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This is Evolutionary Psychology, the podcast.

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Actual evolutionary psychology by actual evolutionary psychologists.

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Boom.

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Let's just say Steve.

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Yeah, we'll say Steve.

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Okay, uh now that we're this is like the Christina introduction where we haven't gotten

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past the name yet.

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But just like the Christina episode, this is a lovely episode.

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And it was a bit different in the sense of we actually are talking a lot about science

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and just sort of history and the ebbs and flows of one person's journey in

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science and how they view it and thinking about evolution and social psychology and

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reputations and old the old guard and the new guard and all those things.

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Yeah, very much about the sociology of science and how Steve has fit into this.

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I mean, he's done a great job of, you know, we mentioned this in the podcast about how he

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he has had some success in translating ideas and getting a lot of

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positive reception among people who have not been steeped in evolutionary ideas, and he's a

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very good translator and missionary for the evolutionary social sciences.

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And we got into, you know, how he pulled that off, where, you know, what barriers

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still remain, um, what problems still remain in in the social sciences and in

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psychology in particular, and and how whether scientific progress is is going in the right

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direction or not.

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Uh yeah, this was kind of a deep meta.

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It was kind of a I I loved it.

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Yeah.

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I think especially if you're a student um uh or a student at heart, Uh I

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don't know.

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It's just it's just sort of like a journey of how do you figure out what the heck we're

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doing?

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This was sort of an episode about that.

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And I think if you're interested in evpsych and social psychology, Steve Newberg is a

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really important person in the history of bringing those areas together.

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But if you're even just more interested in figuring out, well, how do I go to a conference

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where people don't assume what I'm doing makes sense?

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Um, this is also a helpful thing to hear.

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Um and I think we all struggle with that.

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Yeah, for sure.

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No, this was this was this is a great time.

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Steve's a great hang.

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So I think you'll you'll have a good time listening to this one.

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Yeah.

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Enjoy.

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Steve, thanks for being here.

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Um we have had we've had some social psychologists on.

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And some of them are people who grew up in evolutionary social

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psychology.

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We've only had a few people who found evolution after

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they were already in social psychology.

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To my mind, you are one of the key people who brought the two fields together.

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And I don't think I even know this.

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Can you tell us a little bit about either how you found integrating evolution with

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social psychology, either personally or sort of what was your thought process?

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Because I think a lot of students may take it for granted that the two go together, but

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that wasn't always true.

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Yeah, you know, it uh it it came to me late and it actually came to me it

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it came to me in in pieces, I think.

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Uh I actually, I mean, I had a tortured route to becoming a psych major, right?

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I wasn't gonna be a psych major.

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I started as a biomajor.

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I was gonna be uh I was gonna be Hawkeye Pierce.

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I was gonna be a smart ass cardiac surgeon.

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Uh and uh and so I was gonna I was gonna go to med school and when I was an was an

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undergrad uh uh I I hated the all the the

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early level bio courses and chemistry course.

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I mean, they were all memorizing.

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It was it was all sort of leadout for folks who wanted to go to med school.

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And it was really uninspiring and it was boring.

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I was I liked the labs.

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Uh I liked the labs, but I hated what you needed to do, and I just didn't want to do it

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enough, right?

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To uh to be just memorizing all the time and and grinding.

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Uh and so I wasn't I wasn't doing particularly well.

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Uh I wasn't liking it.

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I was exploring a lot.

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I was taking political philosophy classes and I was doing all sorts of things.

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I did take uh an animal behavior class in bio that I found really interesting.

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And uh one day one of my fraternity brothers said, Well, you like animal behavior?

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I'm taking this intro-cycle class.

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Uh I hear it's a great class.

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You know, why don't you why don't you take that?

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You know, people are animals, right?

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Yeah, okay, people are animals.

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And uh and so I took this class and it was uh it was held

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by uh it was held in the in the Cornell Performing Arts uh Auditorium, Bailey

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Hall, Bailey Auditorium, 1500 students.

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And I think I think it was probably the one of the first classes in any discipline that

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went big and went multimedia.

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And so you hit week twelve or whenever they get to social psychology in this.

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And what the instructor had was in addition to like the Milgram films and the Ash films,

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which were great, he had uh Cornell and Stanford were sharing the candid camera

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archives.

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And uh and so he was showing clips of these just funky little s you know social situations

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where essentially, you know, the guy that this is this is the old candle camera back like

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in the in the 60s or whatever.

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Uh they'd be doing like these little experiments, these little sort of demo experiments,

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right?

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And it all sudden occurred to me.

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I'm sitting in the class and I'm I'm hearing about ash and uh the studies there.

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And so, wait, you can do experiments on people, right?

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You can do you can do science on people's behavior way better than other animal behavior,

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you know, from my perspective.

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And I was hooked, you know, I was, you know, the the roof opened up and the sun started

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rays started coming in and doves started singing and angels were flying around.

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And I became a a sort of a social psychologist right at that moment.

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And at at Cornell at the time, if you weren't like in engineering or something, they didn't

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actually let you uh declare a major till the end of your sophomore year if you were in arts

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and sciences.

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And so I, you know, walked over to the psych building.

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This is before internet and online stuff.

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Walked over, you know, walked into the, you know, the secretary's office and said, I want

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to be, I want to, you know, be a psych major and I want to do social psychology research.

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And you know, she said, you know, we've got this brand new uh faculty member coming in in

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the fall from Stanford.

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Uh his name is Tom Gilovich.

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And you know, the back this is students uh we didn't have like professional advising,

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faculty advised students on things.

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He said he'll be your advisor.

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I said, Great, you know, he's social whatever.

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And I showed up and and right off the bat, you know, I was essentially Gilovich's very

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first student.

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Uh he didn't have grad students yet, he hadn't been able to, you know, recruit folks or

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whatever, and just sort of jumped right into stuff and uh and just got to play

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and started thinking and just started thinking about science and stuff but I had the bio

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background a little bit and it was always sort of it was hovering but I really wasn't

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really thinking and he really is he doesn't like I don't know if he'd say this now he he

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doesn't he doesn't really like evo psych he doesn't get it he doesn't understand the

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approaches uh to it Uh social psychologists ought to love

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evolutionary psychology, right?

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Because it's fundamentally about how environments and ecology sort of shape, you know, you

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know, what what our what our psychology is, right?

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I mean, it's it's just it's sort of social psychology writ large and deep, right?

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And and uh they oughta like it.

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But didn't really like it.

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But he was a great mentor and he let me explore and so uh through that I ended

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up, you know, I had another sort of early champion, John Barge, you might know of of John,

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because I was interested, I was I did an honors thesis, which I was only allowed to do

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because my grades weren't good enough.

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My grades weren't good enough to to do an honors thesis, right?

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And and Tom being a young guy and being naive, whatever, you know, pleaded for me or

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whatever.

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And I said, Okay, fine, fine, you're a young guy.

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We'll we'll we'll give you something here.

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And uh they let me do an honors thesis.

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And I met John through just doing a study that was sort of extending some of the work that

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he had and I just really got into it.

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And then uh you know, I did a I did a sexual, I mean my one of my other first studies, my

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first real not real, my first sort of semi-uh research study that wasn't

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with Tom was actually in Sandy Bem's sex rules class, where for an extra credit for a

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fourth credit, you could you could you could do a study.

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And I just did this observational study of who was holding doors open for whom at the

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campus bookstore.

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So here we are, you know, in at highly liberal Cornell University in 1981 or something.

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And you know, did the sex roles, the the the the norms of men holding girls doors open for

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women.

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Women, of course, would be wholly opposed to this, right?

