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So uh so David, do you want to just do one where it's just you?

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Sure.

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Okay.

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So this is taking to say I'm Dave Petrozowski,

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right?

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It would be weird if you said I'm Dave Petrozowski.

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But you could say we're your hosts, David Pencil.

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This is uh yeah, we're your host, David.

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Okay, I do that.

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Yeah, so all right, let's see.

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Three two one ten nine eight seven six five four three two one.

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So take one.

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David, good to see you.

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Good to see you too, Dave.

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We have our first guest today.

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We do.

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I'm very excited.

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Yeah, and a very, a very good guest.

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I think one of the most uh uh excellent top-notch thinkers in the field of evolutionary

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psychology right now, uh applying uh computational and mathematical methodology

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to uh mate choice and how we choose our mates.

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Um absolutely fascinating work uh this guy is doing.

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Um we we get into all of it.

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We get into the origin of evolutionary psychology uh uh as a lens uh to

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understand through which to see human mating.

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Um we get into uh current issues in the study of mate choice, uh, and

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and what Dan's criticisms are of some of this research and and what his takes are on the

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various controversies.

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We cover a lot of ground.

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Yeah.

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And I like this because it's an example of uh people within EvSec actually thinking about

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and characterizing sort of how their own field is going.

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And Dan has just a great perspective on that.

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Uh super fun, um, super informative.

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And yeah, enjoy.

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So Dan Conroy Beam, thanks for being with us today.

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Thanks for having me.

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Um, Dan is a neighbor down the hall and also uh where where we live.

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Um and but you know, I actually realized, Dan, in getting ready for this meeting, there's

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like a lot of questions I've never asked you.

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Um because we see each other all the time that I never think that's

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um but uh Dan, you are a professor at UC Santa Barbara.

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Um and uh you how long have you been at UC Santa Barbara?

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I came here in 2016.

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So what does that mean?

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Coming up on the years.

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We should celebrate the 10 year uh the 10 years.

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Um, and before that, you were at Austin working with David Buss.

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How did you um, and you don't have to answer this if you don't want to, we can talk about

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something else immediately, but how did you um find uh David Buss and how did you get

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interested in Evpsych?

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Yeah.

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Uh you want the long version?

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You want the short version?

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Uh the the the extra long version, which whatever you want.

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Uh all the gory details.

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Yeah, yeah.

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Well, actually, we did like a really long version of ours.

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So that was like an entire episode.

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So yeah.

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Yeah, we like went into our childhoods.

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It got really good.

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It was a therapy.

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It was a therapy session.

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So I was born on a snowy day in Milwaukee, Wisconsin.

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No, uh it wasn't snowy because it was August.

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Um, uh yeah, I mean, so I I did both my my bachelor's and my

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PhD at the University of Texas, uh, which is where David Buss happens to work, or at least

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you know, did by the time I was there.

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Um, so it was total freak accident luck stuff.

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Um I I never really had much of an idea of what I wanted to do with my life.

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Um, I didn't have like a good understanding of what careers existed in the

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world.

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Um I was always really biology was always my favorite subject in school.

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Uh and I was always like really into just nature and wildlife and just living things.

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Uh like as a kid, I would just like that was my thing as a kid, just like drawing different

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animals and I had a zoo books subscription.

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My mom had a zoo books subscription for me.

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Uh and I just like every month when that zoo books came in and you just had a magazine to

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learn about like different animals from around the world, that was like Christmas every

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month.

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Um so like I knew that I liked biology, but I didn't really know that like you could be a

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biologist.

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And I don't know how it never occurred to me that like there were people whose job it was

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to generate this information that I was assuming.

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So I like the only thing I the only job I knew that was like connected to biology was

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just like something in medicine.

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Yeah.

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Um, so I just like I was like, I guess I want to do something related to that.

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I don't really know what.

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Um but I uh I remember, you know, I I started at UT as an

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undergrad.

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I was ostensibly pre-med, but like didn't just because I didn't know what else to

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be.

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Um I took a psych class, um, fully expecting to hate it,

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fully expecting like this is gonna be like, you know, Freud laying on couches

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talking about your mother.

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Uh, is it gonna be stupid?

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I'm interested in science, I'm not interested in this, but it just like fit my schedule.

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It like fulfilled the GE.

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That's I was like, I'll just get this, it'll be easy.

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Uh, and it was taught by David Lewis, who was a grad student in David

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Buss's lab at the time, who was intro-psych.

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Um, it was over the summer, actually.

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Uh, and so he had like probably way too much latitude in how he taught the

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course.

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Uh, so he taught it very much from an evolutionary perspective.

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Um, and uh yeah, I did I just I I remember it was

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mind-blowing.

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First of all, that psychology is a science, that like you can study human thought and

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emotion and behavior scientifically was a revelation to me.

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Uh, and then also the fact that you could take evolutionary theory, you could take this

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biological theory, uh, which I had independently already been really interested in.

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Um, you know, this was like There were a lot of stars that kind of

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aligned, I guess, maybe to like put me on this exact path.

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Because this was, you know, in Texas.

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Uh this is around the time.

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I don't know what the time what is the schedule for this.

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Um, this was around the time where um, you know, the

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the Texas Public School Board was revising standards for textbooks,

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which turns out to matter a lot for the whole country because Texas is such a big textbook

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market that like whatever the Texas public schools decide goes in the textbooks basically

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dictates what goes in the textbooks for the whole country.

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And so there was some debate about how are we going to talk about evolution in, you know,

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Texas school textbooks.

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And so evolution was like very much in the air.

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There were a lot of like this was a sort of resurgence of the like scopes monkey trial

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stuff going on.

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There was a lot of discussion in Texas about, you know, do we teach the controversy or not?

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And so I was like reading a lot about like reading a lot of blogs at the time about like a

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lot of skeptic blogs about evolutionary theory.

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I'd like taken a red rhetoric class and I wrote it about like evolutionary theory,

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skepticism on evolutionary theory.

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Um, and you know, it had always again being interested in biology and wildlife, it had

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always been evolution had always been super interesting to me.

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Um, so the idea that you could take this like embattled scientific theory and apply it to

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humans and apply it to human behavior, I was like, why this is so cool.

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Why didn't someone tell me about this before?

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Um I was super into it.

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I think David noticed I was super into it.

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Um, and you know, as you do when you're teaching a class, you're always on the lookout for

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like, you know, good research assistance.

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Uh so I think you know there's usually like, you know, two or three kids per class who are

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like really into it and really good students and genuinely curious, and everyone else just

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wants to get the grade and wants to know whether it's like gonna be on the test or not.

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And you know, yeah, yeah, exactly.

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Yeah.

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But you were you were one of those, one of those two or three.

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Yeah, yeah.

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I I would say this is one of the first classes that I can remember being like really

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intrinsically motivated to do too.

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Like I just wanted to imbibe as much of this as possible.

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And I I think you know fortunately David just saw that and he's like, you know,

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I think you should maybe do more of this.

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You want to help me out with my research.

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Um so I got involved with David Lewis as a research assistant for him.

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Um, and you know, just really enjoyed doing that, spent a lot of my

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free time in the lab helping DL with all kinds of things.

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Um, you know, as you do starting with like grunt work, running participants, doing

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literature reviews.

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Um, but you know, I think he just kept seeing that I kept being really interested in it and

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really invested in it.

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He kept giving me more and more to do.

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Um and then another, you know, another star that aligned um was UT

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at the time had this, I think it maybe still exists, but had this program uh for

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sort of getting undergraduates more connected in research.

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Um you know, kind of we have similar programs at UCSB, I guess, but it was uh unusually

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well funded.

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Um so DL and I signed up for this.

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It was like a mentorship program.

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And one of the perks was they funded the student to go to an academic conference.

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So after my freshman year of college, I got money to fly out

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to HBus in Fullerton.

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So that HBUS was my very first academic conference.

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I had no idea what an academic conference was like.

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Um flew out there, um, attended that HBS.

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And that was like that, I remember especially it was just a mind-blowing experience, right?

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Like this whole conference halls full of people who are exactly

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as obsessed with this topic as I am.

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And you just get to sit there for three days, you know, nine to five, and just

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hear about all the cool cutting edge science that like everybody, all these people are

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doing.

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You get to hear about these like discoveries before anyone else.

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You're just like drowning in this like really cool topic for days.

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It was so exhilarating.

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It was so fun.

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It was so fun to meet a bunch of people.

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Um and so I think that was like a real turning point.

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I was like, okay, like there's a career here.

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I really enjoy doing this.

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Like, I want to keep coming to this conference as much as I can.

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Um, so yeah, at that point I was like dead set on being an evolutionary psychologist.

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Um and uh, you know, I was already in the bus lab.

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I was already like learning about evolutionary psychology, primarily from David Lewis.

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But you know, I took David Buss's classes after that.

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I took as many classes as I could at UT that sort of like cobbled together like an F-Syc

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degree as much as I could.

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I switched majors immediately.

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I switched in the psych program as soon as I could.

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Um, but I minored in biology and I took as many like biostats psych

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courses to like cobble together and like an as much of an evpsych degree as I could.

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Um, you know, it's probably not an accident that I fell into human mating being in the bus

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lab.

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I mean, I may may have fallen into it anyway, but that just seemed like the natural topic

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to study.

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Um and then, you know, ended up staying there for grad school, not Not

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necessarily intentionally, but that's just what ended up happening.

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And yeah, no, I'm here.

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Does anybody, when anybody ever interviews you, because I've seen you in several

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interviews, does anybody ever ask you how you got interested in mating?

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Or is that is that sort of a yeah, it's maybe a given.

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Right?

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I don't know.

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No, yeah.

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I don't know if that question has ever really come up.

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Uh, how did you guys avoid getting interested in mating?

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Well, for a while, you know, till I turned 10 or something.

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Yeah, I don't know that I was ever not interested.

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It's sort of an intrinsically interesting topic.

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You know, anything related to to sex or death is sort of innately interesting to us, I

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think.

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And I think for me, for me, oh David, sorry, go ahead.

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No, no, go ahead.

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I was just gonna for me, like I think uh as a lot of people, like mating was especially

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like sort of a a gateway drug for Ev Psych too, where it was sort of, you know, as a

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seventeen, eighteen, nineteen year old, whatever, you're like, whoa, a science of this.

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Cause that's that was one of the other things that I found a bit disappointing about

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psychology, as interested as I was, is that the topics were sort of reasoning, problem

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solving.

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And I was like, well, what about like jealousy or anger or mating or love or something like

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that?

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And so for me, that was like definitely um exciting.

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So yeah.

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Yeah.

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No, for me, I think, I mean, I st I I do think mating and I do try to keep up in

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developments and mating psychology as much as I can.

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Uh but uh for me, uh it wasn't that it didn't, you know, it didn't make sense or it wasn't

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insightful and interesting.

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It was almost that it made too much sense and it was too insightful.

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Like you know, like I'm like, Oh, I totally buy this.

241
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This makes so much sense.

242
00:13:54,280 --> 00:13:57,320
I love the connections with other animals, but like I want to move on to the more

243
00:13:57,320 --> 00:14:02,190
mysterious things, like the like what what's going on with you know ideologies and sacred

244
00:14:02,190 --> 00:14:04,990
values like this weird stuff that's totally mysterious.

245
00:14:05,150 --> 00:14:10,750
I wanted to like I I wanted to be more ambitious and like tackle something that was really

246
00:14:11,070 --> 00:14:11,710
confusing.

247
00:14:11,950 --> 00:14:15,470
I don't know that's just my personality I guess you don't open the behavioral ethology

248
00:14:15,630 --> 00:14:21,550
textbook and see like you know political uh ideologies in the gazelles or red stack here.

249
00:14:22,110 --> 00:14:22,590
Right, exactly.

250
00:14:22,750 --> 00:14:23,950
It depends on what book you open.

251
00:14:28,620 --> 00:14:33,420
Um I for for the mating literature, Dan, um, is there um

252
00:14:34,460 --> 00:14:38,460
do you think that like it's been going on long enough that you could characterize sort of

253
00:14:38,460 --> 00:14:39,900
what its trajectory has been?

254
00:14:39,980 --> 00:14:44,860
Or like where where do you think the mating um stuff is at?

255
00:14:45,020 --> 00:14:50,700
Or or maybe even like more broadly, like you know, of psych we talked a little bit about um

256
00:14:51,550 --> 00:14:54,030
people thinking of psych is just a just-so story.

257
00:14:54,110 --> 00:14:59,470
We talked a little bit about um um you know making design or software level claims we

258
00:14:59,470 --> 00:15:03,710
haven't really talked about like evolutionary game theory, you know, and I assume that the

259
00:15:03,710 --> 00:15:08,270
audience of this will be a combination of just sort of people who know a lot, maybe people

260
00:15:08,270 --> 00:15:09,710
who don't know a lot.

261
00:15:10,190 --> 00:15:16,140
One of the things I really like about your work um is uh is that

262
00:15:16,220 --> 00:15:21,980
you know you're bringing these different tools to bear um and uh and i'm

263
00:15:21,980 --> 00:15:27,820
wondering like things like modeling or game theory or selection pressure dynamics um

264
00:15:28,140 --> 00:15:33,740
you know could you talk a little bit either about like how you see those

265
00:15:34,060 --> 00:15:39,820
um affecting the way we study things in ep or or mating more

266
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specifically That's that's two really big,

267
00:15:45,870 --> 00:15:47,470
really good questions.

268
00:15:48,030 --> 00:15:53,550
Um You know, uh it it's gonna be hard to

269
00:15:53,550 --> 00:15:57,230
characterize the trajectory of mating research in a way that's not like totally

270
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self-serving.

271
00:15:58,430 --> 00:16:00,590
Uh I mean uh please be self-serving, Dan.

272
00:16:00,750 --> 00:16:06,620
Please I mean I I can tell you sort of uh let me answer it

273
00:16:06,620 --> 00:16:11,100
this way, maybe to excuse how self-serving it's gonna necessarily be.

274
00:16:11,180 --> 00:16:17,100
Like I can tell you how I, you know, a direction I see that

275
00:16:17,100 --> 00:16:20,780
the work needs to go in, uh, a gap that I try to fill.

276
00:16:20,860 --> 00:16:21,500
Let me put it in there.

277
00:16:21,660 --> 00:16:21,900
Yeah, yeah.

278
00:16:21,980 --> 00:16:26,300
We're gonna do a thousand let a thousand flowers bloom, but what's the flowers that you

279
00:16:26,300 --> 00:16:28,780
think a couple that you you would like to pursue?

280
00:16:28,860 --> 00:16:29,180
Yeah.

281
00:16:29,820 --> 00:16:34,630
So I I I think there's like um, I don't know.

282
00:16:34,790 --> 00:16:40,310
There's maybe like there's maybe like a couple phases

283
00:16:40,950 --> 00:16:46,390
I can see I could see dividing the history of like human mating research into perhaps.

284
00:16:46,710 --> 00:16:52,710
Um I think um you know obviously human mating is at

285
00:16:52,710 --> 00:16:54,870
the core of it what evolutionary psychology is, right?

286
00:16:54,950 --> 00:17:00,870
Like I think Don Simon's um evolution of human sexuality, you could consider the first

287
00:17:00,870 --> 00:17:04,840
F Psych text, uh depending on how you wanna, you know.

288
00:17:05,320 --> 00:17:10,440
I would I would argue that um the descent of man by Darwin is is the first

289
00:17:11,400 --> 00:17:12,280
F-sych text.

290
00:17:12,440 --> 00:17:14,440
But even that is also full of mating stress.

291
00:17:16,920 --> 00:17:18,920
Critique of pure reason I got you guys beaten.

292
00:17:21,320 --> 00:17:27,290
Uh I you know obviously strains of these ideas have been present in lots of places for a

293
00:17:27,290 --> 00:17:31,530
lot of times, but I feel like the first time sort of modern adaptationist evolutionary

294
00:17:31,530 --> 00:17:37,530
psychology cohered in a single place, you know, I would unselfishly call evolution of human

295
00:17:37,530 --> 00:17:38,250
sexuality.

296
00:17:38,410 --> 00:17:41,610
Um was that was that before or after Adapted Mind?

297
00:17:41,930 --> 00:17:44,000
It was about ten years before adapted.

298
00:17:44,240 --> 00:17:46,960
Yeah, that was 778 or 79.

299
00:17:47,360 --> 00:17:47,440
Yeah.

300
00:17:48,000 --> 00:17:48,320
Oh wow.

301
00:17:48,400 --> 00:17:48,480
Okay.

302
00:17:48,560 --> 00:17:48,800
Oh yeah.

303
00:17:48,960 --> 00:17:49,120
All right.

304
00:17:49,200 --> 00:17:50,160
Then then you are correct.

305
00:17:54,320 --> 00:17:54,480
Yeah.

306
00:17:54,560 --> 00:17:54,640
Yeah.

307
00:17:54,800 --> 00:17:55,280
It was great.

308
00:17:55,600 --> 00:17:58,960
Dawn was instrumental in getting John and Lena here.

309
00:17:59,040 --> 00:18:04,400
And I think the, you know, the sort of UCSB,

310
00:18:05,040 --> 00:18:10,950
you know, uh collective, I think really is sort of like forged uh

311
00:18:11,270 --> 00:18:17,190
forged this uh this uh discipline um out of their collection of interests.

312
00:18:17,430 --> 00:18:23,350
Um so you know I I think you know that book was was obviously a you know

313
00:18:23,510 --> 00:18:24,550
a turning point.

314
00:18:24,630 --> 00:18:28,950
Um and that really inspired people like Marco Wilson and Martin Daly.

315
00:18:29,190 --> 00:18:31,350
It also really inspired people like David Buss.

316
00:18:31,670 --> 00:18:37,360
Uh so I think there's like a that sort of first phase in between Dawn and David, where like

317
00:18:37,440 --> 00:18:41,840
the field was kind of coming together and sort of basic like evolutionary.

318
00:18:42,240 --> 00:18:45,520
Don was really sketching out like what are the basic evolutionary principles?

319
00:18:45,760 --> 00:18:51,040
And what are the basic facts of human evolution and human life history as we understand

320
00:18:51,040 --> 00:18:56,160
them at the time that are relevant for you know making predictions about human psychology

321
00:18:56,160 --> 00:18:58,160
in the in the domain of human mating.

322
00:18:58,470 --> 00:19:03,750
Uh, and then I think David Buss, a lot of people picked up and ran with that, but David

323
00:19:03,750 --> 00:19:09,430
Buss really like established a particular brand uh that was very

324
00:19:09,430 --> 00:19:12,150
empirically successful and very popular.

325
00:19:12,790 --> 00:19:18,150
And so I think that maybe starts a kind of second phase of human mating research, which we

326
00:19:18,150 --> 00:19:19,990
may or may not still be in.

327
00:19:20,310 --> 00:19:24,960
Uh, because David, a lot of people don't know this, but David was trained originally as a

328
00:19:24,960 --> 00:19:26,000
personality psychologist.

329
00:19:26,160 --> 00:19:29,040
He was not, you know, obviously he wasn't an evolution trained as an evolutionary

330
00:19:29,040 --> 00:19:32,480
psychologist because there was no possible way to get trained as an evolutionary

331
00:19:32,480 --> 00:19:33,600
psychologist at that time.

332
00:19:33,760 --> 00:19:36,000
So he was trained as a personality psychologist.

333
00:19:36,160 --> 00:19:41,120
And his innovation, his first he got famous originally for personality we work.

334
00:19:41,200 --> 00:19:45,680
Like he got a job at Harvard on his personality stuff, uh and was really famous for

335
00:19:45,680 --> 00:19:51,030
developing this, you know, act nomination procedure for mapping what a personality

336
00:19:51,030 --> 00:19:51,910
construct is, right?

337
00:19:51,990 --> 00:19:56,870
Rather than looking at the dictionary and having people rate all the words in a dictionary

338
00:19:56,870 --> 00:20:01,750
that describe a person and deriving your measures through factor analysis of dictionary

339
00:20:01,750 --> 00:20:02,310
terms.

340
00:20:02,630 --> 00:20:07,670
He just said, let's go to people and just ask them, you know, what are the things that an

341
00:20:07,670 --> 00:20:09,270
extroverted person does?

342
00:20:09,430 --> 00:20:14,940
And let's define the construct in terms of this like collection of behaviors that people

343
00:20:14,940 --> 00:20:16,380
associate with this.

344
00:20:16,620 --> 00:20:22,300
Um so he was already very used to developing scales

345
00:20:22,460 --> 00:20:23,500
and measures.

346
00:20:23,820 --> 00:20:29,820
Um he's used to doing these like large scale survey projects and he was interested in

347
00:20:29,820 --> 00:20:32,060
these evolutionary approaches that were emerging.

348
00:20:32,220 --> 00:20:37,500
He met Lita and John he was a faculty member when Lita and John were like undergrads at

349
00:20:37,500 --> 00:20:38,780
Harvard, right?

350
00:20:38,940 --> 00:20:44,270
And you know they tell the story of like you know going to David's office as he was like

351
00:20:44,350 --> 00:20:47,790
just starting to write about this evolution stuff and telling him he was doing everything

352
00:20:47,790 --> 00:20:48,110
wrong.

353
00:20:48,510 --> 00:20:52,910
Um I once I once asked Lita what she said to David Buss during that, and I forgot what she

354
00:20:52,910 --> 00:20:53,070
said.

355
00:20:53,150 --> 00:20:54,190
We'll have to have Lita on.

356
00:20:55,630 --> 00:20:58,910
Um it sounded like it was very polite, actually, in the end.

357
00:20:58,990 --> 00:21:02,270
It sounded much worse more uh more salacious than it might have been.

358
00:21:02,350 --> 00:21:02,510
Yeah.

359
00:21:02,750 --> 00:21:04,590
Well, you know, you should maybe ask David for his version.

360
00:21:04,830 --> 00:21:05,150
That's true.

361
00:21:05,310 --> 00:21:05,710
Fair enough.

362
00:21:05,790 --> 00:21:08,350
Yeah, they may not have the same version, I don't remember.

363
00:21:08,590 --> 00:21:13,120
Um so I I think there was some exchange of ideas there.

364
00:21:13,440 --> 00:21:19,200
Um so David, I think, took this sort of very, you know,

365
00:21:19,440 --> 00:21:25,280
measuring latent constructs sort of approach from personality psychology and

366
00:21:25,280 --> 00:21:30,240
sort of brought this together with you know the evolutionary insights that Don Simons was

367
00:21:30,240 --> 00:21:30,800
bringing.

368
00:21:30,960 --> 00:21:36,350
So he's saying, you know, okay, if we think drawing from sexual selection theory, there's

369
00:21:36,350 --> 00:21:40,910
reason to expect you know humans have these preferences, but some of them may be sex

370
00:21:40,910 --> 00:21:45,950
differentiated for these particular, you know, evolutionary historic reasons.

