliminated the tendency to categorize by race.

1047
01:07:05,300 --> 01:07:08,500
The first paper that ran this test, I believe, was with sports teams.

1048
01:07:08,980 --> 01:07:12,580
They found that that racial categorization was eliminated.

1049
01:07:12,900 --> 01:07:14,900
They called the paper, Can Race Be Erased?

1050
01:07:15,140 --> 01:07:18,100
And of course, the answer that the paper gave was yes, it can.

1051
01:07:18,580 --> 01:07:24,420
So I I find this to be uh a really inspiring success story for

1052
01:07:24,420 --> 01:07:25,220
the field.

1053
01:07:25,370 --> 01:07:27,770
Uh, do you would you agree with that assessment?

1054
01:07:28,170 --> 01:07:34,170
Yeah, and I and to be I I sort of because it's my own research too, I sort of feel like uh

1055
01:07:34,330 --> 01:07:38,730
a bit, maybe it's false modesty, but I'm kind of like, what you know, there's still a lot

1056
01:07:38,730 --> 01:07:39,370
we don't know.

1057
01:07:39,690 --> 01:07:40,010
Yes.

1058
01:07:40,250 --> 01:07:44,730
Uh what one one thing that's really important to say because if people are thinking about

1059
01:07:44,730 --> 01:07:46,410
it, they might have this concern.

1060
01:07:46,570 --> 01:07:52,330
And I had many concerns, is um we know because of the

1061
01:07:52,330 --> 01:07:55,980
research, we know a lot about how this works.

1062
01:07:56,060 --> 01:07:57,820
So there's a couple things that are important to say.

1063
01:07:57,980 --> 01:08:03,820
One is if you do the exact same manipulation, but instead of

1064
01:08:03,820 --> 01:08:08,700
with race, you do it with sex or with age, which were the big three categories: age, sex,

1065
01:08:08,780 --> 01:08:09,100
and race.

1066
01:08:09,260 --> 01:08:15,180
So, in other words, you instead of crossing race with team, you cross sex with team,

1067
01:08:15,260 --> 01:08:18,940
meaning there's an equal number of men and women on each team, or there's an equal number

1068
01:08:18,940 --> 01:08:20,940
of old people and young people on each team.

1069
01:08:21,420 --> 01:08:21,980
Yeah.

1070
01:08:22,350 --> 01:08:27,070
Age and sex are not affected by the same manipulation.

1071
01:08:27,230 --> 01:08:31,390
And that's really important because you might think well, the reason why people are

1072
01:08:31,390 --> 01:08:37,390
reducing their categorization by race is because the mind is just shifting attention

1073
01:08:37,390 --> 01:08:39,310
from one category to another.

1074
01:08:39,550 --> 01:08:42,350
And so people can only keep track of one category.

1075
01:08:42,510 --> 01:08:47,560
But it turns out people have no trouble keeping track of alliance

1076
01:08:48,200 --> 01:08:51,480
and sex or alliance and age.

1077
01:08:51,720 --> 01:08:56,840
So it really seems to be that alliance is rival with race specifically.

1078
01:08:57,080 --> 01:09:01,720
And the idea for why we believe that is, and this is consistent with this idea, the data

1079
01:09:01,720 --> 01:09:07,240
are consistent with this hypothesis, is because, in fact, race is an instance of

1080
01:09:07,330 --> 01:09:07,810
alliance.

1081
01:09:07,970 --> 01:09:13,170
And the idea is that these this pattern of data is the prediction and

1082
01:09:13,170 --> 01:09:19,010
consistent with that idea that really, as far as the

1083
01:09:19,010 --> 01:09:23,730
mind treats it, race is an instance of an alliance cue.

1084
01:09:24,610 --> 01:09:29,170
There's another thing that's important too, which is that, and this is where the

1085
01:09:29,410 --> 01:09:35,250
evolutionary psychology is smarter than I am, like uh, is

1086
01:09:35,250 --> 01:09:40,240
that I also wanted to know well, how is racial categorization being reduced?

1087
01:09:40,720 --> 01:09:45,040
In memory literature, and it's a memory task, the who said what task is a memory task.

1088
01:09:45,120 --> 01:09:49,200
There's two different ways that information can be lost.

1089
01:09:49,360 --> 01:09:53,280
So if you're like studying for an exam and you forget it, or or if you know you don't know

1090
01:09:53,280 --> 01:09:54,000
the answer.

1091
01:09:54,240 --> 01:09:58,160
One one way is that the information was never encoded in the first place.

1092
01:09:58,320 --> 01:10:02,240
So, for example, you're just like you couldn't, you weren't paying enough attention.

1093
01:10:02,400 --> 01:10:04,880
You just stopped paying attention to race, for example, in this case.

1094
01:10:06,290 --> 01:10:10,690
The other possibility is that the racial information is encoded, but then it's not

1095
01:10:10,690 --> 01:10:12,770
retrieved during the task.

1096
01:10:13,010 --> 01:10:16,450
And I actually didn't know which two uh things it would be.

1097
01:10:16,530 --> 01:10:20,770
And there's a way to experimentally test between encoding versus recall.

1098
01:10:20,850 --> 01:10:26,130
So the question is: is the reduction happening at encoding or is it happening at a recall?

1099
01:10:27,320 --> 01:10:29,720
But there's a way to experimentally test between the two.

1100
01:10:29,800 --> 01:10:31,080
And I ran that study.

1101
01:10:31,240 --> 01:10:37,080
And what I found was that categorization by race was being encoded,

1102
01:10:37,160 --> 01:10:39,560
but it was being inhibited in the system.

1103
01:10:40,600 --> 01:10:44,200
And like there's a paper, you can people can look it up if they want you to know how you

1104
01:10:44,200 --> 01:10:44,520
know that.

1105
01:10:44,680 --> 01:10:47,640
But basically, those details are sort of kind of in the weeds.

1106
01:10:47,800 --> 01:10:53,330
But the point is that that's actually a really smart way for the system to work.

1107
01:10:53,410 --> 01:10:56,610
And that was actually something that I hadn't really thought about.

1108
01:10:56,770 --> 01:11:02,290
But the idea is that if there's an alliance queue that has a

1109
01:11:02,290 --> 01:11:08,290
high prior probability of being relevant across situations in your life,

1110
01:11:08,370 --> 01:11:12,850
and then all of a sudden you're faced with a particular context in which it's no longer

1111
01:11:12,850 --> 01:11:15,730
relevant, the system has two possibilities.

1112
01:11:15,890 --> 01:11:20,450
One is to encode the category, but not use it for this particular context.

1113
01:11:20,660 --> 01:11:23,780
And another is to just ignore the cue altogether.

1114
01:11:24,260 --> 01:11:29,380
And if you think about what a really well-designed system should do that's has the job of

1115
01:11:29,380 --> 01:11:34,820
tracking alliances, if there's a queue that's really high prior probability of being

1116
01:11:34,820 --> 01:11:40,260
relevant, but it's not relevant right now, then a really good system shouldn't code but

1117
01:11:40,260 --> 01:11:40,820
inhibit it.

1118
01:11:40,900 --> 01:11:41,860
We talk about it.

1119
01:11:42,340 --> 01:11:47,940
The expression was promiscuously encode but selectively retrieve these categories.

1120
01:11:48,100 --> 01:11:53,970
And so that was a nice example of sort of an empirically

1121
01:11:54,610 --> 01:12:00,210
generated insight into the design of a system that in retrospect sort of

1122
01:12:00,370 --> 01:12:06,050
uh is the way a well-designed system would have um, you know, uh would

1123
01:12:06,050 --> 01:12:06,690
appear.

1124
01:12:06,850 --> 01:12:10,850
But that's one where even I wasn't, I wasn't even being adaptationist enough about it.

1125
01:12:10,930 --> 01:12:15,200
You know, I was sort of, you know, and so this is a good example of the system is really

1126
01:12:15,520 --> 01:12:20,960
well designed for this function, to the point of even me, a hyper adaptationist,

1127
01:12:21,520 --> 01:12:23,360
wasn't giving it enough credit.

1128
01:12:23,520 --> 01:12:26,240
And it was like, no, no, no, I'm actually really smart here.

1129
01:12:26,320 --> 01:12:28,560
I'm gonna show you this additional design feature.

1130
01:12:29,120 --> 01:12:29,840
That's really cool.

1131
01:12:30,000 --> 01:12:33,280
I mean, so I mean, it it it makes sense, you know, on reflection.

1132
01:12:33,360 --> 01:12:37,040
So, like, let's say we have you know the habitat for humanity, and I don't know what the

1133
01:12:37,040 --> 01:12:37,520
other charity was.

1134
01:12:37,600 --> 01:12:39,360
Let's say it's the Make a Wish Foundation.

1135
01:12:39,550 --> 01:12:44,510
And uh so we have this strong cue that these two groups are in uh a cooperative

1136
01:12:44,510 --> 01:12:48,270
relationship uh with uh other members of of each group.

1137
01:12:48,430 --> 01:12:52,510
Um and so that's gonna be more relevant for this situation than race.

1138
01:12:52,670 --> 01:12:58,590
Um it would be very bad design if if if we just totally forgot about race because it's such

1139
01:12:58,590 --> 01:13:03,080
a relevant and enduring feature of modern social environments, it would be a bad idea to

1140
01:13:03,080 --> 01:13:05,880
completely uh dispense with it altogether, because you never know.

1141
01:13:06,040 --> 01:13:09,000
Maybe there could be a racial conflict between one of these organizations.

1142
01:13:09,160 --> 01:13:13,640
Maybe one uh you know African-American accuses the organization of uh discriminating

1143
01:13:13,640 --> 01:13:18,440
against him or her, or or or uh unfairly treating the black uh staff relative to the white

1144
01:13:18,440 --> 01:13:18,760
staff.

1145
01:13:18,920 --> 01:13:22,520
These issues could easily crop up as they do in workplaces around the country.

1146
01:13:22,680 --> 01:13:25,480
It would be very foolish to forget about race altogether.

1147
01:13:25,850 --> 01:13:30,490
What you want to do is keep the information online, keep it available, but just suppress it

1148
01:13:30,490 --> 01:13:34,250
because there's a more relevant cue right now in this particular situation.

1149
01:13:34,730 --> 01:13:35,130
That's right.

1150
01:13:35,210 --> 01:13:35,450
Yeah.

1151
01:13:35,610 --> 01:13:40,090
And so there's really two conclusions, and then we can maybe loop back to like our broader

1152
01:13:40,090 --> 01:13:42,810
point about why it's not just those stories.

1153
01:13:42,970 --> 01:13:48,730
The two conclusions are: this is evidence that even modern skulls

1154
01:13:49,480 --> 01:13:55,320
are showing the signature of a system that's well designed for an alliance tracking system.

1155
01:13:56,200 --> 01:14:01,640
And the idea that that's a long enduring ancestral adaptive problem

1156
01:14:02,440 --> 01:14:08,440
was the reason why those particular stimuli were created because the idea was if

1157
01:14:08,440 --> 01:14:13,240
that system exists, it should be sensitive to these inputs and should generate this output.

1158
01:14:13,400 --> 01:14:15,960
In this case, we we've so far just talked about categorization.

1159
01:14:16,040 --> 01:14:18,280
There's other outputs we could talk about, but anyway.

1160
01:14:18,440 --> 01:14:18,680
Yeah.

1161
01:14:19,170 --> 01:14:19,330
Yeah.

1162
01:14:19,410 --> 01:14:20,610
No, that's all fascinating.

1163
01:14:20,850 --> 01:14:25,490
And I I I will also add that this that this empirical work is really very much the tip of

1164
01:14:25,490 --> 01:14:26,130
the iceberg.

1165
01:14:26,290 --> 01:14:26,450
Yeah.

1166
01:14:26,690 --> 01:14:30,610
And in in in in terms of the additional empirical work that could be done.

1167
01:14:30,850 --> 01:14:32,930
So this is just uh scratching the surface.

1168
01:14:33,010 --> 01:14:36,450
I mean, yeah, it's like proof of concept.

1169
01:14:37,010 --> 01:14:38,370
So like it's it's incredibly mysterious.

1170
01:14:38,450 --> 01:14:44,060
You know, there are probably many do dozens of cues that are are used to track alliances.

1171
01:14:44,140 --> 01:14:47,740
Um, you just you know gave people a text-based description of you know which group was

1172
01:14:47,740 --> 01:14:51,020
cooperating with whom, but uh you could do further work on this.

1173
01:14:51,100 --> 01:14:55,100
You know, maybe dialect is important, uh, maybe dress is is important.

1174
01:14:55,500 --> 01:15:00,220
Um there are there are lots of really interesting predictions you could make about how the

1175
01:15:00,220 --> 01:15:06,110
alliance detection system is working and reverse engineering it um based on uh details of

1176
01:15:06,110 --> 01:15:11,070
the local context versus um other situations you might have encountered in the past, which

1177
01:15:11,310 --> 01:15:14,430
cues are going to be uh given higher priority when.

1178
01:15:14,670 --> 01:15:19,550
Um there's a lot of work to be done here of really nailing down the specifics of how this

1179
01:15:19,550 --> 01:15:21,630
alliance detection system works.

1180
01:15:21,950 --> 01:15:25,550
Yeah, and and and the inputs and that's the inputs and then there's other work in

1181
01:15:25,550 --> 01:15:30,040
psychology, some of which sort of inadvertently is getting at it too, like spatial

1182
01:15:30,040 --> 01:15:32,120
proximity and like who lives with who.

1183
01:15:32,600 --> 01:15:34,600
And I actually do have some work on accent too.

1184
01:15:34,680 --> 01:15:36,760
We could talk about that another time or not.

1185
01:15:37,560 --> 01:15:39,240
But uh but no, that's right.

1186
01:15:39,320 --> 01:15:41,880
And that's all on the input end, but then there's also the output end, right?

1187
01:15:41,960 --> 01:15:44,600
Which is that the the categorization is a byproduct.

1188
01:15:44,680 --> 01:15:46,440
It's not what the system evolved to do.

1189
01:15:46,600 --> 01:15:52,330
And so there's this whole other thing of um more ecologically

1190
01:15:52,330 --> 01:15:56,410
valid outputs, which is inferring who's going to behave, you know, how they're who's going

1191
01:15:56,410 --> 01:15:57,690
to support who in a conflict.

1192
01:15:57,770 --> 01:16:00,410
And my students and I are working on that as well.

1193
01:16:00,570 --> 01:16:01,210
But that's right.

1194
01:16:01,290 --> 01:16:06,890
The point is that all of a sudden you're moving from stuck with a behavioral

1195
01:16:06,890 --> 01:16:09,130
phenomenon, categorization by race.

1196
01:16:09,450 --> 01:16:12,730
We're standing on our heads trying to get it to change.

1197
01:16:12,970 --> 01:16:13,210
Yep.

1198
01:16:13,450 --> 01:16:18,730
And then coming at this from a different perspective, which is to not just be locked into

1199
01:16:19,780 --> 01:16:24,340
what can I just intuitively think of that might be relevant for categorization by race?