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I mean, this is a highly liberal place.

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You know, we had you know anti-apartheid, you know, shanty towns in the middle of campus,

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right?

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This was a highly activist liberal uh place.

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And it turns out, yeah, yeah, that it turns out that men still open the door the doors for

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women, and women quite happily let them do that.

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And not only that, men open the door for men.

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Uh, and women don't open the door for other women.

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They open, they walk right on through.

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They anyway.

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And so I wrote up this paper on this.

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And the only response I got from Sandy Ben was on the cover of the paper, which said, uh,

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A, uh, this is a great paper.

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Can I put this on reserve in the library as an example for other students?

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And you know, so I got these like mentoring experience.

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I I was getting into the science, thinking about it a little bit, not deeply, but I got

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into it.

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Susan Fisk, uh so I ended up going I almost went to I almost went to UCSP to to work with

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David Hamilton.

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In the end it was between the two of them.

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And the reason, and of course David's never been a fan of uh Evo Psych.

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I I gave a talk before you ended up uh there.

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Actually you may have been a grad student there at the time.

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I gave a talk on on sort of some evo approach to some prejudice work I was doing at the

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time.

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And afterwards he said, Yeah, but why do you need evolution for this?

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I mean, you know, isn't this whatever?

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It's like, well, because you actually want to understand it, David.

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I took a graduate class with David uh Hamilton.

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He was lovely.

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He's always been he is lovely.

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I I think he's lovely.

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But yeah, we there was always a little bit of um uh not entirely meeting uh

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I would put it as yeah.

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You know the reason I didn't go to UCSP because David was a high I mean he was a really

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famous social cognition stereotyping person and that was really up the alley of uh of what

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I was w getting interested in.

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And uh as I was g as the as the days were getting closer to having to make a decision, it's

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probably you April 7th or something.

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I get this manila envelope in the mail.

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Again, there's like no internet.

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I mean, people aren't sending stuff to each other, right?

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I mean, everything's by mail.

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You're getting letters.

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And I get this middle envelope.

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And I open up the middle envelope.

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It's from David.

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I open up the middle envelope and I unfold this big poster of Santa Barbara on the beach,

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right?

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The little marsh there, whatever, right?

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And I look at this thing and say, I'm such a bad student.

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If I go to Santa Barbara, it's gonna be a backfire.

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Right.

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So I went to Pittsburgh and I to work with uh someone who worked with Susan uh Fisk, which

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turned out to be great.

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But I think what led me to, and so this was a really long ramble to get towards your

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answer.

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With Susan, we were sort of on the cutting edge in social cognition of trying to bring

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motivation into cognition.

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I mean the motivation had been in there a little bit, but the but the base model, the

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presumption was at that time was that we operate like a computer and

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emotion and motivation are adds on.

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In fact, Susan's early model actually was just adding tags, right, to c to cognitive

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representation, adding affect tags, plus minus, right, to concepts that we would have.

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I mean, this was sort of the model.

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And we were starting to push this idea that no, that the that the kind of processing you're

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going to engage in was going to differ depending on sort of what what goals were sort of

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important to you at the time.

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And you know, the work that we did uh that ended up I think being pretty important was, you

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know, when do people stereotype and when do they go beyond their stereotypes and

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individuate and what are the circumstances?

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What you know, I was focusing on what are the motivations.

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She was focusing on what are the informational circumstances that would lead you to give up

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your stereotypes.

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And I was really interested in what are the motivational circumstances and really thinking

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about, you what we would now think about in terms of interdependence.

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We were calling it outcome dependency at the time.

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But you know, what's the relationship with this person that would lead me to need to

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understand this person better so I could predict their uh behaviors, right?

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Because the aim uh from my perspective back then, it wasn't all social cognition, was that

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we think in order, we think about people because we want to understand what they're gonna

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do because we have to interact with them.

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And I didn't quite have that wasn't solid in my mind now then like it like it is now, but

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the but the foundations were were really there.

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And I left a I left Carnegie Mellon, I did a year postdoc in Waterloo and I came here and

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I had Kenrick here.

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So you think that Kenrick is the reason why I got into.

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And it actually isn't.

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We did a little bit of work after this, but the very first thing, uh, I presume you guys

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know the name Robin Fox, anthropologist from okay.

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Robin Fox wrote, I don't know if you've ever seen this paper.

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It's more of an essay in Psych Inquiry on stereotyping prejudice.

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And it and what was the title?

248
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The title of the paper is something like an unfinished mind.

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And so it's a target article.

250
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Uh it's a it's a it's a beautifully written article.

251
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It's a fun article uh to read.

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I still assign it to students.

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and uh uh in which he argued that prejudice and stereotyping is sort

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of lower my hand.

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Uh uh for those on on uh uh the acoustic format, Steve just raised his hand in

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Zoom.

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So if you have a question, Steve.

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I'm I'm Jewish, I talk with my hands and possible

259
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and uh he wrote this incredible paper where he argued for the fact that

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prejudice is sort of the default natural state and for good reason, right?

261
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That stereotyping and and and having and having affects towards people that can help drive

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drive behavior towards them, that that was sort of the base.

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And so, you know, it's uh the it's a targeted article with a bunch of invited commentaries.

264
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I don't I was just a kid then.

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I don't know why I was invited, but I was invited to to comment on it.

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And uh I loved the paper uh for a whole bunch of reasons.

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I mean it's a beautiful paper.

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Uh but it was uh the argument was that

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stereotyping was uh was was an evolved uh was was an adaptation for

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for dealing with certain kinds of challenges.

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And as I was thinking about it, I was realized, yeah, but the kind of individuation that I

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talk about and the circumstances under which it happens and for whom we're likely to

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individuate, that also has to be.

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And so what's also has to be an adaptation and part of the part of a well-designed system.

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And then what so now what are what are the factors that sort of switch you from one to the

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other?

277
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How do you need to think about this?

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And so my that my response was yes and right and uh

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and it was really the first time that I really started thinking about my work in a way that

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uh uh uh Might have had those kind of deeper

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foundations to it.

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And so that was one thing.

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And then Doug and I, and a couple of students, did some work on sort of contrast effects on

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attractiveness and dominance and men and women, and you know, who would kind of whatever.

285
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And that was sort of fun stuff, but it really I really wasn't into it.

286
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And then their second thing hit.

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And this uh is with uh uh another one of your colleagues emeritus now, uh

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Dave, uh Brenda Major.

289
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Yeah.

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I had been invited.

291
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Yes, and and Brenda's more open, and Brenda became more open to thinking about sort of

292
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Brenda actually so Rob Kurzman wrote this paper on on stigma.

293
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And he wrote it actually initially for Brenda's class.

294
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Brenda really didn't like the paper.

295
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Yeah, she told me because I took the same class and I was I was the second leadest student

296
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after Rob in that same class in a later class.

297
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Yeah.

298
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So she told me about that.

299
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Yeah.

300
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Yeah, she she likes the paper more now, but I ended up uh we ended up talking a

301
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lot about it, and she sort of came around on it.

302
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But I initially I was at a conference held by Dartmouth University uh up sort

303
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of at on on the estate, they had these small conferences that would turn into books where

304
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they'd invite like 15 people and around a topic.

305
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And so the topic was sort of the you know the social psychology of stigma.

306
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And so it's it was held on the on like the the estate that had been donated by the founder

307
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of CBS to Dartmouth.

308
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So it was literally on Golden Pond.

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You guys may not be old enough to know the movie on Golden Pond with Henry Fonda and Jane

310
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Fonda, but literally it was on this on this place.

311
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So it was a beautiful place.