371
00:21:46,350 --> 00:21:51,790
Let's develop a questionnaire to measure preferences and see do we see the kinds of

372
00:21:51,790 --> 00:21:56,190
patterns one would expect that you know what kinds of things are popular, but most

373
00:21:56,190 --> 00:21:58,670
importantly, what sort of sex differences are there?

374
00:21:58,750 --> 00:22:04,200
Because that's going to be know, David's motivation at the time, also, uh, we have to

375
00:22:04,200 --> 00:22:08,360
remember this is applying evolutionary theory to human behavior was extremely

376
00:22:08,360 --> 00:22:09,560
controversial.

377
00:22:09,800 --> 00:22:14,680
Um, and this is coming after the like sociobiology wars, which you know, David, Lita, and

378
00:22:14,680 --> 00:22:16,920
John were all exposed to firsthand at Harvard.

379
00:22:17,160 --> 00:22:17,480
Right.

380
00:22:17,640 --> 00:22:22,040
So I think in David's mind, I I I don't know, I don't want to speak to him too much.

381
00:22:22,120 --> 00:22:28,040
This is me sort of uh piecing together maybe a history, but you'd have to ask him.

382
00:22:28,200 --> 00:22:33,750
But I imagine part of just from knowing David and knowing the history, I imagine a big part

383
00:22:33,750 --> 00:22:39,590
of his goal here is not necessarily to map the map mating

384
00:22:39,590 --> 00:22:45,430
psychology per se, as much as to like provide a proof of concept that validate

385
00:22:45,430 --> 00:22:50,790
evolutionary approaches in the first place against all of this controversy.

386
00:22:50,950 --> 00:22:56,790
Um so I think you know he gets a lot of flack for focusing a lot on sex differences and

387
00:22:56,790 --> 00:22:58,550
overemphasizing sex differences.

388
00:22:58,710 --> 00:23:02,840
And that's, I think, where this sort of I'll get into that, but I think that's you know

389
00:23:03,080 --> 00:23:05,480
what ends up defining this kind of phase of mating research.

390
00:23:05,560 --> 00:23:10,200
But I think that's because sex differences were like a really natural lever, right?

391
00:23:10,440 --> 00:23:16,440
Like if you want to prove to the world, show the world that like there's some value in

392
00:23:16,440 --> 00:23:21,080
this evolutionary theory stuff, this can make really strong predictions that no one else

393
00:23:21,080 --> 00:23:24,760
can, that you need this evolutionary theory stuff to do your psychology.

394
00:23:25,000 --> 00:23:28,360
Sex differences are a really easy, natural place to start.

395
00:23:28,570 --> 00:23:30,090
And so that's where he started, right?

396
00:23:30,170 --> 00:23:36,010
So that's where like bus 89 comes from is evolutionary theory makes this

397
00:23:36,010 --> 00:23:40,970
really clear prediction that no other existing social psychological theories or preferences

398
00:23:40,970 --> 00:23:46,330
make, uh, which is there should be these cross culturally invariant sex differences on

399
00:23:46,330 --> 00:23:47,130
certain dimensions.

400
00:23:47,290 --> 00:23:49,930
So he took his personality psych know how.

401
00:23:50,730 --> 00:23:55,370
And you know, he actually borrowed I think a lot of people don't know this as well his his

402
00:23:55,370 --> 00:23:56,730
first preference questionnaire.

403
00:23:57,020 --> 00:23:57,980
He didn't come up with it.

404
00:23:58,060 --> 00:24:02,700
He actually just took it from a paper Hill 1945 or something like that.

405
00:24:02,860 --> 00:24:07,420
So it was a preference questionnaire that you know had been in use in the US at that time

406
00:24:07,420 --> 00:24:09,580
for some amount of use for 50 years.

407
00:24:09,660 --> 00:24:14,140
He basically just took Hill's questionnaire and administered it around the world with maybe

408
00:24:14,140 --> 00:24:15,020
some slight modifications.

409
00:24:15,100 --> 00:24:16,140
I don't remember.

410
00:24:16,380 --> 00:24:22,290
Um and yeah, established that there are these cross-culturally universal sex differences,

411
00:24:22,530 --> 00:24:26,770
at least among, you know, thirty-seven relatively industrialized cultures.

412
00:24:27,090 --> 00:24:32,130
Yeah, it's it's interesting, um, just reflecting on the history of evolutionary psychology.

413
00:24:32,290 --> 00:24:37,250
And, you know, you make a very good point that if you want to start somewhere in applying

414
00:24:37,250 --> 00:24:42,920
evolution to human behavior and human psychology, sex differences makes the most

415
00:24:42,920 --> 00:24:43,320
sense.

416
00:24:43,560 --> 00:24:45,800
You know, the the predictions there are the clearest.

417
00:24:45,960 --> 00:24:48,760
You see parallels in other animal species.

418
00:24:49,000 --> 00:24:52,280
Um, there are really large effect sizes to be found there.

419
00:24:52,440 --> 00:24:55,400
You can look, you can do interesting cross-cultural work.

420
00:24:55,640 --> 00:25:01,160
Um so it's a it's a really meaty good place to start if you want to just prove to the world

421
00:25:01,160 --> 00:25:06,690
that hey, this perspective works, it had it makes predictions and discoveries, the

422
00:25:06,690 --> 00:25:08,050
findings are solid.

423
00:25:08,210 --> 00:25:10,530
Um, look at what this field can do.

424
00:25:10,770 --> 00:25:14,690
But I can also imagine a downside to that, and that not only is you know the sex

425
00:25:14,690 --> 00:25:18,290
differences it's the easiest place to start, but it's also the most controversial and

426
00:25:18,290 --> 00:25:21,730
provocative and inflammatory place you could possibly start.

427
00:25:21,970 --> 00:25:27,090
And so I'm I'm imagining like what would evolutionary psychology be in the parallel

428
00:25:27,090 --> 00:25:30,770
universe where it didn't start with sex differences and it started with something else?

429
00:25:30,930 --> 00:25:33,490
Would would the field be completely different today?

430
00:25:33,960 --> 00:25:37,160
And I think there's a good case to be made that it probably would be very different.

431
00:25:37,560 --> 00:25:43,400
That starting with this, you know, uh inflammatory issue of sex differences sort of stamped

432
00:25:43,400 --> 00:25:48,200
the field with this controversial edgelord reputation.

433
00:25:48,600 --> 00:25:53,800
And it attracted all of these people who wanted to be edgelords and wanted to study

434
00:25:53,800 --> 00:25:57,400
controversial things and study titillating topics.

435
00:25:57,800 --> 00:26:03,610
And it sort of provided this inertia for the field that in many ways is probably not a

436
00:26:03,610 --> 00:26:04,330
good thing.

437
00:26:04,570 --> 00:26:10,090
Um yes, the the predictions are solid, the findings are solid, uh, but I really

438
00:26:10,090 --> 00:26:15,210
wonder what evolutionary psychology would have been like if it started somewhere else.

439
00:26:15,370 --> 00:26:19,450
Say if it started with like group psychology, the stuff that Dave studies, or some or or

440
00:26:19,530 --> 00:26:20,250
you know, something else.

441
00:26:20,330 --> 00:26:25,290
I I'm curious what what your reaction to that is in terms of just the his the historical

442
00:26:25,530 --> 00:26:27,370
inertia of the field.

443
00:26:28,020 --> 00:26:31,220
I think that's exactly right.

444
00:26:32,820 --> 00:26:37,940
And I I think that's uh not to criticize David or anything, right?

445
00:26:38,020 --> 00:26:38,900
I think his work is great.

446
00:26:38,980 --> 00:26:44,660
And I think he's done, you know, no one can um no one can

447
00:26:44,660 --> 00:26:46,900
deny David's like service to the field.

448
00:26:46,980 --> 00:26:51,300
And we're talking David, we have David Bus free David's format this conversation.

449
00:26:53,380 --> 00:26:55,700
Both David's here as well as David Bus.

450
00:26:56,050 --> 00:27:00,690
All of my work on mating mating has been really important since the eighties when I was

451
00:27:00,850 --> 00:27:04,530
when I was a some year old, a single digit year old.

452
00:27:04,610 --> 00:27:04,770
Yeah.

453
00:27:05,090 --> 00:27:05,570
It's true.

454
00:27:05,650 --> 00:27:06,370
I should be careful.

455
00:27:06,530 --> 00:27:09,890
Um but yeah, I no one can deny David Buss's you know service to the field.

456
00:27:09,970 --> 00:27:15,650
And you know, he's really he's done more than nearly anyone to like put the field on the

457
00:27:15,650 --> 00:27:16,050
map.

458
00:27:16,210 --> 00:27:21,410
Um but I do think there have been downsides to the particular approach that he chose.

459
00:27:21,730 --> 00:27:27,700
Um and I I think um you know, there's there's several sort of founders of

460
00:27:27,700 --> 00:27:29,060
the field that you could identify, right?

461
00:27:29,140 --> 00:27:33,460
If we're talking about capital E, capital P evolutionary psychology per se, and not just

462
00:27:33,460 --> 00:27:37,940
all approaches to evolution behavior, you know, I think of like Lita Cosmodies, John Tuby,

463
00:27:38,020 --> 00:27:42,660
kind of together, Steve Pinker, Martin Daly, Margot Wilson, the people in that picture,

464
00:27:42,820 --> 00:27:43,140
right?

465
00:27:43,460 --> 00:27:46,020
Um, David Buss, Don Simons.

466
00:27:46,250 --> 00:27:50,010
Um and they I think they had sort of different approaches to this.

467
00:27:50,170 --> 00:27:53,770
And you can sort of see the lineage of their work.

468
00:27:53,930 --> 00:27:57,770
Because yeah, David David's David Buss has never been one to shy away from controversy,

469
00:27:57,930 --> 00:27:58,730
that's for sure.

470
00:27:58,890 --> 00:28:03,770
Uh and I don't think he's quite edge lowered.

471
00:28:04,010 --> 00:28:06,250
Um there are he's a very lovely man.

472
00:28:06,330 --> 00:28:08,490
He definitely does not have this reputation.

473
00:28:08,730 --> 00:28:10,810
Uh we should have that reputation.

474
00:28:11,130 --> 00:28:15,400
Oh I mean No, no, he hasn't earned it.

475
00:28:16,840 --> 00:28:17,000
Yeah.

476
00:28:17,160 --> 00:28:17,400
Yeah.

477
00:28:17,720 --> 00:28:21,800
There are certainly some people who uh relish in controversy.

478
00:28:21,960 --> 00:28:25,480
David does not, uh, but David does not shy away from it either.

479
00:28:25,640 --> 00:28:30,040
Um and he's actually, yeah, I think he's actually he's he's a very savvy guy.

480
00:28:30,120 --> 00:28:34,690
I he wouldn't be where he was if he wasn't, you know, good at at navigating these kinds of

481
00:28:34,690 --> 00:28:35,090
topics.

482
00:28:35,250 --> 00:28:39,330
But I think, you know, like Lita Cosmanese and John Tube, they did kind of go the round

483
00:28:39,330 --> 00:28:40,450
that you were talking about, right?

484
00:28:40,610 --> 00:28:44,930
Like they wanted to prove evolutionary psychology as a as a useful discipline.

485
00:28:45,090 --> 00:28:49,890
And so they did go to something very, you know, pretty uncontroversial, very like

486
00:28:49,890 --> 00:28:50,770
cooperation, right?

487
00:28:50,850 --> 00:28:53,650
It's very heartwarming, very positive.

488
00:28:53,890 --> 00:28:57,650
And you know, they they try to demonstrate that you can make useful predictions in this

489
00:28:57,650 --> 00:29:01,420
area that there should be something that we can all agree is a good thing and people should

490
00:29:01,420 --> 00:29:02,940
be minimally angry about.

491
00:29:03,260 --> 00:29:08,220
I did I don't know what's your sense, Dave, as a student of theirs.

492
00:29:08,380 --> 00:29:13,580
Like, you know, I see David, he started at Harvard, so that probably helped him.

493
00:29:13,740 --> 00:29:16,300
So did they, but he was like faculty at Harvard already.

494
00:29:16,540 --> 00:29:22,460
I think he was able to parlay that into a position at Michigan, maybe still riding off the

495
00:29:22,460 --> 00:29:23,340
personality fame.

496
00:29:23,420 --> 00:29:27,500
Like David had a massive advantage in already being a very successful personality

497
00:29:27,500 --> 00:29:28,220
psychologist.

498
00:29:28,370 --> 00:29:31,650
So he was able to do this very controversial stuff.

499
00:29:31,810 --> 00:29:37,570
Um, just like using the last of his personality psych credit, like just burning all of

500
00:29:37,570 --> 00:29:43,570
that, and then he just got lucky that this F-Syc stuff took off in time before people hated

501
00:29:43,570 --> 00:29:45,890
him, basically, for doing that sort of stuff.

502
00:29:46,130 --> 00:29:51,490
Um, I don't know that he that you know, Lita and John have obviously been extremely

503
00:29:51,490 --> 00:29:56,500
successful and extremely influential, like in the long game played out, but I don't know

504
00:29:56,500 --> 00:30:02,180
that they had the like immediate success that David had for going with something that was

505
00:30:02,180 --> 00:30:04,420
more salacious and controversial.

506
00:30:05,140 --> 00:30:10,340
Yeah, I think I mean, so they I think the the group or the the cooperation thing,

507
00:30:10,900 --> 00:30:16,810
um, and I don't I don't know this for sure, but I think uh what I the

508
00:30:16,970 --> 00:30:21,450
the cooperation thing, you're right, is not as salacious immediately and it's sort of warm

509
00:30:21,450 --> 00:30:21,930
and fuzzy.

510
00:30:22,090 --> 00:30:28,090
My understanding of what I do know is and what Lita has said is that um I

511
00:30:28,090 --> 00:30:33,130
don't know the how strategic using cooperation was.

512
00:30:33,290 --> 00:30:38,650
What I do know was what was strategic, and this is sort of not along the salacious

513
00:30:38,650 --> 00:30:44,490
dimension, but along the scientific dimension, which is I love about John and Lita

514
00:30:44,570 --> 00:30:50,060
um is uh is their thinking, well, reasoning

515
00:30:50,380 --> 00:30:55,900
is a bastion of sort of unitary assumptions, right?

516
00:30:56,060 --> 00:31:00,380
Like what I love about John Alita's work was it was an articulation of the assumptions that

517
00:31:00,380 --> 00:31:04,060
were such deep assumptions that they weren't even treated as assumptions.

518
00:31:04,220 --> 00:31:04,860
Um, right.

519
00:31:05,020 --> 00:31:07,580
Like I think that's that's what I really love about the work.

520
00:31:07,660 --> 00:31:13,570
And so it was strategic to say reasoning is something we're going to go after and

521
00:31:13,570 --> 00:31:18,370
say, look, this idea that reasoning is content-independent, a unitary thing, that an

522
00:31:18,370 --> 00:31:21,010
evolutionary approach doesn't help you for thinking about reasoning.

523
00:31:21,090 --> 00:31:22,450
We're going to go after that.

524
00:31:22,930 --> 00:31:26,610
And so I think that was the idea.

525
00:31:26,690 --> 00:31:31,010
And then after there was an acceptance of that, people would say something like, Well, but

526
00:31:31,010 --> 00:31:35,800
emotions, you know, aren't going to, you know, so so it was just sort of following the um

527
00:31:35,960 --> 00:31:38,440
and what about this, what about that, and sort of following that.

528
00:31:38,520 --> 00:31:43,160
So I believe that was their um str strategy.

529
00:31:43,400 --> 00:31:48,680
Um so I think it was really at the level of the scientific claims and not about the

530
00:31:48,680 --> 00:31:51,560
reactions um of people per se.

531
00:31:55,170 --> 00:32:00,930
Yeah, well, I mean, um so I I to your point, David, I I think you've

532
00:32:00,930 --> 00:32:04,290
described a lot of the history exactly right, unfortunately.

533
00:32:04,450 --> 00:32:08,770
Um, you know, I think the the sex difference and stuff, that was that was that 1989

534
00:32:08,930 --> 00:32:11,090
behavioral and brain sciences paper, that was huge.

535
00:32:11,170 --> 00:32:15,250
That was yeah, you know, that was a big paper in you know, psychology period.

536
00:32:15,490 --> 00:32:20,610
Um, and that really planted a flag for this like evolutionary psychology stuff.

537
00:32:20,770 --> 00:32:25,420
You know, from there, David went on to he picked up some ideas again that trace themselves

538
00:32:25,420 --> 00:32:29,340
to Don Simons through Martin Daly and Margot Wilson on jealousy.

539
00:32:29,580 --> 00:32:33,180
Again, you know, looking at sex differences and jealousy as a really natural prediction,

540
00:32:33,340 --> 00:32:38,700
just showing we can make a prediction that no one else can and we can validate this around

541
00:32:38,700 --> 00:32:39,180
the world.

542
00:32:39,340 --> 00:32:43,100
And then, you know, Busin Schmidt ninety three, he went to mating strategy.

543
00:32:43,270 --> 00:32:47,910
Again, you know, it's sort of picking up there's this like intuitive kind of dimension

544
00:32:47,910 --> 00:32:51,670
along which mating relationships vary between, you know, they called it short-term,

545
00:32:51,830 --> 00:32:53,190
long-term at the time.

546
00:32:53,350 --> 00:32:59,110
You know, these sort of like high commitment, monogamous romantic relationships, which seem

547
00:32:59,110 --> 00:33:04,310
to be somewhat human unique, versus these sort of like short-term, uncommitted sexual

548
00:33:04,310 --> 00:33:05,030
relationships.

549
00:33:05,110 --> 00:33:10,640
And David just like sicked his personality psychology training on that, and you know,

550
00:33:10,800 --> 00:33:15,440
developed some measures and made a bunch of sex different again, sex difference predictions

551
00:33:15,440 --> 00:33:19,360
about how these things should be sex differentiated, drawing on ideas, going back again to

552
00:33:19,360 --> 00:33:20,080
Simon's.

553
00:33:20,240 --> 00:33:26,000
Um, so that sort of set up this like holy trinity of mating research, right?

554
00:33:26,080 --> 00:33:28,320
Like jealousy, preferences, mating strategy.

555
00:33:28,560 --> 00:33:34,320
Those are like big three constructs in mating psychology because of David Buss's early work

556
00:33:34,560 --> 00:33:39,750
and uh you know a huge amount of mating psychology research following that has been

557
00:33:40,070 --> 00:33:45,350
basically like pick one of those three or any combination they're in, you know, and then

558
00:33:45,350 --> 00:33:51,270
either, you know, show some kind of sex difference in it, you know, riff on it a little

559
00:33:51,270 --> 00:33:57,270
bit, like, you know, uh, you know, we want to demonstrate a sex difference in mating

560
00:33:57,270 --> 00:34:02,180
strategy either through people's attitudes or through people's behaviors or, you know, the

561
00:34:02,180 --> 00:34:05,300
kinds of things that they regret doing, you know, post hoc, right?

562
00:34:05,380 --> 00:34:09,380
Just like show, you know, come up with a new way to demonstrate the same sex difference in

563
00:34:09,380 --> 00:34:13,380
the same dimension, but yeah, either in a new context or a new cultural context or with

564
00:34:13,380 --> 00:34:14,500
some kind of new measure.

565
00:34:14,740 --> 00:34:20,740
And so so much of the mating research for the last what has it been, 30 years

566
00:34:20,900 --> 00:34:26,900
has been just sort of rehashing through those same three constructs again and show

567
00:34:26,900 --> 00:34:31,950
a sex difference in some kind of slightly novel way that David Bus didn't technically

568
00:34:31,950 --> 00:34:33,630
already show in 1990.

569
00:34:33,950 --> 00:34:37,150
Um, and I think that's been bad.

570
00:34:37,550 --> 00:34:42,350
Uh I mean that has generated a lot of knowledge, generated like a really robust foundation

571
00:34:42,350 --> 00:34:45,870
for human mating psychology research, which I'm grateful for.

572
00:34:46,350 --> 00:34:51,460
Um, but I think, you know, my opinion is we've we've done it.

573
00:34:51,620 --> 00:34:52,660
We've exhausted.

574
00:34:52,740 --> 00:34:53,140
Yeah.

575
00:34:53,300 --> 00:34:54,980
Uh we know that now.

576
00:34:55,140 --> 00:34:59,220
We don't need any more papers on sex differences and mate preferences, despite being a

577
00:34:59,220 --> 00:35:01,300
person who's published some of those recently.

578
00:35:01,540 --> 00:35:06,500
Uh I mean it is like a nice it's you can there's always money in the banana stand, right?

579
00:35:06,580 --> 00:35:10,980
Like you can always get another paper on on sex differences and mate preferences if you

580
00:35:10,980 --> 00:35:12,180
just need something.

581
00:35:12,500 --> 00:35:18,210
Um uh but yeah, I I I think that stuff has

582
00:35:18,210 --> 00:35:22,290
attracted a lot of people who, yeah, are not necessarily as interested in the science as

583
00:35:22,290 --> 00:35:23,650
they are in pissing people off.

584
00:35:23,810 --> 00:35:27,410
And I think that kind of work is just always easy to do.

585
00:35:28,050 --> 00:35:28,370
Right.

586
00:35:28,610 --> 00:35:34,450
And it it's just it's become it's it was so influential, it was so valuable

587
00:35:34,690 --> 00:35:38,530
that sex differences have kind of come to like dominate.

588
00:35:39,250 --> 00:35:45,120
Um kind of come to dominate the literature to the point where I think it's a very important

589
00:35:45,120 --> 00:35:45,120
thing.

590
00:35:45,200 --> 00:35:48,480
Or or at the very least, the the public perception of the field.

591
00:35:48,640 --> 00:35:52,640
I don't know if it necessarily, you know, uh has a disproportionate number of researchers

592
00:35:52,640 --> 00:35:53,280
working on the topic.

593
00:35:53,360 --> 00:35:54,000
Maybe it does.

594
00:35:54,160 --> 00:35:58,640
But even beyond that, just the public perception of it, I feel like, is dominated by the

595
00:35:58,640 --> 00:36:02,560
sex differences research, even more than perhaps exists in reality.

596
00:36:03,040 --> 00:36:05,200
I think the public perception's about right.

597
00:36:05,680 --> 00:36:05,840
Really?

598
00:36:06,000 --> 00:36:06,480
You think so?

599
00:36:06,800 --> 00:36:11,430
I I think I think all there's people out there who are not doing sex differences research.

600
00:36:11,830 --> 00:36:12,150
Yeah.

601
00:36:12,390 --> 00:36:13,510
I think that's true.