1200
01:16:24,580 --> 01:16:30,100
But to then come from this perspective of weirdly, we're not allowed to think there's a

1201
01:16:30,100 --> 01:16:31,460
system for categorization by race.

1202
01:16:31,540 --> 01:16:36,180
It's got to be a byproduct of another system because of an evolutionary history where race

1203
01:16:36,180 --> 01:16:37,060
was not present.

1204
01:16:37,220 --> 01:16:42,770
And because we're only allowed to stipulate that there would be software in the mind around

1205
01:16:42,770 --> 01:16:43,970
adaptive problems.

1206
01:16:44,210 --> 01:16:50,050
And then immediately the hypothesis based on an adaptive problem generated a prediction

1207
01:16:50,130 --> 01:16:51,410
and you get this result.

1208
01:16:51,570 --> 01:16:53,250
Now it might be oversimplified.

1209
01:16:53,330 --> 01:16:58,530
There might be a million adaptations in the social world, and this is just the first pass

1210
01:16:58,530 --> 01:17:00,850
at it, and it is still oversimplified.

1211
01:17:01,010 --> 01:17:06,450
But it's a really nice example of the just so story of

1212
01:17:07,170 --> 01:17:12,440
look, um, it's racial categorization is inevitable, right?

1213
01:17:12,520 --> 01:17:14,920
Because of our intrinsic tribalism.

1214
01:17:15,160 --> 01:17:20,600
Or even the just so story of it's not inevitable, it's a byproduct of our alliance

1215
01:17:20,600 --> 01:17:21,240
tracking.

1216
01:17:21,480 --> 01:17:27,320
The thing is, is that the sense in which these are not just so stories

1217
01:17:27,400 --> 01:17:30,840
is that they're making additional design predictions, right?

1218
01:17:31,080 --> 01:17:31,400
Yes.

1219
01:17:31,640 --> 01:17:36,650
Um even this, even the eyeglasses, and so there's this fanciful thing, Dr.

1220
01:17:36,730 --> 01:17:41,450
Pangloss, the Panglossing thing where, like, you know, the reason why we have a nose is to

1221
01:17:41,450 --> 01:17:42,890
hold up eyeglasses.

1222
01:17:43,450 --> 01:17:48,970
People one of the ways people care criticize adaptationism is to say,

1223
01:17:49,690 --> 01:17:51,610
is to use that example, right?

1224
01:17:51,770 --> 01:17:56,400
And to say, well, you're just obviously that's um stupid.

1225
01:17:56,560 --> 01:18:01,360
But the thing that I think is funny about that is they're being an adaptationist to make

1226
01:18:01,360 --> 01:18:06,080
that point, which is that it's very obvious that noses are not well designed to hold up

1227
01:18:06,080 --> 01:18:07,040
eyeglasses.

1228
01:18:07,280 --> 01:18:12,160
If I was gonna build something that was well designed to hold up eyeglasses, I wouldn't

1229
01:18:12,160 --> 01:18:17,120
make it sloped and greasy, um, such that you had to like have things around your ears,

1230
01:18:17,200 --> 01:18:17,440
right?

1231
01:18:17,520 --> 01:18:20,510
Like something well designed to hold up eyeglasses on your nose.

1232
01:18:20,590 --> 01:18:22,990
Like a nose is not designed to hold up eyeglasses well at all.

1233
01:18:23,150 --> 01:18:28,270
It's it's really eyeglasses are well designed to stay on noses, which are not designed well

1234
01:18:28,270 --> 01:18:29,230
to hold anything.

1235
01:18:29,390 --> 01:18:31,470
They're super slippery slopes, right?

1236
01:18:31,630 --> 01:18:36,910
Um, and so the point is when you make a claim about

1237
01:18:37,230 --> 01:18:42,700
something is for something, it makes predictions about how it should be

1238
01:18:42,700 --> 01:18:43,340
structured.

1239
01:18:43,580 --> 01:18:46,300
It makes new predictions in the future.

1240
01:18:46,620 --> 01:18:52,140
And what adaptationism is and why it's not a just so story

1241
01:18:52,380 --> 01:18:56,860
is that the logic of what follows from the claim about function.

1242
01:18:57,020 --> 01:19:02,460
For example, the function is not race per se, but it's about alliances that

1243
01:19:02,460 --> 01:19:08,030
predicts that the system should start to care about alliances that are not racial and

1244
01:19:08,030 --> 01:19:09,790
should stop caring about race.

1245
01:19:10,110 --> 01:19:15,870
So it's an example of claims about function make predictions, and that's why

1246
01:19:15,870 --> 01:19:17,790
it's not a just so story.

1247
01:19:18,270 --> 01:19:18,910
Yes.

1248
01:19:19,390 --> 01:19:23,150
Form follows function, is my mantra.

1249
01:19:23,470 --> 01:19:29,390
Um, and if you are trying to develop a theory of the form of the human mind, the

1250
01:19:29,390 --> 01:19:35,070
best way to do that is to come up with a good theory of what the function of

1251
01:19:35,180 --> 01:19:39,020
the human mind is or what the function of the part of the mind you're looking at is.

1252
01:19:39,340 --> 01:19:44,140
Once you have a good theory of what its function is, and that function is necessarily going

1253
01:19:44,140 --> 01:19:48,300
to be an evolutionary theory because evolution is the only source of antientropic

1254
01:19:48,300 --> 01:19:53,340
functional organization we know of, once you make a claim about function, all of a sudden

1255
01:19:53,340 --> 01:19:55,420
all the form falls into place.

1256
01:19:55,580 --> 01:20:00,940
You have a beautiful framework for predicting what form that system should take.

1257
01:20:01,340 --> 01:20:01,900
Right.

1258
01:20:02,250 --> 01:20:02,490
Yeah.

1259
01:20:02,570 --> 01:20:06,250
And I think in, you know, the racial categorization work, it's a nice example.

1260
01:20:06,330 --> 01:20:11,770
But then there's all this work on, for example, uh, work on anger, which is a really

1261
01:20:11,770 --> 01:20:13,050
important thing to understand.

1262
01:20:13,210 --> 01:20:18,410
And this approach has also an adaptationist approach has revolutionized our understanding

1263
01:20:18,410 --> 01:20:23,290
of anger, what elicits anger, what reduces anger, which is extremely important because

1264
01:20:23,290 --> 01:20:26,570
anger is the basis of a lot of domestic violence.

1265
01:20:26,730 --> 01:20:29,980
It's the basis of a lot of group based conflict.

1266
01:20:30,220 --> 01:20:35,820
Um things like um shame or pride, same same analysis.

1267
01:20:35,980 --> 01:20:39,820
Uh, David, your work on humor, another example, right?

1268
01:20:40,060 --> 01:20:45,420
Where um, you know, these these things that we phenomena we all know.

1269
01:20:45,740 --> 01:20:51,660
Um, you know, obviously we experience race, we experience shame or pride or things being

1270
01:20:51,660 --> 01:20:57,340
funny, but to then unpack the logic of it such that we can predict what is

1271
01:20:57,340 --> 01:21:01,990
funny or when people will feel shame or pride um or anger.

1272
01:21:02,150 --> 01:21:07,750
Um that's that I think is a really good example of the

1273
01:21:07,750 --> 01:21:09,350
power of this approach.

1274
01:21:09,510 --> 01:21:12,390
And it's we're just it's sort of just getting started.

1275
01:21:12,790 --> 01:21:13,590
Absolutely.

1276
01:21:13,830 --> 01:21:14,230
Yeah.

1277
01:21:14,310 --> 01:21:20,230
Uh it would be very difficult to try to understand how anger works or how pride or

1278
01:21:20,230 --> 01:21:26,150
shame works or how humor works without having any idea of what these things are for,

1279
01:21:26,720 --> 01:21:28,560
of what their function is.

1280
01:21:28,960 --> 01:21:34,960
Um and once you have a good idea of what their function is, all of a sudden you begin you

1281
01:21:34,960 --> 01:21:36,400
you're drowning in predictions.

1282
01:21:36,560 --> 01:21:41,280
That's some one of the things that uh really shocks me when people uh level this accusation

1283
01:21:41,280 --> 01:21:44,560
against evolutionary psychology that you know it doesn't make predictions or it's

1284
01:21:44,560 --> 01:21:45,920
unfalsifiable or whatever.

1285
01:21:46,160 --> 01:21:52,080
And in my experience as an evolutionary psychologist, uh doing work in this field, my

1286
01:21:52,080 --> 01:21:56,650
problem uh is not having a lack of hypotheses to test.

1287
01:21:56,890 --> 01:22:02,810
My problem is being overwhelmed with with predictions and hypotheses to test and just

1288
01:22:02,810 --> 01:22:07,770
being filled with deep sadness that there aren't enough hours in the day to go out and test

1289
01:22:07,770 --> 01:22:09,130
all these hypotheses.

1290
01:22:09,370 --> 01:22:12,170
That is really more is closer to my experience.

1291
01:22:12,410 --> 01:22:17,690
That it's really uh I'm so d I'm drowning in this stuff and I and I I need an army of

1292
01:22:17,690 --> 01:22:20,890
people to go out and do this research and that army isn't here.

1293
01:22:21,240 --> 01:22:21,480
Right.

1294
01:22:21,560 --> 01:22:21,800
Yes.

1295
01:22:22,040 --> 01:22:27,640
No, I mean, so I started teaching a grad class, even though UCSB is a really important

1296
01:22:27,880 --> 01:22:32,040
hub and one of the origin places of evolutionary psychology.

1297
01:22:32,200 --> 01:22:34,200
There had never been a graduate seminar in it.

1298
01:22:34,280 --> 01:22:38,040
And one of the things that I had done, I did in the graduate seminar, was have the graduate

1299
01:22:38,040 --> 01:22:39,800
students do a task analysis.

1300
01:22:40,040 --> 01:22:44,200
And we did task analyses of jealousy, um, other things.

1301
01:22:44,280 --> 01:22:49,270
Um and and basically would fill up a whiteboard and maybe we can talk a little bit about

1302
01:22:49,270 --> 01:22:54,230
what doing a task analysis means um maybe or we you know we can talk about that but

1303
01:22:54,230 --> 01:23:00,150
basically you know it's taking an adaptive problem like you know not starving to death

1304
01:23:00,230 --> 01:23:05,110
for example you know um or taking something like jealousy and then sort of saying well what

1305
01:23:06,060 --> 01:23:09,740
everybody sort of examine your intuitions or what you know about jealousy.

1306
01:23:09,820 --> 01:23:14,060
Like what kind of a um, you know, does it quack like a duck, does it sound like a duck,

1307
01:23:14,140 --> 01:23:15,020
does it swim like a duck?

1308
01:23:15,100 --> 01:23:15,500
That kind of thing.

1309
01:23:15,580 --> 01:23:16,140
Like what is it?

1310
01:23:16,220 --> 01:23:19,100
What uh what is jealousy compared to everything else?

1311
01:23:19,340 --> 01:23:24,940
And then at a certain point, it's characterizing that phenomenon like

1312
01:23:24,940 --> 01:23:28,810
jealousy or that adaptive problem like not starving to death.

1313
01:23:28,970 --> 01:23:34,330
And then just saying, well, what are all the design features that would be necessary,

1314
01:23:34,490 --> 01:23:36,410
almost sort of like in a robot, right?

1315
01:23:36,650 --> 01:23:42,090
To actually achieve, to successfully like navigate a world in which this is the

1316
01:23:43,210 --> 01:23:46,810
desirable outcome to navigate this thing, to not starve.

1317
01:23:47,050 --> 01:23:51,140
And then immediately, like if you just and we just fill up a whiteboard where you just sort

1318
01:23:51,140 --> 01:23:53,620
of say, well, like, okay, an organism needs to not starve.

1319
01:23:53,700 --> 01:23:55,220
Well, then it has to figure out, well, what's food?

1320
01:23:55,300 --> 01:23:55,860
Well, that's a problem.

1321
01:23:55,940 --> 01:23:57,140
Well, how does it know what's food?

1322
01:23:57,300 --> 01:24:00,740
You know, and maybe like it's koala bear, there's a template, but then maybe not.

1323
01:24:00,820 --> 01:24:04,980
And this is like part of Annie Wirtz's point, like for for humans who are extractive

1324
01:24:04,980 --> 01:24:07,620
foragers, who occupy a lot of different food niches.

1325
01:24:07,780 --> 01:24:11,860
We're omnivores, we don't have like any reliable cue, and so it's a social learning

1326
01:24:11,860 --> 01:24:12,100
problem.

1327
01:24:12,260 --> 01:24:16,740
So maybe there's social cues of like the adults around me are so are alive, they haven't

1328
01:24:16,740 --> 01:24:17,780
been poisoned to death.

1329
01:24:18,050 --> 01:24:20,850
They're so somehow like they've learned what's food.

1330
01:24:20,930 --> 01:24:26,210
And so the learning system, like the alliance tracking system, is a learning system for

1331
01:24:26,210 --> 01:24:30,450
tracking relationships of like, you know, literally what do people put in their mouth?

1332
01:24:30,530 --> 01:24:31,170
Okay, what is that?

1333
01:24:31,330 --> 01:24:35,570
Intent to that, remember that, extrapolate, like how where did that come from?

1334
01:24:35,730 --> 01:24:40,610
Um and you can just go through the list of like if you were going to build a robot that

1335
01:24:40,610 --> 01:24:46,360
could grow up and say, what Very hard.

1336
01:24:46,680 --> 01:24:49,960
Even even just the simple heuristic of eat what other people around you are eating.

1337
01:24:50,120 --> 01:24:54,680
If I'm a kid and I see my dad drinking coffee, which my daughter often does, she never

1338
01:24:54,680 --> 01:24:56,200
wants to t have a sip of my coffee.

1339
01:24:56,360 --> 01:24:57,160
She's not interested in it.

1340
01:24:57,480 --> 01:24:57,800
That's right.

1341
01:24:57,880 --> 01:25:01,880
And the extr and the in even the inference rule of like it was it that particular cup?

1342
01:25:02,040 --> 01:25:04,120
Is it anything that has that color, right?

1343
01:25:04,200 --> 01:25:08,680
This is the the the the the um Hume's problem of induction, right?

1344
01:25:08,760 --> 01:25:14,710
Or it's the uh the the Gavagai problem um in uh in philosophy, which

1345
01:25:14,710 --> 01:25:19,190
is that the referent or the the or the rule could be almost anything, right?

1346
01:25:19,270 --> 01:25:25,110
And so so even just not starving to death and then learning how to extract

1347
01:25:25,110 --> 01:25:28,790
things or forage and like you know, exerting them, you have to exert a certain number of

1348
01:25:28,790 --> 01:25:30,310
calories to like get food.

1349
01:25:30,470 --> 01:25:32,310
So there has to be a calculation for that.

1350
01:25:32,470 --> 01:25:35,430
There has to be a representation of when do I get this thing?