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You're out in the middle of the woods.

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Uh and and the the way the little work conference thing was, is that you didn't talk about

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your own work.

315
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In fact, you only you had seven minutes after dinner, during drink time,

316
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to talk about your work.

317
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And we would do that like every night for four or five nights.

318
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And uh but what you do is that you sit around a big table and there'd be a question for the

319
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morning session, a question for the afternoon, and you got and we you'd argue about the

320
00:17:45,340 --> 00:17:48,780
question, you talk it through, and at the end people decide what do they want to write

321
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about to go into into this this edited volume on the social psychology stigma.

322
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And you know, it was interesting, it was fun, there were a lot of very cool people there.

323
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Schaller was was there, he'd probably be the other person who uh uh ended up

324
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being sort of ebo.

325
00:18:06,330 --> 00:18:09,610
And uh you know, I and you were rooming with people, right?

326
00:18:09,770 --> 00:18:10,730
So is that this right?

327
00:18:10,890 --> 00:18:14,010
Because it was and so I was rooming with Jack DeVideo, which was sort of cool.

328
00:18:14,090 --> 00:18:16,250
A very different kind of social psychologist, right?

329
00:18:16,410 --> 00:18:18,490
Very different view than than than mine.

330
00:18:18,730 --> 00:18:23,530
But I'm out on a boat during one of these breaks with Brenda Major and Jenny Crocker, who

331
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longtime friends, very, very close.

332
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And as they're talking about stigma, I realized that they viewed it as entirely everything

333
00:18:31,840 --> 00:18:33,040
was arbitrary, right?

334
00:18:33,200 --> 00:18:39,120
I mean, you know, the stigma of whether you wore Jordash or Wrangler or Levi's jeans was

335
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functionally the same as being sort of stigmatized because you uh you free ride

336
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uh on your community members or because you're walking around all diseasy or you're because

337
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you're from a different tribe or because right, whatever.

338
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Uh and for them it was all it was just all sort of deviance off of some kind of norm, and

339
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that norm could be entirely arbitrary.

340
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And I'm on the boat and I realize this makes no sense at all.

341
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Of course, this isn't the case.

342
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There has to be some kind of uh uh universality, some deeper function.

343
00:19:08,270 --> 00:19:12,350
And then I started thinking about well, what would be the things that we would stigmatize?

344
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And that really sort of got me into the whole perspective that I have, you know, thinking

345
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about okay, well, what is the nature of human groups?

346
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What do human groups need to be like in order to uh to be uh you

347
00:19:25,470 --> 00:19:30,480
know uh valuable that and you know add fitness value for its members, right?

348
00:19:30,640 --> 00:19:34,400
And then could we derive from that what those features needed to be?

349
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What are the things that then would be stigmatized?

350
00:19:36,640 --> 00:19:39,200
So stigma as a form of social control, right?

351
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To enable groups to be successful so that, you know, for so that individuals would be

352
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getting the fitness benefits out of it.

353
00:19:47,200 --> 00:19:49,760
And it was really that that was the big trigger.

354
00:19:49,930 --> 00:19:55,530
I mean, and and and and then Shaler and I were started talking about these kinds of things.

355
00:19:55,610 --> 00:20:00,250
And and he, you know, uh uh, I don't know if you've had him on yet.

356
00:20:00,330 --> 00:20:04,090
Uh he's just brilliant and a really creative thinker and really fun to play with.

357
00:20:04,170 --> 00:20:06,330
I mean really fun to play with over ideas.

358
00:20:06,490 --> 00:20:10,970
And we really started uh building some stuff together and then going in other directions

359
00:20:11,050 --> 00:20:12,810
and then pulling those directions back together.

360
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And uh that's really I think that's really it.

361
00:20:16,410 --> 00:20:20,500
So in some ways, you know, you know, Robin Fox, right?

362
00:20:20,820 --> 00:20:24,820
Uh you know, Brenda Major, right?

363
00:20:24,900 --> 00:20:30,260
Out of uh by being by saying by talking about things in ways that made no sense, right?

364
00:20:30,420 --> 00:20:32,340
I teased Brenda about this, right?

365
00:20:32,820 --> 00:20:36,180
Brenda, you know, your your ignorance turned me into what I am.

366
00:20:37,300 --> 00:20:42,660
Uh but then having really good mentors along the way that just led me to be open minded and

367
00:20:42,660 --> 00:20:43,700
to be thinking integrated.

368
00:20:43,940 --> 00:20:48,990
Susan Fisk is a very integrative thinker and and she views herself as sort of supportive of

369
00:20:49,070 --> 00:20:53,790
of evo stuff but she doesn't really get it uh in in in a lot of ways I say with great

370
00:20:53,790 --> 00:20:58,350
affection Susan if you hear this uh really really important and a and a an incredible

371
00:20:58,350 --> 00:21:02,910
mentor and you know Gilovich who's just you know go explore you know do your own thing you

372
00:21:02,910 --> 00:21:06,430
know you you you figure out an honors thesis right I'll I'll support you and if you want a

373
00:21:06,430 --> 00:21:10,110
project I'll help you at the end if you can't find something but you know just the just the

374
00:21:10,110 --> 00:21:13,700
notion of of being open to thinking about different ideas.

375
00:21:13,780 --> 00:21:16,180
And but that Robin Fox essay was really important.

376
00:21:16,260 --> 00:21:20,420
And then having dug around, right, to be talking about these things and to be building on

377
00:21:20,420 --> 00:21:26,180
them and and and having the the friendship with Shaler and uh we overlap one year

378
00:21:26,180 --> 00:21:26,820
here, right?

379
00:21:26,980 --> 00:21:32,420
I was a first year faculty member when he was finishing up uh uh here with uh with Chaldini

380
00:21:33,460 --> 00:21:35,810
uh and Kenrick and so all those.

381
00:21:36,050 --> 00:21:39,810
So that's a really long-winded answer to a very it's a very vivid picture.

382
00:21:39,970 --> 00:21:40,450
That's great.

383
00:21:41,250 --> 00:21:41,490
Yeah.

384
00:21:41,570 --> 00:21:47,090
No, it's one of it's it's great because I think you are um the first guest we've had who

385
00:21:47,090 --> 00:21:52,050
sort of came into evolutionary psychology indirectly, and that you had a successful career

386
00:21:52,050 --> 00:21:55,730
as a psychologist without um taking an evolutionary perspective, and then all of a sudden

387
00:21:55,810 --> 00:22:00,770
you were you just had various influences and you were persuaded about the value of these

388
00:22:00,770 --> 00:22:03,810
ideas, uh and then started running with it.

389
00:22:04,050 --> 00:22:08,860
Um I I think one of the key things here, and Kim Hill said something to me, uh that you

390
00:22:08,860 --> 00:22:13,820
know, another great colleague across campus, being at ASU was really great uh uh for this

391
00:22:13,820 --> 00:22:14,140
as well.

392
00:22:14,300 --> 00:22:20,220
I mean, there's so many people around around campus to talk to, but uh you know, I had an

393
00:22:20,220 --> 00:22:26,220
I had an idea and I tested that idea, and the data started coming back and and the data

394
00:22:26,220 --> 00:22:27,420
are the data, right?

395
00:22:27,740 --> 00:22:33,030
Uh and uh one of the things Kim told me once was that he thought that

396
00:22:33,030 --> 00:22:38,470
psychology was gonna become more substantially evolutionary before

397
00:22:38,470 --> 00:22:43,830
anthropology be accepted more by more traditional folks uh because

398
00:22:43,830 --> 00:22:49,270
psychologists care about data was was was was his uh line on this that the cultural

399
00:22:49,270 --> 00:22:55,120
anthropologists it's not really it's not fundamentally uh about about the data to

400
00:22:55,120 --> 00:22:55,360
them.