602
00:36:14,870 --> 00:36:20,550
But I think a lot of the you know a lot of the human

603
00:36:20,550 --> 00:36:26,550
mating research has been studying sex differences in psychology, I think to the exclusion

604
00:36:26,550 --> 00:36:28,390
of studying the psychology itself.

605
00:36:29,030 --> 00:36:32,470
So that's what I would like to see as like a third phase of human mating research.

606
00:36:32,550 --> 00:36:37,980
Like just getting back to, you know, I I the way I think of it is while Lita and John were

607
00:36:38,060 --> 00:36:43,260
playing this long game of like, you know, how do you really

608
00:36:43,580 --> 00:36:49,100
carefully, yeah, systematically pick a topic and just really systematically map the

609
00:36:49,100 --> 00:36:53,500
information processing design of that psychology, really systematically map the design of

610
00:36:53,500 --> 00:36:57,100
cooperation psychology, of emotion psychology, of group psychology.

611
00:36:57,340 --> 00:37:03,340
Um, that maybe doesn't get like as big of headlines as like you know, new

612
00:37:03,340 --> 00:37:09,150
universal sex difference, you know, men are men are, you

613
00:37:09,150 --> 00:37:14,910
know, new research finds that that men are uh uh men are all

614
00:37:14,910 --> 00:37:18,590
hussies and women are all you know chased or whatever.

615
00:37:18,750 --> 00:37:21,550
Uh you know, that'll get you like fun headlines.

616
00:37:21,710 --> 00:37:24,590
Um, but it doesn't really tell you that much about how the psychology works.

617
00:37:24,830 --> 00:37:28,590
Um and I think human mating research maybe needs to get more back into that.

618
00:37:28,750 --> 00:37:34,700
Yeah, like let's return to some of the more Don Simon-y approach to of like, let's

619
00:37:34,700 --> 00:37:40,380
be really clear-eyed about what are the adaptive problems that humans would have

620
00:37:40,380 --> 00:37:43,900
recurrently faced in human mating in the in the mating domain.

621
00:37:43,980 --> 00:37:49,740
And especially like, yeah, I just I just feel like uh the old guard, I think,

622
00:37:49,900 --> 00:37:52,540
get very defensive about this kind of thing.

623
00:37:52,780 --> 00:37:55,750
Um, but sex differences are important.

624
00:37:55,910 --> 00:37:56,630
Don't get me wrong.

625
00:37:56,790 --> 00:38:00,470
Again, I've published sex differences papers, I don't know, recently within the last couple

626
00:38:00,470 --> 00:38:01,110
of years, probably.

627
00:38:01,190 --> 00:38:02,150
I can't remember.

628
00:38:02,310 --> 00:38:08,310
Um, but I feel like a five year moratorium on sex differences papers would just like help

629
00:38:08,310 --> 00:38:08,870
the field.

630
00:38:08,950 --> 00:38:14,710
Like not ban it forever, but just like force people to be a little creative in finding

631
00:38:14,710 --> 00:38:16,150
other things to study.

632
00:38:16,870 --> 00:38:17,270
Right.

633
00:38:17,510 --> 00:38:22,760
I mean, the downside of of the complexity of the human mind and of human nature is that

634
00:38:22,760 --> 00:38:27,480
when you pick one part of it, it's easy to get carried away and think that that part of it

635
00:38:27,480 --> 00:38:28,760
represents the whole.

636
00:38:29,160 --> 00:38:29,400
Right.

637
00:38:29,480 --> 00:38:32,440
Like, yes, we can all agree men and women are different.

638
00:38:32,600 --> 00:38:35,560
They have different they have face different selection pressures throughout our

639
00:38:35,560 --> 00:38:36,520
evolutionary history.

640
00:38:36,760 --> 00:38:40,360
We can make specific predictions about how they're going to be different and we can, you

641
00:38:40,360 --> 00:38:44,200
know, see parallels between those differences and the differences you see in other species

642
00:38:44,200 --> 00:38:45,720
facing similar selection pressures.

643
00:38:45,880 --> 00:38:46,440
Yes.

644
00:38:46,770 --> 00:38:47,570
agreed.

645
00:38:47,890 --> 00:38:49,410
But there's a huge but.

646
00:38:49,650 --> 00:38:54,130
There's so much more to the story than that simple starting point, right?

647
00:38:54,370 --> 00:38:57,650
Yes, men and women are different and they have different mating strategies, etc.

648
00:38:57,970 --> 00:39:02,770
But they are also more similar to one another relative to other animals than you know many

649
00:39:02,770 --> 00:39:05,090
animals uh in the animal kingdom.

650
00:39:05,250 --> 00:39:10,050
Um the degree of paternal investment in offspring is way higher uh in humans than you see

651
00:39:10,050 --> 00:39:11,330
in many other animals.

652
00:39:11,570 --> 00:39:15,040
Um the we without a doubt have a parabonding psychology.

653
00:39:15,200 --> 00:39:19,360
We without a doubt have substantial similarities between men and women in that parabonding

654
00:39:19,360 --> 00:39:20,080
psychology.

655
00:39:20,160 --> 00:39:26,160
Uh and the sophistication with which we look for mates, with which we uh uh

656
00:39:26,400 --> 00:39:32,240
maintain relationships, look for alternative relationships, et cetera, is uh uh mind

657
00:39:32,320 --> 00:39:32,880
boggling.

658
00:39:32,960 --> 00:39:34,720
So there's just so much more to the story.

659
00:39:34,960 --> 00:39:37,920
Once you once you have this foundation, it's a good foundation to have, it's a good

660
00:39:37,920 --> 00:39:38,560
starting point.

661
00:39:38,720 --> 00:39:44,330
But yes, we need to move beyond this starting point and and drill into the complexity of

662
00:39:44,330 --> 00:39:49,610
what is going on with with human mating psychology beyond, you know, male, female sex uh

663
00:39:49,770 --> 00:39:51,210
sexual psychology.

664
00:39:51,770 --> 00:39:52,970
Yeah, agreed completely.

665
00:39:53,130 --> 00:39:58,090
And and I there's also you throw in the sort of like perverse incentives of academia where,

666
00:39:58,410 --> 00:40:04,400
you know, to get a job, to get tenure, you need a a sort of baseline level of productivity,

667
00:40:04,480 --> 00:40:07,440
you need to be getting papers out the door on a pretty regular basis.

668
00:40:07,600 --> 00:40:09,280
And so I don't blame people, right?

669
00:40:09,600 --> 00:40:15,280
Like if you're a young human mating researcher, you know you need a certain number of

670
00:40:15,280 --> 00:40:18,640
papers to stay alive or make it to the next stage.

671
00:40:18,800 --> 00:40:19,920
Like, what are you gonna do?

672
00:40:20,080 --> 00:40:25,440
Are you gonna pick the easy topic that you know is gonna result in some kind of finding

673
00:40:25,440 --> 00:40:29,760
that someone is gonna publish somewhere, or are you gonna go on a limb and you know try to

674
00:40:29,760 --> 00:40:34,510
make a bold hypothesis about how something works that may or may not pan out.

675
00:40:34,910 --> 00:40:39,310
Um so you know it it's the safe sex differences is the safe pick.

676
00:40:39,470 --> 00:40:45,070
Uh yeah I mean you you seem to have escaped the gravitational pull of this process, at

677
00:40:45,070 --> 00:40:50,270
least in your in your research on you know mate preference integration, uh

678
00:40:50,590 --> 00:40:52,190
desirability covariation.

679
00:40:52,270 --> 00:40:54,680
This stuff is not sex differentiated.

680
00:40:54,760 --> 00:40:55,880
And you can correct me if I'm wrong.

681
00:40:55,960 --> 00:41:00,120
The mate preference integration, this is exists in both men and women.

682
00:41:00,280 --> 00:41:06,120
Uh you we have these wide variety of of things that we're looking for in a partner, whether

683
00:41:06,120 --> 00:41:11,400
it be looks, kindness, uh shared culture, uh intelligence, whatever.

684
00:41:11,560 --> 00:41:13,640
Uh we have all of these desired preferences.

685
00:41:13,800 --> 00:41:16,840
We the mind needs some way to integrate them.

686
00:41:17,150 --> 00:41:20,270
And what you're after is how does it integrate them?

687
00:41:20,430 --> 00:41:24,750
Uh it's actually uh a a really tough question to answer.

688
00:41:24,910 --> 00:41:26,270
It's not obvious what the solution is.

689
00:41:26,350 --> 00:41:30,190
There are many candidate ways that the mind can integrate these preferences.

690
00:41:30,270 --> 00:41:34,270
Um so this is a clear aspect of our mating psychology that does not appear to have strong

691
00:41:34,270 --> 00:41:35,710
sex differentiation.

692
00:41:35,950 --> 00:41:39,220
Um it's uh deeply computational.

693
00:41:39,540 --> 00:41:44,100
Um you cannot study this problem except in computational terms.

694
00:41:44,420 --> 00:41:46,260
How to integrate different preferences?

695
00:41:46,340 --> 00:41:49,380
Like I I don't see an alternative way of thinking about that topic.

696
00:41:49,620 --> 00:41:54,980
So it's intrinsically computational, intrinsically non-sex differentiated, and you went in

697
00:41:54,980 --> 00:41:58,340
this direction and you you're successful.

698
00:41:58,420 --> 00:42:01,780
You're at Santa Barbara professor, uh almost 10 years now.

699
00:42:01,940 --> 00:42:04,500
Uh how did you escape the gravitational pull?

700
00:42:05,140 --> 00:42:09,910
Well, I I don't know that I fully escaped it because along the way I've been publishing sex

701
00:42:10,070 --> 00:42:11,670
differences stuff too, right?

702
00:42:11,990 --> 00:42:15,110
Uh so my first paper was on sex differences and preferences.

703
00:42:15,190 --> 00:42:19,190
You know, we had a big replication paper in 20 whatever, 2016.

704
00:42:19,590 --> 00:42:24,470
You know, so it it has been that has been old, reliable for me too, right?

705
00:42:24,630 --> 00:42:30,560
Like, um, but yeah, we've been doing that on the side of some more risky stuff

706
00:42:30,560 --> 00:42:33,280
that that has kind of just happened to pan out.

707
00:42:33,600 --> 00:42:37,760
Um which is, you know, a a strategy I I would recommend to my students.

708
00:42:37,920 --> 00:42:42,880
And I I try to try try to um to advise them through.

709
00:42:43,040 --> 00:42:48,320
Um so I mean where that stuff comes from is yeah, what I this is the self serving part,

710
00:42:48,400 --> 00:42:52,400
like what I would sincerely hope ends up becoming kind of like a third phase of human

711
00:42:52,400 --> 00:42:53,680
mating research.

712
00:42:53,840 --> 00:42:59,630
Um which is like this is a good, a good example of why focusing so much on sex differences

713
00:42:59,790 --> 00:43:05,710
really hurt us because there was this, you know, 20, 30 years of research on mate

714
00:43:05,790 --> 00:43:11,070
preferences, which is basically take a questionnaire that asks people, you know, what do

715
00:43:11,070 --> 00:43:12,590
you want your ideal partner to look like?

716
00:43:12,750 --> 00:43:16,110
They just say, I want them to have these features, I don't want them to have those

717
00:43:16,110 --> 00:43:16,830
features.

718
00:43:17,100 --> 00:43:21,660
And then you know, you show there's a sex difference in how people respond to those some of

719
00:43:21,660 --> 00:43:22,060
those questions.

720
00:43:22,140 --> 00:43:24,380
You write the paper, you send it off, you call it a day.

721
00:43:24,540 --> 00:43:27,180
Uh and people were doing that for 20, 30 years.

722
00:43:27,500 --> 00:43:32,700
And people kind of forgot to ask, do those

723
00:43:32,700 --> 00:43:36,940
preferences actually get reflected in behavior?

724
00:43:37,180 --> 00:43:42,140
Like when you look at the partners people actually choose, do they really pursue those

725
00:43:42,140 --> 00:43:42,540
things?

726
00:43:42,700 --> 00:43:45,110
Uh And then they didn't entirely forget to do that.

727
00:43:45,190 --> 00:43:49,190
I mean, so there were some studies that tried to get at that with like hypothetical choice

728
00:43:49,190 --> 00:43:50,070
paradigms.

729
00:43:50,230 --> 00:43:52,230
You know, here's like two profiles.

730
00:43:52,390 --> 00:43:53,670
Which profile do you choose?

731
00:43:53,750 --> 00:43:56,150
Or they they would look at things like personals ads.

732
00:43:56,230 --> 00:44:01,190
Do you see these sex differences reflected in the kinds of personals ads people post or or

733
00:44:01,190 --> 00:44:02,070
respond to?

734
00:44:02,710 --> 00:44:07,430
Um, you know, David had looked a little bit at uh David Buss had looked at a little bit at

735
00:44:07,880 --> 00:44:11,960
do people's actual chosen partners reflect the things that they say that they want?

736
00:44:12,120 --> 00:44:15,480
Although, you know, there's all kinds of methodological problems with that.

737
00:44:15,800 --> 00:44:19,240
You don't necessarily know just because your partner matches your preferences, you don't

738
00:44:19,240 --> 00:44:23,480
know necessarily that's because your preferences cause that choice versus you said you

739
00:44:23,480 --> 00:44:25,400
wanted those things because your partner had them.

740
00:44:25,880 --> 00:44:29,800
So there had been like a little bit of work throughout the years just sort of like as but

741
00:44:29,800 --> 00:44:33,160
it was so it's sort of seen as just like a validation of the preferences.

742
00:44:33,450 --> 00:44:36,730
It wasn't seen as like a research topic in and of itself.

743
00:44:36,890 --> 00:44:42,890
Like, can we actually predict people's behavior on the basis of these abstract preferences

744
00:44:42,970 --> 00:44:44,170
they say they have?

745
00:44:44,810 --> 00:44:48,970
Uh, so that people were so interested in the sex differences they just kind of forgot about

746
00:44:48,970 --> 00:44:50,170
that more basic question.

747
00:44:50,410 --> 00:44:56,410
Until about the mid-2000s, there happened to be like a series of papers from

748
00:44:56,620 --> 00:45:02,140
as far as I'm aware, totally disconnected research groups that all use the same

749
00:45:02,140 --> 00:45:04,140
methodology to test this question.

750
00:45:04,380 --> 00:45:10,220
There was uh you know Peter Todd and colleagues in Germany, there's Rob Kurzban, uh, and

751
00:45:10,220 --> 00:45:11,740
then there was Paul Eastwick.

752
00:45:12,140 --> 00:45:17,740
Um, all around the same time, had the same thought we can use speed dating,

753
00:45:17,970 --> 00:45:23,250
which was like you know, a popular new invention at the time, new ish invention at the

754
00:45:23,250 --> 00:45:23,490
time.

755
00:45:23,650 --> 00:45:28,370
You can use speed dating as like a natural experiment to test do people actually choose the

756
00:45:28,370 --> 00:45:31,170
partners that they say they want on these abstract preference questionnaires.

757
00:45:31,570 --> 00:45:35,010
So they would administer the same kinds of questionnaires that people are using for this

758
00:45:35,010 --> 00:45:37,330
preference research just before a speed dating event.

759
00:45:37,410 --> 00:45:40,770
So they'd have either they would arrange one or they would work with a company.

760
00:45:40,930 --> 00:45:46,210
You know, you'd have 10 to 20 people who all showed up, single people interested in being

761
00:45:46,210 --> 00:45:51,700
in a relationship, they all talk to each other in little five to 10 minute

762
00:45:51,700 --> 00:45:52,340
sessions.

763
00:45:52,580 --> 00:45:55,780
And then afterwards, they just say, Do you want to go on a date with that person?

764
00:45:55,940 --> 00:45:56,500
Yes or no?

765
00:45:56,660 --> 00:46:01,060
And it's a perfect little, in theory, it's a perfect little mating experiment, right?

766
00:46:01,140 --> 00:46:04,260
You can see really quickly a lot of decisions that one person makes.

767
00:46:04,340 --> 00:46:09,220
And you can see, do they actually say, Yes, I want to date the person who has the features

768
00:46:09,220 --> 00:46:12,260
I just said I wanted on that abstract preference questionnaire?

769
00:46:12,500 --> 00:46:16,590
And from those initial studies, the answer seemed to be no.

770
00:46:17,070 --> 00:46:23,070
Uh, that people were not, by and large, you know, knowing what a person's preferences were

771
00:46:23,070 --> 00:46:28,750
before that speed dating event did not give you a lot of statistical power to predict the

772
00:46:28,750 --> 00:46:30,990
people they actually said yes to in that event.

773
00:46:31,150 --> 00:46:36,510
And that was kind of uh that that was a big moment in mating research too.

774
00:46:36,590 --> 00:46:39,390
Like that that is perplexing, right?

775
00:46:39,550 --> 00:46:39,950
Yes.

776
00:46:40,190 --> 00:46:43,600
Um and and people took that in a lot of different directions, right?

777
00:46:43,680 --> 00:46:49,280
So I think the the sort of Kurzman interpretation was

778
00:46:49,280 --> 00:46:53,280
something between, you know, maybe you're not quite getting to know this person enough,

779
00:46:53,440 --> 00:46:57,440
maybe speed dating is activating more of a short-term mating context.

780
00:46:57,520 --> 00:47:00,160
And so your long-term preferences don't apply.

781
00:47:00,400 --> 00:47:04,570
Uh, I think at one point he speculated maybe, and he did have some evidence for this.

782
00:47:04,730 --> 00:47:10,250
Like maybe there are these sort of consensual preferences that matter, but these individual

783
00:47:10,250 --> 00:47:12,810
differences and preferences, maybe that's just noise.

784
00:47:12,970 --> 00:47:18,570
Um, and you would see that, like, you know, if you stratify the speed dating events by, for

785
00:47:18,570 --> 00:47:22,730
example, like age or professional status, you would see, you know, people went to the speed

786
00:47:22,730 --> 00:47:26,640
dating events that sort of catered to their general desires.

787
00:47:26,800 --> 00:47:30,240
But then within those dates, within those events, you couldn't necessarily predict the

788
00:47:30,240 --> 00:47:31,680
specific person each person chose.

789
00:47:32,000 --> 00:47:36,320
So maybe there's some sort of like general preference for age or something like that.

790
00:47:36,480 --> 00:47:39,040
But like your is specifically doesn't matter.

791
00:47:39,280 --> 00:47:42,640
Is the idea there that it's not that mate preferences don't matter?

792
00:47:42,800 --> 00:47:46,640
It's that the ones that matter are a part of human nature and a part of human mating

793
00:47:46,640 --> 00:47:51,890
psychology, and the ones that individuals vary on, at least as we can judge based on their

794
00:47:51,890 --> 00:47:53,970
questionnaire responses, those don't matter.

795
00:47:54,130 --> 00:47:57,810
But that doesn't is that isn't to say that preferences in general don't matter.

796
00:47:58,370 --> 00:47:59,570
That's one interpretation.

797
00:47:59,810 --> 00:48:00,050
Yeah.

798
00:48:00,290 --> 00:48:03,090
And I think that's something that Kurzman kind of floated.

799
00:48:03,330 --> 00:48:03,650
I don't know.

800
00:48:03,730 --> 00:48:04,850
I don't know if that's fair.

801
00:48:05,010 --> 00:48:08,050
He might disagree with, he would disagree with whatever I say because he's Kurzman.

802
00:48:08,770 --> 00:48:14,290
But uh, you know, that's may maybe one read I would put into his interpretation.

803
00:48:14,610 --> 00:48:18,820
You know, the the Todd and colleagues' interpretation was, you know, there is a preference

804
00:48:18,820 --> 00:48:23,380
in there somewhere that matters, but it's not what people are able to verbalize.

805
00:48:23,460 --> 00:48:29,060
Whatever people are verbalizing, that's just some sort of like weird, you know, ad hoc like

806
00:48:29,300 --> 00:48:30,500
folk theory of what they want.

807
00:48:30,900 --> 00:48:33,460
So it's not the preferences don't matter, it's that we're measuring them the wrong way.

808
00:48:33,620 --> 00:48:34,500
The measurements suck.

809
00:48:34,740 --> 00:48:34,980
Okay.

810
00:48:35,140 --> 00:48:35,380
Yeah.

811
00:48:35,540 --> 00:48:35,780
Yeah.

812
00:48:35,860 --> 00:48:38,900
And then the Eastwick interpretation was that preferences don't matter.

813
00:48:39,700 --> 00:48:40,980
People don't know what they want.

814
00:48:41,140 --> 00:48:45,860
And he's really like come to a point where like he's really kind of arguing that like

815
00:48:45,940 --> 00:48:49,270
attraction might be fundamentally unpredictable.

816
00:48:49,510 --> 00:48:54,230
Um and and he would argue, he he also has kind of come around.

817
00:48:54,470 --> 00:48:57,910
I don't think he sees it this way, but I see it as him coming around at the sort of

818
00:48:57,910 --> 00:48:59,670
Curzbanian view.

819
00:48:59,830 --> 00:49:04,950
Um, where he argues like, in order to show that a preference matters, you need to show that

820
00:49:04,950 --> 00:49:06,790
the individual differences and preferences matter.

821
00:49:06,870 --> 00:49:12,070
So you need to show that, like, because you value age more than I do, because you value

822
00:49:12,070 --> 00:49:15,990
older partners more than I do, you choose older partners more often than I do.

823
00:49:16,240 --> 00:49:20,880
But if you show that like the average preference for older partners, if you show that on

824
00:49:20,880 --> 00:49:24,400
average people have a preference for older partners, like he would count that as there not

825
00:49:24,400 --> 00:49:26,480
being a preference, which I think is bizarre.

826
00:49:26,640 --> 00:49:28,240
Because yeah, how would you measure that?

827
00:49:28,800 --> 00:49:30,640
Yeah, how would you get there otherwise?

828
00:49:31,040 --> 00:49:32,080
Uh yeah.

829
00:49:32,240 --> 00:49:37,600
I I think if you show that humans in general tend to choose older partners, you have shown

830
00:49:37,600 --> 00:49:39,520
that humans have a preference for older partners.

831
00:49:39,680 --> 00:49:42,400
And that's that's how we measure preferences in non-human animals, right?

832
00:49:42,480 --> 00:49:46,830
We show that in general prefer peacocks with more elaborate tails, right?

833
00:49:47,070 --> 00:49:48,430
We more elaborate training.

834
00:49:48,830 --> 00:49:52,990
I mean, my my intuition just hearing this is I uh maybe I'm wrong.

835
00:49:53,070 --> 00:49:54,110
You can correct me if I'm wrong.

836
00:49:54,350 --> 00:49:56,990
The most plausible one to me is just the measurement suck.