1351
01:25:35,670 --> 01:25:37,270
What's the processing to get it?

1352
01:25:37,430 --> 01:25:39,900
So there's this you know enormous problems.

1353
01:25:39,270 --> 01:25:39,510
problem.

1354
01:25:40,380 --> 01:25:41,340
How valuable is this food?

1355
01:25:41,420 --> 01:25:45,180
How much work should I be willing to expend to exactly.

1356
01:25:45,340 --> 01:25:51,260
And so, you know, modern environments where you have a whole industry of people sort

1357
01:25:51,260 --> 01:25:55,660
of pulling the levers of this psychology, like it's a very complicated psychology, and

1358
01:25:55,660 --> 01:25:58,540
that's why people can pull the levers on like highly processed food.

1359
01:25:58,620 --> 01:26:01,980
And it just you know turns off uh stop eating signals.

1360
01:26:02,140 --> 01:26:07,790
But like, but the idea is there's a really complicated machinery for For not

1361
01:26:07,790 --> 01:26:08,750
starving to death.

1362
01:26:08,910 --> 01:26:14,590
And if you map out that problem, or if the pro any other problem of like not losing status,

1363
01:26:14,670 --> 01:26:20,350
right, or competing in a status game, any any number of things, or coordinating about like

1364
01:26:20,350 --> 01:26:21,550
making a mistake.

1365
01:26:21,710 --> 01:26:27,600
Um, the second that you you think about what are all the entailments of this, you start

1366
01:26:27,600 --> 01:26:32,640
to populate the whiteboard figuratively and literally with a bunch of additional functions

1367
01:26:32,640 --> 01:26:33,920
and subfunctions.

1368
01:26:34,080 --> 01:26:39,360
And it really is the kind of thing where any one empirical project just gets at one or two

1369
01:26:39,360 --> 01:26:45,200
of these elements, but it would organize an entire career or a whole research discipline of

1370
01:26:45,200 --> 01:26:46,480
empirical work.

1371
01:26:46,720 --> 01:26:52,290
And I'm always struck with how little we know about any one of these functions and how

1372
01:26:52,290 --> 01:26:54,370
little empirical work there is on it.

1373
01:26:54,610 --> 01:27:00,610
So I completely agree with you that the

1374
01:27:00,610 --> 01:27:04,210
limiting problem is not predictions.

1375
01:27:04,370 --> 01:27:06,450
It's not knowing what to look for.

1376
01:27:09,240 --> 01:27:13,000
having a community of people to actually start to test these ideas.

1377
01:27:13,080 --> 01:27:17,080
And I would say to the extent they've been tested, for example, the shame, the guilt work,

1378
01:27:17,160 --> 01:27:22,840
the anger work, the racial categorization alliance work, uh, Annie's work on uh learning

1379
01:27:22,840 --> 01:27:25,560
about food and plants uh and children.

1380
01:27:25,720 --> 01:27:29,400
Um, I mean, you just uh name name the area.

1381
01:27:29,560 --> 01:27:32,360
It's just been extremely um fruitful.

1382
01:27:32,600 --> 01:27:38,530
Um And I think this is all uh uh examples of why

1383
01:27:38,530 --> 01:27:44,450
it's not a just so story and what it is positively, uh aside from sort of

1384
01:27:44,450 --> 01:27:48,770
addressing the negative ideas about what evolutionary psychology is.

1385
01:27:49,170 --> 01:27:51,090
Yeah, absolutely.

1386
01:27:52,210 --> 01:27:57,760
Um should we maybe take a look at one of those things you mentioned?

1387
01:27:58,000 --> 01:28:04,000
Either anger or shame or pride or humor, just to take a take a dive into one of those?

1388
01:28:04,240 --> 01:28:05,600
Yeah, what do you want to do?

1389
01:28:07,600 --> 01:28:08,880
All right, why don't we do anger?

1390
01:28:09,120 --> 01:28:10,240
Yeah, that's great.

1391
01:28:10,560 --> 01:28:12,000
Uh I I I love this work.

1392
01:28:12,080 --> 01:28:16,640
This is uh uh Aaron Sell uh and Leda Cosmodies and John Tubi have done work on this.

1393
01:28:16,880 --> 01:28:21,390
Um Aaron actually gave a talk at UCLA at our lab.

1394
01:28:21,870 --> 01:28:26,110
And he had a talk on the 12 triggers of anger.

1395
01:28:26,270 --> 01:28:27,310
Yes, that's 12.

1396
01:28:27,630 --> 01:28:32,110
So he had a bunch of participants just tell him stories, just submit stories of a time that

1397
01:28:32,110 --> 01:28:34,110
they were mad at somebody about something.

1398
01:28:34,350 --> 01:28:39,950
And he looked through all those stories and he was able to glean 12 distinct triggers that

1399
01:28:39,950 --> 01:28:41,390
commonly reemerged.

1400
01:28:42,030 --> 01:28:47,840
And he was able to dissect each anecdote um in in a way that was

1401
01:28:47,840 --> 01:28:49,360
so brilliant and inspiring.

1402
01:28:49,440 --> 01:28:54,560
Like I I am not aware of any social science theory that could look at a specific anecdote

1403
01:28:54,560 --> 01:29:00,000
of of human behavior and be able to explain each precise detail the way that he was able

1404
01:29:00,000 --> 01:29:00,160
to.

1405
01:29:00,480 --> 01:29:00,640
Yeah.

1406
01:29:00,800 --> 01:29:05,520
And to just and to just take a step back, the idea is not that, uh just to clarify for our

1407
01:29:05,520 --> 01:29:10,160
listeners, because I know this and you I know you know this, but uh it's not that Aaron was

1408
01:29:10,160 --> 01:29:11,840
sort of saying, well, I don't know how anger works.

1409
01:29:11,920 --> 01:29:17,870
I'm gonna just get surveys and then do a a um latent thing of like what clusters

1410
01:29:17,870 --> 01:29:18,830
in the surveys.

1411
01:29:18,990 --> 01:29:24,270
It was the complete opposite, where the idea was there are current theories of anger, some

1412
01:29:24,270 --> 01:29:26,590
of which are like things like he went through the list.

1413
01:29:26,670 --> 01:29:28,190
I mean, his dissertation is wonderful.

1414
01:29:28,270 --> 01:29:30,030
There's a lot of empirical work on this.

1415
01:29:30,270 --> 01:29:35,470
A good example, though, just to to just sort of give one example was frustration

1416
01:29:35,550 --> 01:29:36,030
aggression.

1417
01:29:36,110 --> 01:29:38,910
So the idea is that when your goals are blocked, you get angry.

1418
01:29:39,020 --> 01:29:41,340
And that seems like an intuitive, reasonable thing enough.

1419
01:29:41,500 --> 01:29:45,020
But Erin, Erin and I overlapped in the CP, and it was talking about this example.

1420
01:29:45,100 --> 01:29:47,580
And I give this in classes when I talk about this.

1421
01:29:48,220 --> 01:29:49,580
That predicts that.

1422
01:29:49,740 --> 01:29:55,660
So, for example, imagine you're driving and um somebody cuts you off in traffic.

1423
01:29:55,820 --> 01:29:59,260
Um, and uh, you know, imagine how angry you would be.

1424
01:29:59,340 --> 01:30:01,580
Or, like, let's say, even worse, a four-way stop.

1425
01:30:01,660 --> 01:30:05,900
You stop, and then somebody like doesn't stop and goes through the four-way stop sign.

1426
01:30:05,980 --> 01:30:07,580
Like, clearly their fault, right?

1427
01:30:07,750 --> 01:30:09,750
Just think about how angry you would be.

1428
01:30:10,390 --> 01:30:15,670
Now imagine that that car was just like, you know, uh Mercedes-Benz Silver convertible

1429
01:30:15,830 --> 01:30:17,510
versus was an ambulance.

1430
01:30:18,310 --> 01:30:18,870
Right.

1431
01:30:19,190 --> 01:30:19,510
Yeah.

1432
01:30:19,750 --> 01:30:23,990
There's a real difference in how much anger you feel between those two kinds of cars.

1433
01:30:24,230 --> 01:30:24,470
Yeah.

1434
01:30:24,630 --> 01:30:26,310
And they're both they're both thwarting your goals.

1435
01:30:26,470 --> 01:30:29,910
And that's exactly Aaron's point, is that they're both thwarting your goals.

1436
01:30:29,990 --> 01:30:34,390
And if the idea, the function of anger is that you get angry when your goals are thwarted,

1437
01:30:34,720 --> 01:30:39,200
then there's nothing in that theory that explains why the ambulance is different from the

1438
01:30:39,200 --> 01:30:41,840
um the Mercedes, right?

1439
01:30:42,080 --> 01:30:47,120
And Aaron's idea, I mean, do you want to do you want to give Aaron's I mean Aaron's idea?

1440
01:30:48,160 --> 01:30:48,720
Yeah.

1441
01:30:49,760 --> 01:30:55,200
Aaron's idea and David you you'll flesh it out even better is just that um

1442
01:30:56,160 --> 01:31:01,970
what anger is, is a set of adaptations for negotiating treatment

1443
01:31:01,970 --> 01:31:03,410
and how people treat one another.

1444
01:31:03,570 --> 01:31:08,770
So how much people trade off their welfare with each other is a really fundamental

1445
01:31:09,010 --> 01:31:09,890
important thing.

1446
01:31:10,050 --> 01:31:15,890
Um, meaning uh when we make decisions, we're deciding is the

1447
01:31:15,890 --> 01:31:17,570
thing I'm doing benefiting me?

1448
01:31:17,810 --> 01:31:19,970
Is it going to benefit somebody else?

1449
01:31:20,290 --> 01:31:26,160
And when there's rivalry between these two things, To what degree

1450
01:31:26,160 --> 01:31:28,400
do I trade off my welfare for their?

1451
01:31:28,560 --> 01:31:34,480
So, for example, my son, I am very willing to trade off my welfare for

1452
01:31:34,480 --> 01:31:35,280
his, right?

1453
01:31:35,920 --> 01:31:40,560
Um, so that's very different though than like a stranger, right?

1454
01:31:40,640 --> 01:31:42,880
So I would not be willing to do that.

1455
01:31:43,440 --> 01:31:49,410
And we have this trade off between your welfare and somebody

1456
01:31:49,410 --> 01:31:49,970
else's.

1457
01:31:50,130 --> 01:31:55,330
And Aaron's idea, and Lita and John and Daniel Schnitzer and other people have been doing

1458
01:31:55,330 --> 01:31:56,050
work on this.

1459
01:31:56,290 --> 01:32:01,330
The idea is that what anger is, is it's a program,

1460
01:32:02,130 --> 01:32:07,730
software in the mind for negotiating and bargaining for better

1461
01:32:07,730 --> 01:32:08,370
treatment.

1462
01:32:08,530 --> 01:32:14,040
So it detects situations in which you are

1463
01:32:14,680 --> 01:32:19,320
not being treated with the correct welfare trade-off.

1464
01:32:20,280 --> 01:32:25,320
And then it deploys a number of different strategies.

1465
01:32:25,560 --> 01:32:29,000
And those strategies are often relationship-dependent.

1466
01:32:29,160 --> 01:32:35,080
So, for example, if you are in a close relationship with somebody and they

1467
01:32:35,080 --> 01:32:40,630
do something that suggests that they're not taking your welfare into account well,

1468
01:32:41,510 --> 01:32:46,710
then the first step would be to like be motivated to find out why they did that thing.

1469
01:32:46,790 --> 01:32:49,990
That seems like they weren't treating you well because there can just be like, you know,

1470
01:32:50,310 --> 01:32:50,950
not another.

1471
01:32:51,190 --> 01:32:54,790
So so one example would be something like, I left the door open and your cat got out.

1472
01:32:54,950 --> 01:32:56,630
Maybe I didn't know you had a cat, right?

1473
01:32:56,790 --> 01:33:01,440
And so before you decide that I'm I'm a jerk, you should just be like, hey man, did you

1474
01:33:01,440 --> 01:33:02,880
know I have a cat and my cat got out?

1475
01:33:03,040 --> 01:33:06,320
Like it's a low benefit to you, a high cost to me, you know?

1476
01:33:06,480 --> 01:33:10,320
Um and and my reaction would be extremely different depending on what you said.

1477
01:33:10,480 --> 01:33:12,960
If you said, Oh, I'm so sorry, I didn't know you had a cat, my bad.

1478
01:33:13,040 --> 01:33:16,320
I'll next time I'll close the door, my anger would evaporate.

1479
01:33:16,400 --> 01:33:16,560
Right.

1480
01:33:16,720 --> 01:33:18,960
But if you said, uh, yeah, I know you had a cat, whatever, I don't care.

1481
01:33:19,200 --> 01:33:19,680
Yeah, exactly.

1482
01:33:19,760 --> 01:33:20,080
Yeah, yeah.

1483
01:33:20,400 --> 01:33:21,360
Forget about your cat.

1484
01:33:21,600 --> 01:33:26,080
So in in the idea is that this is again gets at this level of invariance thing, right?

1485
01:33:26,320 --> 01:33:32,270
Where it's there's benefits to me and cost to you, benefit of me of

1486
01:33:32,270 --> 01:33:34,830
opening the door, or just the cost to you of losing your cat.

1487
01:33:35,070 --> 01:33:40,990
And you want to see, look, is Dave not taking my interest into

1488
01:33:40,990 --> 01:33:41,550
account?

1489
01:33:41,790 --> 01:33:47,710
Do I need to change either how I treat him because he's a jerk, more of a jerk than I

1490
01:33:47,710 --> 01:33:48,030
thought?

1491
01:33:48,270 --> 01:33:54,190
Or do I need to let him know that this particular situation was a bigger cost than I'm

1492
01:33:54,190 --> 01:33:55,310
willing to put up with?

1493
01:33:55,470 --> 01:33:57,550
So I want to make sure he doesn't do it in the future.

1494
01:33:57,710 --> 01:33:57,950
Right.

1495
01:33:58,420 --> 01:34:03,460
And so that's that's sort of the underlying logic of anger.

1496
01:34:04,100 --> 01:34:09,860
And if we have a good relationship, it can be checking on that you know.

1497
01:34:10,100 --> 01:34:14,820
Well, sorry, if we have a good relationship, we're checking first, did you even know that

1498
01:34:14,820 --> 01:34:16,740
you were imposing a cost on me?

1499
01:34:17,940 --> 01:34:23,450
And then uh if we if I did, and I'm not sure

1500
01:34:23,690 --> 01:34:28,890
that I want to change my behavior, then David, your recourse can be

1501
01:34:28,890 --> 01:34:30,810
withdrawing cooperation.

1502
01:34:31,450 --> 01:34:37,290
So, so anybody who's in a romantic relationship will probably recognize this, where if you

1503
01:34:37,290 --> 01:34:43,290
know your partner is mad, what their partner looking like mad is not what a stranger

1504
01:34:43,290 --> 01:34:43,850
looks like mad.

1505
01:34:44,010 --> 01:34:47,450
What a partner looking like mad is just somebody with a stone face, right?