401
00:22:55,600 --> 00:23:01,040
And so to have for folks like him to have sway there, he was way more

402
00:23:01,040 --> 00:23:05,280
pessimistic about that than he was about, you know, folks like me and folks like you guys

403
00:23:05,280 --> 00:23:08,640
having sway within uh within uh psychology.

404
00:23:09,680 --> 00:23:10,400
Yeah, it's interesting.

405
00:23:10,480 --> 00:23:11,920
That may well be correct.

406
00:23:12,080 --> 00:23:18,010
Um and I and I feel like if psychology has been more receptive to evolutionary ideas,

407
00:23:18,090 --> 00:23:21,050
particularly social psychology, I think it is largely due to you.

408
00:23:21,210 --> 00:23:26,330
I I feel like you're one of the best people for um persuading other

409
00:23:26,490 --> 00:23:31,290
non-evolutionary psychologists about the value of these ideas, uh interfacing with social

410
00:23:31,290 --> 00:23:36,010
psychologists and persuading them that these ideas are relevant and valuable to them.

411
00:23:36,170 --> 00:23:40,400
Um you're one of the best people at at getting your students jobs in social psychology

412
00:23:40,400 --> 00:23:44,400
departments and you know teaching them how to frame their ideas in a way that will be

413
00:23:44,400 --> 00:23:49,360
receptive to people who uh are who didn't you know naturally come to these ideas or or or

414
00:23:49,440 --> 00:23:51,520
you know or weren't already steeped in them.

415
00:23:51,760 --> 00:23:56,720
Um I I feel like you're you're one of the best people who uh who does what I might half

416
00:23:56,720 --> 00:24:02,560
jokingly call missionary work of of of bringing people on board um uh to

417
00:24:02,560 --> 00:24:03,120
these ideas.

418
00:24:03,200 --> 00:24:08,590
And I'm and I kinda I'm curious about you know if you have any insight into um why you've

419
00:24:08,590 --> 00:24:10,190
been so successful at that?

420
00:24:10,350 --> 00:24:15,230
Um has it been because you know you yourself were persuaded about the value of these ideas

421
00:24:15,310 --> 00:24:19,470
and so you know what worked on you and and and you sort of use those same tools on other

422
00:24:19,470 --> 00:24:25,470
people, or what is it that allows you to um bring these ideas to other people in a way

423
00:24:25,470 --> 00:24:29,630
that doesn't turn them off, and a way that has you know had such an impact in making

424
00:24:29,630 --> 00:24:34,830
evolutionary ideas um more accepted and uh and more mainstream in psychology?

425
00:24:35,310 --> 00:24:37,280
Yeah, well, first of all, th thank you for that.

426
00:24:37,440 --> 00:24:40,400
Uh I'm I'm flattered uh by that.

427
00:24:40,880 --> 00:24:46,080
Uh I I think it's I think it's a few

428
00:24:46,400 --> 00:24:47,040
things.

429
00:24:47,360 --> 00:24:53,280
I th I think part of it is uh and and and this this

430
00:24:53,280 --> 00:24:58,960
may partially be based on my own inconfidence and insecurity, that I often

431
00:24:58,960 --> 00:25:04,850
don't lead with sort of the strict derivations from the the

432
00:25:04,850 --> 00:25:10,770
deep I I don't I don't so if if if we listen to a talk from a

433
00:25:10,770 --> 00:25:16,050
UCSB person, it'll often start with, okay, so now if we start with first principles and we

434
00:25:16,050 --> 00:25:19,090
start with this thing right here, which by the way is going to be foreign to all of you

435
00:25:19,090 --> 00:25:20,450
folks over right, or whatever.

436
00:25:20,690 --> 00:25:20,850
Right.

437
00:25:21,010 --> 00:25:24,210
And then we say and we sort of apply this and we sort of work our way through.

438
00:25:24,370 --> 00:25:29,900
Uh one of the benefits I have is that uh I I was never trained as an

439
00:25:29,900 --> 00:25:31,020
evolutionary biologist.

440
00:25:31,100 --> 00:25:37,020
I never got to take an Evo course from Lita and John or or any of

441
00:25:37,020 --> 00:25:37,580
those folks.

442
00:25:37,660 --> 00:25:39,420
So I have never taken an Evo course, right?

443
00:25:39,500 --> 00:25:44,780
I mean um it's it's it's it's self-taught and with costs, which I which I'll admit because

444
00:25:44,780 --> 00:25:48,860
I think I think there are times that uh I get loose and I appreciate folks when they say,

445
00:25:48,940 --> 00:25:51,500
you know, you're being a little bit loose uh loose here.

446
00:25:51,660 --> 00:25:52,540
Okay, help me.

447
00:25:52,700 --> 00:25:57,550
Uh figures out so I think I think part of it is that because if you because if you've if

448
00:25:57,550 --> 00:26:03,230
you start at a place where that feels really foreign to folks I think it's uh even even

449
00:26:03,390 --> 00:26:09,310
well intentioned it's it's it's it's it requires work and if the foreignness

450
00:26:09,470 --> 00:26:14,510
is associated with a lot of the stuff that evil psych has unfortunately been associated

451
00:26:14,510 --> 00:26:19,180
with right you know just just a lot of wrong inferences about what what our assumptions

452
00:26:19,180 --> 00:26:23,820
actually are, uh, then I then I think it's really easy for people just sort of to t turn

453
00:26:23,820 --> 00:26:24,060
off.

454
00:26:24,540 --> 00:26:28,380
I remember what so so Chris Crandall is a very traditional social psychologist.

455
00:26:28,460 --> 00:26:29,100
He's a very good friend.

456
00:26:29,180 --> 00:26:32,380
I've known him for I actually met him when he was interviewing for a faculty position at

457
00:26:32,380 --> 00:26:35,900
Carnegie Mellon when I was a grad student like a last year grad student there.

458
00:26:36,060 --> 00:26:39,740
So we've known each other for what coming up on 40 years now or something.

459
00:26:39,980 --> 00:26:45,950
Uh And he once came when I when I first presented some of the work that

460
00:26:45,950 --> 00:26:51,150
I've been doing with with Kathy Cottrell on there these, you know, prejudice isn't just

461
00:26:51,150 --> 00:26:51,550
valence.

462
00:26:51,710 --> 00:26:55,230
It's not just negative, negative affect towards groups, right?

463
00:26:55,310 --> 00:26:57,870
There are these different, you know, emotional flavors to them.

464
00:26:57,950 --> 00:27:02,990
And those are anger, you know, anger focused prejudices, disgust focused prejudices, and

465
00:27:02,990 --> 00:27:06,350
fear and and and uh and they're there for a reason, right?

466
00:27:06,430 --> 00:27:12,040
They're they they are they are you know those are those are uh effective adaptive

467
00:27:12,040 --> 00:27:15,640
responses to particular threats that these groups are perceived as po and when I started

468
00:27:15,640 --> 00:27:21,400
doing that research and I I was as with a talk I was at a conference on on prejudice, I

469
00:27:21,400 --> 00:27:27,240
think up in Madison, and uh I I gave I gave the talk on it, which was really foreign

470
00:27:27,480 --> 00:27:31,160
and and it and it was threatening uh to social because it meant that you have to measure

471
00:27:31,160 --> 00:27:31,930
prejudice different.

472
00:27:32,090 --> 00:27:34,570
It's not there's no prejudice, it's prejudices, right?