837
00:49:57,150 --> 00:50:02,350
That, like, yeah, I would obviously expect preferences to matter um in shaping behavior,

838
00:50:02,510 --> 00:50:07,000
uh, but I don't think I know what my preferences are deep down.

839
00:50:07,160 --> 00:50:10,760
I don't think most people have access to that information.

840
00:50:11,320 --> 00:50:13,960
Um at least in any straightforward sense.

841
00:50:14,040 --> 00:50:17,240
You know, I uh when I'm attracted to someone, I know it when I see it, but I don't know

842
00:50:17,240 --> 00:50:20,520
that I can articulate what it is about that person that drew me to them.

843
00:50:20,680 --> 00:50:23,240
And maybe people just don't have conscious access to this.

844
00:50:23,770 --> 00:50:26,490
Or or if you do, like it's a restricted range thing too.

845
00:50:26,570 --> 00:50:27,610
It sounds like that was the other thing.

846
00:50:27,770 --> 00:50:31,690
So, like, you know, people, there's a there are studies of people s arguing, well, look,

847
00:50:31,770 --> 00:50:36,410
like using drugs doesn't affect life outcomes because their sample is college students.

848
00:50:37,370 --> 00:50:39,610
You know, and that's a restricted range issue, right?

849
00:50:39,690 --> 00:50:43,290
You know, it's a sub it's a bias sample of everybody is high functioning enough to be in

850
00:50:43,290 --> 00:50:43,690
college.

851
00:50:43,850 --> 00:50:49,610
But if you looked across from homeless people to um to successful people and you looked at

852
00:50:49,610 --> 00:50:51,370
drug use, you would find a different result.

853
00:50:51,450 --> 00:50:51,850
So yeah.

854
00:50:52,250 --> 00:50:52,650
Yeah, totally.

855
00:50:52,810 --> 00:50:52,890
Yeah.

856
00:50:53,040 --> 00:50:56,400
And and normally he has made that argument in the context of the speed dating stuff, right?

857
00:50:56,480 --> 00:51:00,400
Like, especially in these like speed dating studies of college students, which a lot of

858
00:51:00,400 --> 00:51:04,240
these are, you know, yeah, it's not a random sample of humanity that's showing up to these

859
00:51:04,240 --> 00:51:05,120
speed dating events.

860
00:51:05,280 --> 00:51:05,840
It's yes.

861
00:51:06,080 --> 00:51:10,640
Again, especially for these college students, it's mostly other young, relatively wealthy,

862
00:51:10,720 --> 00:51:13,440
relatively successful college students that you're picking among.

863
00:51:13,520 --> 00:51:15,600
And so yeah, there's just not a lot of restriction of range.

864
00:51:15,680 --> 00:51:20,330
So he he he did a study where they literally like they intentionally tried to expand the

865
00:51:20,330 --> 00:51:22,970
range of people in the speed dating events beyond just college students.

866
00:51:23,050 --> 00:51:26,730
Like they literally like intentionally went out and recruited like gas station attendants

867
00:51:26,730 --> 00:51:29,050
to participate alongside the college students.

868
00:51:29,610 --> 00:51:33,850
And they did see they did find evidence in that case that that preferences were more

869
00:51:33,850 --> 00:51:38,330
predictive when you increase the the types of people who are showing up to these events.

870
00:51:39,370 --> 00:51:44,380
But the point is you know this this was a huge uh

871
00:51:44,860 --> 00:51:46,060
puzzle, right?

872
00:51:46,460 --> 00:51:52,300
Um and I think there's now a a good handful of people who have been

873
00:51:52,300 --> 00:51:57,740
weighing in on this sort of emerging debate on what actually predicts people's mate choice

874
00:51:57,740 --> 00:52:02,780
behavior and why do these speed dating studies come out the way that they do.

875
00:52:03,130 --> 00:52:08,570
And I I don't think a clear consensus I have my opinions, um, but I don't think a clear

876
00:52:08,570 --> 00:52:11,130
consensus has emerged and it's been really exciting.

877
00:52:11,210 --> 00:52:17,130
I and this is this is a much again as as much as I value obviously like I got

878
00:52:17,130 --> 00:52:22,810
into evolutionary psychology because of that sort of like second phase 90s era mating

879
00:52:22,970 --> 00:52:23,770
research.

880
00:52:24,010 --> 00:52:29,220
That I think this has been a much more interesting and productive direction

881
00:52:29,780 --> 00:52:33,700
than maybe what was happening in a lot of the like early 2000s.

882
00:52:33,780 --> 00:52:39,700
Uh and what it like, I think the field has like come to a point where, yeah, we can

883
00:52:39,860 --> 00:52:43,940
now be asking serious questions about how the psychology of human mating work.

884
00:52:44,260 --> 00:52:45,380
How does it work?

885
00:52:45,540 --> 00:52:48,340
Um, and what sorts of predictions can we actually make?

886
00:52:48,500 --> 00:52:52,740
Um, you know, for my part, I think there's a lot of things going on.

887
00:52:53,230 --> 00:52:58,590
Uh I think speed dating just sucks as an institution.

888
00:52:59,470 --> 00:53:03,070
I mean there is some evidence that you know people do form relationships in speed dating

889
00:53:03,070 --> 00:53:03,470
events.

890
00:53:03,630 --> 00:53:09,310
So I don't think it's like totally worthless, but yeah, it's a really, really brief

891
00:53:09,310 --> 00:53:11,070
exposure to a person.

892
00:53:11,630 --> 00:53:15,790
I think when you know saying yes or no to someone at the end of a speed date is not really

893
00:53:15,790 --> 00:53:16,590
a mate choice.

894
00:53:16,670 --> 00:53:20,190
It's it's just like, yeah, I'd be willing to talk to that person more.

895
00:53:21,240 --> 00:53:25,160
And it's it's probably a pretty you're getting a pretty noisy snapshot of what that person

896
00:53:25,160 --> 00:53:29,400
is like, and you're pretty you're making a pretty you know low commitment bid.

897
00:53:29,640 --> 00:53:29,880
Yeah.

898
00:53:30,120 --> 00:53:34,680
So I don't know that we should expect preferences to predict those choices all that much.

899
00:53:35,080 --> 00:53:35,400
Sure.

900
00:53:35,560 --> 00:53:39,560
And especially if you think from an evolutionary perspective, this is such an artificial

901
00:53:39,560 --> 00:53:39,960
context.

902
00:53:40,120 --> 00:53:44,200
Throughout our evolutionary history, we almost certainly would have had tons of exposure to

903
00:53:44,200 --> 00:53:48,370
the person to a person before attempting to form a romantic relationship with him.

904
00:53:48,530 --> 00:53:53,090
So this is just such a weird artificial context to study mating.

905
00:53:53,250 --> 00:53:53,570
Yeah.

906
00:53:53,730 --> 00:53:54,050
Yeah.

907
00:53:54,210 --> 00:53:54,450
Yeah.

908
00:53:54,610 --> 00:53:57,330
And this, I mean, this by the way is how I got into this work, right?

909
00:53:57,410 --> 00:53:59,570
So I was originally, I was interested in human mating.

910
00:53:59,650 --> 00:54:00,370
I was in grad school.

911
00:54:00,450 --> 00:54:02,370
I was thinking about doing totally different stuff.

912
00:54:02,530 --> 00:54:03,730
And then all these papers came out.

913
00:54:03,890 --> 00:54:06,450
Paul Eastwick was at UT at the time.

914
00:54:06,770 --> 00:54:11,410
Uh, so I was having, you know, face-to-face interactions with him when he was saying, you

915
00:54:11,410 --> 00:54:13,400
know, these preferences don't matter.

916
00:54:13,560 --> 00:54:19,480
I also think like to be honest, I think there's there's part there's a bit of I there's a

917
00:54:19,480 --> 00:54:25,320
bit of ideology here um in that I think some of the people, I won't

918
00:54:25,320 --> 00:54:31,240
name names, but some of the people who are highly invested in this debate, um, I think

919
00:54:31,240 --> 00:54:34,920
they're very excited about these findings, especially these speed dating findings where

920
00:54:34,920 --> 00:54:39,790
preferences don't seem to predict choice very well because, you they have this sort of

921
00:54:39,790 --> 00:54:43,390
ideological opposition to evolutionary psychology as a discipline.

922
00:54:43,550 --> 00:54:48,590
And mate preferences have been, you know, one of the key success stories of evolutionary

923
00:54:48,590 --> 00:54:49,150
psychology.

924
00:54:49,310 --> 00:54:53,870
So if you're able to show that these preferences don't predict choices, well, that, you

925
00:54:53,870 --> 00:54:56,910
know, that disproves evolutionary psychology, right?

926
00:54:56,990 --> 00:54:58,830
That takes a lot of the wind out of our sails.

927
00:54:58,910 --> 00:55:01,390
That undoes one of our major success stories.

928
00:55:01,630 --> 00:55:06,340
So I think there are people who are highly invested in demonstrating that preferences don't

929
00:55:06,340 --> 00:55:10,740
predict choice just because they want to undermine evolutionary psychology as a field.

930
00:55:10,900 --> 00:55:15,620
Um, and I I think that's that partly got me interested in this just because I was like

931
00:55:15,620 --> 00:55:17,380
annoyed as a partisan.

932
00:55:17,940 --> 00:55:21,940
Annoyed at these people trying to like take a pot shot at our field.

933
00:55:22,180 --> 00:55:27,690
Um and I also think it's it's just kind of like a really it is an annoying just kind of

934
00:55:27,690 --> 00:55:32,090
crappy rhetorical position because it's you know if you want to find a null result it's not

935
00:55:32,090 --> 00:55:37,770
that hard to do right um yeah arguing for the null is is a really weak uh

936
00:55:37,930 --> 00:55:42,170
rhetorical position but I think just because evolutionary psychology is controversial

937
00:55:42,170 --> 00:55:45,290
enough for for reasons that we've earned in many ways.

938
00:55:45,370 --> 00:55:49,050
Yeah um I think there's a lot of people who are willing to tolerate kind of crappy

939
00:55:49,050 --> 00:55:54,160
arguments and crappy data in the surface of undermining this unlikable field.

940
00:55:54,480 --> 00:56:00,400
It's it's such a bizarre way to gratify yourself intellectually, because if that's correct,

941
00:56:00,640 --> 00:56:06,400
that the most biologically important decision we can make throughout our entire

942
00:56:06,400 --> 00:56:12,000
lifetimes is essentially random, if that's correct, that not only demolishes evolutionary

943
00:56:12,000 --> 00:56:17,930
psychology, that demolishes evolutionary theory, sexual selection, modern biology as we

944
00:56:17,930 --> 00:56:18,410
know it.

945
00:56:18,570 --> 00:56:22,810
Like that is devastating to our understanding of reality itself.

946
00:56:23,210 --> 00:56:25,050
That that is not something to celebrate.

947
00:56:25,210 --> 00:56:30,010
That is something to say, like, holy shit, we really need to think twice before we

948
00:56:30,650 --> 00:56:32,170
advance this position.

949
00:56:32,330 --> 00:56:38,280
Like, shouldn't we be trying to evaluate the plausibility of our hypotheses

950
00:56:38,280 --> 00:56:44,120
in light of how consistent they are with existing knowledge before we go out and and argue

951
00:56:44,120 --> 00:56:44,440
for them?

952
00:56:44,520 --> 00:56:44,840
Right.

953
00:56:45,000 --> 00:56:50,360
Like it should have basic evolutionary plausibility, basic consistency with everything we

954
00:56:50,360 --> 00:56:51,960
know about how the world works.

955
00:57:00,280 --> 00:57:03,690
But yeah, I mean I th I think the people who feel this way probably don't see it that way.

956
00:57:03,770 --> 00:57:07,690
I think they see it as like I I probably I don't know I don't know what they think.

957
00:57:07,770 --> 00:57:09,370
I can't get into their heads because I'm not them.

958
00:57:09,450 --> 00:57:14,250
But you know, I think they probably see it as like i evolutionary theory is still fine, but

959
00:57:14,250 --> 00:57:15,050
we're humans, right?

960
00:57:15,130 --> 00:57:20,250
We're smarter, we have free will and consciousness, and so we're freed from our genetic

961
00:57:20,250 --> 00:57:21,370
puppet strings.

962
00:57:21,640 --> 00:57:22,600
Yeah, it's so dumb.

963
00:57:22,840 --> 00:57:23,000
Yeah.

964
00:57:23,240 --> 00:57:28,280
So I mean so we have this really interesting result, which is that preferences don't appear

965
00:57:28,280 --> 00:57:31,960
to matter, at least when you measure them in speed dating contexts, and you ask people on

966
00:57:31,960 --> 00:57:34,120
questionnaires what they're looking for in a partner.

967
00:57:34,360 --> 00:57:36,360
We floated a number of solutions to the puzzle.

968
00:57:36,520 --> 00:57:37,640
Maybe the measurements suck.

969
00:57:37,720 --> 00:57:39,080
Maybe speed dating is weird.

970
00:57:39,160 --> 00:57:43,080
Maybe preferences don't actually matter, and we're just picking it random uh when it comes

971
00:57:43,080 --> 00:57:46,040
to our most biologically important uh decision we can make.

972
00:57:46,200 --> 00:57:51,350
Um, or maybe it's it's human nature that matters, but individual variation doesn't matter

973
00:57:51,350 --> 00:57:51,750
as much.

974
00:57:51,910 --> 00:57:53,670
Maybe there are unseen forces at play.

975
00:57:53,750 --> 00:57:56,470
Maybe we don't have conscious awareness of our mate preferences.

976
00:57:56,630 --> 00:58:00,230
Out of all of these different possibilities, all these different buckets, where are you

977
00:58:00,230 --> 00:58:03,350
putting uh your vote in?

978
00:58:03,590 --> 00:58:07,030
What do you what do you what do you think is the most likely solution to this puzzle if

979
00:58:07,030 --> 00:58:07,670
there is one?

980
00:58:07,990 --> 00:58:10,390
I I think there's a bit of a lot of things going on.

981
00:58:10,630 --> 00:58:12,630
Um I think speed dating just sucks.

982
00:58:12,740 --> 00:58:16,180
Uh and I think you can partly see that there are other study designs.

983
00:58:16,260 --> 00:58:20,020
So, you know, there's been a couple of nice longitudinal papers that have come out in the

984
00:58:20,020 --> 00:58:20,820
last couple of years.

985
00:58:20,980 --> 00:58:25,780
For example, from like Tanya Gerlock's group, Lars Penko's group, uh, where you know you

986
00:58:25,780 --> 00:58:27,860
measure someone's preferences when they're single.

987
00:58:28,020 --> 00:58:30,420
One of them actually comes out of one of these speed dating studies.

988
00:58:30,500 --> 00:58:34,740
They manage to go back like 15 years after one of these speed dating studies, get the

989
00:58:34,740 --> 00:58:39,590
original speed daters, follow up with them, and then you know, ask them well who are you

990
00:58:39,590 --> 00:58:44,790
with now uh and they were able to use their preferences from that speed dating study 15

991
00:58:44,790 --> 00:58:49,510
years ago and use that to try to predict you know who do they end up with 15 years later.

992
00:58:49,670 --> 00:58:49,910
Interesting.

993
00:58:50,630 --> 00:58:52,710
And they do predict right so okay.

994
00:58:52,950 --> 00:58:57,590
Yeah yeah it's not you know it's not huge but there is a significant correlation between

995
00:58:57,590 --> 00:59:01,350
what you were looking for in a partner you know I forget maybe I'm forgetting the details

996
00:59:01,430 --> 00:59:04,550
but it's something like 15 years ago and who you're actually with now.

997
00:59:04,720 --> 00:59:05,680
Um, and you can do that.

998
00:59:05,760 --> 00:59:08,800
They've also done that on like a shorter time scale, like a three-month time period.

999
00:59:08,880 --> 00:59:12,080
You know, I ask you what you're looking for now when you're single, come back with you

1000
00:59:12,080 --> 00:59:13,200
three months later.

1001
00:59:13,360 --> 00:59:16,960
Um, and your preferences from three months ago predict what your partner is like now.

1002
00:59:17,120 --> 00:59:20,880
We haven't published this yet, but you know, Dave knows my student Carlos has just

1003
00:59:20,880 --> 00:59:21,920
replicated this.

1004
00:59:22,480 --> 00:59:28,430
Um, so preferences can predict future choices when you are looking at, and Lauren

1005
00:59:28,510 --> 00:59:29,950
Campbell has a similar paper.

1006
00:59:30,030 --> 00:59:34,830
Uh, when you're looking at sort of naturalistic real world choices that are not, you met

1007
00:59:34,830 --> 00:59:37,870
this person for five minutes, do you want to see them again?

1008
00:59:38,270 --> 00:59:42,430
It's an actual real world mate choice out, you know, in free ranging humans.

1009
00:59:42,590 --> 00:59:46,350
Um, their their preference, their response to these preference questionnaires do predict

1010
00:59:46,350 --> 00:59:48,030
what their later partners look like.

1011
00:59:48,270 --> 00:59:53,630
Um, I think a lot of the measurement in these preference uh these speed dating studies just

1012
00:59:53,630 --> 00:59:54,190
sucks.

1013
00:59:54,740 --> 00:59:59,620
This is, again, I think an artifact of being so focused on sex differences.

1014
00:59:59,700 --> 01:00:05,140
And also, I think honestly, coming out of this personality psych tradition where,

1015
01:00:05,540 --> 01:00:10,900
you know, you're only ever thinking about abstract latent

1016
01:00:10,900 --> 01:00:14,820
variables, uh, but you're not necessarily thinking about like what does that latent

1017
01:00:14,820 --> 01:00:20,210
variable mean in terms of an information processing variable in the mind.

1018
01:00:21,010 --> 01:00:25,330
So people have been studying preferences for a really long time, but have been really

1019
01:00:25,330 --> 01:00:28,370
unclear on what a preference is supposed to be.

1020
01:00:28,610 --> 01:00:32,130
And the result of that is if you look at the way people measure preferences across the

1021
01:00:32,130 --> 01:00:34,210
literature, it's super heterogeneous.

1022
01:00:34,610 --> 01:00:39,330
So some people, you know, two different people will say they're studying the same thing.

1023
01:00:39,490 --> 01:00:43,380
They'll say they're doing the same, uh, they're replicating the same measure or uh

1024
01:00:43,460 --> 01:00:47,700
methodology but if you look at how are you measuring preferences in one case it'll be

1025
01:00:47,700 --> 01:00:52,340
something like well how important and a lot of the speed dating studies do this they'll ask

1026
01:00:52,500 --> 01:00:58,100
the participants how important is physical attractiveness to you in a partner one to ten

1027
01:00:58,580 --> 01:01:03,430
and then they'll ask you know how physically attractive is this partner you know, one to

1028
01:01:03,430 --> 01:01:03,670
10?

1029
01:01:03,750 --> 01:01:07,830
And then they'll ask, does your answer to that importance question predict the physical

1030
01:01:07,830 --> 01:01:10,070
attractiveness of the person that you chose?

1031
01:01:10,390 --> 01:01:16,230
And that it feels kind of reasonable if you don't think about it too hard, but asking how

1032
01:01:16,230 --> 01:01:21,030
important physical attractiveness is to you is not the same as asking how important or how

1033
01:01:21,030 --> 01:01:22,390
attractive you want your partner to be.

1034
01:01:22,550 --> 01:01:26,470
It could be very important to you that your partner is unattractive, right?

1035
01:01:26,740 --> 01:01:28,260
Those are distinct things.

1036
01:01:28,500 --> 01:01:33,140
Or it could just be that it's very important to me that my partner isn't a total uggo.

1037
01:01:33,380 --> 01:01:33,620
Yeah.

1038
01:01:33,780 --> 01:01:36,580
But once they're not a total ugly, like ever anything's fine, right?

1039
01:01:36,660 --> 01:01:36,900
Yeah.

1040
01:01:37,060 --> 01:01:37,220
Yeah.

1041
01:01:37,460 --> 01:01:39,940
So there's lots of like implicit models of preference.

1042
01:01:40,020 --> 01:01:40,180
Yeah.

1043
01:01:40,580 --> 01:01:40,980
Yeah.

1044
01:01:41,220 --> 01:01:46,100
That you could have that different people seem to have that aren't translated out clearly

1045
01:01:46,100 --> 01:01:46,980
to the measures.

1046
01:01:47,150 --> 01:01:50,750
And so a lot of these papers are saying like we're finding that preferences aren't

1047
01:01:50,750 --> 01:01:51,470
measuring choice.

1048
01:01:51,550 --> 01:01:53,550
But then you look at well, how did you measure preferences?

1049
01:01:53,630 --> 01:01:54,590
How did you measure choice?

1050
01:01:54,670 --> 01:01:56,270
And it's all over the place.

1051
01:01:56,430 --> 01:02:01,310
And it's not really like a theoretically motivated what should we expect the preference to

1052
01:02:01,310 --> 01:02:05,310
look like and how should we expect that to lead out to a choice.

1053
01:02:05,790 --> 01:02:09,390
So I think if you clean up the measurement a little bit, things look clearer.

1054
01:02:09,630 --> 01:02:12,990
And then this is also how I got into that preference integration stuff, right?

1055
01:02:13,070 --> 01:02:17,720
There's a major issue here too in that a lot of this work is strictly univariate.

1056
01:02:17,800 --> 01:02:21,320
So it's looking at what is your physical attractiveness preference?

1057
01:02:21,480 --> 01:02:23,560
How attractive is the person that you chose, right?

1058
01:02:23,720 --> 01:02:24,040
Yes.

1059
01:02:24,200 --> 01:02:27,400
Um, but we know people have more than just one preference, right?

1060
01:02:27,560 --> 01:02:31,160
Especially when you're looking at like a speed dating event, the most attractive person you

1061
01:02:31,160 --> 01:02:32,040
only talk to 10 people.

1062
01:02:32,120 --> 01:02:34,440
The most attractive person you talk to might have been a total asshole, right?

1063
01:02:34,520 --> 01:02:35,560
They might have been an idiot.

1064
01:02:35,880 --> 01:02:38,920
And you can only pick one person at the at the end of the day, right?

1065
01:02:39,080 --> 01:02:41,880
And one person does not have one trait, they have many traits.

1066
01:02:41,960 --> 01:02:46,410
Yeah, and you have to make a balancing consideration of all of their traits together.

1067
01:02:46,490 --> 01:02:51,130
Do I like this whole bundle of traits uh uh enough for me to mate with this person?

1068
01:02:51,290 --> 01:02:54,730
It's not just, oh, they're they meet my attractiveness threshold, therefore I will mate

1069
01:02:54,730 --> 01:02:54,890
with them.

1070
01:02:54,970 --> 01:03:00,570
It's no, this person is a hugely complicated entity with all sorts of traits and costs and

1071
01:03:00,570 --> 01:03:01,210
benefits.