1506
01:34:47,610 --> 01:34:47,770
Yeah.

1507
01:34:47,930 --> 01:34:50,920
Like, and that's just a cue of withdrawing cooperation.

1508
01:34:51,160 --> 01:34:51,320
Yes.

1509
01:34:51,560 --> 01:34:57,240
Now, for somebody that doesn't have a relationship with you, then uh

1510
01:34:57,400 --> 01:35:00,360
the idea is that it's a threat to impose costs.

1511
01:35:00,520 --> 01:35:06,360
So looking angry, you know, and either social costs or physical costs, or at least the

1512
01:35:06,360 --> 01:35:07,320
threat of that.

1513
01:35:07,480 --> 01:35:13,430
Um, and the idea is that those costs we either of withdrawing benefits that

1514
01:35:13,430 --> 01:35:19,430
are currently existing or imposing new costs actively, um, is a way to

1515
01:35:19,430 --> 01:35:21,190
negotiate for better treatment.

1516
01:35:21,350 --> 01:35:25,270
And the idea is that this is the logic of that software.

1517
01:35:25,430 --> 01:35:31,270
So that's all the background to now David talking about the vignettes that Aaron

1518
01:35:31,270 --> 01:35:31,990
presented.

1519
01:35:32,150 --> 01:35:37,830
Um how Aaron was able to extract in a very detailed level,

1520
01:35:37,990 --> 01:35:39,110
um yeah.

1521
01:35:39,520 --> 01:35:40,160
Yes.

1522
01:35:40,400 --> 01:35:45,920
Um so first I I want to see if I can maybe do a quick summary of what you just said, just

1523
01:35:45,920 --> 01:35:48,800
in case it's still unclear for people in their heads.

1524
01:35:49,120 --> 01:35:54,960
So um when something uh makes me angry, um

1525
01:35:55,280 --> 01:36:01,120
there are four important things that are within that angering scenario.

1526
01:36:01,360 --> 01:36:07,310
The first is the benefit So let's say, let's take the example

1527
01:36:07,310 --> 01:36:10,110
of you leaving my door open and my cat running out.

1528
01:36:10,350 --> 01:36:16,270
Um so I'm representing how much that benefited you, Dave, to uh save a bit of time,

1529
01:36:16,350 --> 01:36:17,550
you know, closing the door.

1530
01:36:17,710 --> 01:36:17,790
Right.

1531
01:36:17,950 --> 01:36:20,830
How much does it benefit you to just be able to walk out without closing the door?

1532
01:36:20,990 --> 01:36:21,230
Okay.

1533
01:36:21,390 --> 01:36:23,630
That's the first part that the mind is representing.

1534
01:36:23,950 --> 01:36:29,220
The second part is the cost that was inflicted on me as a result of that action.

1535
01:36:29,460 --> 01:36:35,300
So how costly was it for me for my cat to run out of the door and for me to uh chase my cat

1536
01:36:35,300 --> 01:36:35,940
around?

1537
01:36:36,180 --> 01:36:36,820
Right.

1538
01:36:37,380 --> 01:36:40,660
The third part is the ratio between those two numbers.

1539
01:36:40,900 --> 01:36:46,900
Um so when anger happens, um, the benefit to Dave is

1540
01:36:46,900 --> 01:36:49,460
very small and the cost to me is very large.

1541
01:36:49,620 --> 01:36:51,140
I'll say that again.

1542
01:36:51,450 --> 01:36:57,370
When anger happens, the benefit to the person making you angry is small, and the cost to

1543
01:36:57,370 --> 01:36:59,290
you is large.

1544
01:36:59,610 --> 01:37:05,450
So if you inflict a huge cost on me in order to get a very small benefit for

1545
01:37:05,450 --> 01:37:08,570
yourself, that is going to piss me off.

1546
01:37:09,290 --> 01:37:09,610
Okay.

1547
01:37:10,970 --> 01:37:16,860
And once so I'm my mind is basically trying to figure out what that ratio is.

1548
01:37:17,020 --> 01:37:18,060
What's the benefit to you?

1549
01:37:18,140 --> 01:37:19,100
What's the cost to me?

1550
01:37:19,340 --> 01:37:22,940
If it is too low, then anger gets activated.

1551
01:37:23,100 --> 01:37:29,020
And what anger is, is a way for me to uh without neurosurgery, changing that ratio

1552
01:37:29,020 --> 01:37:29,580
in your head.

1553
01:37:29,740 --> 01:37:29,980
Correct.

1554
01:37:30,220 --> 01:37:36,220
So that um you are no longer willing to impose those costs on me at that exchange rate

1555
01:37:36,220 --> 01:37:38,590
to yourself, so that you treat me better in the future.

1556
01:37:38,750 --> 01:37:42,830
So the idea is that we all have these ratios in our head for every person in our life.

1557
01:37:42,990 --> 01:37:47,790
We have a level of cost that we're willing to inflict at them for a level of benefit we're

1558
01:37:47,790 --> 01:37:48,750
willing to receive.

1559
01:37:48,910 --> 01:37:49,230
Okay.

1560
01:37:49,550 --> 01:37:52,590
And the idea is we have to have these ratios, otherwise, we wouldn't be able to make

1561
01:37:52,590 --> 01:37:53,470
decisions.

1562
01:37:53,950 --> 01:37:58,990
So everyone we have, everyone in our lives, we have a welfare trade-off ratio.

1563
01:37:59,390 --> 01:38:04,740
Um and what anger is, is a way of uh trying to

1564
01:38:04,740 --> 01:38:08,340
recalibrate someone else's welfare trade off ratio toward you.

1565
01:38:08,420 --> 01:38:13,620
So let's say yours toward me is say one one over four, and I think that's too low.

1566
01:38:13,860 --> 01:38:18,020
What anger is doing is I'm trying to get that up to a one over three or a one over two or

1567
01:38:18,100 --> 01:38:23,860
or whatever I think is the correct or uh justifiable ratio or the the ratio

1568
01:38:23,860 --> 01:38:29,490
that I deserve based on a variety of factors like my social status or or how kind I am to

1569
01:38:29,490 --> 01:38:32,290
you or or or history as friends or whatever.

1570
01:38:32,770 --> 01:38:34,290
So that's what anger is.

1571
01:38:34,450 --> 01:38:40,210
Um it's a way of recalibrating uh other people's uh welfare trade-off ratios toward

1572
01:38:40,210 --> 01:38:43,250
you um without doing neurosurgery.

1573
01:38:43,410 --> 01:38:47,010
Um and and the way you do that is by threatening to inflict costs.

1574
01:38:47,090 --> 01:38:49,650
So if you don't change, if you don't treat me better, if you don't change your welfare

1575
01:38:49,810 --> 01:38:54,420
trade-off ratio, I'm gonna punch you um, or I'm gonna uh or I'm gonna withhold benefits,

1576
01:38:54,500 --> 01:38:55,780
I'm gonna stop talking to you.

1577
01:38:55,940 --> 01:38:59,220
I'm going to stop uh sharing my food with you, whatever.

1578
01:38:59,380 --> 01:39:04,100
Uh it's these are these are attempts to inflict costs or withhold benefits, uh uh

1579
01:39:04,340 --> 01:39:09,620
conditional on the person um recalibrating their welfare trade-off ratio and expressing

1580
01:39:09,620 --> 01:39:14,740
that they've recalibrated it through an apology or a show of guilt, the function of which

1581
01:39:14,740 --> 01:39:19,540
is to change your um welfare trade-off ratio towards someone who you've wronged so that you

1582
01:39:19,540 --> 01:39:21,140
treat them better in the future.

1583
01:39:22,030 --> 01:39:22,350
Okay.

1584
01:39:22,990 --> 01:39:28,830
Um there's one beautiful example that uh Aaron gives, which is that imagine uh

1585
01:39:28,910 --> 01:39:33,310
Dave and I are uh eating uh French fries together.

1586
01:39:33,630 --> 01:39:38,350
Um and uh Dave has a bit of ketchup on his lip.

1587
01:39:38,590 --> 01:39:42,270
And we're both we're we're we're wearing beautiful uh nice suits.

1588
01:39:42,510 --> 01:39:48,190
And uh Dave reaches across the table and takes my beautiful nice tie and wipes the ketchup

1589
01:39:48,510 --> 01:39:50,510
off his face with my tie.

1590
01:39:50,920 --> 01:39:51,800
True story.

1591
01:39:52,520 --> 01:39:53,320
This actually happened?

1592
01:39:53,480 --> 01:39:54,040
No, I'm kidding.

1593
01:39:54,360 --> 01:39:55,000
No, no, no, no.

1594
01:39:55,400 --> 01:39:57,000
I I'm this might have happened to Aaron.

1595
01:39:57,240 --> 01:39:57,480
I don't know.

1596
01:39:59,000 --> 01:40:03,320
What's so beautiful about that is that it's it's it's the perfect angering scenario.

1597
01:40:03,560 --> 01:40:09,000
The benefit to you of wiping the ketchup off your face is so small.

1598
01:40:09,240 --> 01:40:12,040
You could have easily just gotten a napkin.

1599
01:40:12,120 --> 01:40:12,360
Yeah.

1600
01:40:12,600 --> 01:40:17,210
And and the and the cost to me, if you're ruining my tie, is huge.

1601
01:40:17,370 --> 01:40:19,450
The ratio is so out of whack there.

1602
01:40:19,530 --> 01:40:19,610
Yeah.

1603
01:40:20,010 --> 01:40:22,650
I would be so pissed off if you did that.

1604
01:40:22,890 --> 01:40:23,130
Yeah.

1605
01:40:23,210 --> 01:40:28,090
It's it's a great, it's I love about it that examples really just, you know, like saying

1606
01:40:28,090 --> 01:40:32,010
the abstract logic sounds really stilted and weird and foreign.

1607
01:40:32,330 --> 01:40:36,730
But then the second you give examples, uh, like like the door thing, right?

1608
01:40:36,810 --> 01:40:38,570
Like I left the cat, I let your cat go out.

1609
01:40:38,650 --> 01:40:44,580
Well, what if like, you know, I had like severed my like artery was running out the door.

1610
01:40:44,740 --> 01:40:46,340
You wouldn't you wouldn't think twice.

1611
01:40:46,580 --> 01:40:49,300
You wouldn't be angry at all about me leaving the door open.

1612
01:40:49,700 --> 01:40:55,460
Because it was it was a super uh I mean I was there was there it was super

1613
01:40:55,460 --> 01:40:59,620
high benefit to me um to to just go out the door, right?

1614
01:40:59,780 --> 01:41:04,020
Um and so you wouldn't care at all about the fact that your cat, I mean you might be, but

1615
01:41:04,020 --> 01:41:05,700
you're gonna be angry at me, you know.

1616
01:41:05,780 --> 01:41:08,980
But if I was just like no good reason, then it would be very different.

1617
01:41:09,270 --> 01:41:09,430
Right.

1618
01:41:09,510 --> 01:41:13,270
So in that scenario, you would have three different strategies for diffusing my anger.

1619
01:41:13,510 --> 01:41:17,750
The first one would be to highlight how the benefit to you was actually much larger than I

1620
01:41:17,750 --> 01:41:18,070
thought.

1621
01:41:18,230 --> 01:41:21,830
So I didn't know that you were you know gushing blood and you were rushing out the door.

1622
01:41:21,990 --> 01:41:26,070
Had I known that, then the benefit of you uh of getting to the hospital quicker and not

1623
01:41:26,070 --> 01:41:28,310
having to close the door, that was actually a pretty big benefit.

1624
01:41:28,390 --> 01:41:30,630
And it's probably worth it for you to not close the door.

1625
01:41:30,870 --> 01:41:33,910
So in that case, your welfare trade off ratio toward me was fine.

1626
01:41:33,990 --> 01:41:35,350
It's fine that you didn't close the door.

1627
01:41:35,510 --> 01:41:37,240
It was a really big benefit to you.

1628
01:41:37,560 --> 01:41:37,880
That's right.

1629
01:41:37,960 --> 01:41:39,080
I'm not the kind of that's right.

1630
01:41:39,160 --> 01:41:43,320
I'm not the kind of person who wouldn't ordinarily like take your cats into account, but

1631
01:41:43,400 --> 01:41:44,520
man, like I was dying.

1632
01:41:44,680 --> 01:41:44,840
Yeah.

1633
01:41:44,920 --> 01:41:45,160
Exactly.

1634
01:41:45,560 --> 01:41:45,880
Exactly.

1635
01:41:45,960 --> 01:41:46,280
Exactly.

1636
01:41:46,520 --> 01:41:48,440
So that's one w strategy you could use.

1637
01:41:48,920 --> 01:41:53,400
The other strategy is to say that the cost inflicted on me actually wasn't that great or

1638
01:41:53,400 --> 01:41:54,360
what wasn't that huge.

1639
01:41:54,440 --> 01:41:55,000
And you knew that.

1640
01:41:55,080 --> 01:41:58,490
So like yeah your cat always runs uh out the door and always comes back.

1641
01:41:58,570 --> 01:41:59,690
It's never it's never a big deal.

1642
01:41:59,770 --> 01:42:00,410
Like, who cares?

1643
01:42:00,490 --> 01:42:02,170
Why are you getting so bent up about this?

1644
01:42:02,490 --> 01:42:02,650
Right.

1645
01:42:02,810 --> 01:42:06,570
That's another strategy that it wasn't that big of a cost to me, so I should chill out

1646
01:42:06,570 --> 01:42:07,210
about it.

1647
01:42:07,610 --> 01:42:12,410
Uh, and the third strategy you could use is ignorance that you did just didn't know.

1648
01:42:12,570 --> 01:42:13,930
You didn't know how big of a cost.

1649
01:42:14,250 --> 01:42:17,850
You didn't know I had a cat, or you didn't know that the cat has you know run away in the

1650
01:42:17,850 --> 01:42:22,170
past and has caused me a lot of stress and and pain, or or whatever.

1651
01:42:22,250 --> 01:42:27,580
Um, and in that case, your behavior is not reflecting your true welfare trade-off ratio

1652
01:42:27,580 --> 01:42:28,220
toward me.

1653
01:42:28,300 --> 01:42:30,860
Um, had you known, you would have acted differently.

1654
01:42:31,020 --> 01:42:33,580
So this is the your apparent behavior is misleading.

1655
01:42:33,660 --> 01:42:36,700
It was a product of of you not knowing and you being uninformed.

1656
01:42:36,860 --> 01:42:40,940
So those three strategies, if successful, could diffuse my anger.

1657
01:42:41,980 --> 01:42:43,340
Um, okay.

1658
01:42:44,220 --> 01:42:46,060
Um, other examples.

1659
01:42:46,220 --> 01:42:51,420
So uh Aaron, when he came in, he gave tons of vignettes of real vignettes, real things that

1660
01:42:51,420 --> 01:42:52,300
happen to people.