473
00:27:34,650 --> 00:27:36,730
And they're these qualitatively different things.

474
00:27:36,890 --> 00:27:40,730
Uh and those qual and those qualitative distinctions make a really big difference.

475
00:27:40,970 --> 00:27:46,090
You know, if you actually want to intervene, right, then intervening, presuming that these

476
00:27:46,090 --> 00:27:49,930
are all the same thing, you're you're you're really going to not be very effective.

477
00:27:50,090 --> 00:27:51,930
And in fact, we haven't been very effective.

478
00:27:52,090 --> 00:27:56,760
Uh and you know, so I gave this talk and it was threatening to a lot of folks, but you

479
00:27:56,760 --> 00:28:00,440
know, Chris came up to me afterwards and says, you know, you you this has to be right.

480
00:28:00,680 --> 00:28:01,160
Right.

481
00:28:01,400 --> 00:28:07,320
And and I think it was the combination of the data and then and the

482
00:28:07,320 --> 00:28:13,240
logic that goes to it and and a and a simpler logic, one

483
00:28:13,240 --> 00:28:19,050
that that doesn't need to did it come from first principle I think

484
00:28:19,050 --> 00:28:24,890
this is an interesting I should finish sentences right uh so

485
00:28:25,050 --> 00:28:30,970
I think this is maybe an interesting difference between sort of the model that we have here

486
00:28:31,050 --> 00:28:36,810
for example and the and the UCSB model and I and I see this with uh so Michael Barlow is a

487
00:28:36,810 --> 00:28:41,900
colleague of mine now uh and uh and and one of the reasons why I brought him in a long time

488
00:28:41,900 --> 00:28:47,180
ago as a as a postdoc, right, was because I wanted to to to put these two perspectives

489
00:28:47,180 --> 00:28:51,020
together and sort of see how uh see how they worked and how they were similar, how they

490
00:28:51,100 --> 00:28:56,220
different, and and and how they could build each each other, is that we'll sometimes start

491
00:28:56,220 --> 00:29:02,190
with a a phenomenon and then sort of work our way back a little

492
00:29:02,190 --> 00:29:04,990
bit and then and and and and cycle a little bit.

493
00:29:05,150 --> 00:29:07,470
Okay, here's the phenomena to be explained.

494
00:29:07,630 --> 00:29:10,670
What what are the possible explanations and then cycle back?

495
00:29:10,830 --> 00:29:16,190
Uh and and I think you know a UCSB model is some is is often starting with the first

496
00:29:16,190 --> 00:29:19,870
principles and then saying, okay, well what would now would we expect in working the way

497
00:29:20,190 --> 00:29:20,510
out.

498
00:29:20,910 --> 00:29:26,580
And I think uh I think it's the the model

499
00:29:26,740 --> 00:29:32,580
we have is just a naturally more uh comfortable one for social

500
00:29:32,660 --> 00:29:34,420
psychologists, I think.

501
00:29:34,580 --> 00:29:37,460
Uh it's it's it's one that they've been doing their whole career, right?

502
00:29:37,540 --> 00:29:41,780
I mean it's it's the one that you know I sort of start with and you know I wasn't trained

503
00:29:41,780 --> 00:29:45,620
as an evolutionary uh uh psychologist or or biologist.

504
00:29:45,860 --> 00:29:51,650
And and so I think I think that's part of it too, that uh that that people can maybe

505
00:29:51,650 --> 00:29:56,610
more quickly get the grasp on the phenomenon and the nuance in the phenomenon.

506
00:29:56,770 --> 00:30:01,970
And then if the nuance is a bit of a threat to their current beliefs, okay now maybe and if

507
00:30:01,970 --> 00:30:04,850
they're serious scientists, then they need to think about it.

508
00:30:05,010 --> 00:30:05,330
Right.

509
00:30:05,650 --> 00:30:11,570
Uh I I have I have serious scientists who who focus who do stereotyping and prejudice

510
00:30:11,810 --> 00:30:17,580
who still come up to me uh and uh including a former uh recently a former

511
00:30:17,580 --> 00:30:22,460
David Hamilton uh social cognition student who said you know you have to be right it's the

512
00:30:22,540 --> 00:30:27,980
it's the it's the like the evo packaging that has so many people uh sort of sort of

513
00:30:27,980 --> 00:30:32,060
uncomfortable uh with it and then thinking through what would the implications be.

514
00:30:32,220 --> 00:30:35,350
So Carlos Navarette, I don't know if you guys ever knew him.

515
00:30:35,670 --> 00:30:39,510
Yeah, I knew Carlos because he was a grad student when I was a grad student at UCLA.

516
00:30:39,830 --> 00:30:39,990
Okay.

517
00:30:40,150 --> 00:30:42,310
He was at UCLA when I was at UCSB, yeah.

518
00:30:42,710 --> 00:30:43,430
Right, right.

519
00:30:43,910 --> 00:30:48,870
And uh after we published this PAS paper on sort of uh

520
00:30:49,190 --> 00:30:53,750
ecology and stereotypes being confounded with race stereotypes, right?

521
00:30:53,910 --> 00:30:59,860
People from you know more harsh, more unpredictable environments that pull for certain kind

522
00:30:59,860 --> 00:31:03,060
of behaviors, certain kind of characteristics, certain kind of strategies.

523
00:31:03,220 --> 00:31:08,980
And it turns out that those are highly correlated with some stereotypes about

524
00:31:09,300 --> 00:31:12,500
African Americans in the United States, right?

525
00:31:12,660 --> 00:31:17,950
And so that that may be a lot of the stereotypes that that we see uh in the United States

526
00:31:18,110 --> 00:31:20,670
aren't really fundamentally stereotypes about race, right?

527
00:31:20,750 --> 00:31:25,870
But they're but they're maybe fundamentally stereotypes about uh you know uh about the

528
00:31:25,870 --> 00:31:29,790
ecology that pe people are are presumed to come from and of course that's very valuable

529
00:31:29,790 --> 00:31:33,230
information to have if in fact ecology shapes behavior, which it does.

530
00:31:33,390 --> 00:31:36,910
And uh he came after that paper got published, he came up to me at a conference and said,

531
00:31:37,070 --> 00:31:38,270
Wow, that was really brave.

532
00:31:38,590 --> 00:31:42,060
I said, Why what what was what was brave about that?

533
00:31:42,220 --> 00:31:46,460
Uh, you know, you know, psychologists, social psychologists in particular should should

534
00:31:46,460 --> 00:31:47,500
love the idea, right?

535
00:31:47,660 --> 00:31:53,180
That it's not fundamentally about race and that it's about uh it's about environments and

536
00:31:53,180 --> 00:31:53,900
things like that, right?

537
00:31:54,060 --> 00:31:55,260
He said, no, no, no, no.

538
00:31:55,340 --> 00:32:00,700
One of the implications of this is that maybe there's a kernel of truth to the stereotypes,

539
00:32:00,940 --> 00:32:01,260
right?

540
00:32:01,500 --> 00:32:07,190
And and the thing, right, because that the that the uh not that the behaviors being

541
00:32:07,190 --> 00:32:11,830
engaged in, they're being engaged in because of the environment, but but that pe people are

542
00:32:11,830 --> 00:32:15,270
sort of picking up on those behaviors and they're using them to make inferences and they're

543
00:32:15,270 --> 00:32:20,310
extending them out there to the group that there might be a kernel of truth to stereotypes.

544
00:32:20,390 --> 00:32:25,670
And I was talking with this former student at David Hamilton's about this a few months ago.

545
00:32:25,830 --> 00:32:27,830
And he said, yeah, but that's not a kernel of truth.