1072
01:03:01,370 --> 01:03:06,090
How am I going to evaluate this complicated uh bundle of costs and benefits?

1073
01:03:06,250 --> 01:03:07,850
And that's what what you're interested in.

1074
01:03:08,250 --> 01:03:08,650
Exactly.

1075
01:03:08,730 --> 01:03:09,050
Yeah.

1076
01:03:09,130 --> 01:03:09,530
Yeah.

1077
01:03:09,770 --> 01:03:15,080
Um so yeah, my argument has been if you if you consider that sort of balancing act that

1078
01:03:15,080 --> 01:03:20,680
people are doing, you probably see clearer correspondence between uh

1079
01:03:20,840 --> 01:03:21,800
preferences and choice.

1080
01:03:21,880 --> 01:03:23,960
And I think we have some evidence of that.

1081
01:03:25,000 --> 01:03:27,640
And that's also been like a good way of shoeh I don't know.

1082
01:03:27,880 --> 01:03:31,720
I don't know how successful I've been in this, but I I I've seen it as a good way of

1083
01:03:31,720 --> 01:03:36,670
shoehorning in this more adaptationist, you know, psychological

1084
01:03:36,670 --> 01:03:40,990
design-oriented thinking into the mating psych literature in general, right?

1085
01:03:41,150 --> 01:03:45,950
Like we need to stop with this sort of purely statistical approach where we're just

1086
01:03:45,950 --> 01:03:50,510
predicting latent constructs from latent constructs and really ask hard questions about how

1087
01:03:50,510 --> 01:03:55,950
do we think the mind works and let let those hypotheses about the design of the mind guide

1088
01:03:55,950 --> 01:03:57,390
our predictions about people's behavior.

1089
01:03:57,720 --> 01:04:02,040
And what is a plausible function that the mind evolved to perform?

1090
01:04:02,280 --> 01:04:07,240
The mind did not evolve to pick uh dates at a speed dating uh

1091
01:04:07,880 --> 01:04:09,000
event, right?

1092
01:04:09,320 --> 01:04:11,480
Uh it evolved in a very different context.

1093
01:04:11,720 --> 01:04:16,440
And the decision that the mind evolved to make from an evolutionary standpoint is not is

1094
01:04:16,440 --> 01:04:22,040
this person uh you know uh a six or above on my attractiveness meter, therefore I'm gonna

1095
01:04:22,120 --> 01:04:22,600
mate with them.

1096
01:04:22,760 --> 01:04:27,770
It's okay, I can only pick one person to rear offspring with, right?

1097
01:04:28,090 --> 01:04:32,890
And they might be, you know, a bit uh more attractive than than usual, but a bit dumber

1098
01:04:32,890 --> 01:04:37,130
than usual, or a bit nicer than usual, or you know, a bit you know younger than I'd like,

1099
01:04:37,210 --> 01:04:37,770
or whatever.

1100
01:04:37,930 --> 01:04:41,530
Like there are all these considerations to make, and that is the decision that is of

1101
01:04:41,530 --> 01:04:42,810
evolutionary relevance.

1102
01:04:43,050 --> 01:04:48,010
That is the decision that natural selection is going to be selecting for in uh in terms of

1103
01:04:48,010 --> 01:04:50,730
making that decision uh well and effectively.

1104
01:04:50,970 --> 01:04:54,460
It's not the decision of are they hot enough for me?

1105
01:04:54,620 --> 01:04:59,980
It's is this a good choice for me to uh is this person a good choice for me to rear

1106
01:04:59,980 --> 01:05:05,740
offspring with cooperatively uh in a way that will uh increase my fitness in future

1107
01:05:05,740 --> 01:05:06,220
generations?

1108
01:05:06,300 --> 01:05:11,900
And that is a much more complicated decision to make than is this person hot enough?

1109
01:05:12,220 --> 01:05:12,540
Yeah.

1110
01:05:12,700 --> 01:05:13,020
Yeah.

1111
01:05:13,260 --> 01:05:13,580
Yeah.

1112
01:05:13,820 --> 01:05:19,410
It's also uh I think we've neglected a lot of the people who've

1113
01:05:19,730 --> 01:05:23,010
come at this, they're coming from sort of like social psych and cognitive psych

1114
01:05:23,170 --> 01:05:27,890
perspectives on decision making, where you're normally studying a thing where you're the

1115
01:05:27,890 --> 01:05:29,490
one only one making a decision, right?

1116
01:05:29,570 --> 01:05:35,490
Like you're you're the decision you make is like what brand of laundry detergent do I buy,

1117
01:05:35,650 --> 01:05:41,640
or what car do I buy, or like what I don't know, political party do I choose to support,

1118
01:05:41,720 --> 01:05:42,680
or something like that.

1119
01:05:42,920 --> 01:05:45,640
But these are very unilateral decisions.

1120
01:05:45,720 --> 01:05:49,160
Like you just get to pick what you want, but mating doesn't work that way, right?

1121
01:05:49,240 --> 01:05:54,440
You're making the choice in the context of a mating market where you have to pick a partner

1122
01:05:54,440 --> 01:05:56,200
and also be picked back by them.

1123
01:05:56,440 --> 01:06:01,410
And so, you know, it might not be rational to pick a partner that you don't expect to pick

1124
01:06:01,410 --> 01:06:02,370
you back as well.

1125
01:06:02,530 --> 01:06:06,370
And so you have to consider, like especially in a speed dating event where you're getting

1126
01:06:06,370 --> 01:06:10,530
immediate feedback from this person, uh, are they mutually interested in you?

1127
01:06:10,690 --> 01:06:10,930
Right.

1128
01:06:11,010 --> 01:06:15,730
There might be partners who in a different world maybe you would choose, but you know, by

1129
01:06:15,730 --> 01:06:19,970
virtue of uh their preferences, you decide to go elsewhere.

1130
01:06:20,210 --> 01:06:25,340
So you also need to consider the the broader, you know, social networks that people are

1131
01:06:25,340 --> 01:06:30,060
embedded in and the feedback systems that that happen in in mating market dynamics.

1132
01:06:30,540 --> 01:06:30,700
Yeah.

1133
01:06:30,940 --> 01:06:31,100
Yeah.

1134
01:06:31,180 --> 01:06:32,300
And totally.

1135
01:06:33,020 --> 01:06:34,860
A whole nother comp set of complications.

1136
01:06:35,180 --> 01:06:40,540
The costs of pursuing a mate that's not going to reciprocate your affections, uh, the costs

1137
01:06:40,540 --> 01:06:44,620
of being more into them than they are into you, or vice versa.

1138
01:06:45,420 --> 01:06:46,650
Yeah, it's huge.

1139
01:06:46,810 --> 01:06:52,730
I mean, so this brings us to another uh topic that you're interested in, which is your

1140
01:06:52,730 --> 01:06:54,490
desirability as a mate.

1141
01:06:54,810 --> 01:07:00,810
Um, so another potential solution to this puzzle of why uh mate preferences

1142
01:07:00,810 --> 01:07:06,490
don't appear to matter is that um it takes two to tango and you need the other partner to

1143
01:07:06,490 --> 01:07:07,530
reciprocate.

1144
01:07:07,690 --> 01:07:12,500
Um and perhaps the biggest mate preference of all we have is that the mate has to be into

1145
01:07:12,660 --> 01:07:13,140
you too.

1146
01:07:13,380 --> 01:07:15,700
That's probably the mother of all mate preferences, right?

1147
01:07:15,940 --> 01:07:18,100
If they're not into you, then then the deal is off.

1148
01:07:18,260 --> 01:07:18,500
Yeah.

1149
01:07:18,660 --> 01:07:18,980
Yeah.

1150
01:07:19,380 --> 01:07:25,300
Um so uh the problem is um, you know, if you are

1151
01:07:25,300 --> 01:07:30,500
not a very desirable mate, then you're going to have a very limited pool of of mates to

1152
01:07:30,500 --> 01:07:35,930
choose from, even if even if you really care about hotness as your number one criteria in a

1153
01:07:35,930 --> 01:07:39,530
mate, well, the most of the hot people aren't out there aren't willing to mate with you,

1154
01:07:39,610 --> 01:07:41,210
and you have to choose the hottest mate you can get.

1155
01:07:41,290 --> 01:07:45,210
So even if I really want a 10, and I say that on a questionnaire, I really want to mate

1156
01:07:45,210 --> 01:07:47,530
with a 10 and all the 10s reject me.

1157
01:07:47,690 --> 01:07:51,610
Well and and you know a three is the is the hottest partner I can get, well, there's going

1158
01:07:51,610 --> 01:07:56,240
to be a really low correlation between my hotness preference and and the the mate I end up

1159
01:07:56,240 --> 01:07:56,320
with.

1160
01:07:56,480 --> 01:07:58,080
But that's not because it doesn't matter to me.

1161
01:07:58,160 --> 01:08:01,040
You know, I still would probably prefer the three over the two over the one.

1162
01:08:01,200 --> 01:08:05,360
It's that there are constraints in the in the mating market based on my desirability.

1163
01:08:05,600 --> 01:08:11,520
Um so would you expect a greater correlation between preferences

1164
01:08:11,520 --> 01:08:15,600
and outcomes among more desirable mates than among less desirable mates?

1165
01:08:15,680 --> 01:08:17,200
And do you actually see that empirically?

1166
01:08:17,920 --> 01:08:20,000
I would argue you would expect that.

1167
01:08:20,160 --> 01:08:22,160
And we have evidence that that's true.

1168
01:08:22,320 --> 01:08:24,240
We have evidence that's true around the world.

1169
01:08:24,550 --> 01:08:30,470
I would argue, you know, that's a major reason to doubt uh the interpretations that people

1170
01:08:30,470 --> 01:08:32,550
have drawn of these feed dating studies.

1171
01:08:32,630 --> 01:08:34,950
Uh, but that tends to fall on deaf ears.

1172
01:08:35,830 --> 01:08:41,590
Um you know, I I I if I put my like tinfoil hat on, this is my like,

1173
01:08:41,830 --> 01:08:46,070
this is the problem the the the problems we're seeing in mating psychology are just

1174
01:08:46,070 --> 01:08:49,590
reflective of the broader problem with in psychology as a whole.

1175
01:08:49,830 --> 01:08:54,540
Um, which uh, you know, Dave, you both heard me talk about this probably endlessly, but uh

1176
01:08:54,620 --> 01:08:57,820
this is blog post uh from 2013.

1177
01:08:57,980 --> 01:08:59,500
I think Denny Borsboom.

1178
01:09:00,540 --> 01:09:04,780
Yeah, I just adore and he you know puts a name to this issue that I I hadn't heard before.

1179
01:09:04,860 --> 01:09:08,220
I don't know if he came up with it or not, but you know, he says psychologists are stricken

1180
01:09:08,220 --> 01:09:14,140
with theoretical amnesia, where like we just don't know what a scientific theory even looks

1181
01:09:14,140 --> 01:09:17,740
like, and we end up replacing scientific theories with statistical models.

1182
01:09:17,820 --> 01:09:21,660
Like we we can't see the difference between a statistical model and a theoretical model.

1183
01:09:21,820 --> 01:09:26,870
Uh, and that's so emblematic, I think, of what's happened in this mate choice literature,

1184
01:09:27,190 --> 01:09:33,190
where you know, people are so the whole approach has just been, I'm going to set

1185
01:09:33,270 --> 01:09:35,190
up this linear regression model.

1186
01:09:35,350 --> 01:09:39,990
And if preferences predict choice, then I should be able, I have these data where I've

1187
01:09:39,990 --> 01:09:43,590
collected people's preferences and I've collected the choices they've made.

1188
01:09:43,840 --> 01:09:48,640
if preferences predict choice, then the preference should predict the choice in this linear

1189
01:09:48,640 --> 01:09:49,440
regression model.

1190
01:09:49,520 --> 01:09:53,600
And I do my linear regression model and I get a p-value greater than 0.05.

1191
01:09:54,000 --> 01:09:56,720
So therefore, preferences don't predict choice.

1192
01:09:56,960 --> 01:10:01,360
And I think that makes a lot of sense if you don't think about it very hard.

1193
01:10:01,520 --> 01:10:06,400
But then when you do this harder work of thinking about, well, what is the problem people

1194
01:10:06,400 --> 01:10:08,080
are actually trying to solve?

1195
01:10:08,240 --> 01:10:11,360
What is the problem selection has actually built us to solve?

1196
01:10:11,570 --> 01:10:14,770
you think through like, how does the system have to work, right?

1197
01:10:14,850 --> 01:10:18,930
What are the things, yeah, selection would design an organism to pay attention to?

1198
01:10:19,090 --> 01:10:23,250
How would you integrate those all down into one decision value?

1199
01:10:23,410 --> 01:10:27,490
How would you enter a market where you've got a certain amount of buying power, you have a

1200
01:10:27,490 --> 01:10:32,050
limited number of options available to you, you've got to negotiate a match, given your

1201
01:10:32,050 --> 01:10:36,690
preferences, your you know, your affordances, their preferences, their affordances?

1202
01:10:37,250 --> 01:10:41,680
You know, how is that going to cohere into this, you know, singular choice?

1203
01:10:41,840 --> 01:10:45,920
I think when you think all of that through, when you build models of how all that has to

1204
01:10:45,920 --> 01:10:50,880
work, you can see the predictions of that theoretical model are not necessarily one, you

1205
01:10:50,880 --> 01:10:56,320
can see that linear regression model is a really impoverished picture of what's

1206
01:10:56,320 --> 01:10:57,840
happening in the world.

1207
01:10:58,000 --> 01:11:02,990
And it's like trivial to show this theoretical model can actually predict that you wouldn't

1208
01:11:02,990 --> 01:11:04,990
find anything in that linear regression model, right?

1209
01:11:05,150 --> 01:11:10,670
Like you, if you want to see what you're looking for, you need, you need a more complete

1210
01:11:10,670 --> 01:11:11,710
theoretical model.

1211
01:11:11,870 --> 01:11:17,630
Um, but I think psychologists are not capable of seeing the relevance of

1212
01:11:17,630 --> 01:11:19,550
that theoretical model to making predictions.

1213
01:11:19,710 --> 01:11:22,960
They don't understand that like your predictions should come out of a theory.

1214
01:11:23,040 --> 01:11:24,800
They shouldn't come out of a statistical model.

1215
01:11:25,200 --> 01:11:26,320
And that's crazy.

1216
01:11:26,640 --> 01:11:26,720
Yeah.

1217
01:11:26,800 --> 01:11:31,280
And Dan, you're doing some of that in the computational agent based modeling work.

1218
01:11:31,360 --> 01:11:32,000
Is that right?

1219
01:11:32,320 --> 01:11:32,560
Yeah.

1220
01:11:32,640 --> 01:11:34,640
I mean, I that's the point of the agent based models, right?

1221
01:11:34,720 --> 01:11:38,320
The point of the agent based models is it's a representation of the theoretical model that

1222
01:11:38,320 --> 01:11:43,840
allows you to you can parameterize it with data from real people and you can make

1223
01:11:43,840 --> 01:11:46,160
predictions about how those real people will behave.

1224
01:11:46,320 --> 01:11:50,310
And you can see, do their predictions line up with their real behavior?

1225
01:11:50,470 --> 01:11:55,590
And sometimes the predictions are that yeah, they won't choose a partner that matches what

1226
01:11:55,590 --> 01:11:56,790
they said their preference was.

1227
01:11:57,030 --> 01:11:59,430
That doesn't mean that they're not acting on their preference.

1228
01:11:59,510 --> 01:12:04,630
And that I think is a really subtle idea that's hard to get across to people who are just

1229
01:12:04,630 --> 01:12:06,310
used to looking at correlation tables.

1230
01:12:06,790 --> 01:12:07,030
Right.

1231
01:12:07,270 --> 01:12:10,950
And what are you thinking about in terms of so you're talking about the adaptive problem

1232
01:12:10,950 --> 01:12:12,630
and underlying psychology?

1233
01:12:12,870 --> 01:12:17,360
Um, you know, there's this, these, these backwards looking issues about why this result

1234
01:12:17,680 --> 01:12:18,800
didn't happen.

1235
01:12:19,120 --> 01:12:22,960
As you're going forward and thinking about what is the psychology?

1236
01:12:23,280 --> 01:12:26,640
And I know you've talked a bit about, you know, like love, right?

1237
01:12:26,800 --> 01:12:28,480
Um, or attraction.

1238
01:12:29,040 --> 01:12:34,640
Um, have you either personally or in the lab or you know, thinking down the road, are there

1239
01:12:34,640 --> 01:12:39,830
things that you're interested in tackling or that you've been thinking about uh sort of the

1240
01:12:40,070 --> 01:12:45,990
the system and how it works that we haven't been looking at yet uh yeah

1241
01:12:46,070 --> 01:12:51,590
it's I mean we've been doing so much work on choice um you know I I don't know that like

1242
01:12:51,670 --> 01:12:57,350
we're right about anything sure um I think we have some you know intriguing evidence I

1243
01:12:57,350 --> 01:13:02,230
think we've contributed helpfully I hope to some of these debates and you know we have

1244
01:13:02,230 --> 01:13:07,960
models of what kind of computational object are these preferences, which I

1245
01:13:07,960 --> 01:13:09,000
think work okay.

1246
01:13:09,240 --> 01:13:13,160
We have models of how these preferences are integrated, yeah, into like mate value

1247
01:13:13,160 --> 01:13:15,400
estimates, which I think work okay.

1248
01:13:15,640 --> 01:13:18,920
We have models of sort of the psychology of attraction.

1249
01:13:19,080 --> 01:13:23,240
How do you integrate those mate value estimates and the kind of feedback you're getting

1250
01:13:23,240 --> 01:13:26,520
from other people to guide who you actually pursue?

1251
01:13:26,760 --> 01:13:28,200
Those seem to work okay.

1252
01:13:28,360 --> 01:13:30,520
Like um, I think they can be improved.

1253
01:13:30,600 --> 01:13:35,610
Hopefully, there's there's more work to do, and hopefully we're like inspiring people to

1254
01:13:35,610 --> 01:13:36,970
have more of those conversations.

1255
01:13:37,050 --> 01:13:38,730
And I should say I'm not doing this work alone.

1256
01:13:38,810 --> 01:13:43,690
Like I'm you know in dialogue with these people, Paul Eastwick, Tony Gerlock, Jordan

1257
01:13:43,770 --> 01:13:47,050
Brandner, um, Norm Lee, Peter Todd.

1258
01:13:47,290 --> 01:13:51,690
Like uh I think it's been a really productive debate among all of us.

1259
01:13:51,850 --> 01:13:56,890
Um, and I think yeah, I I'm I'm I'm happy with a lot of the contribution contributions

1260
01:13:56,890 --> 01:13:57,770
we've made so far.

1261
01:13:57,930 --> 01:14:03,440
And I want to keep doing that, but yeah, I do I do want to push beyond choice

1262
01:14:03,760 --> 01:14:09,200
increasingly um and and try to get some purchase on what happens after

1263
01:14:09,200 --> 01:14:09,840
choice.

1264
01:14:10,000 --> 01:14:15,680
Um how do people make decisions about you know how to behave toward their

1265
01:14:15,680 --> 01:14:19,760
relationship partner I mean the way you said it before David is exactly right like it's a

1266
01:14:19,840 --> 01:14:24,090
it's a it's a it's a cooperative relationship it's just a cooperative relationship that's

1267
01:14:24,090 --> 01:14:30,010
focused on reproduction rather than like food production or yes uh you know other kinds of

1268
01:14:30,010 --> 01:14:35,770
things so uh you know how do people navigate this particular cooperative relationship how

1269
01:14:35,770 --> 01:14:39,290
do you decide how do you decide how to behave your towards your partner how do you decide

1270
01:14:39,290 --> 01:14:43,680
when to end a relationship when to pursue a different relationship Um, I'd really, really

1271
01:14:43,680 --> 01:14:45,680
love to study that kind of stuff.

1272
01:14:45,840 --> 01:14:50,800
Um, it feels like going out on a limb because I I I don't know that I have really clear

1273
01:14:50,800 --> 01:14:53,120
ideas about how that psychology works.

1274
01:14:53,440 --> 01:14:53,760
Yeah.

1275
01:14:54,080 --> 01:14:59,760
I mean, for my part, I'm shocked at the extent at how little integration there has been

1276
01:14:59,760 --> 01:15:05,470
between cooperation research and mating research, given that a mateship is

1277
01:15:05,470 --> 01:15:10,670
inherently a cooperative relationship, you would think that all of the lessons we learn

1278
01:15:10,670 --> 01:15:15,470
from cooperation and game theory would apply naturally to mating.

1279
01:15:15,630 --> 01:15:21,310
You know, not defecting in prisoners' dilemmas, you know, detecting cheaters, uh, you know,

1280
01:15:21,390 --> 01:15:27,230
uh uh uh contributing when uh the benefits outweigh the costs, uh calculating,

1281
01:15:27,310 --> 01:15:28,990
you know, are are they pulling their weight?

1282
01:15:29,070 --> 01:15:30,910
Is this is this a fair division of resources?

1283
01:15:31,070 --> 01:15:37,060
You know, all this stuff uh is the the warp and weft of our relationships from

1284
01:15:37,220 --> 01:15:42,180
from date anyone who's been in a relationship knows that it is a constant cooperative, uh

1285
01:15:42,420 --> 01:15:48,180
endlessly varying, uh uh endlessly negotiated relationship.

1286
01:15:48,660 --> 01:15:53,940
Um and there are things being traded, there are things being offered, uh uh things being

1287
01:15:53,940 --> 01:15:59,780
threatened to uh uh be taken away or or you know all all this stuff comes to bear.

1288
01:15:59,940 --> 01:16:05,030
So why hasn't cooperation uh been integrated with uh mating.

1289
01:16:05,510 --> 01:16:06,550
And parenting too.

1290
01:16:06,870 --> 01:16:08,790
And parent parenting, yeah, that's the big one.

1291
01:16:08,870 --> 01:16:12,630
That's the whole reason why this this machinery exists in the first place is that you know

1292
01:16:12,710 --> 01:16:16,390
these relationships ultimately exist so that we can parent together.

1293
01:16:16,550 --> 01:16:21,270
Uh wha why is there so little research on parenting, which which is the whole point of this

1294
01:16:21,430 --> 01:16:23,430
this relationship at the end of the day.

1295
01:16:23,670 --> 01:16:24,070
Yeah.

1296
01:16:24,230 --> 01:16:24,470
Yeah.

1297
01:16:24,710 --> 01:16:27,190
I I think part of it is historical artifact, right?

1298
01:16:27,270 --> 01:16:31,020
As we've been talking about sort of David Buss and mating research went one way.