1661
01:42:52,490 --> 01:42:57,850
And he was able to identify the benefit to the person, the cost inflicted on the

1662
01:42:57,850 --> 01:43:03,850
aggrieved party, whether it was too high or too low, whether it was intentional or not,

1663
01:43:04,010 --> 01:43:09,290
whether the person knew the ext magnitude of the cost or the or the benefit that they would

1664
01:43:09,290 --> 01:43:10,010
be receiving.

1665
01:43:10,170 --> 01:43:15,700
And he was able to just dissect each individual scenario in a way that was so beautiful and

1666
01:43:15,700 --> 01:43:16,340
inspiring.

1667
01:43:16,820 --> 01:43:22,740
And it it was also beautiful in the way that it was so specific that it's not merely

1668
01:43:22,740 --> 01:43:25,700
behavior that anger is directed at.

1669
01:43:25,940 --> 01:43:30,900
So anger isn't about your actions, it's about a number in your head.

1670
01:43:30,980 --> 01:43:36,020
It's about the ratio in your head, and it is exquisitely fine-tuned to that ratio and not

1671
01:43:36,020 --> 01:43:37,540
to your overt behavior.

1672
01:43:37,810 --> 01:43:41,810
So a beautiful example that he gave, uh, this is a real example from someone's life.

1673
01:43:41,970 --> 01:43:47,970
Um, so um uh a woman and her boyfriend, and um they have had previous

1674
01:43:47,970 --> 01:43:51,570
interactions where the boyfriend has insulted her driving ability.

1675
01:43:51,730 --> 01:43:55,570
So she the boyfriend is constantly giving her shit for being a shitty driver, right?

1676
01:43:56,050 --> 01:43:57,570
Or he perceives her as a shitty driver.

1677
01:43:58,050 --> 01:43:59,490
He perceives her as a shitty driver.

1678
01:43:59,810 --> 01:44:05,570
Um, and because our welfare trade off ratio depends on how much we value the person, you

1679
01:44:05,700 --> 01:44:08,740
know, if the if the boyfriend thinks she's a shitty driver, he's he's gonna have a lower

1680
01:44:08,740 --> 01:44:13,300
welfare trade-off ratio toward her and not treat her as as as well as he otherwise would.

1681
01:44:13,540 --> 01:44:17,380
So that that in and of itself could be a could be a problem that would make her angry.

1682
01:44:17,620 --> 01:44:23,620
Um so in this scenario, um, she uh misses the exit and cuts someone

1683
01:44:23,620 --> 01:44:26,980
off in in traffic and you know almost gets into an accident.

1684
01:44:27,460 --> 01:44:33,300
And um the boyfriend doesn't even say anything, doesn't even do

1685
01:44:33,620 --> 01:44:34,420
anything.

1686
01:44:34,580 --> 01:44:35,060
Yeah.

1687
01:44:35,370 --> 01:44:37,290
And she says, don't.

1688
01:44:37,770 --> 01:44:39,930
And she got mad at the boyfriend at that moment.

1689
01:44:40,090 --> 01:44:40,250
Sure.

1690
01:44:40,410 --> 01:44:42,490
Because she because she knew what he was thinking.

1691
01:44:42,730 --> 01:44:43,130
Yeah.

1692
01:44:43,290 --> 01:44:43,610
Yeah.

1693
01:44:43,770 --> 01:44:44,330
Yeah.

1694
01:44:44,570 --> 01:44:46,170
So he didn't do anything at all.

1695
01:44:46,410 --> 01:44:48,970
There the anger was not caused by any overt behavior.

1696
01:44:49,050 --> 01:44:54,090
It was caused by a belief about what was going on inside his head.

1697
01:44:54,330 --> 01:44:54,890
That's right.

1698
01:44:55,130 --> 01:44:59,850
Which is such a beautiful example of the specificity of this emotion.

1699
01:45:00,020 --> 01:45:00,260
Yeah.

1700
01:45:00,500 --> 01:45:05,140
That it's designed to pick up on something inside the other person's head about how much

1701
01:45:05,140 --> 01:45:06,340
they value you.

1702
01:45:06,500 --> 01:45:10,820
Um and if it's too low and they're not valuing you high enough, you're gonna get angry.

1703
01:45:10,980 --> 01:45:11,620
Yeah.

1704
01:45:12,100 --> 01:45:13,780
Um so that was my favorite example.

1705
01:45:13,860 --> 01:45:15,460
Uh there are other others that I can't remember.

1706
01:45:15,780 --> 01:45:20,100
Yeah, but but but it sounds like what you're saying is that you know, a way a way to put it

1707
01:45:20,100 --> 01:45:21,300
is there's a grammar.

1708
01:45:21,620 --> 01:45:26,980
So there's Erin, this idea of taking the adaptive problem of how people treat one another,

1709
01:45:27,310 --> 01:45:31,710
understanding that it's a long-standing problem, understanding that there is a level of

1710
01:45:31,710 --> 01:45:37,470
specificity where there are commonalities, there are invariances like cost, benefit, the

1711
01:45:37,470 --> 01:45:42,190
person not holding a high enough regard for your welfare, check to see if they understood

1712
01:45:42,190 --> 01:45:42,350
it.

1713
01:45:42,510 --> 01:45:43,870
Are they ignorant or not?

1714
01:45:44,110 --> 01:45:45,150
Do I negotiate?

1715
01:45:45,310 --> 01:45:49,950
Do I need to impose a cost, withdraw benefits, impose active costs?

1716
01:45:50,190 --> 01:45:54,670
These are all the things that are common across individuals, across time, across

1717
01:45:54,670 --> 01:45:56,980
generations that are built into the software.

1718
01:45:57,060 --> 01:46:03,060
And by thinking about all of those invariances, Aaron was able

1719
01:46:03,060 --> 01:46:09,060
to sort of create a grammar, a social grammar, if you will, that then

1720
01:46:10,020 --> 01:46:13,620
was common in all of these vignettes.

1721
01:46:13,700 --> 01:46:19,690
And you could look at the vignette and go in and really lift out in each case

1722
01:46:19,850 --> 01:46:25,050
the reason why somebody is saying this thing is because they're trying to communicate that

1723
01:46:25,050 --> 01:46:30,330
the cost wasn't so great, as in like the cat really didn't go very far, or I had a huge

1724
01:46:30,330 --> 01:46:34,490
benefit because you know I was bleeding and I needed to actually like get out the door, I

1725
01:46:34,490 --> 01:46:35,130
would die.

1726
01:46:35,450 --> 01:46:40,970
Um and so again, it comes back to this thing of if you have a theory of function,

1727
01:46:42,580 --> 01:46:48,260
It reduces down all of the complexities and all of the noise

1728
01:46:48,500 --> 01:46:54,100
and blooming, buzzing confusion, sort of uh of the data.

1729
01:46:54,340 --> 01:46:54,500
Yes.

1730
01:46:54,740 --> 01:47:00,740
And then you can really compactly and economically describe when

1731
01:47:00,900 --> 01:47:06,820
somebody's angry, what they will do, in the same way you can compactly describe sort of how

1732
01:47:06,820 --> 01:47:08,180
a plant will grow towards light.

1733
01:47:08,260 --> 01:47:10,020
Is that sort of the point?

1734
01:47:10,660 --> 01:47:11,220
Yes.

1735
01:47:11,410 --> 01:47:11,810
Yes.

1736
01:47:11,970 --> 01:47:12,690
Well put.

1737
01:47:12,930 --> 01:47:13,570
Yeah.

1738
01:47:14,130 --> 01:47:17,330
So I think the so the anger thing is a really great example.

1739
01:47:17,410 --> 01:47:21,170
So I think both the anger thing and the racial categorization thing are really nice

1740
01:47:21,170 --> 01:47:27,010
examples of taking uh a phenomenon we already know about.

1741
01:47:27,250 --> 01:47:27,650
Mm-hmm.

1742
01:47:27,970 --> 01:47:29,890
Anger, racial categorization.

1743
01:47:30,050 --> 01:47:32,450
I mean, people have been studying anger for for decades.

1744
01:47:32,610 --> 01:47:34,130
There were different theories of anger.

1745
01:47:34,530 --> 01:47:36,690
People have been studying racial categorization for decades.

1746
01:47:36,770 --> 01:47:39,410
There are many theories about why that was happening.

1747
01:47:39,650 --> 01:47:45,580
Um, and you know the you even really smart people,

1748
01:47:46,140 --> 01:47:50,060
you know, um it's not enough to just be smart.

1749
01:47:50,220 --> 01:47:52,780
You have to think about what the thing is for.

1750
01:47:52,940 --> 01:47:57,660
It's to take an artifact analogy, like if you don't know what a car is for, you can be

1751
01:47:57,660 --> 01:48:00,540
really smart, but you can come at it the wrong way.

1752
01:48:00,780 --> 01:48:06,710
And I'm not it's not saying that anyone approaches right, and and there are there can be

1753
01:48:06,710 --> 01:48:10,950
wrong evolutionarily informed hypotheses, but that's fine because you're at least narrowing

1754
01:48:10,950 --> 01:48:11,990
down the possibilities.

1755
01:48:12,150 --> 01:48:17,350
But in these cases, this welfare trade-off and this alliance tracking

1756
01:48:17,990 --> 01:48:23,110
idea really cut through all the confusion surrounding these

1757
01:48:23,510 --> 01:48:24,070
phenomena.

1758
01:48:24,150 --> 01:48:27,190
And these are just two examples sort of off the top of our head.

1759
01:48:27,590 --> 01:48:28,230
Yes.

1760
01:48:29,080 --> 01:48:35,080
The m one of the main benefits I see to doing this kind of task analysis, reverse

1761
01:48:35,080 --> 01:48:41,000
engineering, um adaptationism, whatever you want to call it, is that it really constrains

1762
01:48:41,000 --> 01:48:45,720
the hypothesis space once you start thinking in this way.

1763
01:48:46,040 --> 01:48:51,720
So if you're gonna do a good task analysis of an adaptive problem uh that our

1764
01:48:51,720 --> 01:48:57,000
hunter-gatherer ancestors uh would have reliably faced throughout our evolutionary history,

1765
01:48:57,510 --> 01:49:02,950
uh, and you're and you're going to posit a cognitive system that evolved in response to

1766
01:49:02,950 --> 01:49:07,270
this selection pressure, and you're going to test for the existence of that cognitive

1767
01:49:07,270 --> 01:49:07,590
system.

1768
01:49:08,150 --> 01:49:13,990
Already you have wiped away 99.99% of all

1769
01:49:13,990 --> 01:49:18,360
the possible hypotheses you could have about the thing you were studying.

1770
01:49:18,520 --> 01:49:23,160
So, like right off the bat, um, I'm I'm positing an adaptive problem our ancestors would

1771
01:49:23,160 --> 01:49:23,960
have likely faced.

1772
01:49:24,040 --> 01:49:28,920
That screens out tons of hypotheses because there were lots of things, like uh racial

1773
01:49:28,920 --> 01:49:32,360
groups, that our ancestors would not have plausibly encountered.

1774
01:49:32,600 --> 01:49:37,240
And so, right off the bat, that suggests that any adaptation for racial categorization is

1775
01:49:37,240 --> 01:49:38,120
implausible.

1776
01:49:38,280 --> 01:49:40,840
We should not explore that hypothesis.

1777
01:49:41,160 --> 01:49:41,560
Right?

1778
01:49:41,800 --> 01:49:42,360
Right.

1779
01:49:42,840 --> 01:49:48,470
So right off the bat you have constraints about what the ancestral environment would have

1780
01:49:48,470 --> 01:49:52,630
plausibly been like, what kinds of challenges our ancestors would have likely faced.

1781
01:49:52,870 --> 01:49:56,070
Um another Yeah, can I just inter interrupt really quick?

1782
01:49:56,390 --> 01:49:59,670
One thing I think that's really important to say, because I can imagine people listening

1783
01:49:59,830 --> 01:50:04,630
thinking this, and it's an important thing to say, is people often say, Well, we don't

1784
01:50:04,630 --> 01:50:06,310
know, we can't know for certain.

1785
01:50:06,550 --> 01:50:12,220
But that that is exactly like the um uh criticism of uh

1786
01:50:12,460 --> 01:50:15,100
just so stories because the nose is poorly designed.

1787
01:50:15,180 --> 01:50:21,020
It uses the principle to reject the principle, which is of course we can't know

1788
01:50:21,020 --> 01:50:22,220
certain things for certain.

1789
01:50:22,300 --> 01:50:26,460
So that's why you are always thinking for the thing that you're most certain about.

1790
01:50:26,620 --> 01:50:31,420
We can be certain that alliances were present over evolutionary time.

1791
01:50:31,550 --> 01:50:34,270
The idea that there was a particular kind of alliance is less certain.

1792
01:50:34,350 --> 01:50:37,230
It might still be more certain than like even something less certain.

1793
01:50:37,550 --> 01:50:43,390
But the idea is that we're constantly criticizing our thinking

1794
01:50:43,710 --> 01:50:49,310
and trying to describe things in a way that would be the most certain.

1795
01:50:49,550 --> 01:50:49,870
Yes.

1796
01:50:50,110 --> 01:50:54,030
That you can't get at if you just ignore the issue altogether.

1797
01:50:54,190 --> 01:50:57,710
So when people sort of say, well, you can't know anything about the evolutionary past,

1798
01:50:58,240 --> 01:51:03,360
often what they were saying then is that we shouldn't even think about how likely it is

1799
01:51:04,080 --> 01:51:07,280
that there were certain selection pressures as opposed to others.

1800
01:51:07,440 --> 01:51:12,480
But that's the exact opposite of their own point, which is that we should actually just try

1801
01:51:12,480 --> 01:51:16,400
to stay in the range of things like where can we pre certain people impose costs on each

1802
01:51:16,400 --> 01:51:19,520
other or confer benefits, you know, and needed to negotiate that.

1803
01:51:19,600 --> 01:51:20,720
There's the anger thing.

1804
01:51:20,960 --> 01:51:22,240
That's very likely.

1805
01:51:22,480 --> 01:51:27,510
So I just want to point out that yes, weirdly, people will often say things like, Well, we

1806
01:51:27,510 --> 01:51:33,510
can't know anything with certainty, and then therefore, any attempt to be more or less

1807
01:51:33,510 --> 01:51:35,270
certain is is hopeless.

1808
01:51:35,430 --> 01:51:37,270
That second thing doesn't follow at all.

1809
01:51:37,430 --> 01:51:42,390
So I just I don't want to interrupt too much, but I want to say that important, yeah.

1810
01:51:42,870 --> 01:51:43,990
Crucial point, yeah.

1811
01:51:44,150 --> 01:51:49,880
We want to build our evolutionary theories off of things that are most certain.

1812
01:51:50,040 --> 01:51:54,120
To the extent that we're building our theories on a on a shaky foundation of uncertain

1813
01:51:54,120 --> 01:51:59,480
premises about our evolutionary past, well, that should cause us to doubt the hypothesis,

1814
01:51:59,640 --> 01:52:01,640
the more uncertain that that premise is.