546
00:32:27,910 --> 00:32:31,640
What a kernel of truth means, it's not about predicting the it's about that there's an

547
00:32:31,640 --> 00:32:33,000
essence that is genetically based.

548
00:32:33,320 --> 00:32:34,200
No, no, no, no, no.

549
00:32:34,280 --> 00:32:39,480
And I think there's an inference that people make about evo stuff that what we're saying,

550
00:32:39,720 --> 00:32:45,640
because there may be these systems that exist that drive these things, that uh uh

551
00:32:45,800 --> 00:32:50,680
that they're inherent and that they're deterministic and whatever, and and they're and the

552
00:32:50,680 --> 00:32:53,560
ideology just doesn't let them go there, right?

553
00:32:53,790 --> 00:32:54,590
I'm not going there.

554
00:32:54,750 --> 00:32:56,030
None of us go there, right?

555
00:32:56,190 --> 00:32:57,950
They think they think we're going there with it.

556
00:32:58,030 --> 00:33:03,310
And so if they're if they adopt a perspective that they're going there or they'll be seen

557
00:33:03,310 --> 00:33:04,110
as going there.

558
00:33:04,190 --> 00:33:08,510
And I gave a talk once at at a conference down in Sydney.

559
00:33:08,670 --> 00:33:12,190
Uh again, one of these small conferences, they pull people together.

560
00:33:12,350 --> 00:33:18,030
Uh uh Kenrick had been to this conference a couple of years earlier, uh, and Wendy Wood had

561
00:33:18,030 --> 00:33:19,230
been there as well.

562
00:33:19,470 --> 00:33:25,420
And you know, they just just hated uh hated that stuff, hated all the all those ideas

563
00:33:25,500 --> 00:33:31,500
uh that Doug was talking about, uh, where he was talking about uh sex differences and and

564
00:33:31,500 --> 00:33:32,940
mating and things like that.

565
00:33:33,180 --> 00:33:37,340
And I gave a talk on sort of more social cognition-y things and in fact didn't talk about

566
00:33:37,340 --> 00:33:38,380
sex differences at all.

567
00:33:38,540 --> 00:33:41,740
But I was talking about different motivational systems and how it was shaping different

568
00:33:41,740 --> 00:33:43,820
aspects of of cognition about people.

569
00:33:43,980 --> 00:33:48,780
Uh and afterwards he came up to me said, now that's a kind of evolutionary psychology I can

570
00:33:48,780 --> 00:33:48,940
like.

571
00:33:49,170 --> 00:33:54,930
that I can right and that I that I can and why because it had nothing to do with sex

572
00:33:54,930 --> 00:34:00,930
differences and she had these commitments to what it meant what what it meant to be male

573
00:34:00,930 --> 00:34:04,690
and female and and what differences look like and where they must come from.

574
00:34:04,770 --> 00:34:08,770
And if they came from here then oh my God, if they came from there then that would be okay.

575
00:34:08,850 --> 00:34:12,930
And it would right and and and so it was it was sort of driven by commitments.

576
00:34:13,170 --> 00:34:14,530
I think we still have that problem.

577
00:34:14,690 --> 00:34:16,440
I think some of that problem is coming back.

578
00:34:16,600 --> 00:34:18,680
I think over the last five years ago.

579
00:34:18,840 --> 00:34:24,520
I think uh, you know, maybe since the murder of Geor George Floyd and a lot more uh sort of

580
00:34:24,760 --> 00:34:29,880
social justice activism uh within academia and now backlash and backlash for the backlash

581
00:34:29,960 --> 00:34:30,440
and all that.

582
00:34:30,600 --> 00:34:35,400
Uh I think there is more concern about how one comes across uh uh a little bit.

583
00:34:35,720 --> 00:34:41,510
Uh but in the end, you know, the the data are the data,

584
00:34:41,670 --> 00:34:42,870
yes, they need to be interpreted.

585
00:34:42,950 --> 00:34:47,110
And yes, when there are alternative interpretations, we ought to work really, really hard

586
00:34:47,110 --> 00:34:48,870
to sort of tease them apart.

587
00:34:49,110 --> 00:34:49,430
Right.

588
00:34:50,150 --> 00:34:55,670
But what's really clear is that in the areas that I focus on, you know, how people

589
00:34:55,910 --> 00:35:01,830
think is so much more nuanced and and and so much more based on trying to

590
00:35:01,830 --> 00:35:07,510
solve fundamental challenges of of social living than what our science has uh

591
00:35:07,640 --> 00:35:09,400
uh has presumed it to be.

592
00:35:09,560 --> 00:35:13,800
You know, if we measure things really simply, you don't you don't uh you don't you don't

593
00:35:13,800 --> 00:35:14,840
discover the complexity.

594
00:35:14,920 --> 00:35:18,600
And we've had very simple measures because our theories initially call for very simple

595
00:35:18,600 --> 00:35:19,240
measures.

596
00:35:19,320 --> 00:35:23,320
Uh and so we don't see the complexity and so people can keep moving on, but we're not

597
00:35:23,320 --> 00:35:26,920
making progress without uh diving in deeper, I don't think.

598
00:35:27,560 --> 00:35:27,800
Yeah.

599
00:35:27,960 --> 00:35:33,150
I kind of want to see if I can take a stab at summarizing your

600
00:35:33,790 --> 00:35:34,190
answer.

601
00:35:35,790 --> 00:35:41,630
What I hear you saying is that you know there are two approaches to um framing evolutionary

602
00:35:41,630 --> 00:35:44,830
ideas and their utility um to studying humans.

603
00:35:44,990 --> 00:35:48,910
Um and there's the the Santa Barbara I'm probably caricaturing, but um the Santa Barbara

604
00:35:49,390 --> 00:35:51,950
approach is very much we're gonna start with the Big Bang.

605
00:35:52,270 --> 00:35:54,030
And if you read the John Tubi talk.

606
00:35:54,270 --> 00:35:55,150
The John Tubi method.

607
00:35:55,230 --> 00:35:57,950
And if you read any Tubi papers, they tend to start with the Big Bang.

608
00:35:58,200 --> 00:36:04,040
They start with you know the thermodynamics and uh replicators and then you know work their

609
00:36:04,040 --> 00:36:06,760
way from first principles to the phenomenon that you're interested in.

610
00:36:07,000 --> 00:36:10,760
Yeah I did I didn't learn until listening to the the leader thing that he started off as

611
00:36:10,760 --> 00:36:11,640
like a physics major.

612
00:36:11,720 --> 00:36:13,640
So you can it makes sense in retrospect.

613
00:36:13,720 --> 00:36:19,080
Yeah there's not totally there's not in it a mental state anywhere in that story either

614
00:36:19,320 --> 00:36:24,120
which I love but but but yes exactly like it's it's uh physics and design.

615
00:36:24,200 --> 00:36:25,320
Yeah totally.

616
00:36:25,480 --> 00:36:25,640
Yeah.

617
00:36:25,950 --> 00:36:26,270
Yeah.

618
00:36:26,350 --> 00:36:28,670
Um, but you take a a very different approach.

619
00:36:28,750 --> 00:36:33,470
Uh rather than starting with the Big Bang or the law of thermodynamics, um, which could

620
00:36:33,470 --> 00:36:37,470
alienate people who uh don't really think about that or don't find it relevant.

621
00:36:37,630 --> 00:36:41,630
Um, you start with the thing that people actually care about, which is say prejudice.

622
00:36:41,870 --> 00:36:45,390
So we all it's just so immediately you get on the same page with the people you're talking

623
00:36:45,390 --> 00:36:45,550
to.