1299
01:16:31,180 --> 01:16:35,100
You know, John T B and Lida Cosmities and Cooperation Research went another way.

1300
01:16:35,260 --> 01:16:35,500
Yeah.

1301
01:16:35,660 --> 01:16:40,460
David was very focused on this sort of like personality, psych just map these abstract

1302
01:16:40,620 --> 01:16:46,460
latent constructs and map relationships between these constructs, but not really digging

1303
01:16:46,460 --> 01:16:49,180
all that deep into the the psychological design.

1304
01:16:49,490 --> 01:16:53,490
very emphasis, very heavy emphasis on sex differences rather than design.

1305
01:16:53,650 --> 01:16:59,250
And so mating people very much go into that area and they don't necessarily read as much of

1306
01:16:59,250 --> 01:17:00,210
the cooperation stuff.

1307
01:17:00,370 --> 01:17:04,850
You know, Lita and John took cooperation in this very like cognitive science, very

1308
01:17:04,850 --> 01:17:09,250
cognitive psychology, you know, map decision rules of cooperation.

1309
01:17:09,410 --> 01:17:13,330
Um, and so I think just different kinds of people end up being interested in the different

1310
01:17:13,330 --> 01:17:15,650
topics and they they pick different questions.

1311
01:17:15,890 --> 01:17:21,500
Um and I I think there is a lot to learn uh in mating psychology from

1312
01:17:21,500 --> 01:17:22,620
cooperation research.

1313
01:17:22,780 --> 01:17:26,780
And I've been really inspired by that, especially since coming to Santa Barbara, right?

1314
01:17:26,940 --> 01:17:31,500
Like the best mate choice models we have are reciprocity models, and they look almost

1315
01:17:31,500 --> 01:17:36,140
indistinguishable from the kinds of models you would use to model reciprocity and other

1316
01:17:36,140 --> 01:17:38,060
kinds of cooperative exchanges.

1317
01:17:38,220 --> 01:17:40,940
Uh so I think that's gonna be an obvious place to start.

1318
01:17:41,020 --> 01:17:44,380
And I have, you know, a new grad student starting in the fall who's interested in these

1319
01:17:44,380 --> 01:17:44,620
questions.

1320
01:17:44,700 --> 01:17:49,270
So I'm really hoping I can, you know, he and I can, this is a good opportunity for both of

1321
01:17:49,270 --> 01:17:52,950
us maybe to dig into like how do we study relationships from this adaptationist

1322
01:17:52,950 --> 01:17:53,590
perspective.

1323
01:17:53,750 --> 01:17:58,230
Um I will say my impression, which is maybe ignorant, because again I'm a mating guy, I'm

1324
01:17:58,230 --> 01:17:59,350
not a cooperation guy.

1325
01:17:59,510 --> 01:18:05,110
Um but my impression is a lot of the cooperation literature is very focused on

1326
01:18:06,390 --> 01:18:11,350
relatively, how do I say this, kind of like isolated cooperative dilemmas?

1327
01:18:11,510 --> 01:18:17,500
Like how do you make choices in this cooperative scenario, but isn't as

1328
01:18:17,500 --> 01:18:19,900
focused on relationships per se?

1329
01:18:20,300 --> 01:18:20,700
Yeah.

1330
01:18:20,860 --> 01:18:23,500
So it's like, you know, how do you have this?

1331
01:18:23,660 --> 01:18:29,420
Uh and that's maybe not entirely fair, but like, how do you have like a sort of how do you

1332
01:18:29,420 --> 01:18:33,900
navigate a repeated prisoner's dilemma kind of situation is maybe the closest you would get

1333
01:18:33,900 --> 01:18:39,170
to like a relationship, but like a relationship is a bunch of different cooperative

1334
01:18:39,170 --> 01:18:39,810
dilemmas.

1335
01:18:40,050 --> 01:18:40,370
Yes.

1336
01:18:40,450 --> 01:18:40,690
Yes.

1337
01:18:40,930 --> 01:18:42,210
All with the same person.

1338
01:18:42,370 --> 01:18:48,130
And like there is something complicated about like playing multiple games with the

1339
01:18:48,130 --> 01:18:52,530
same person across multiple different sorts of different resource types.

1340
01:18:52,690 --> 01:18:53,570
And yes.

1341
01:18:54,210 --> 01:18:59,100
What does the ledger look like when it's like, yeah, time spent parenting versus time

1342
01:18:59,100 --> 01:19:03,740
spent, you know, foraging versus time spent on sex and stuff like that.

1343
01:19:03,900 --> 01:19:06,780
Like it's yeah, it's it's a mindfuck.

1344
01:19:06,860 --> 01:19:11,340
Uh and it it speaks again to this issue we've been bumping into, which is the clash between

1345
01:19:11,340 --> 01:19:14,940
the complexity of reality and the crudeness of our methods.

1346
01:19:15,260 --> 01:19:15,900
Yeah.

1347
01:19:16,780 --> 01:19:21,470
Um and I think there's a theme too of the history.

1348
01:19:21,790 --> 01:19:26,590
I've almost I've always thought about like there's like a provisional evps and evpsy

1349
01:19:26,750 --> 01:19:28,510
proper, like pep and ep.

1350
01:19:29,070 --> 01:19:31,710
Um and it's and it's sort of it was this thing.

1351
01:19:31,790 --> 01:19:35,630
Like I remember reading David's BBS paper, and I remember people being like, Well, this is

1352
01:19:35,630 --> 01:19:37,310
great, but you need more data, right?

1353
01:19:37,470 --> 01:19:43,390
And like really it was an incredible thing of that generation to to provide data

1354
01:19:43,800 --> 01:19:49,080
And even for Alita and John's work, like the cheater detection work, the domain general

1355
01:19:49,080 --> 01:19:50,520
versus domain specific thing.

1356
01:19:50,600 --> 01:19:53,240
You know, that was the analog of the sex differences thing.

1357
01:19:53,400 --> 01:19:57,240
But I oftentimes a lot of eager students will come in and they want to be like, well, I

1358
01:19:57,240 --> 01:19:59,000
want to show something's domain specific.

1359
01:19:59,560 --> 01:20:03,640
And I think like one of the things we're we're kind of the theme we're we're we're talking

1360
01:20:03,640 --> 01:20:09,250
about is that this the the the third wave sort of or this of like

1361
01:20:09,490 --> 01:20:12,450
proper thing is, well, no, you just do a task analysis, right?

1362
01:20:12,530 --> 01:20:18,130
It's like nobody's thought about, well, how do you model a family as a relationship or

1363
01:20:18,530 --> 01:20:19,410
reciprocity thing?

1364
01:20:19,490 --> 01:20:22,290
So there's no domain-specific or general argument to be made.

1365
01:20:22,370 --> 01:20:24,210
It's that you've got to come up with this de nouveau.

1366
01:20:24,610 --> 01:20:25,490
It's not a measure.

1367
01:20:25,570 --> 01:20:27,410
It's not a personality survey.

1368
01:20:27,490 --> 01:20:29,570
Um, it's not a waste and task.

1369
01:20:29,890 --> 01:20:35,040
You're not reaffying the measure, you're actually going adaptive problem task analysis

1370
01:20:35,040 --> 01:20:35,280
first.

1371
01:20:35,360 --> 01:20:36,320
And you're exactly right, Dan.

1372
01:20:36,560 --> 01:20:40,080
I think like the incentives, the perverse incentives, and this is what the Burzroom paper,

1373
01:20:40,160 --> 01:20:44,800
too, is like if you don't have data, uh, and if you don't have a lot of papers with a lot

1374
01:20:44,800 --> 01:20:48,000
of data, then it's really hard to be competitive.

1375
01:20:48,080 --> 01:20:51,600
And actually, what we're arguing is that you need, no, you need to like derive what you

1376
01:20:51,600 --> 01:20:53,920
should be looking for with a task analysis.

1377
01:20:54,080 --> 01:20:59,430
And, you know, and and how would you study that is down the road from what is it you should

1378
01:20:59,430 --> 01:21:00,870
be looking for in the first place.

1379
01:21:01,030 --> 01:21:06,790
So um so no, I think like that's that theme of going from sort

1380
01:21:06,790 --> 01:21:12,390
of a task analysis adaptive problem first as opposed to reaffying the measures um

1381
01:21:12,630 --> 01:21:18,470
or the arguments that were necessary to like make Evpsych uh even uh

1382
01:21:19,030 --> 01:21:25,030
part of the discussion scientifically yeah yeah and I I mean it this connects something to

1383
01:21:25,110 --> 01:21:29,940
something you were saying earlier David about like these sort of early conversations, the

1384
01:21:29,940 --> 01:21:31,940
kinds of people that they attract to the field.

1385
01:21:32,100 --> 01:21:37,460
Um again, going back to Dawn, this is a quote that around here gets attributed to Dawn a

1386
01:21:37,460 --> 01:21:40,340
lot, but I'm never actually sure what the source of this quote is.

1387
01:21:40,500 --> 01:21:44,740
But he apparently would say that you can't understand what someone is saying unless you

1388
01:21:44,740 --> 01:21:46,340
understand who they're arguing with.

1389
01:21:46,580 --> 01:21:50,740
Um, and I think if you look back at a lot of the early F-Syc work, exactly like what you're

1390
01:21:50,740 --> 01:21:55,950
just saying, Dave, There's part of it that is sketching out what

1391
01:21:55,950 --> 01:21:57,550
adaptationism should look like.

1392
01:21:57,710 --> 01:22:02,030
This is this is what the adaptationist program for studying psychology should be.

1393
01:22:02,590 --> 01:22:08,110
But there's another part of it that is just, you know, applying that sort of stuff in the

1394
01:22:08,110 --> 01:22:12,350
background, but really just trying to establish the validity of this approach.

1395
01:22:12,590 --> 01:22:17,230
And so a lot of these early founders picked these particular topics, yeah, like sex

1396
01:22:17,230 --> 01:22:23,060
differences, like domain specificity, because they were like useful points of leverage for

1397
01:22:23,060 --> 01:22:26,020
showing that this adaptationist program was useful.

1398
01:22:26,180 --> 01:22:31,060
Um, and that was very successful in sort of like getting F-Sec in the door.

1399
01:22:31,220 --> 01:22:36,740
But then I think when you have these newer generations who maybe aren't as

1400
01:22:36,740 --> 01:22:42,610
familiar with who the interlocutors were at the time, they don't know who

1401
01:22:42,610 --> 01:22:47,810
people were arguing with when they were proposing sex differences or proposing arguments

1402
01:22:47,810 --> 01:22:51,650
about domain generality, domain specificity that they missed that, like, no, that was just

1403
01:22:51,650 --> 01:22:57,170
supposed to be a useful wedge to like sneak in this adaptationist program stuff.

1404
01:22:57,250 --> 01:22:59,810
So, like, we're we're past that now, hopefully.

1405
01:23:00,210 --> 01:23:05,170
Like enough people agree evolutionary psychology is a worthwhile thing to do.

1406
01:23:05,330 --> 01:23:09,280
And so we need to, we need to give up on these like old dead debates.

1407
01:23:09,520 --> 01:23:14,720
And we need to just apply this like adaptationist program that people, you know, put a lot

1408
01:23:14,720 --> 01:23:18,720
of work into crafting and just apply it to the topics we want to study now.

1409
01:23:18,880 --> 01:23:23,280
But I I think if if you weren't there for a lot of those conversations, it's it's easy to

1410
01:23:23,280 --> 01:23:25,600
miss that that's what we're supposed to be doing now.

1411
01:23:26,290 --> 01:23:27,810
Do you think that's happening, Dan?

1412
01:23:28,290 --> 01:23:29,970
Like like applying adaptationism?

1413
01:23:30,050 --> 01:23:34,770
I mean, do you think that that's effective or do you think um I don't.

1414
01:23:35,090 --> 01:23:35,810
I don't know.

1415
01:23:36,370 --> 01:23:38,610
I'm I'm I'm a little pessimistic.

1416
01:23:38,770 --> 01:23:39,410
I don't know.

1417
01:23:39,650 --> 01:23:45,570
I think um I think there are a lot of people who are in the field now because they

1418
01:23:45,570 --> 01:23:47,250
just like making people angry.

1419
01:23:47,410 --> 01:23:52,600
Um so they they just like those arguments they just like those debates and so you know,

1420
01:23:52,760 --> 01:23:57,880
they really just want to keep like banging the sex differences, pots and pans, and making

1421
01:23:57,880 --> 01:23:59,640
as much noise as possible.

1422
01:24:00,040 --> 01:24:04,040
Um, I I I don't know.

1423
01:24:04,440 --> 01:24:10,120
Uh you know, Dave, you know we've been recently cleaning out the the physical CEP lab

1424
01:24:10,120 --> 01:24:11,880
space, trying to prepare a move.

1425
01:24:12,040 --> 01:24:17,690
And it's been a trip like going through uh just like 30 years of

1426
01:24:18,090 --> 01:24:20,570
nothing that ever entered that room ever left it.

1427
01:24:20,730 --> 01:24:25,130
So there's just 30 years of like F-Syc history in this physical space.

1428
01:24:25,530 --> 01:24:31,370
We found like an old uh HBS program from like 1992

1429
01:24:31,450 --> 01:24:35,450
or something like that, and just like thumbing through the pages of that.

1430
01:24:35,770 --> 01:24:41,300
Like I think the quality of work is probably overall higher now than it was back then on a

1431
01:24:41,300 --> 01:24:42,420
lot of dimensions.

1432
01:24:42,740 --> 01:24:48,420
But I had the sense just from like a quick thumb through that there were a lot, there was

1433
01:24:48,420 --> 01:24:52,340
much more diversity of topic in that older program.

1434
01:24:52,420 --> 01:24:56,980
And there were a lot of people that were just like, I want to study this topic.

1435
01:24:57,060 --> 01:25:01,620
Like here's my attempt at an adaptationist approach to that topic.

1436
01:25:02,980 --> 01:25:07,790
And I feel like that doesn't happen as much at ACS these days.

1437
01:25:07,950 --> 01:25:12,430
I think there's a there's a much higher percentage that's just like I'm just gonna riff off

1438
01:25:12,430 --> 01:25:14,750
of this thing from the 90s.

1439
01:25:14,990 --> 01:25:18,190
Um and many fewer people not none.

1440
01:25:18,350 --> 01:25:22,670
I think there are there's some really good work out there that really makes me hopeful for

1441
01:25:22,670 --> 01:25:23,310
the future.

1442
01:25:23,470 --> 01:25:29,390
But I I worry that the the percentage of like adaptationist approaches is decreasing

1443
01:25:29,390 --> 01:25:29,870
over time.

1444
01:25:30,420 --> 01:25:32,020
I don't know what your responses are on that.

1445
01:25:32,500 --> 01:25:34,660
Adaptationist as compared to what?

1446
01:25:34,900 --> 01:25:39,220
So for for for those who who don't know, we should d briefly define adaptationism as a kind

1447
01:25:39,220 --> 01:25:45,060
of reverse engineering approach to uh the mind, um, where you try to th uh

1448
01:25:45,220 --> 01:25:50,420
think about what a a plausible adaptive problem would have been for our ancestors and map

1449
01:25:50,420 --> 01:25:52,740
out what a viable solution to that problem would be.

1450
01:25:52,820 --> 01:25:58,180
And then you make predictions based on on your model of what uh that effective solution

1451
01:25:58,180 --> 01:25:59,810
might look like very briefly.

1452
01:25:59,970 --> 01:26:05,250
Um uh so adaptation is you you you have been bemoaning the decline of

1453
01:26:05,250 --> 01:26:06,130
adaptationism.

1454
01:26:06,370 --> 01:26:08,610
Yeah yeah uh what what has been replacing it?

1455
01:26:08,770 --> 01:26:11,490
What what is it what is the uh the foil to it?

1456
01:26:11,970 --> 01:26:17,650
I I think um what it is is sort of like mainstream

1457
01:26:17,650 --> 01:26:21,810
psychology with just a sort of twist of evolution.

1458
01:26:21,970 --> 01:26:26,060
It's like yes yeah F Psych flavored LaCroix or something like that.

1459
01:26:27,100 --> 01:26:28,780
That's a I buy that.

1460
01:26:29,980 --> 01:26:33,260
It's a beautiful and hideous analogy at the same time.

1461
01:26:33,580 --> 01:26:33,820
Yeah.

1462
01:26:33,980 --> 01:26:35,980
It's you know, again, I I don't know.

1463
01:26:36,060 --> 01:26:38,380
I I I don't want to shit talk people to you.

1464
01:26:38,540 --> 01:26:41,580
Like, you know, people are doing their this is this is the place to do it, man.

1465
01:26:41,660 --> 01:26:43,740
This is the place where all the shit gets out.

1466
01:26:44,700 --> 01:26:45,740
It's just us three, man.

1467
01:26:45,980 --> 01:26:46,620
It's just us three.

1468
01:26:46,700 --> 01:26:48,780
It's just I love HBass.

1469
01:26:48,940 --> 01:26:54,410
It's my favorite conference, you know, and and God bless anyone who's who's out there

1470
01:26:54,410 --> 01:26:56,330
trying to do evolutionary psychology.

1471
01:26:56,410 --> 01:26:59,290
Um, and again, I think there are a lot of people out there really trying, but I I think

1472
01:26:59,290 --> 01:27:05,050
there are people who, again, they're just either just trying to stir controversy, they're

1473
01:27:05,050 --> 01:27:08,330
not really trying to eliminate how the mind works, they're just trying to say things that

1474
01:27:08,330 --> 01:27:10,170
makes people that will make people angry.

1475
01:27:10,410 --> 01:27:15,940
And then I think there are people who are kind of just like they're just applying the sort

1476
01:27:15,940 --> 01:27:21,700
of same statistical theoretical amnesia from like mainstream social psych or cognitive

1477
01:27:21,700 --> 01:27:27,220
psych or developmental psych or whatever, but towards questions that historically have been

1478
01:27:27,220 --> 01:27:33,140
of interest to evolutionary psychologists, but not even questions, like topic areas.

1479
01:27:33,300 --> 01:27:37,300
They're taking a topic area that has been popular in evolutionary psychology and just doing

1480
01:27:37,300 --> 01:27:38,740
mainstream psychology on it.

1481
01:27:38,900 --> 01:27:43,750
And because it's a mating topic, it sort of gets classified as evolutionary psychology.

1482
01:27:43,910 --> 01:27:45,110
But there's no task analysis.

1483
01:27:45,430 --> 01:27:50,150
There's not really much consideration of like what is the specific adaptive problem that

1484
01:27:50,150 --> 01:27:51,270
you're studying here?

1485
01:27:51,350 --> 01:27:54,550
What's your evidence that this would have been a recurrent reproductive problem throughout

1486
01:27:54,630 --> 01:27:55,830
human evolutionary history?

1487
01:27:55,990 --> 01:27:56,310
Right.

1488
01:27:56,470 --> 01:28:02,150
There's no consideration of like what is a what are the possible psychological designs that

1489
01:28:02,150 --> 01:28:03,990
could actually have been good at solving this problem?

1490
01:28:04,070 --> 01:28:07,700
And how do you know that they actually would have been good at solving this problem?

1491
01:28:08,020 --> 01:28:13,540
And then how do those psychological designs interact with the features of the modern

1492
01:28:13,540 --> 01:28:16,340
environment that you think are relevant to generate behavior?

1493
01:28:16,580 --> 01:28:22,260
It's just like, well, David Buss found this sex difference in preferences, but

1494
01:28:22,420 --> 01:28:24,820
uh, you know, Tinder exists now.

1495
01:28:24,900 --> 01:28:28,820
And so nobody has asked, do these preferences also manifest on Tinder?

1496
01:28:28,990 --> 01:28:33,390
So we looked at people's Tinder choices and looked to see if the sex differences are there.

1497
01:28:33,870 --> 01:28:38,110
There's a much higher volume of that kind of stuff and a much lower volume of like, you

1498
01:28:38,110 --> 01:28:41,630
know, I'm I'm interested in, I don't know.

1499
01:28:41,870 --> 01:28:47,470
I mean I won't name names, but like I remember specifically showing you, Dave, in that

1500
01:28:47,470 --> 01:28:53,070
program uh some work of a person who I don't have a very high opinion of their current

1501
01:28:53,310 --> 01:28:53,870
watch.

1502
01:28:55,280 --> 01:28:58,640
and I wasn't aware of like the kind of stuff that they were doing back when they were

1503
01:28:58,640 --> 01:28:59,120
younger.

1504
01:28:59,680 --> 01:29:04,560
Um, and I I remember looking at their abstract and thinking, holy crap, like this really

1505
01:29:04,720 --> 01:29:04,800
good.

1506
01:29:06,880 --> 01:29:12,240
They were really swinging for the fences, they were really trying to come up with a deep

1507
01:29:12,480 --> 01:29:15,360
adaptationist theory of I don't even remember what the topic was.

1508
01:29:15,520 --> 01:29:16,720
It might have been parenting.

1509
01:29:16,960 --> 01:29:22,870
Like they're doing, you know, they were trying to do some serious evolutionary psychology

1510
01:29:22,870 --> 01:29:28,870
at one time, and then I don't know, they got hit in the head with a coconut and now do uh

1511
01:29:29,510 --> 01:29:31,190
really crazy stuff.

1512
01:29:31,430 --> 01:29:33,270
Uh now they're a provocateur.

1513
01:29:33,510 --> 01:29:35,190
You gotta watch it for those coconuts.

1514
01:29:35,510 --> 01:29:36,150
Yeah.

1515
01:29:36,790 --> 01:29:40,470
Um yeah, yeah.

1516
01:29:41,700 --> 01:29:42,020
Yeah.

1517
01:29:42,180 --> 01:29:43,300
Well that's depressing.

1518
01:29:43,540 --> 01:29:49,460
Um wha what are the parts of the field that give you hope to s you

1519
01:29:49,460 --> 01:29:52,660
know, we're starting to wrap things up or drift in that direction.

1520
01:29:52,980 --> 01:29:54,260
Be good to end on a high note.

1521
01:29:54,500 --> 01:29:56,900
What are the the trends that you see as positive?

1522
01:29:57,060 --> 01:29:59,540
Where do you see uh the hope?

1523
01:30:00,020 --> 01:30:00,340
Yeah.

1524
01:30:00,500 --> 01:30:04,820
I mean I I I think these discussions, like this this focus on this debate in the mate

1525
01:30:04,820 --> 01:30:06,420
choice area has been really positive.

1526
01:30:07,290 --> 01:30:11,370
I think that's pushed mating research in a much better direction than it was going.

1527
01:30:12,890 --> 01:30:14,330
I don't think I said Brendan Zietz's name.

1528
01:30:14,410 --> 01:30:17,690
Brendan Zieg has also been contributing to this literature in a really nice way.