1815
01:52:01,720 --> 01:52:02,200
That's right.

1816
01:52:09,720 --> 01:52:15,320
Insofar as we're building our theories on foundations or on assumptions that we're not sure

1817
01:52:15,320 --> 01:52:18,350
about, that should weaken our confidence in the theory?

1818
01:52:18,510 --> 01:52:23,870
So the anger stuff is based on some pretty plausible assumptions that there were people in

1819
01:52:23,870 --> 01:52:28,510
the ancestral environment and they could have imposed costs on us uh in order to benefit

1820
01:52:28,510 --> 01:52:30,910
themselves, and they likely did in various ways.

1821
01:52:31,230 --> 01:52:35,470
That is a pretty that is that's pretty hard to deny that that was a feature of ancestral

1822
01:52:35,630 --> 01:52:36,670
environments, right?

1823
01:52:36,830 --> 01:52:40,190
We know that our ancestors were social, we know that other primates are social, we know

1824
01:52:40,190 --> 01:52:44,190
that humans are intensely social, and simply by existing in the world, humans have

1825
01:52:44,190 --> 01:52:49,200
opportunities to inflict costs on one another, and there would have been selection pressure

1826
01:52:49,200 --> 01:52:50,880
for minimizing those costs.

1827
01:52:51,120 --> 01:52:56,480
Okay, so that theory is resting on a pretty solid foundation on uh what uh ancestral

1828
01:52:56,480 --> 01:52:58,240
selection pressures would have been like.

1829
01:52:58,400 --> 01:53:01,120
Um similarly with the racial categorization work.

1830
01:53:01,360 --> 01:53:05,840
We know from evolutionary genetics works work that skin color is a recent adaptation and

1831
01:53:05,840 --> 01:53:09,590
would uh would have uh not been an enduring feature of ancestral environments.

1832
01:53:09,750 --> 01:53:13,910
And even even if it was, the idea that our ancestors were engaging in intercontinental

1833
01:53:13,910 --> 01:53:15,030
travel is implausible.

1834
01:53:15,110 --> 01:53:19,510
So that theory is resting on a really shaky foundation, and therefore we should have lower

1835
01:53:19,510 --> 01:53:23,510
confidence in that in that theory that we have adaptations for racial categorization.

1836
01:53:23,670 --> 01:53:26,470
And that's part of how we can rule out that hypothesis.

1837
01:53:26,630 --> 01:53:30,550
We can also rule it out with empirical data showing that we don't, in fact, categorize by

1838
01:53:30,550 --> 01:53:33,670
race when there are other alliance uh cues present.

1839
01:53:33,880 --> 01:53:37,160
But another way we can rule it out is just by saying that this is evolutionarily

1840
01:53:37,160 --> 01:53:37,560
implausible.

1841
01:53:37,880 --> 01:53:38,200
That's right.

1842
01:53:38,280 --> 01:53:42,440
And if somebody disagrees with that, they can make that claim and say, but that's the point

1843
01:53:42,600 --> 01:53:43,800
is you say it explicitly.

1844
01:53:43,880 --> 01:53:49,480
And then that's the thing is by making it explicit, it's not less falsifiable.

1845
01:53:49,560 --> 01:53:55,400
It's more because you're actually giving the logic of implicitly or explicitly, I think

1846
01:53:55,400 --> 01:53:57,720
this is an enduring, long-standing problem.

1847
01:53:57,800 --> 01:54:03,310
And that's why I'm thinking there's a system that has X, Y, and Z, like the anger system.

1848
01:54:03,550 --> 01:54:09,390
And by making that explicit, it's not naive, it's or it's

1849
01:54:09,390 --> 01:54:14,990
not sort of uh incautious about certainty about ancestral environments.

1850
01:54:15,070 --> 01:54:21,000
It's actually so by making it explicit, if somebody wants to claim Aaron, for

1851
01:54:21,000 --> 01:54:24,920
example, like I don't think that's a feature of ancestral environments.

1852
01:54:25,240 --> 01:54:31,080
By making it explicit, you open yourself up correctly, I think, to even a discussion about

1853
01:54:31,080 --> 01:54:31,240
that.

1854
01:54:31,400 --> 01:54:37,000
And there are many examples of within the evolutionary social sciences of different

1855
01:54:37,000 --> 01:54:43,000
evolutionary hyp hypotheses about certain selection pressures, like how how large were

1856
01:54:43,000 --> 01:54:47,850
social groups over evolutionary time, for example, or other things where where we can have

1857
01:54:47,850 --> 01:54:48,890
these discussions.

1858
01:54:49,050 --> 01:54:54,730
But if you don't make explicit the idea of here is the

1859
01:54:54,730 --> 01:55:00,170
claim about the enduring feature of the environment, then it's not more

1860
01:55:00,170 --> 01:55:04,170
careful about certainty, it's less careful.

1861
01:55:04,650 --> 01:55:05,130
Exactly.

1862
01:55:05,290 --> 01:55:10,890
It it is not it is the opposite of unfalsifiable because what it does is it opens up new

1863
01:55:10,890 --> 01:55:14,570
avenues for falsification and for criticism of the theory.

1864
01:55:14,810 --> 01:55:18,620
If you're explicit about the assumptions you're making about the ancestral environment,

1865
01:55:18,780 --> 01:55:23,660
that opens you up to new kinds of criticisms and arguments against your theory.

1866
01:55:23,820 --> 01:55:29,660
You are making your theory more vulnerable to being challenged or even falsified.

1867
01:55:32,140 --> 01:55:37,180
To take the example of race, if you're arguing that we have adaptations for

1868
01:55:37,660 --> 01:55:41,660
detecting race, and I come along and show you some evidence from genetics showing that

1869
01:55:41,660 --> 01:55:45,150
actually race is a really recent trait and it wouldn't have been present.

1870
01:55:45,310 --> 01:55:49,390
Well, you've falsified my hypothesis, or you've at least cast significant doubt on it.

1871
01:55:49,470 --> 01:55:53,550
So what you're doing when you talk about ancestral selection pressures is you are opening

1872
01:55:53,550 --> 01:55:56,430
up new opportunities for falsification.

1873
01:55:56,670 --> 01:55:57,310
Right.

1874
01:55:57,790 --> 01:56:00,190
So um moving right along.

1875
01:56:00,270 --> 01:56:05,070
So right off the bat you have to come up with an ancestral selection pressure that would

1876
01:56:05,070 --> 01:56:09,230
have been plausible, a foundation that you can build your theory on.

1877
01:56:09,470 --> 01:56:12,820
That rules out adaptations for racial categorization.

1878
01:56:12,900 --> 01:56:17,220
It rules out tons of other hypotheses that you would be inclined to make.

1879
01:56:17,620 --> 01:56:23,380
Number two, the system you're positing has to uh

1880
01:56:23,620 --> 01:56:28,420
be a good solution to that adaptive problem you're positing.

1881
01:56:28,660 --> 01:56:30,660
Um, and what does it mean to be a good solution?

1882
01:56:30,740 --> 01:56:36,470
It has to be well designed, It has to actually get the job done of, say, finding food or

1883
01:56:36,470 --> 01:56:39,830
categorizing alliances or negotiating for better treatment.

1884
01:56:39,990 --> 01:56:45,270
And to the extent that it it does those things poorly, then that's another avenue by which

1885
01:56:45,270 --> 01:56:46,950
your hypothesis can be falsified.

1886
01:56:47,270 --> 01:56:52,790
What you're trying to do empirically is to show that this system does the job really well.

1887
01:56:53,120 --> 01:56:58,000
Anger does the job of recalibrating welfare trade-off ratios really well.

1888
01:56:58,240 --> 01:57:03,280
The the degree to which it is non-randomly organized to fulfill this function of

1889
01:57:03,280 --> 01:57:09,280
recalibrating welfare trade-off ratios, that level of organization can only be explained

1890
01:57:09,280 --> 01:57:10,160
by natural selection.

1891
01:57:10,240 --> 01:57:12,640
It cannot be explained by random noise.

1892
01:57:13,120 --> 01:57:15,520
This is the best fit for the data.

1893
01:57:15,680 --> 01:57:17,120
This is the best theory.

1894
01:57:18,290 --> 01:57:19,330
that's what you're doing.

1895
01:57:19,490 --> 01:57:23,010
So it has to be consistent with what we know about evolutionary history.

1896
01:57:23,090 --> 01:57:28,930
The feature uh to which the adaptation um uh is is adapted to must have been present.

1897
01:57:29,170 --> 01:57:34,530
The the system you're positing uh must actually solve the problem in question, and it must

1898
01:57:34,530 --> 01:57:39,730
solve it uh efficiently, reliably, precisely, and effectively.

1899
01:57:40,610 --> 01:57:46,260
Um just incorporating that into your theory building

1900
01:57:46,260 --> 01:57:48,500
rules out so many hypotheses.

1901
01:57:49,220 --> 01:57:54,900
Um there's so much psychology, for example, that argues that the function of a

1902
01:57:54,900 --> 01:58:00,100
cognitive system is to pursue happiness or to generate positive

1903
01:58:00,260 --> 01:58:05,090
hedonic states, to uh to make us feel good.

1904
01:58:05,330 --> 01:58:11,090
So social identity theory argues that we we like to identify with groups and um

1905
01:58:11,410 --> 01:58:15,650
uh defend the reputation of our groups because we feel good when we belong to a group and

1906
01:58:15,650 --> 01:58:17,730
we feel good when our group looks good.

1907
01:58:17,970 --> 01:58:23,250
And and the function of this system is to produce positive emotional states.

1908
01:58:24,050 --> 01:58:29,620
If you're doing good evolutionary psychology, good adaptationism, the function of

1909
01:58:29,620 --> 01:58:35,540
pursuing happiness or increasing positive hedonic states is not a viable

1910
01:58:35,860 --> 01:58:37,620
evolutionary function.

1911
01:58:39,380 --> 01:58:44,420
Evolution does not design organisms to get stuff inside of their own heads.

1912
01:58:44,660 --> 01:58:50,500
Evolution designs organisms to get stuff in the world that would have reliably increased

1913
01:58:50,500 --> 01:58:53,300
their fitness in ancestral environments.

1914
01:58:53,540 --> 01:58:58,340
The idea that we have adaptations for increasing happiness is

1915
01:58:58,970 --> 01:59:00,730
incredibly implausible.

1916
01:59:00,890 --> 01:59:06,730
Even if you were to assume that happiness, for whatever reason, was correlated with fitness

1917
01:59:06,730 --> 01:59:07,930
in ancestral environments.

1918
01:59:08,090 --> 01:59:09,050
Let's just make that assumption.

1919
01:59:09,130 --> 01:59:14,330
Let's make the dubious assumption that in our hunter-gatherer past, people who were happier

1920
01:59:14,410 --> 01:59:16,330
uh were more likely to survive and reproduce.

1921
01:59:16,410 --> 01:59:18,650
I don't think it's plausible, but let's make that assumption.

1922
01:59:18,890 --> 01:59:24,410
Even if that's true, that would not result in a motivational system designed to

1923
01:59:24,410 --> 01:59:26,060
seek happiness.

1924
01:59:26,300 --> 01:59:30,220
The result would be that we would evolve to be happier.

1925
01:59:31,500 --> 01:59:36,540
Just as if a squirrel is insufficiently fearful of predators, the squirrel would not evolve

1926
01:59:36,540 --> 01:59:40,780
to pursue fear as a goal and try to like, they wouldn't be jumping out of the bushes of

1927
01:59:40,780 --> 01:59:42,780
each other and scaring each other to pursue fear.

1928
01:59:42,940 --> 01:59:44,620
No, they would just become more fearful.

1929
01:59:44,780 --> 01:59:45,100
Right?

1930
01:59:45,260 --> 01:59:49,020
If happiness truly increased our fitness, we wouldn't evolve to pursue happiness, we would

1931
01:59:49,020 --> 01:59:49,900
just become happier.

1932
01:59:50,060 --> 01:59:55,710
So, right off the bat, this is ruling out, you know, a huge chunk of existing psychology.

1933
01:59:56,350 --> 01:59:57,950
Can I can I push back a little bit?

1934
01:59:58,750 --> 02:00:01,070
And I think we should have a happiness uh description.

1935
02:00:01,230 --> 02:00:02,590
Yeah, that would be a good good topic.

1936
02:00:02,670 --> 02:00:02,830
Yeah.

1937
02:00:03,070 --> 02:00:06,030
I mean, what about the argument that it's a proxy?

1938
02:00:06,190 --> 02:00:11,390
I mean, uh the way I think about those claims is that those are fine descriptions.

1939
02:00:11,550 --> 02:00:13,870
And we even talked about this because you know I study groups.

1940
02:00:14,340 --> 02:00:16,980
People are motivated, they feel good when they join a group.

1941
02:00:17,140 --> 02:00:23,060
That's a perfectly fine sort of within the experience of a person description of

1942
02:00:23,060 --> 02:00:24,260
sort of how they work.

1943
02:00:24,500 --> 02:00:30,260
But it it but then you can translate into a more evolutionary perspective, which is well,

1944
02:00:30,420 --> 02:00:36,020
what features of a group um would actually uh why would people feel

1945
02:00:36,020 --> 02:00:41,930
happy about joining a group, or what should if we think about sort of like that's the

1946
02:00:41,930 --> 02:00:45,130
robot expressing this is a good situation.

1947
02:00:45,530 --> 02:00:49,610
If if somebody says, like so, again, like thinking about people from this level of

1948
02:00:49,610 --> 02:00:51,450
software, like people are robots.

1949
02:00:51,850 --> 02:00:56,890
If the robot tells you I feel good right now because I'm a member of a group, you could be

1950
02:00:56,890 --> 02:01:02,330
an engineer about it by thinking, well, okay, the robot software is registering, it's in a

1951
02:01:02,330 --> 02:01:07,340
good situation from an evolutionary perspective, given what

1952
02:01:07,980 --> 02:01:12,940
affordances and functions group alignment membership is,

1953
02:01:13,740 --> 02:01:18,700
what can we predict about the kinds of cues or the kinds of software this robot would have

1954
02:01:18,700 --> 02:01:24,220
to detect what counts as a good group, what counts as a bad group, and correspondingly when

1955
02:01:24,220 --> 02:01:25,900
it should feel good or not good.

1956
02:01:26,140 --> 02:01:29,180
Um and I think that's the way for me, at least I think about it, right?

1957
02:01:29,260 --> 02:01:34,790
So it gives teeth to what is otherwise trapped inside the internal

1958
02:01:36,070 --> 02:01:39,430
arbitrary thing of just like it's essentializes, right?

1959
02:01:39,510 --> 02:01:43,990
It's saying like a group is an essentialized category, feeling good is an essentialized

1960
02:01:43,990 --> 02:01:46,950
category, and they're stuck together, like velcro together.

1961
02:01:47,110 --> 02:01:51,590
And what an evolutionary approach does is it says group, you're not allowed to think a

1962
02:01:51,590 --> 02:01:52,550
group exists.