624
00:36:45,710 --> 00:36:49,310
We're both interested in prejudice, we're both interested in in what causes it and how we

625
00:36:49,310 --> 00:36:50,350
can change it, right?

626
00:36:50,560 --> 00:36:54,720
And when you start from there and then bring in the evolutionary ideas, well, here is how

627
00:36:54,720 --> 00:36:58,960
we can gain insight into prejudice and where it comes from and how to change it.

628
00:36:59,040 --> 00:37:02,480
Uh then people are going to be much more receptive because you're starting on a on a place

629
00:37:02,480 --> 00:37:06,320
of common ground, we share the same goals, and then here's how my approach can help you

630
00:37:06,320 --> 00:37:08,080
achieve these goals that we share.

631
00:37:08,400 --> 00:37:09,600
Yeah, I I think that's right.

632
00:37:09,760 --> 00:37:12,530
But I also think that both are absolutely necessary.

633
00:37:12,690 --> 00:37:17,730
And the notion of, you know, Cialdini talks about full cycle psychology in a different kind

634
00:37:17,730 --> 00:37:17,970
of way.

635
00:37:18,050 --> 00:37:24,050
But if we think about sort of, you know, just you know, observing uh phenomena and you

636
00:37:24,050 --> 00:37:28,610
know understanding the this isn't gonna come out right.

637
00:37:28,850 --> 00:37:34,770
Uh uh requiring ourselves to have sort of the the deep

638
00:37:34,770 --> 00:37:37,460
logic, Both of those things are true.

639
00:37:37,700 --> 00:37:43,460
And I th I think, you know, where I benefit from interacting with uh

640
00:37:44,180 --> 00:37:50,020
uh with folks that come out of the Lita and John uh tradition is that

641
00:37:50,020 --> 00:37:55,380
they sort of really force me to to think harder and deeper about those things.

642
00:37:55,540 --> 00:38:01,470
I think some of the value we add is that we're we're maybe seeing earlier a lot of

643
00:38:01,470 --> 00:38:04,750
the complexity that needs to be explained, right?

644
00:38:05,230 --> 00:38:07,470
And and those those have to meet, right?

645
00:38:07,550 --> 00:38:12,190
Those those those have to meet to have a really, really s strong science of what we're

646
00:38:12,190 --> 00:38:13,230
trying to do here, I think.

647
00:38:13,390 --> 00:38:15,470
So I I th I think they're entirely complementary.

648
00:38:15,550 --> 00:38:20,110
I don't I don't see them as being competing at all, but but maybe there's a little bit of a

649
00:38:20,430 --> 00:38:26,220
uh uh uh an aesthetic difference in sort of where one started or maybe like i said

650
00:38:26,300 --> 00:38:31,020
it may it may just be a practice difference right i mean it's i grew up in one place i

651
00:38:31,020 --> 00:38:35,260
didn't grow up in the other place and so it's a sort of where where where my mind goes

652
00:38:35,260 --> 00:38:35,500
first.

653
00:38:35,820 --> 00:38:39,100
Yeah and I like I did I did the a first graduate class.

654
00:38:39,180 --> 00:38:43,420
We've there had never been a graduate class in evolutionary psychology at UCSB, believe it

655
00:38:43,420 --> 00:38:43,820
or not.

656
00:38:44,300 --> 00:38:50,290
And I did I tra transform what was the undergrad class that Lita had been teaching, that I

657
00:38:50,290 --> 00:38:55,250
had been teaching since I was a graduate student, and that I taught when I left and taught

658
00:38:55,250 --> 00:38:55,890
elsewhere.

659
00:38:56,050 --> 00:39:01,090
I form reformatted that into a grad class and it was doing largely doing a task analysis.

660
00:39:01,330 --> 00:39:05,730
Uh and there is and this is also in the um David Lewis et al.

661
00:39:05,890 --> 00:39:10,930
bus lab paper, where you can go phenomenon first or adapt a problem first.

662
00:39:11,090 --> 00:39:16,760
And you can just sort of and and when you do phenomenon first, it's really, you know, is

663
00:39:16,760 --> 00:39:18,120
it, does it quack like a duck?

664
00:39:18,200 --> 00:39:19,080
Does it sound like a duck?

665
00:39:19,160 --> 00:39:20,040
Does it swim like a duck?

666
00:39:20,120 --> 00:39:23,560
You know, you're really just interrogating, well, what is the phenomenon you're talking

667
00:39:23,560 --> 00:39:23,800
about?

668
00:39:23,960 --> 00:39:29,960
But as you said, Steve, then you're translating that into the job of an evolutionary

669
00:39:29,960 --> 00:39:35,320
psychologist is to take an important phenomenon and then have this gambit or these

670
00:39:35,320 --> 00:39:40,350
guesses of what are the likely adaptations that are underlying this, you know?

671
00:39:40,430 --> 00:39:45,230
And I like both of you, you like David with humor or with like status games or Steve

672
00:39:45,390 --> 00:39:49,310
looking at and looking at prejudice or discrimination or stigma.

673
00:39:49,790 --> 00:39:55,630
The skill in the art is to look at a complicated real-world phenomena and

674
00:39:55,630 --> 00:40:01,080
pare it down to at least one or two really plausible sets of

675
00:40:01,080 --> 00:40:05,960
adaptive problems, which is not easy, but I think that's I think you're describing, Steve,

676
00:40:06,040 --> 00:40:10,520
exactly like what it is to be day to day an evolutionary psychologist is you're just

677
00:40:10,520 --> 00:40:11,800
looking at the world.

678
00:40:11,960 --> 00:40:16,760
Um, and this is even something John Tuby used to say like your job is to just sort of the

679
00:40:16,760 --> 00:40:22,680
news, history, day to day life, you're always translating that into what

680
00:40:22,680 --> 00:40:26,520
are the adaptations or likely sets of adaptations causing that.

681
00:40:28,520 --> 00:40:30,110
Yeah, no, I I think that's right.

682
00:40:30,270 --> 00:40:31,310
I think that's right.

683
00:40:31,550 --> 00:40:33,310
Uh it's fun.

684
00:40:33,470 --> 00:40:39,470
You know, I I like the fact that they're um that there's

685
00:40:39,470 --> 00:40:43,710
sort of these different flavors of approach to it.

686
00:40:43,870 --> 00:40:47,390
I mean I I find that uh I I find that enriching.

687
00:40:47,550 --> 00:40:53,520
And and I have to say, so uh this is this is the first sabbatical I think I've I've had

688
00:40:53,600 --> 00:40:54,800
I'm on tobacco right now.

689
00:40:54,960 --> 00:40:56,960
I can't tell that I'm on sabbac right now.

690
00:40:57,040 --> 00:40:59,120
I shouldn't be here in my office.

691
00:41:01,440 --> 00:41:07,200
That I haven't actually gone to UCSB for a week or so to hang out and to talk to

692
00:41:07,200 --> 00:41:12,880
Lita and and the social psychologists and and uh uh everyone

693
00:41:12,880 --> 00:41:18,800
else uh there about the idea that would that's like bouncing around in my head, right?

694
00:41:19,250 --> 00:41:23,410
And uh I I've done that of I've done that a few times and it's been incredible.

695
00:41:23,570 --> 00:41:27,250
I I probably need to find a way of showing when when is your semester over?

696
00:41:27,330 --> 00:41:28,290
So I can show you how to do it.

697
00:41:30,290 --> 00:41:30,770
You're not teaching.

698
00:41:31,890 --> 00:41:32,370
I have no idea.