1529
01:30:18,410 --> 01:30:19,050
Yeah.

1530
01:30:19,450 --> 01:30:21,610
So I think that stuff is positive.

1531
01:30:22,570 --> 01:30:26,490
And just behavior behavioral genetics, just for people who aren't familiar, bringing

1532
01:30:26,490 --> 01:30:31,770
behavioral genetics analysis into uh uh conversation with the mating psychology literature,

1533
01:30:31,850 --> 01:30:33,050
which I think is extremely useful.

1534
01:30:33,290 --> 01:30:33,930
Yeah, yeah.

1535
01:30:34,650 --> 01:30:38,620
Um, you know, I I I think cooperation stuff has always been going strong and that still

1536
01:30:38,620 --> 01:30:39,260
goes strong.

1537
01:30:39,420 --> 01:30:42,860
Um at HBest this last year, I thought HBest is last year was great.

1538
01:30:43,020 --> 01:30:46,300
Uh I thought it was one of the best programs I can remember in a while.

1539
01:30:46,380 --> 01:30:50,300
I don't know that I'm uh I don't know how popular of an opinion that is, but like in my

1540
01:30:50,300 --> 01:30:53,820
opinion, I I thought this was an extremely strong program, maybe too small of a program,

1541
01:30:53,980 --> 01:30:55,580
maybe a little too restrictive.

1542
01:30:55,740 --> 01:30:59,660
Um uh but uh uh I thought the overall quality was really good.

1543
01:30:59,740 --> 01:31:04,230
And I I was like really, really impressed with the stuff coming out of like the Paris

1544
01:31:04,230 --> 01:31:04,630
school.

1545
01:31:04,710 --> 01:31:05,350
Uh oh, yeah.

1546
01:31:06,070 --> 01:31:06,870
Paris school rules.

1547
01:31:07,270 --> 01:31:07,670
Yeah.

1548
01:31:07,830 --> 01:31:13,830
Um again, I think really inventive questions approached in a really just sober,

1549
01:31:14,470 --> 01:31:17,670
um dedicated, adaptationist way.

1550
01:31:17,750 --> 01:31:21,990
Um, I was so impressed with um a lot of the stuff coming out.

1551
01:31:22,150 --> 01:31:27,110
Um again, either the like sort of Toulouse, the sort of new there seemed to be like a kind

1552
01:31:27,110 --> 01:31:32,300
of new approach to cultural evolution that was cohering that like a lot of talks were, you

1553
01:31:32,300 --> 01:31:37,420
know, Nicola Bamar and um uh Leo Fitucci and

1554
01:31:37,980 --> 01:31:43,420
Singh and uh I think a new way of sort of bridging a sort of Santa Barbara style

1555
01:31:43,660 --> 01:31:49,500
Boye kind of perspective on cultural evolution with a sort of UCLA boy

1556
01:31:49,660 --> 01:31:52,700
Richardson Henrik style of thinking about cultural evolution.

1557
01:31:52,940 --> 01:31:57,980
Um I I hope that coheres into its own sort of moot like

1558
01:31:58,430 --> 01:32:03,950
perspective soon, because I I was just hearing things across those talks that I hadn't

1559
01:32:03,950 --> 01:32:07,790
quite heard as like commonalities and ways people were thinking about things yet.

1560
01:32:07,950 --> 01:32:09,710
And I think that's that's super exciting.

1561
01:32:09,790 --> 01:32:14,990
And I think that's going to be really good for yeah bridging a divide that I think has

1562
01:32:14,990 --> 01:32:18,110
gotten too big and and too weird.

1563
01:32:18,420 --> 01:32:19,380
Um totally.

1564
01:32:19,540 --> 01:32:21,780
And such an understudied area too.

1565
01:32:21,940 --> 01:32:27,220
Um, I remember so uh Tom Scott Phillips is another great scholar um who studies uh you know

1566
01:32:27,300 --> 01:32:29,620
the game theory of communication, evolution of language.

1567
01:32:29,780 --> 01:32:35,140
Uh and he recently I remember him remarking at how little work there was being done on

1568
01:32:35,140 --> 01:32:36,740
communication at HBS.

1569
01:32:37,140 --> 01:32:40,900
There's barely any work being done on communication, even though communication is basically

1570
01:32:40,900 --> 01:32:42,180
our superpower as a species.

1571
01:32:42,420 --> 01:32:45,730
It's like the main thing we do as an animal if we spend most of our time.

1572
01:32:45,970 --> 01:32:48,930
I mean, HBS is itself just a bunch of communication.

1573
01:32:49,810 --> 01:32:53,730
And how little we know about communication is kind of mind-boggling.

1574
01:32:54,290 --> 01:32:57,970
It should be at the front and center of what we're doing, and it's not there.

1575
01:32:59,330 --> 01:33:02,130
Similarly, you know, you're talking about the Paris School, Hugo Mercier.

1576
01:33:02,290 --> 01:33:08,130
It's a wonderful book, Not Born Yesterday, on our skepticism

1577
01:33:08,130 --> 01:33:09,090
of information.

1578
01:33:10,180 --> 01:33:13,860
You wouldn't expect us to be easily duped and easily exploited and manipulated.

1579
01:33:13,940 --> 01:33:19,940
So we have a sophisticated information-seeking psychology that is sensitive to the costs

1580
01:33:19,940 --> 01:33:25,300
of being manipulated and to people's competence and benevolence toward us.

1581
01:33:25,620 --> 01:33:26,580
Fascinating stuff.

1582
01:33:27,140 --> 01:33:31,540
He also has a theory of reasoning where reasoning evolved in this social interactionist

1583
01:33:31,540 --> 01:33:36,580
context where reasoning is not just this solitary thing that we do in our heads to arrive

1584
01:33:36,580 --> 01:33:42,410
at wisdom, but something that uh uh occurs between people, that we we use reasoning to

1585
01:33:42,410 --> 01:33:45,450
persuade other people and to justify our actions.

1586
01:33:45,690 --> 01:33:47,130
Uh that stuff is awesome.

1587
01:33:47,210 --> 01:33:50,890
And yet, as far as I'm aware, he's the only one working on reasoning.

1588
01:33:51,130 --> 01:33:56,890
Um as far as I'm aware, him and a handful of other people are the only ones working on our

1589
01:33:56,890 --> 01:34:01,960
skepticism toward communicated information and what that skeptical psychology should look

1590
01:34:01,960 --> 01:34:02,200
like.

1591
01:34:02,360 --> 01:34:06,600
And yet these are at the center of human existence, and we know barely anything about them.

1592
01:34:06,840 --> 01:34:12,280
So, yeah, uh the lopsidedness of what we're focused on uh as as a research

1593
01:34:12,280 --> 01:34:14,440
community is kind of startling.

1594
01:34:14,600 --> 01:34:18,680
Even within mate, I mean, I agree that mating should be, you know, front and center of of

1595
01:34:18,680 --> 01:34:20,600
of you know studies of human nature.

1596
01:34:20,680 --> 01:34:24,360
Mating is huge, it's one of the most important things going on in our lives.

1597
01:34:24,600 --> 01:34:29,010
And yet even within mating, the parts of mating that we're focusing on are the are the

1598
01:34:29,010 --> 01:34:30,130
least important parts of it.

1599
01:34:30,210 --> 01:34:32,050
We're we're focusing on choice, right?

1600
01:34:32,130 --> 01:34:32,850
Or attraction.

1601
01:34:33,010 --> 01:34:38,610
The initial feelings of attraction you feel towards someone and not parenting, which is

1602
01:34:38,610 --> 01:34:42,850
completely ignored, which is the whole purpose of of of mating, right?

1603
01:34:43,010 --> 01:34:47,170
And yet we know nothing about parenting and we know tons of crappy stuff about attraction

1604
01:34:47,170 --> 01:34:48,450
in a speed dating context.

1605
01:34:48,610 --> 01:34:54,400
That's basically uh so the the lopsidedness of of what our

1606
01:34:54,400 --> 01:34:57,840
priorities are in terms of what to study is is startling.

1607
01:34:59,280 --> 01:35:04,720
That said, the few people who are working on reasoning and communication and epistemic

1608
01:35:04,720 --> 01:35:08,560
vigilance are our skepticism of information, those people are doing awesome work.

1609
01:35:08,720 --> 01:35:12,890
It's really insightful, inspiring, beautiful work.

1610
01:35:13,130 --> 01:35:15,050
Um, people doing work on emotions.

1611
01:35:15,210 --> 01:35:17,450
Aaron Sell's work on anger is incredible.

1612
01:35:17,530 --> 01:35:21,370
Uh he recently did a guest talk uh at at our lab at UCLA.

1613
01:35:21,530 --> 01:35:23,450
Uh mind blowing stuff.

1614
01:35:23,530 --> 01:35:27,130
Uh Dan Sneezer doing work on pride and shame and cross cultural regularity.

1615
01:35:27,290 --> 01:35:28,410
That stuff's awesome.

1616
01:35:28,570 --> 01:35:32,250
Uh so there is there is a lot of good stuff happening.

1617
01:35:32,410 --> 01:35:37,050
I wish there were more of it, and I wish um the awesome stuff was growing.

1618
01:35:37,290 --> 01:35:39,320
Uh but it is there.

1619
01:35:39,880 --> 01:35:41,480
Jamie Krems and friendship.

1620
01:35:41,720 --> 01:35:42,120
Yeah.

1621
01:35:42,360 --> 01:35:42,920
Yeah.

1622
01:35:43,160 --> 01:35:48,280
Excellent stuff on friendship and how it's not just this dyadic uh uh

1623
01:35:48,520 --> 01:35:54,520
reciprocity relationship, but a complex uh uh uh dynamic where you have to uh figure out

1624
01:35:54,520 --> 01:35:58,600
whether you're more loyal to me than other people or you know what my relationship with you

1625
01:35:58,600 --> 01:36:01,800
says about my relationships to other people and when and thinking about friendship

1626
01:36:01,800 --> 01:36:07,510
networks, like that stuff is again this this clash between the complexity of

1627
01:36:07,510 --> 01:36:10,070
reality and the simplicity of our methods.

1628
01:36:10,310 --> 01:36:15,350
Um Jamie Krims is an excellent example of of looking at the actual complexity of

1629
01:36:15,350 --> 01:36:15,910
friendship.

1630
01:36:15,990 --> 01:36:18,550
Uh and we'll we'll talk to her on a on a on our next episode.

1631
01:36:18,630 --> 01:36:19,750
I'm excited about that.

1632
01:36:19,990 --> 01:36:24,870
Um but yeah, there is there are stars in in the darkness.

1633
01:36:25,900 --> 01:36:28,540
Dan, I have uh yeah, oh Dan, I have a question.

1634
01:36:28,700 --> 01:36:34,460
Uh if you could wave a magic wand, uh how would you uh what would be

1635
01:36:34,460 --> 01:36:38,780
different either about uh HBS or of psych or psychology?

1636
01:36:40,060 --> 01:36:41,100
Oh man.

1637
01:36:41,820 --> 01:36:47,810
Uh if I could wave a magic I mean, part of you know, we'll see

1638
01:36:47,810 --> 01:36:53,730
if our symposium at HBiscets uh shopping this talk around that is partly like if I could

1639
01:36:53,730 --> 01:36:59,090
wave a magic wand, I would I would yeah, force all psychologists to

1640
01:36:59,330 --> 01:37:04,610
express their hypotheses in the form of a formal adaptationist model.

1641
01:37:04,930 --> 01:37:09,920
Uh that you need to give a you know logico mathematical

1642
01:37:10,160 --> 01:37:15,840
computational formalism for what you think is the relative relevant adaptive problem,

1643
01:37:16,160 --> 01:37:22,160
and what you think are the designs that are you know reasonably good, improbably

1644
01:37:22,160 --> 01:37:24,320
good at solving that problem.

1645
01:37:24,800 --> 01:37:30,800
Um and how do those uh psychological models make predictions

1646
01:37:30,800 --> 01:37:32,560
about the kinds of behavior people will make?

1647
01:37:32,720 --> 01:37:38,690
Uh so yeah, I think I would love it if not all people would agree with me, I guess,

1648
01:37:38,770 --> 01:37:39,010
on this.

1649
01:37:39,090 --> 01:37:43,330
You know, we do have to be mindful uh in these conversations that HBS is not just

1650
01:37:43,330 --> 01:37:44,450
evolutionary psychology.

1651
01:37:44,610 --> 01:37:48,850
So I think, you know, our anthropology colleagues, especially our behavioral ecology

1652
01:37:48,850 --> 01:37:51,570
colleagues, have been studying a lot of these topics like parenting.

1653
01:37:51,730 --> 01:37:52,050
Yes.

1654
01:37:52,130 --> 01:37:53,730
Um that we've been neglecting.

1655
01:37:53,890 --> 01:37:54,210
Totally.

1656
01:37:54,370 --> 01:37:58,050
Uh I think they've been rightfully annoyed at us evolutionary psychologists for being,

1657
01:37:58,130 --> 01:38:03,240
yeah, so obsessed with like sex and dating to the exclusion of, yeah, these these very big

1658
01:38:03,240 --> 01:38:04,440
parts of human life as well.

1659
01:38:04,600 --> 01:38:05,640
Yeah, foraging.

1660
01:38:05,800 --> 01:38:06,280
Yeah.

1661
01:38:06,600 --> 01:38:06,920
Yeah.

1662
01:38:07,000 --> 01:38:07,400
Yeah.

1663
01:38:08,040 --> 01:38:13,640
So I think it's not necessarily H best's problem as a whole, as much as it is as like the

1664
01:38:13,640 --> 01:38:19,320
evolutionary psychologists have not been uh holding up their end of the bargain, maybe.

1665
01:38:19,560 --> 01:38:23,960
Um so I do want to give credit to our anthropology friends for doing that.

1666
01:38:24,040 --> 01:38:28,210
And I also, you know, so that's why part of me why I want to say like all submissions to

1667
01:38:28,210 --> 01:38:31,010
HBAS need to be explicitly adaptationist.

1668
01:38:31,170 --> 01:38:34,850
But like I think it's fine if the behavioral ecologists and maybe even the cultural

1669
01:38:34,850 --> 01:38:35,810
evolutionists aren't.

1670
01:38:35,890 --> 01:38:40,690
But at least maybe you should have to say what wing, what which of the three fields are you

1671
01:38:40,690 --> 01:38:41,250
submitting in?

1672
01:38:41,330 --> 01:38:45,570
And if you're submitting as an evolutionary psychologist, like you need to include a task

1673
01:38:45,570 --> 01:38:47,010
analysis in your submission.

1674
01:38:47,440 --> 01:38:49,120
That's actually a beautiful idea.

1675
01:38:49,280 --> 01:38:55,280
Um it's just just when you're filling out the form to submit a talk or symposium, there's

1676
01:38:55,280 --> 01:38:58,960
just a s a section on task analysis, adaptive problem, and you have to and you have to

1677
01:38:58,960 --> 01:39:01,280
input those, and that's the way you submit something.

1678
01:39:01,440 --> 01:39:04,160
I think potentially very interesting idea.

1679
01:39:04,400 --> 01:39:06,720
Um Yeah, might cut submissions a bit.

1680
01:39:07,280 --> 01:39:08,000
That's true.

1681
01:39:08,320 --> 01:39:13,760
Or it might force people to think in in terms of adaptationist you know frameworks.

1682
01:39:13,920 --> 01:39:14,560
Yeah.

1683
01:39:14,800 --> 01:39:16,170
Um, which might be a good thing.

1684
01:39:16,330 --> 01:39:16,570
I don't know.

1685
01:39:16,890 --> 01:39:17,050
Yeah.

1686
01:39:17,130 --> 01:39:20,730
Do you think it's a lack of knowledge and that if we just provide the knowledge or force

1687
01:39:20,730 --> 01:39:26,090
people to do it in their submission uploads but uh or is it are there perverse incentives

1688
01:39:26,090 --> 01:39:31,130
or structural things in the way too I think it's a bit of both.

1689
01:39:31,210 --> 01:39:37,140
But yeah I I think the the structural issue here is the perverse incentives I think should

1690
01:39:37,140 --> 01:39:38,420
not be understated, right?

1691
01:39:38,580 --> 01:39:43,380
Like I think it's it's just y you need papers, man, and it's so easy to publish a six

1692
01:39:43,460 --> 01:39:44,660
differences paper.

1693
01:39:44,820 --> 01:39:49,620
Uh it's so hard to take a lot of time trying to build a a really precise model of some

1694
01:39:49,780 --> 01:39:50,980
evolutionary system.

1695
01:39:51,300 --> 01:39:56,980
Um so yeah, I I don't blame people, you know, especially these days when resources in

1696
01:39:56,980 --> 01:39:58,340
academia are especially taxed.

1697
01:39:58,500 --> 01:40:00,580
Like to just go especially, yeah.

1698
01:40:00,660 --> 01:40:05,130
I mean I mean the the the line you said that has been haunting me is that a lot of the the

1699
01:40:05,130 --> 01:40:10,250
worst F Psych is just like um just psychology with an evolutionary twist, like a like a

1700
01:40:10,330 --> 01:40:13,930
like a LaCroix with evolutionary flavoring.

1701
01:40:15,130 --> 01:40:18,970
Uh and and I think you know part of that comes from the fact that, you know, we are

1702
01:40:18,970 --> 01:40:22,250
psychologists, we have to get jobs in in psychology departments.

1703
01:40:22,380 --> 01:40:26,860
A lot of people come into F Psych from psychology departments, and that has a way of

1704
01:40:26,860 --> 01:40:29,180
thinking, a methodology behind it.

1705
01:40:29,260 --> 01:40:33,420
And often it's the path of least resistance to just do psychology with an evolutionary

1706
01:40:33,420 --> 01:40:33,660
twist.

1707
01:40:33,740 --> 01:40:37,900
And that's the best way to get a job in a psychology department is to do things that are

1708
01:40:37,900 --> 01:40:41,660
recognizable to other psychologists, but have this cool twist that, you know, sets you

1709
01:40:41,660 --> 01:40:43,100
apart from other people.

1710
01:40:43,420 --> 01:40:49,270
Um so Yeah, and I think I mean I think there's other, like obviously, there's

1711
01:40:49,350 --> 01:40:52,950
like many good people in lots of areas of psychology who are trying to get away from what's

1712
01:40:52,950 --> 01:40:54,390
called effectology, right?

1713
01:40:54,470 --> 01:41:00,070
And there's fortunately one of the things in the theory crisis literature is this idea.

1714
01:41:00,470 --> 01:41:05,590
Um uh Iris von Rouge, I I I don't know how to say your last name, apologies, but you know,

1715
01:41:05,670 --> 01:41:09,270
it talks about you can't just take a bunch of effects and like cobble them together like if

1716
01:41:09,270 --> 01:41:13,300
you bunch like almost like a bunch of iron filings thrown into a magnetic field that it's

1717
01:41:13,300 --> 01:41:14,740
all going to coalesce around a theory.

1718
01:41:14,820 --> 01:41:18,820
Like that's not, if you look across the history of sciences, that's not effects, collecting

1719
01:41:18,820 --> 01:41:21,460
effects is not um the way, the way things work.

1720
01:41:21,540 --> 01:41:26,180
And so I do think um the the idea that you have to think about the underlying psychology

1721
01:41:26,180 --> 01:41:29,460
and the design, whether or not people take an evolutionary approach or not, that you're

1722
01:41:29,460 --> 01:41:34,430
getting at the underlying the invariance you want is how the system works and what its

1723
01:41:34,430 --> 01:41:35,070
function is.

1724
01:41:35,470 --> 01:41:38,350
And I think I think people are aware of that.

1725
01:41:38,510 --> 01:41:42,430
But yeah, I wonder, like even when I do task analyses here, like I've been I taught a grad

1726
01:41:42,430 --> 01:41:43,790
course this fall.

1727
01:41:44,030 --> 01:41:49,550
Um it's very much like, you know, there's a lot of uncertainty when you're doing a task

1728
01:41:49,550 --> 01:41:53,470
analysis is very much a creative process of and it's sort of brainstorming.

1729
01:41:53,550 --> 01:41:57,230
It's sort of, well, given what are all the sub problems entailed, you know, and just even

1730
01:41:57,230 --> 01:42:00,190
not starving to death, what are all the systems, what are all the functions?

1731
01:42:00,350 --> 01:42:05,720
And you can really see in students that there's a reluctance to not be wrong, to not say

1732
01:42:05,720 --> 01:42:08,280
something that they don't have already have evidence for.

1733
01:42:08,440 --> 01:42:13,880
Um, and I think like that's a real problem because you know that we're talking about, and

1734
01:42:13,880 --> 01:42:19,160
this is Borsboom's point, is that we need theory to derive what to look for in the first

1735
01:42:19,160 --> 01:42:19,320
place.

1736
01:42:19,400 --> 01:42:25,160
Like Dan, I think your work is some of the most lovely in terms of doing lots of

1737
01:42:25,160 --> 01:42:29,400
methods to derive what to look for ahead of time.

1738
01:42:29,750 --> 01:42:35,510
And I think we we've we've we've trained generations of students who don't feel like

1739
01:42:35,510 --> 01:42:41,270
they're allowed to say what we should be looking for unless you already have data for it.

1740
01:42:41,510 --> 01:42:46,470
And I think that sounds rigorous if you think about it for one second, but if you think

1741
01:42:46,470 --> 01:42:50,950
about it for longer than one second, um it becomes looking under it's the person looking

1742
01:42:50,950 --> 01:42:55,670
for their keys under the light where we're trivializing the things we're looking for

1743
01:42:55,750 --> 01:42:59,680
because we were only allowed to look for the things we already have data for.

1744
01:42:59,920 --> 01:43:05,840
And I think that's a real um structural issue of we have to

1745
01:43:05,840 --> 01:43:11,840
let a task analysis breathe and not request data from it right away, for example, is

1746
01:43:12,000 --> 01:43:12,880
what I think.

1747
01:43:13,920 --> 01:43:14,080
Yeah.

1748
01:43:14,240 --> 01:43:18,400
And we need a a healthier respect for theory in general.

1749
01:43:18,750 --> 01:43:22,110
Um not just more theory, because there's lots of crappy theories in psychology.

1750
01:43:22,190 --> 01:43:26,990
I don't I don't mean to like any theory, like uh a respect for for what a good theory is.

1751
01:43:27,310 --> 01:43:29,230
Um it's not a factor analysis.

1752
01:43:29,310 --> 01:43:32,670
I mean, there's there's a place for organizing disparate findings, and that can be

1753
01:43:32,670 --> 01:43:33,630
extremely useful.