1963
02:01:52,710 --> 02:01:58,480
It has to be composed of a bunch of evolutionarily recurrent cues and happiness,

1964
02:01:58,560 --> 02:02:04,240
or like the detection of this is a situation that's good, or maybe more sophisticatedly, a

1965
02:02:04,240 --> 02:02:08,320
detection of a situation that's even better than is expected for now.

1966
02:02:08,560 --> 02:02:13,440
Um what would those kinds of situations be?

1967
02:02:13,680 --> 02:02:13,920
Yeah.

1968
02:02:14,160 --> 02:02:20,000
And from an evolutionary perspective, and that gives that unessentializes and turns

1969
02:02:20,000 --> 02:02:21,600
into an engineering problem.

1970
02:02:22,320 --> 02:02:22,640
Yes.

1971
02:02:22,880 --> 02:02:27,130
What is otherwise the bland statement of like, I like to be happy because I'm a member of a

1972
02:02:27,130 --> 02:02:27,370
group.

1973
02:02:27,610 --> 02:02:29,850
Like, I don't think it's a problem for people to say that.

1974
02:02:29,930 --> 02:02:33,690
It's just it's a very limited perspective on the broader phenomenon.

1975
02:02:34,090 --> 02:02:34,570
Got it.

1976
02:02:34,730 --> 02:02:38,490
I'm I'm going to do something I rarely do on this podcast, which is disagree with you.

1977
02:02:38,970 --> 02:02:39,290
Excellent.

1978
02:02:39,370 --> 02:02:39,530
Yes.

1979
02:02:39,770 --> 02:02:41,290
I think it is a problem when people do that.

1980
02:02:41,610 --> 02:02:41,770
Good.

1981
02:02:42,010 --> 02:02:43,370
Um, and here's why.

1982
02:02:43,610 --> 02:02:49,420
If I'm designing a robot to say, uh join groups and defend

1983
02:02:49,420 --> 02:02:50,780
group reputations.

1984
02:02:51,260 --> 02:02:55,660
Uh and I'm drawing up my blueprints of what the robot needs to be sensitive to and what it

1985
02:02:55,660 --> 02:02:57,100
should be motivated to go out and get.

1986
02:02:57,420 --> 02:03:01,580
There's gonna be no spot on my diagram for happiness or for good vibes, right?

1987
02:03:01,740 --> 02:03:02,860
I don't need that.

1988
02:03:03,100 --> 02:03:08,270
I can just program the robot to go out and and find groups and detect them and join them.

1989
02:03:08,350 --> 02:03:12,030
And if it detects cues that its group is under attack and needs to defend the group's

1990
02:03:12,030 --> 02:03:16,030
reputation, the robot will spit out a compelling monologue about why the group is actually

1991
02:03:16,030 --> 02:03:19,870
heroic and brave and making the world a better place or whatever.

1992
02:03:20,350 --> 02:03:26,270
But I don't need happiness to motivate the robot to do those things.

1993
02:03:27,150 --> 02:03:32,670
And so we need to ask the adaptationist question about happiness itself, about feeling good

1994
02:03:32,670 --> 02:03:32,990
itself.

1995
02:03:33,150 --> 02:03:34,190
What is that for?

1996
02:03:34,360 --> 02:03:35,800
Why does that exist?

1997
02:03:36,600 --> 02:03:42,040
And once we ask that adaptationist question, uh people are inclined to give the answer, oh,

1998
02:03:42,200 --> 02:03:44,600
it's it evolved to motivate us to go out and get things.

1999
02:03:44,840 --> 02:03:48,200
That is a bad adaptationist answer.

2000
02:03:48,760 --> 02:03:53,880
Because if the purpose of happiness is to motivate me to go out and get stuff that

2001
02:03:53,880 --> 02:03:59,480
increases my fitness, well then how does evolution motivate me to want happiness?

2002
02:03:59,960 --> 02:04:00,200
Right.

2003
02:04:00,250 --> 02:04:01,530
I remember that.

2004
02:04:01,690 --> 02:04:03,770
Does it have to give me does it have to give me more happiness?

2005
02:04:04,010 --> 02:04:04,330
Yeah, yeah.

2006
02:04:04,410 --> 02:04:05,210
It's a circular problem.

2007
02:04:05,290 --> 02:04:06,810
So what is what is completely circular.

2008
02:04:06,970 --> 02:04:08,730
Yeah, so what's your argument for what it is?

2009
02:04:08,810 --> 02:04:09,130
Yeah.

2010
02:04:09,610 --> 02:04:15,130
So my argument is that um what happiness is is a way of

2011
02:04:15,130 --> 02:04:20,570
recalibrating our motivations and our expectations when

2012
02:04:20,570 --> 02:04:26,280
something turns out to be better than we intuitively expected.

2013
02:04:27,000 --> 02:04:32,680
So if I'm uh, let's say making a paella and I'm not

2014
02:04:32,680 --> 02:04:37,880
confident about it, and uh and I think it's gonna taste bad, and it ends up being

2015
02:04:37,880 --> 02:04:43,320
amazing, um, well, my mind has a lot of recalibration to do.

2016
02:04:43,480 --> 02:04:49,350
I had some mistaken beliefs about the quality of paella and my own ability as a

2017
02:04:49,350 --> 02:04:49,670
cook.

2018
02:04:49,750 --> 02:04:51,990
And those beliefs need to be recalibrated.

2019
02:04:52,150 --> 02:04:54,710
And also my motivations need to be recalibrated.

2020
02:04:54,790 --> 02:05:00,470
I now need to jack up my motivations to make more Spanish cuisine in the future.

2021
02:05:00,790 --> 02:05:04,870
And so all that recalibrational work has to be done somehow.

2022
02:05:05,110 --> 02:05:09,190
And I think the job of happiness is to do that recalibrational work.

2023
02:05:09,430 --> 02:05:15,360
So what it what happiness does is it forces you to slow down, stop, pay attention to the

2024
02:05:15,360 --> 02:05:16,960
awesome thing that's happening to you.

2025
02:05:17,200 --> 02:05:20,160
Figure out how this thing could have happened.

2026
02:05:20,480 --> 02:05:23,360
What how could how could you have been so mistaken?

2027
02:05:23,520 --> 02:05:23,840
Right?

2028
02:05:24,160 --> 02:05:26,080
Where did you go wrong in your expectations?

2029
02:05:26,240 --> 02:05:28,880
Where did you go wrong in your priorities and your motivations?

2030
02:05:29,040 --> 02:05:32,240
Pay attention to the thing and figure out what is causing it, what is unique to this

2031
02:05:32,240 --> 02:05:32,640
outcome.

2032
02:05:32,880 --> 02:05:38,080
Once you figure that out, change your priorities, change your expectations, seek out more

2033
02:05:38,080 --> 02:05:39,120
of this thing in the future.

2034
02:05:39,280 --> 02:05:44,210
The next time you encounter it, encounter it, expect it to be good or expect it to be

2035
02:05:44,210 --> 02:05:44,530
better.

2036
02:05:44,690 --> 02:05:44,930
Yeah.

2037
02:05:45,090 --> 02:05:45,250
Right?

2038
02:05:45,570 --> 02:05:45,730
Good.

2039
02:05:45,890 --> 02:05:46,530
Yeah, yeah.

2040
02:05:46,690 --> 02:05:48,370
And and so that's excellent.

2041
02:05:48,450 --> 02:05:49,570
And that is you're right.

2042
02:05:49,650 --> 02:05:50,850
It's much more sophisticated.

2043
02:05:51,010 --> 02:05:56,850
I wonder if then so like let's imagine, let's go back to social identity

2044
02:05:56,850 --> 02:05:57,330
theory.

2045
02:05:57,490 --> 02:05:57,810
Yeah.

2046
02:05:57,970 --> 02:06:03,410
Um for me, which is like I think it's right, and it's for me it's a source of additional

2047
02:06:03,410 --> 02:06:08,520
hypotheses about additional design, but I agree it's not fully fleshed out in the way that

2048
02:06:08,520 --> 02:06:09,800
they talk about it.

2049
02:06:10,040 --> 02:06:16,040
Um imagine you're sort of

2050
02:06:16,040 --> 02:06:21,880
um just going around and then like you just decide somebody is like you know got

2051
02:06:22,120 --> 02:06:27,800
involved you in something on on the weekend and you go to it and it's like a really great

2052
02:06:27,800 --> 02:06:32,360
social experience and you and it's a group, it's some group thing.

2053
02:06:32,600 --> 02:06:34,680
All of a sudden you feel really happy.

2054
02:06:34,990 --> 02:06:40,910
I think the the argument would be like all those same functions are there, which is that

2055
02:06:40,990 --> 02:06:46,510
you know, you were mistaken, you weren't expecting this to be an important part of your uh

2056
02:06:46,910 --> 02:06:52,910
uh the benefits, the sort of grammar of my representations of like, is this

2057
02:06:52,910 --> 02:06:57,310
a group or set of people that I'm gonna invest in that I get benefits out of that are worth

2058
02:06:57,420 --> 02:07:02,140
prioritizing compared to all the other things I could do, that feeling of happiness is

2059
02:07:02,140 --> 02:07:03,660
happening now for that group.

2060
02:07:03,820 --> 02:07:09,660
And so I wonder, and maybe this is just saying the same thing in a different

2061
02:07:09,660 --> 02:07:15,660
way, but for me, like when I hear social identity theory, I'm translating like people are

2062
02:07:15,660 --> 02:07:21,180
motivated to feel good or to join groups because it feels good, as um

2063
02:07:22,060 --> 02:07:27,850
that the feeling good is the thing that is leading them

2064
02:07:27,850 --> 02:07:33,690
towards of all possible groups, the ones that

2065
02:07:33,690 --> 02:07:38,650
are in a gradient towards better than what they're currently in.

2066
02:07:38,890 --> 02:07:44,890
And the step-by-step movement towards better than they're currently in is

2067
02:07:44,890 --> 02:07:48,010
caused exactly by this process you're describing.

2068
02:07:48,840 --> 02:07:49,240
Yes.

2069
02:07:49,480 --> 02:07:53,800
So that is a much better way of uh because then you have some sophisticated predictions

2070
02:07:53,800 --> 02:07:55,880
about when you're gonna feel good joining a group.

2071
02:07:56,120 --> 02:07:56,280
Correct.

2072
02:07:56,520 --> 02:07:59,960
When the group is better and a better investment than you would have expected compared to

2073
02:07:59,960 --> 02:08:01,400
the existing alternative groups.

2074
02:08:01,640 --> 02:08:05,000
And so we have another example of a beautiful prediction you can make by taking an

2075
02:08:05,000 --> 02:08:07,080
evolutionary perspective.

2076
02:08:07,320 --> 02:08:10,520
So um And when you should be dissatisfied with the group too.

2077
02:08:10,680 --> 02:08:10,840
Yeah.

2078
02:08:11,160 --> 02:08:12,120
Yes, exactly.

2079
02:08:12,360 --> 02:08:17,910
Um but uh we can also say that uh being part of a group shouldn't necessarily always make

2080
02:08:17,910 --> 02:08:18,710
you feel happy.

2081
02:08:18,950 --> 02:08:19,590
Right.

2082
02:08:19,830 --> 02:08:25,350
Um if if you know the group is is treating you exactly as well as you thought and exactly

2083
02:08:25,430 --> 02:08:27,510
it's exactly as cohesive as you thought, yeah.

2084
02:08:27,670 --> 02:08:28,710
There's no reason to feel happy.

2085
02:08:29,110 --> 02:08:32,710
Your motivations are are set correctly, your expectations are set correctly, you can hang

2086
02:08:32,710 --> 02:08:35,910
out with the group all day and not feel much happiness at all.

2087
02:08:36,860 --> 02:08:42,540
And so that's one case where taking this hedonic perspective of everything is about

2088
02:08:42,540 --> 02:08:44,060
pursuing happiness will lead you astray.

2089
02:08:45,420 --> 02:08:49,100
And there are even cases where um defending the group will make you feel unhappy.

2090
02:08:49,340 --> 02:08:54,940
So being vigilant against threats to the group and and thinking in a conspiratorial way

2091
02:08:54,940 --> 02:08:59,980
about all the people who might be out to get you or all the all the harms that might befall

2092
02:08:59,980 --> 02:09:02,380
your group, that's going to make you sad a lot of the time.

2093
02:09:02,770 --> 02:09:06,930
Uh, but we we should still evolve to do it and still adaptive to do it, because what we're

2094
02:09:06,930 --> 02:09:11,410
pursuing is not happiness, but group integrity and group success in competitions.

2095
02:09:11,730 --> 02:09:12,290
Yeah, that's right.

2096
02:09:12,370 --> 02:09:16,450
And it makes predictions about to the extent that the group membership thing, what you're

2097
02:09:16,450 --> 02:09:22,290
getting out of it is social benefits and compared to alternatives or your own intrinsic

2098
02:09:22,290 --> 02:09:26,450
value with respect to the group, it makes predictions of you should become more

2099
02:09:26,450 --> 02:09:31,820
dissatisfied with a group to the extent that, for example, if all of a sudden your social

2100
02:09:31,820 --> 02:09:37,740
status or bargaining power increases and nobody else is in the group does, that

2101
02:09:37,740 --> 02:09:39,740
should make you more dissatisfied with the group.

2102
02:09:39,900 --> 02:09:45,340
Or if another group all of a sudden becomes available and it has a better, it's better for

2103
02:09:45,340 --> 02:09:45,500
you.

2104
02:09:45,580 --> 02:09:48,220
And the argument is none of this is conscious, quote unquote.

2105
02:09:48,300 --> 02:09:50,460
It's just the systems detecting this.

2106
02:09:50,780 --> 02:09:54,780
Then all of a sudden the new opportunity should make you more dissatisfied with the current

2107
02:09:54,780 --> 02:09:55,020
group.

2108
02:09:55,180 --> 02:10:00,750
And so these are you're you're right, these are all predictions that are

2109
02:10:00,990 --> 02:10:06,590
unpacking what is otherwise a description staying at the level of emotions.

2110
02:10:06,750 --> 02:10:11,470
It doesn't, and it's like kind of what Jamie Krem said in the other uh a previous episode,

2111
02:10:11,550 --> 02:10:15,310
which is there's an additional why question, which is and how questions.

2112
02:10:15,390 --> 02:10:17,150
It's well, what is a group?

2113
02:10:17,230 --> 02:10:19,150
Why does join a group make you feel good?

2114
02:10:19,230 --> 02:10:20,830
And and why and how, right?

2115
02:10:20,910 --> 02:10:22,270
And what are the what are the predictions?

2116
02:10:22,430 --> 02:10:24,800
And so I think so, yeah.

2117
02:10:24,880 --> 02:10:27,520
I mean, do you think that that's fair, the what we just characterized?

2118
02:10:27,760 --> 02:10:28,960
I think we just kind of converged on.

2119
02:10:29,280 --> 02:10:30,560
Yeah, I think I think we did converge.