1754
01:43:33,790 --> 01:43:38,510
But many theories, it's again this you're not allowed to theorize unless you have data, and

1755
01:43:38,510 --> 01:43:43,310
then it it's it's a uh it's a uh a a factor analysis.

1756
01:43:43,470 --> 01:43:45,060
Um It's not deductive.

1757
01:43:45,140 --> 01:43:45,780
It's induction.

1758
01:43:45,860 --> 01:43:50,260
It's just sort of here's what we have evidence for, and I will just characterize the common

1759
01:43:50,260 --> 01:43:54,260
variable or latent variable underlying these effects.

1760
01:43:54,420 --> 01:43:57,300
I think that kind of theorizing is allowed.

1761
01:44:00,260 --> 01:44:06,230
Yeah, I I don't, again, I I genuinely don't think a lot of psychologists are aware

1762
01:44:06,230 --> 01:44:07,670
of what a theory is.

1763
01:44:07,990 --> 01:44:13,590
Um, a lot of what gets called theory in psychology, yeah, is either a factor

1764
01:44:13,590 --> 01:44:19,590
analysis or yeah, it's like a string of empirical general generalizations,

1765
01:44:19,750 --> 01:44:19,990
right?

1766
01:44:20,070 --> 01:44:26,070
Like Murray at all 1975 found this, and Campbell et

1767
01:44:26,070 --> 01:44:26,230
al.

1768
01:44:26,470 --> 01:44:27,910
1980 found that.

1769
01:44:28,120 --> 01:44:33,880
And so, given those two observations, my hunch is you combine those two

1770
01:44:33,880 --> 01:44:37,480
facts, you know, a third fact should be true.

1771
01:44:37,640 --> 01:44:41,800
Or what we don't know what happens if you combine those two facts.

1772
01:44:41,880 --> 01:44:43,880
And so here's some possibilities.

1773
01:44:44,040 --> 01:44:49,960
Um, but they're not none of these are yeah, descriptions of how you think the

1774
01:44:49,960 --> 01:44:53,160
world works grounded in some sort of broader theoretical principle.

1775
01:44:53,240 --> 01:44:57,030
It's just either these things correlate.

1776
01:44:57,190 --> 01:45:03,110
And so here's yeah, here's the shared variance, or it's here's three things that

1777
01:45:03,110 --> 01:45:04,230
people have found before.

1778
01:45:04,470 --> 01:45:07,750
And so here's how they mash together.

1779
01:45:08,390 --> 01:45:09,030
Yeah.

1780
01:45:10,150 --> 01:45:15,910
Or or here's here's a an analogy to a the mind is a

1781
01:45:15,910 --> 01:45:17,510
symphony and there can be dissonant notes.

1782
01:45:17,590 --> 01:45:21,270
So there's cognitive dissonance, or you know, the mind is a hydraulic system and we need to

1783
01:45:21,270 --> 01:45:26,040
let out steam, so there's venting, and you know, like these kinds of uh glib analogies also

1784
01:45:26,040 --> 01:45:29,320
populate our our psychology in a troubling way, anyway.

1785
01:45:29,560 --> 01:45:33,720
I'll even take an analogy because an analogy is at least like makes it something

1786
01:45:35,480 --> 01:45:40,440
has an internal logic, and if you follow that logic out, it makes predictions that could be

1787
01:45:40,440 --> 01:45:41,640
right or wrong.

1788
01:45:42,360 --> 01:45:45,080
But like a path model doesn't really.

1789
01:45:45,720 --> 01:45:45,960
I know.

1790
01:45:46,120 --> 01:45:47,960
Most most theories aren't even wrong.

1791
01:45:48,280 --> 01:45:49,320
Yeah, yeah.

1792
01:45:49,570 --> 01:45:49,810
Yeah.

1793
01:45:50,290 --> 01:45:53,490
Uh Dan, any question that we should have asked you?

1794
01:45:55,570 --> 01:45:57,170
Uh that's a great question.

1795
01:45:57,410 --> 01:45:59,170
I should have anticipated that question.

1796
01:46:00,130 --> 01:46:02,290
Should we have asked you that very question?

1797
01:46:04,130 --> 01:46:06,050
Is there any question we shouldn't have asked?

1798
01:46:08,450 --> 01:46:10,050
Uh I don't know.

1799
01:46:10,290 --> 01:46:11,650
Or do you have a question for us?

1800
01:46:11,970 --> 01:46:15,500
This has been a great this has been a great uh been a great conversation.

1801
01:46:15,580 --> 01:46:15,980
I don't know.

1802
01:46:16,140 --> 01:46:18,300
Yeah, no, it's really nice to this is the thing.

1803
01:46:18,380 --> 01:46:21,340
This is also, I mean, like, this is part of the reason I'm doing this too.

1804
01:46:21,420 --> 01:46:25,660
It's very selfish on my part too, because it's just like you really like day to day you

1805
01:46:25,660 --> 01:46:30,940
just see people and you're like, I really respect people as scientists, present company

1806
01:46:31,100 --> 01:46:36,220
excluded, but um but uh no no for real like I mean I like you guys I deeply respect you

1807
01:46:36,220 --> 01:46:40,540
guys and uh and but then I you know we see each other and other things are going on and you

1808
01:46:40,540 --> 01:46:44,230
don't get a chance to talk about you know, like what are you actually thinking about and

1809
01:46:44,230 --> 01:46:45,030
thinking deeply.

1810
01:46:45,110 --> 01:46:49,910
And it's one of the things I love about being a scientist is that

1811
01:46:51,350 --> 01:46:56,470
the people you get to meet and and be with over time.

1812
01:46:56,870 --> 01:47:01,590
And like both of you are a great example of like, you know, when I when I see you in

1813
01:47:01,590 --> 01:47:07,430
person, it's like no time has changed or passed, you know, and it's just um and knowing

1814
01:47:07,430 --> 01:47:13,360
people who are sort of fellow travelers and getting to do it with people

1815
01:47:13,360 --> 01:47:18,320
like you it's just a real pleasure so it's nice to be able to talk um not about like the

1816
01:47:18,320 --> 01:47:22,000
mundane stuff but sort of about what you're thinking about it's one of the reasons I wanted

1817
01:47:22,000 --> 01:47:22,880
to do this.

1818
01:47:25,440 --> 01:47:30,160
Well I mean one question I can ask both of you this is something we I think the three of us

1819
01:47:30,160 --> 01:47:35,920
have talked about informally but but maybe we can just sort of make it all mutual knowledge

1820
01:47:36,080 --> 01:47:42,050
is like how do you think our field's stock is doing Are

1821
01:47:42,050 --> 01:47:42,930
we on the rise?

1822
01:47:43,010 --> 01:47:45,090
Are we are we flat?

1823
01:47:45,250 --> 01:47:46,370
Are we going down?

1824
01:47:46,770 --> 01:47:48,450
What's your impression?

1825
01:47:50,370 --> 01:47:50,850
Interesting.

1826
01:47:51,010 --> 01:47:52,610
Uh I have conflicting intuitions.

1827
01:47:52,770 --> 01:47:57,970
On the one hand, I think it's undeniable that our stock has gone up in the past 30 years.

1828
01:47:59,010 --> 01:48:04,850
Um and you know, I think evolutionary psychology used to be incredibly controversial

1829
01:48:04,850 --> 01:48:05,730
and disdained.

1830
01:48:05,810 --> 01:48:10,930
It is now much more mainstream and accepted uh as as a valid perspective.

1831
01:48:11,540 --> 01:48:16,180
It's much easier to get uh a publication accepted in a journal with an explicitly

1832
01:48:16,180 --> 01:48:19,940
evolutionary approach than it used to be 30 years ago.

1833
01:48:20,180 --> 01:48:25,780
Um you will get way fewer uh adverse reactions to

1834
01:48:26,020 --> 01:48:28,820
bringing up evolutionary psych ideas.

1835
01:48:29,540 --> 01:48:34,100
Um and you know the uh and I think uh in some ways the quality has increased.

1836
01:48:34,180 --> 01:48:39,790
You know, we've we've gotten um new perspectives, new methodologies, um

1837
01:48:40,110 --> 01:48:44,270
new ideas from cultural evolution, uh evolutionary game theory.

1838
01:48:44,590 --> 01:48:50,030
Um so I think in some ways uh the work is getting better.

1839
01:48:50,270 --> 01:48:54,110
Um it's slower than I'd like.

1840
01:48:54,590 --> 01:48:57,630
You know, I I do think it's headed in the right direction.

1841
01:48:58,240 --> 01:49:00,720
it's it's like a fucking sloth.

1842
01:49:00,880 --> 01:49:03,200
I want it to pick up the pace, you know.

1843
01:49:03,440 --> 01:49:07,360
But maybe that's just an un maybe that's just how the world works, and you know, that's the

1844
01:49:07,360 --> 01:49:10,480
best we can hope for is for things to slowly get better.

1845
01:49:10,640 --> 01:49:15,040
Um, you know, if you look at progress in any other area of human life, it's it tends to be

1846
01:49:15,040 --> 01:49:16,000
pretty slow.

1847
01:49:16,240 --> 01:49:20,800
Um, so so maybe this is just uh as fast as we're gonna get, and we just gotta wait for the

1848
01:49:20,800 --> 01:49:23,040
sloth to to make its way forward.

1849
01:49:23,280 --> 01:49:29,170
Um part of me worries that maybe we're we're starting to decline a bit, that maybe we've

1850
01:49:29,410 --> 01:49:32,050
we've um I don't know.

1851
01:49:32,690 --> 01:49:37,250
The we're we're starting to go downhill and that the number of people with truly

1852
01:49:37,250 --> 01:49:40,530
adaptationist ideas is starting to decline.

1853
01:49:41,250 --> 01:49:42,850
Um I don't know.

1854
01:49:42,930 --> 01:49:44,370
That's that's a fear I have.

1855
01:49:46,370 --> 01:49:47,410
What do you think?

1856
01:49:49,820 --> 01:49:52,300
I agree that you know our stock has risen considerably.

1857
01:49:52,460 --> 01:49:57,420
I mean, um, you know, I I became a student or I was interested in working with John Alita

1858
01:49:57,740 --> 01:50:00,300
when I was coming up into things.

1859
01:50:00,460 --> 01:50:05,020
And uh there are some people who read the psychological foundations of culture.

1860
01:50:05,420 --> 01:50:10,300
Um, Rob Kurzman called it the uh standard social science straw man or something.

1861
01:50:10,380 --> 01:50:13,100
Standard, you know, he was like, I don't think this is like true.

1862
01:50:13,420 --> 01:50:19,370
The the um uh I really found that to be exactly the water I was swimming in

1863
01:50:19,370 --> 01:50:20,010
as an undergrad.

1864
01:50:20,170 --> 01:50:26,010
I mean, the the what was described as the SSSM in that chapter was my undergraduate

1865
01:50:26,010 --> 01:50:26,490
education.

1866
01:50:26,650 --> 01:50:32,250
So for me, um the there's been quite a change in uh

1867
01:50:32,730 --> 01:50:35,610
in in our stock in that respect.

1868
01:50:35,850 --> 01:50:41,690
The the the degree to which people are just saying, oh, from an evolutionary perspective,

1869
01:50:41,770 --> 01:50:46,780
and genuinely meaning like this is adding something, and it's not, there's no blink,

1870
01:50:46,940 --> 01:50:50,700
there's no, you know, it's just sort of without you know, just in passing.

1871
01:50:50,860 --> 01:50:56,140
Um, so I think the idea that evolution is useful, which is something that Lita

1872
01:50:56,300 --> 01:51:01,420
famously talked about, how her cognition waste and stuff, uh, the reviewers were like,

1873
01:51:01,580 --> 01:51:04,380
Well, you can't say that you got this idea from evolution.

1874
01:51:04,540 --> 01:51:08,530
Lita would always say, you know, if I had the idea like in the shower, it would have been

1875
01:51:08,530 --> 01:51:08,770
fine.

1876
01:51:08,930 --> 01:51:13,090
The problem wasn't the theory, the problem wasn't the data, the problem wasn't the

1877
01:51:13,090 --> 01:51:16,850
implications about the design of the mind, the problem was the source of the hypothesis.

1878
01:51:16,930 --> 01:51:22,850
Um, and it was a real, real uh stretch to publish something that was premised on this is

1879
01:51:22,850 --> 01:51:27,570
where I got the idea for it from, which is exactly what you would think in a science where

1880
01:51:27,570 --> 01:51:29,090
you would want theory, right?

1881
01:51:29,330 --> 01:51:33,400
Um, and so I don't think it's an accident that the theory crisis exists because you know

1882
01:51:33,560 --> 01:51:35,880
Lita, for example, and John went through that.

1883
01:51:36,120 --> 01:51:36,920
Went through that.

1884
01:51:37,160 --> 01:51:38,920
So I think that's very different.

1885
01:51:39,000 --> 01:51:44,520
The idea, the general idea that evolutionary approaches are helpful and useful is well

1886
01:51:44,520 --> 01:51:45,480
understood.

1887
01:51:45,960 --> 01:51:51,320
My opinion is there's two things that are not going great.

1888
01:51:51,560 --> 01:51:57,160
One is what we've characterized sort of as provisional of psych is um

1889
01:51:58,150 --> 01:52:03,430
Is sort of largely what's understood and so uh as what evpsy is.

1890
01:52:03,590 --> 01:52:07,430
So the idea of sort of, you know, there are certain things that evolutionary psychology can

1891
01:52:07,430 --> 01:52:09,910
tell you, but not everything is domain-specific, right?

1892
01:52:10,070 --> 01:52:11,990
Not everything is a sex difference.

1893
01:52:12,150 --> 01:52:17,430
Um, and so the what sort of gets understood as what evpsy is,

1894
01:52:18,150 --> 01:52:20,080
is is some things.

1895
01:52:20,240 --> 01:52:22,640
It applies to some things, but not everything.

1896
01:52:22,880 --> 01:52:27,360
And and then people sort of have this map then of, well, you know, it's great, it's an

1897
01:52:27,440 --> 01:52:30,320
overlayer approach, but it's not really relevant to what I study.

1898
01:52:30,720 --> 01:52:36,240
If people understood adaptationism, if people understood task analysis,

1899
01:52:36,560 --> 01:52:40,560
I think it would look very different in the way evolutionary psychology would be

1900
01:52:40,560 --> 01:52:44,630
interfacing with the rest of psychology and where it is would be very different.

1901
01:52:44,790 --> 01:52:49,670
The way I think about it is Ev PSYC is answering a question that isn't largely being asked,

1902
01:52:50,070 --> 01:52:54,470
which is sort of, you know, what are the design features underlying a lot of these

1903
01:52:54,470 --> 01:52:55,270
phenomena?

1904
01:52:55,590 --> 01:53:01,110
And I think unfortunately for Evpsych, if Ev PSYC had come along at a time where

1905
01:53:01,110 --> 01:53:06,020
psychology was more asking questions about what's the underlying design features, then the

1906
01:53:06,500 --> 01:53:08,740
relevance of the answer would have been clearer.

1907
01:53:08,820 --> 01:53:12,180
And I think it's it's we're still fighting that battle.

1908
01:53:12,340 --> 01:53:14,500
Um, that's outside of EvSec.

1909
01:53:14,740 --> 01:53:17,620
But I do think people are generally okay with it.

1910
01:53:17,940 --> 01:53:23,300
But I I do think, and in this is coming back to this other problem of sort of people being

1911
01:53:23,300 --> 01:53:28,870
interested in controversy, I I appreciate and understand, and John

1912
01:53:29,030 --> 01:53:30,550
Alita talked about this a lot.

1913
01:53:30,950 --> 01:53:36,950
People felt like it was a real personal point of courage to be able to stand up and say, I

1914
01:53:36,950 --> 01:53:38,550
take an evolutionary approach.

1915
01:53:38,790 --> 01:53:44,470
And there were there were there was a lot of controversy, and there were a lot of

1916
01:53:44,470 --> 01:53:50,070
accusations about people being malicious for taking an evolutionary approach.

1917
01:53:50,340 --> 01:53:56,340
Um, and even why Don Simons is was at UCSB apparently is because uh he was

1918
01:53:56,340 --> 01:54:00,820
at Berkeley and there wasn't really it wasn't appreciated that he was applying evolutionary

1919
01:54:00,820 --> 01:54:04,580
approaches to humans, so he he went down to Santa Barbara from Berkeley, which is why we're

1920
01:54:04,580 --> 01:54:06,180
here Dan now, basically.

1921
01:54:06,420 --> 01:54:12,030
Um but yeah, um but I do

1922
01:54:12,190 --> 01:54:18,190
worry that collecting people who are interested in controversy does uh

1923
01:54:18,750 --> 01:54:24,590
it leads to a dynamic where sometimes controversy is sort of uh coddled at the expense

1924
01:54:24,590 --> 01:54:25,870
of good science.

1925
01:54:26,190 --> 01:54:31,790
Um and and more to the point is I do believe we have earned social

1926
01:54:32,030 --> 01:54:35,790
capital with respect to like other scientists.

1927
01:54:36,030 --> 01:54:41,500
And I and I do appreciate that people have different

1928
01:54:41,500 --> 01:54:47,420
experiences, people have different political views, and people can feel really put upon and

1929
01:54:47,420 --> 01:54:52,860
want to express um when they feel like things have been unfair or unjust.

1930
01:54:53,020 --> 01:54:58,140
Um and and I I wouldn't question that or suggest they shouldn't be able to do that.

1931
01:54:58,540 --> 01:55:04,510
But from an ideal perspective, one of the things I worry is when people talk

1932
01:55:04,510 --> 01:55:10,350
about Evpsych being controversial, they're they're we're using up the

1933
01:55:10,350 --> 01:55:14,430
social capital for things that are not about EV-psych.

1934
01:55:14,990 --> 01:55:20,910
So one of the things like I I worry about is people who are attracted to Evpsy

1935
01:55:21,230 --> 01:55:27,150
and who are saying, look, you know, uh, we're there's there's not enough diversity

1936
01:55:27,310 --> 01:55:33,060
of viewpoints in psychology, they're not talking about the lack of adaptationism in

1937
01:55:33,060 --> 01:55:33,780
psychology.

1938
01:55:33,940 --> 01:55:38,660
They're not talking about the lack of task analyses in psychology.

1939
01:55:39,140 --> 01:55:45,140
And as an evolutionary psychologist, that's what I would have hoped that our

1940
01:55:45,140 --> 01:55:50,980
social capital would have earned us, is that argument.

1941
01:55:51,460 --> 01:55:55,940
And if uh and that's not to say other arguments should be excluded, but I think to the

1942
01:55:55,940 --> 01:56:00,730
extent they are, that's the thing that I find really frustrating: is we're using up

1943
01:56:00,730 --> 01:56:06,650
whatever social capital we had as a collective to make points that have nothing

1944
01:56:06,650 --> 01:56:10,970
to do with evolutionary psychology or if they do, they're very indirect.

1945
01:56:11,450 --> 01:56:15,130
Um and so that's my that's my two cents.

1946
01:56:17,530 --> 01:56:17,930
Yeah.

1947
01:56:18,090 --> 01:56:24,010
It's a tragedy of the commons situation where we have this common resource of our

1948
01:56:24,060 --> 01:56:29,980
credibility as a field and people are are squandering it and not using it efficiently.

1949
01:56:30,220 --> 01:56:31,500
Um yeah.

1950
01:56:31,900 --> 01:56:33,660
Yeah, I think that's exactly right.

1951
01:56:33,820 --> 01:56:36,700
I think I agree with with both of those perspectives.

1952
01:56:37,580 --> 01:56:41,900
Well, um hopefully this uh is a little bit of light.

1953
01:56:42,060 --> 01:56:46,700
Um Dan, it was uh it was a pleasure to to talk to you.

1954
01:56:46,860 --> 01:56:52,700
And um um your your lab uh has a website, so people want to sort of keep up to

1955
01:56:52,700 --> 01:56:55,930
date on your work, um, they should go there.

1956
01:56:57,050 --> 01:56:57,530
Yeah, yeah.

1957
01:56:57,770 --> 01:56:59,450
Danconraybeam.com.

1958
01:56:59,770 --> 01:57:00,010
Okay.

1959
01:57:00,250 --> 01:57:01,770
Computational Mate Choice Lab.

1960
01:57:02,010 --> 01:57:02,730
Yeah, is that right?

1961
01:57:02,810 --> 01:57:03,290
Yeah, yeah.

1962
01:57:03,370 --> 01:57:03,610
Yep.

1963
01:57:03,770 --> 01:57:04,090
Yep.

1964
01:57:04,410 --> 01:57:05,370
Fantastic.

1965
01:57:05,610 --> 01:57:06,010
Good.

1966
01:57:06,170 --> 01:57:07,770
Well, well, Dan, thank you so much.

1967
01:57:07,930 --> 01:57:08,890
It was a pleasure.

1968
01:57:09,050 --> 01:57:14,490
And uh we'll um maybe we should we'll all get together at HBES when we see each other in in

1969
01:57:14,490 --> 01:57:16,170
real life, as the kids say.

1970
01:57:16,810 --> 01:57:17,690
That sounds great.

1971
01:57:17,770 --> 01:57:18,970
Thanks, thanks so much for having me.

1972
01:57:19,050 --> 01:57:20,410
This is a really great conversation.

1973
01:57:20,650 --> 01:57:21,210
Yeah, thanks.

1974
01:57:21,370 --> 01:57:23,100
Yeah, Thanks for coming, man.

1975
01:57:29,180 --> 01:57:31,420
Well, that about does it for this episode.

1976
01:57:31,580 --> 01:57:32,780
Thank you for listening.

1977
01:57:32,860 --> 01:57:36,380
Uh, if you like what you're hearing, please don't be shy.

1978
01:57:36,620 --> 01:57:37,980
Leave us a kind review.

1979
01:57:38,060 --> 01:57:43,820
Uh, spread the word on social media, uh, visit our Patreon page if you want to support us.

1980
01:57:44,060 --> 01:57:48,030
Uh, and the plan is we're going to do this again next week, right, Dave?

1981
01:57:48,190 --> 01:57:48,830
Yeah, that's right.

1982
01:57:48,990 --> 01:57:53,470
David, um, we will do this once a week and and who knows?

1983
01:57:53,550 --> 01:57:55,310
We'll just we'll just keep going.

1984
01:57:55,390 --> 01:57:56,590
The sky's the limit.

1985
01:57:56,830 --> 01:57:57,150
Yeah.

1986
01:57:57,230 --> 01:58:00,430
So make sure you subscribe to this podcast so you get the next one.

1987
01:58:00,590 --> 01:58:02,030
And uh we'll see you next week.

1988
01:58:02,270 --> 01:58:02,510
Yeah.

1989
01:58:02,590 --> 01:58:05,870
Enjoy your week and be kind to yourself this week.