2120
02:10:30,640 --> 02:10:30,880
Totally.

2121
02:10:31,040 --> 02:10:31,760
Yeah, agreed.

2122
02:10:31,840 --> 02:10:32,080
Yeah.

2123
02:10:32,160 --> 02:10:37,920
No, I it's okay to say that we do things um to feel good, I suppose, as long as you're

2124
02:10:37,920 --> 02:10:41,680
unpacking what it means to feel good from an adaptationist perspective.

2125
02:10:42,000 --> 02:10:42,320
That's right.

2126
02:10:42,480 --> 02:10:42,800
Yeah, yeah.

2127
02:10:43,040 --> 02:10:48,490
Otherwise, you're stuck in sort of this um uh Marvin Minsky has a book that's called The

2128
02:10:48,490 --> 02:10:49,210
Emotion Machine.

2129
02:10:49,290 --> 02:10:54,090
And it's interesting because he's coming at it from an uh uh an AI perspective, but it's

2130
02:10:54,090 --> 02:10:55,930
very much this engineering perspective.

2131
02:10:56,170 --> 02:11:01,450
And it's the Emotion Machine is it's his follow-up book to the much more popular Society of

2132
02:11:01,450 --> 02:11:04,090
Mind book, which I recommend people read if they haven't already.

2133
02:11:04,330 --> 02:11:08,250
The Emotion Machine book, in some sense, it's very sophisticated, in other ways, it's not,

2134
02:11:08,330 --> 02:11:13,200
because some of the things he appeals to are sort of not in his wheelhouse, but but it's a

2135
02:11:13,200 --> 02:11:14,960
very good book in in some respects.

2136
02:11:15,040 --> 02:11:19,040
And it's about sort of high-level uh cognitive architecture things.

2137
02:11:19,280 --> 02:11:24,480
And one of the things he talks about in this book is that if you stay at the level of what

2138
02:11:24,480 --> 02:11:27,680
we had talked about before is the intentional level, he doesn't use this language, but he

2139
02:11:27,680 --> 02:11:30,880
sort of stumbles on this idea of motivations.

2140
02:11:31,040 --> 02:11:35,440
So the person is motivated to like pursue groups that make them feel good.

2141
02:11:35,610 --> 02:11:35,770
Yeah.

2142
02:11:36,090 --> 02:11:39,770
It's sort of it really it's not an engineering problem, right?

2143
02:11:39,930 --> 02:11:43,930
Or if you are an engineer, you just you're stuck with these questions, these deeper why

2144
02:11:43,930 --> 02:11:45,690
questions that like Jamie pointed out.

2145
02:11:45,850 --> 02:11:51,370
And so I think this is again another reason why it's not a just so

2146
02:11:51,690 --> 02:11:52,170
story.

2147
02:11:52,410 --> 02:11:56,970
In some sense, it's actually people are motivated to join groups they like, is a just so

2148
02:11:57,130 --> 02:11:57,450
story.

2149
02:11:57,660 --> 02:11:59,020
It's kind of ironic, right?

2150
02:11:59,100 --> 02:12:04,860
It's that staying at the intentional level and not translating that into the fleshed out

2151
02:12:04,860 --> 02:12:06,780
with teeth, with predictions.

2152
02:12:07,020 --> 02:12:10,380
What counts as a why should we feel good?

2153
02:12:10,540 --> 02:12:16,460
Translating emotions and concepts like groups and belongingness

2154
02:12:16,780 --> 02:12:22,620
um into a set of circumstances and outcomes that is the

2155
02:12:22,620 --> 02:12:24,620
opposite of a just so story.

2156
02:12:24,970 --> 02:12:25,690
I agree.

2157
02:12:25,850 --> 02:12:31,690
Um, I I wanna chime in on that point in particular, which is I

2158
02:12:31,690 --> 02:12:36,490
have this belief that there is no such thing as non-evolutionary psychology.

2159
02:12:36,730 --> 02:12:38,890
I don't think that exists.

2160
02:12:39,050 --> 02:12:43,210
I don't think you can do psychology in a non-evolutionary way.

2161
02:12:43,370 --> 02:12:48,650
What you can do is do psychology with your evolutionary assumptions unstated and

2162
02:12:48,650 --> 02:12:49,610
implicit.

2163
02:12:50,170 --> 02:12:51,600
Um, you can do that.

2164
02:12:51,840 --> 02:12:56,320
And that allows you to come up with theories that are evolutionarily implausible and have

2165
02:12:56,480 --> 02:13:00,480
uh uh dubious assumptions attached to them because you don't bother to state those

2166
02:13:00,480 --> 02:13:03,040
assumptions and make them vulnerable to criticism.

2167
02:13:03,280 --> 02:13:08,800
So you can do uh psychology, uh you can do bad evolutionary psychology without knowing

2168
02:13:08,800 --> 02:13:11,920
you're doing bad evolutionary psychology because you haven't made your assumptions

2169
02:13:11,920 --> 02:13:12,480
explicit.

2170
02:13:12,640 --> 02:13:18,080
But at the end of the day, the psyche is uh an evolved organ, it is a product of evolution

2171
02:13:18,160 --> 02:13:24,010
like any other organ, It is divided into subsystems with specific functions, like all of

2172
02:13:24,010 --> 02:13:25,210
our organs are.

2173
02:13:26,410 --> 02:13:31,690
The only way to study the design of that organ is

2174
02:13:32,330 --> 02:13:37,130
by properly understanding the evolutionary history that gave rise to it,

2175
02:13:38,250 --> 02:13:41,450
or the functions that were selected for.

2176
02:13:42,820 --> 02:13:48,420
So when you're doing psychology, there's no way to study the psyche as something other than

2177
02:13:48,420 --> 02:13:49,380
an evolved organ.

2178
02:13:49,620 --> 02:13:53,860
If you're s making a claim about the mind, you are implicitly making an evolutionary claim

2179
02:13:54,020 --> 02:13:55,860
because the mind is a product of evolution.

2180
02:13:56,020 --> 02:13:59,780
Any claim about it entails certain evolutionary assumptions.

2181
02:14:00,020 --> 02:14:05,140
And so what evolutionary psychology is, is just making those assumptions explicit, forcing

2182
02:14:05,140 --> 02:14:10,430
you to make those assumptions explicit so that they are open to criticism and that they

2183
02:14:10,430 --> 02:14:16,270
allow you to screen out implausible hypotheses and constrain the hypothesis space

2184
02:14:16,350 --> 02:14:21,070
and open up new avenues for criticism and refutation and falsification.

2185
02:14:21,310 --> 02:14:26,990
It's just doing psychology, but you're being explicit about all the assumptions you're

2186
02:14:26,990 --> 02:14:27,230
making.

2187
02:14:27,560 --> 02:14:28,280
Yeah, that's right.

2188
02:14:28,360 --> 02:14:28,600
Yeah.

2189
02:14:28,680 --> 02:14:31,400
And Dan Nettle and Tom Scott Phillips have this great paper.

2190
02:14:31,560 --> 02:14:34,200
Is a non evolutionary psychology possible?

2191
02:14:34,520 --> 02:14:39,560
Um and I think that uh you know roughly is their point as well.

2192
02:14:39,720 --> 02:14:42,440
I think that's sort of a a way of putting it.

2193
02:14:42,600 --> 02:14:43,720
Um yeah.

2194
02:14:44,440 --> 02:14:45,000
Cool.

2195
02:14:45,400 --> 02:14:51,400
So uh yeah that so yeah so number one that's why uh number one point is just that's

2196
02:14:51,480 --> 02:14:56,520
that's why evolutionary psychology isn't a just so story or um

2197
02:14:57,250 --> 02:15:02,690
as Lita once once said it, one of her students used to say that it's just so, meaning like

2198
02:15:02,930 --> 02:15:05,090
it just spits everything just so.

2199
02:15:05,250 --> 02:15:09,650
Um oh by the way, Richard Kipling, like uh, you know, of the just so stories.

2200
02:15:10,130 --> 02:15:10,610
Rudyard.

2201
02:15:10,930 --> 02:15:12,210
Rudyard, is that yeah, yeah.

2202
02:15:12,850 --> 02:15:14,690
Um super racist.

2203
02:15:15,010 --> 02:15:15,490
Oh really?

2204
02:15:15,730 --> 02:15:19,650
And not in like a like, oh well, we have to like understand like he's a product of his

2205
02:15:19,650 --> 02:15:19,890
time.

2206
02:15:20,050 --> 02:15:25,320
Like uh Mark Twain, uh George Orwell were contemporaries were like

2207
02:15:25,560 --> 02:15:27,000
scathing about him.

2208
02:15:27,160 --> 02:15:28,440
Uh yeah, no, no, no.

2209
02:15:28,520 --> 02:15:32,680
So uh so it's kind of funny people kind of throw Rudyard, how did you say it?

2210
02:15:32,760 --> 02:15:35,000
I can't even say Rudyard or Rudyard I don't know how to do it.

2211
02:15:35,560 --> 02:15:36,680
I don't know how to apologies.

2212
02:15:36,840 --> 02:15:37,880
Well not really but yeah apologies.

2213
02:15:40,360 --> 02:15:45,480
Like uh yeah no no no so like people kind of throw that those just so stories um out of

2214
02:15:45,560 --> 02:15:51,350
psych but they're sort of throwing a very racist imperialist uh person um at

2215
02:15:51,350 --> 02:15:56,630
evpsy which is i think sort of ironically i i wasn't aware of that that little bit of

2216
02:15:56,630 --> 02:16:02,390
history yeah yeah yeah uh he has this book called um or it's a poem the white man's burden

2217
02:16:02,550 --> 02:16:08,390
um you know oh okay uh and then mark twain did a uh spoof on it sort of

2218
02:16:08,390 --> 02:16:13,590
to the person sitting in darkness or something like that and it's sort of uh so Kipling's

2219
02:16:13,590 --> 02:16:18,230
point was sort of imperialism you know it's sort of like for the good of the half demons uh

2220
02:16:18,310 --> 02:16:20,120
I think is a quote Yeah.

2221
02:16:20,280 --> 02:16:23,480
And Mark Twain was sort of like maybe not.

2222
02:16:24,600 --> 02:16:24,920
Okay.

2223
02:16:25,080 --> 02:16:25,400
All right.

2224
02:16:25,480 --> 02:16:30,360
Well, that gives us yet another reason to be happy that our discipline is not engaged in

2225
02:16:30,360 --> 02:16:36,040
just so storytelling and is not uh associated with ruddyard or ruddyard Kipling.

2226
02:16:36,280 --> 02:16:36,920
Yeah, that's right.

2227
02:16:37,000 --> 02:16:42,760
And and and maybe check your uh if you're gonna use Kipl just so stories as a as a a wedge

2228
02:16:42,760 --> 02:16:46,280
or as a cudgel, just check who you're who you're citing before you do that.

2229
02:16:46,450 --> 02:16:47,250
But yeah, yeah.

2230
02:16:47,330 --> 02:16:49,570
Maybe maybe Panglossianism would be the better site.

2231
02:16:49,650 --> 02:16:51,570
Although I'm sure Molière was was racist too.

2232
02:16:51,650 --> 02:16:51,970
Who knows?

2233
02:16:52,850 --> 02:16:53,730
Yes, exactly.

2234
02:16:53,810 --> 02:16:54,130
Yes.

2235
02:16:54,210 --> 02:16:55,410
Uh things get better.

2236
02:16:55,570 --> 02:16:55,730
Um.

2237
02:16:57,490 --> 02:16:58,770
So yeah.

2238
02:16:59,570 --> 02:16:59,890
Okay.

2239
02:17:00,130 --> 02:17:01,170
Have we have we done it?

2240
02:17:01,250 --> 02:17:03,650
Have we explained how to be a good evolutionary psychologist?

2241
02:17:04,050 --> 02:17:04,930
Or today.

2242
02:17:05,250 --> 02:17:05,570
Okay.

2243
02:17:05,810 --> 02:17:06,050
All right.

2244
02:17:06,210 --> 02:17:08,130
I mean, this is very much a to be continued.

2245
02:17:08,450 --> 02:17:11,650
To be that's a p that pun pun intended to be continued.

2246
02:17:12,210 --> 02:17:13,010
Very, very nice.

2247
02:17:13,090 --> 02:17:13,330
Okay.

2248
02:17:14,240 --> 02:17:14,880
All right.

2249
02:17:18,400 --> 02:17:21,200
Uh well, here we are at the end of the episode.

2250
02:17:21,280 --> 02:17:22,320
Thank you for listening.

2251
02:17:22,480 --> 02:17:26,320
Uh, if you like what you're hearing, uh please don't be shy.

2252
02:17:26,400 --> 02:17:28,880
Uh tell people about it on social media.

2253
02:17:28,960 --> 02:17:30,800
Uh shout it from the mountaintops.

2254
02:17:30,960 --> 02:17:34,640
We're a new podcast, we're trying to build an audience and gain support for what we're

2255
02:17:34,640 --> 02:17:34,800
doing.

2256
02:17:34,880 --> 02:17:37,680
And and where can people uh support us, Dave?

2257
02:17:38,130 --> 02:17:43,330
Well, they can support us emotionally however they want, but in terms of behaviorally, they

2258
02:17:43,330 --> 02:17:45,090
can sort of leave a good review.

2259
02:17:45,570 --> 02:17:47,730
They can support us on Patreon.

2260
02:17:48,370 --> 02:17:53,010
And yeah, just listening, liking, subscribing, and leaving reviews

2261
02:17:54,290 --> 02:17:58,050
that are neutral to positive is certainly helpful.

2262
02:17:58,940 --> 02:17:59,660
Absolutely.

2263
02:17:59,820 --> 02:18:00,060
Yeah.

2264
02:18:00,620 --> 02:18:05,100
If you feel that way, you know, if you feel like it's you feel negatively about it.

2265
02:18:05,500 --> 02:18:07,580
Um you know, I'll leave that to your discretion.

2266
02:18:07,820 --> 02:18:07,900
Yeah.

2267
02:18:08,140 --> 02:18:08,220
Yeah.

2268
02:18:08,300 --> 02:18:10,220
You if you hate us, you can send us hate mail too.

2269
02:18:10,300 --> 02:18:11,020
Uh but you know.

2270
02:18:11,420 --> 02:18:13,580
I would not maybe no, maybe not hate mail.

2271
02:18:13,900 --> 02:18:17,340
No, if you hate us, just think about why you hate us and maybe think about something more

2272
02:18:17,340 --> 02:18:18,620
productive you could do with your time.

2273
02:18:18,860 --> 02:18:21,740
Yeah, if you have nothing nice to say, then don't say it at all.

2274
02:18:22,060 --> 02:18:23,930
I think that's a good rules to live by.

2275
02:18:24,010 --> 02:18:27,690
So but you know, you take that wo take that with a grain of salt.

2276
02:18:27,770 --> 02:18:31,450
So but uh but yeah, thanks for listening and we'll see you next week.

2277
02:18:31,690 --> 02:18:32,170
See ya