699
00:41:32,450 --> 00:41:32,610
Yeah.

700
00:41:32,850 --> 00:41:38,130
You have to ask any kind of uh uh but yeah, I mean couple weeks.

701
00:41:38,530 --> 00:41:39,490
Couple weeks, okay.

702
00:41:39,650 --> 00:41:43,410
Yeah, I probably probably I probably missed the opportunity this this year for that.

703
00:41:43,650 --> 00:41:49,360
Uh but yeah, uh I've I've always benefited greatly from uh from going to Santa

704
00:41:49,360 --> 00:41:55,040
Barbara and uh and talking with folks and throwing the ideas out there and then you know

705
00:41:55,360 --> 00:42:01,280
having them uh gently of over a six hour period of time, three or four

706
00:42:01,280 --> 00:42:06,640
hours in the in the C E P meetings and then over dinner with Lita and John afterwards, uh

707
00:42:06,800 --> 00:42:10,400
you know, having them interrogated uh in really sort of fun ways.

708
00:42:13,750 --> 00:42:19,510
So you mentioned earlier um that you you work with Tom Gilovich and um he just

709
00:42:19,510 --> 00:42:21,590
didn't get it in in your words.

710
00:42:21,670 --> 00:42:24,070
And and there are still some people who who don't get it.

711
00:42:24,230 --> 00:42:27,430
Uh and I'm curious what you think is going on there.

712
00:42:27,510 --> 00:42:29,910
What is ex what explains the the holdouts?

713
00:42:30,150 --> 00:42:33,830
I mean you mentioned some of it, whether there's some political concerns about there being,

714
00:42:33,910 --> 00:42:37,670
you know, genetic determinism or uh or or stuff like that.

715
00:42:37,910 --> 00:42:39,910
Um that's probably part of it.

716
00:42:40,100 --> 00:42:43,620
Uh do you think that's all the i that's what's not all of it.

717
00:42:43,940 --> 00:42:44,180
Okay.

718
00:42:44,740 --> 00:42:48,580
Yeah, I I I think that another aspect of it is sort of the David Hamilton comment.

719
00:42:48,660 --> 00:42:49,700
Yeah, but why do we need it?

720
00:42:49,860 --> 00:42:50,100
Right.

721
00:42:50,260 --> 00:42:54,580
And I think this has to do uh I th I used this term in a little bit of a different sense a

722
00:42:54,580 --> 00:42:57,780
few minutes ago, of a sort of a scientific aesthetic.

723
00:42:57,940 --> 00:43:02,660
That is what what what are you really trying to accomplish with your sci I mean what sort

724
00:43:02,660 --> 00:43:06,970
of feels right or looks right for you at at at what level do you really want to explain?

725
00:43:07,050 --> 00:43:08,970
I mean, what counts as explanation for you?

726
00:43:09,130 --> 00:43:11,050
What counts as understanding for you?

727
00:43:11,290 --> 00:43:14,890
And I th I think that's actually probably the bigger thing.

728
00:43:15,130 --> 00:43:17,610
It's like, yeah, yeah, fine, but why do we need it?

729
00:43:17,690 --> 00:43:21,370
Let's just, you know, you know, you you got you got a long pathway of a model here.

730
00:43:21,450 --> 00:43:22,730
Why don't we just start right here?

731
00:43:22,810 --> 00:43:23,050
Right?

732
00:43:23,210 --> 00:43:28,840
You know, why why do we need to understand that stuff uh uh as well right

733
00:43:29,080 --> 00:43:34,440
and and i think that's and and that and the assumption there uh especially for those

734
00:43:34,440 --> 00:43:40,040
psychologists who are interested in at least having their work be relevant to intervention

735
00:43:40,280 --> 00:43:43,800
well geez you know the closer you can intervene to the thing that you want to change maybe

736
00:43:43,800 --> 00:43:47,880
the better off you are anyway so do you really need to understand this bigger frame that's

737
00:43:47,960 --> 00:43:53,160
that's deeper and and and sort of causally further back uh and

738
00:43:53,720 --> 00:43:58,850
I've always wanted to sort of dive in and to and to play with that idea a little bit more

739
00:43:58,930 --> 00:44:03,570
because, you know, my intuition on it is that no, it makes a huge difference because it it

740
00:44:03,650 --> 00:44:07,810
it it gives you it tells you what territory you need to be in, right?

741
00:44:08,050 --> 00:44:10,850
And I think we're missing huge territories, right?

742
00:44:11,010 --> 00:44:12,130
Because we're not asking.

743
00:44:12,290 --> 00:44:15,810
Uh that because because we're not understanding the adaptive problem.

744
00:44:15,970 --> 00:44:18,690
So we're not looking in the right places, right?

745
00:44:18,930 --> 00:44:23,640
And so we're we're, you know, uh yeah, we're blind that we're blind, right?

746
00:44:23,800 --> 00:44:29,800
We're sort of theory blind to where a lot of the gr the the the the stronger possibilities

747
00:44:29,800 --> 00:44:31,560
might might be, right?

748
00:44:31,960 --> 00:44:35,800
And sort of thinking that through and developing that uh a little more.

749
00:44:35,880 --> 00:44:40,920
I'll I'll never do it, but I I think that would be a useful thing, you know, in terms of

750
00:44:41,000 --> 00:44:46,870
uh, you know, help helping folks uh who who aren't as driven

751
00:44:46,870 --> 00:44:50,150
as much by the ideology but just still don't understand, yeah, but why do we need it?

752
00:44:50,390 --> 00:44:53,830
And I th and I think there's also this this this different level of curiosity, right?

753
00:44:53,910 --> 00:44:56,310
I mean so so Tubi was starting as a physicist.

754
00:44:56,390 --> 00:44:59,030
Everything starts it right I mean curious about a lot of things.

755
00:44:59,110 --> 00:44:59,990
Everything needs to connect.

756
00:45:00,150 --> 00:45:01,670
Everything needs to connect, right?

757
00:45:02,070 --> 00:45:05,990
And uh and I think for a lot of folks everything doesn't need to connect.

758
00:45:07,180 --> 00:45:07,980
That's really interesting.

759
00:45:08,140 --> 00:45:12,060
Yeah, it's almost like um there are different appetites for explanation.

760
00:45:12,220 --> 00:45:17,820
And we just have a really deep hunger to get as deep as possible in the explanatory uh uh

761
00:45:18,780 --> 00:45:21,100
depth of of what we're what we're looking at.

762
00:45:21,260 --> 00:45:24,620
Um and some people uh are not as hungry for explanatory depth.

763
00:45:24,700 --> 00:45:30,220
They're they're they're happy if they can just explain something at at a shallow level, and

764
00:45:30,220 --> 00:45:33,580
um that might be you know an individual difference variable.

765
00:45:33,900 --> 00:45:38,970
Yeah, I mean at a what I would say for a lot of them it would be at a

766
00:45:38,970 --> 00:45:44,650
mechanistic level, but not understanding, you know, why

767
00:45:44,730 --> 00:45:49,130
why those mechanisms and therefore maybe not understanding nuances that they don't see

768
00:45:49,130 --> 00:45:50,650
because they don't measure the right stuff.

769
00:45:50,810 --> 00:45:51,050
Right.

770
00:45:51,130 --> 00:45:54,890
Or they're not seeing alternative mechanisms as well because again they're not thinking

771
00:45:54,890 --> 00:45:59,290
about it in terms of the problem that the that this that this ultimate behavior is trying

772
00:45:59,290 --> 00:46:02,970
to uh or problems that that they're is trying to solve, right?

773
00:46:03,050 --> 00:46:08,940
And so uh I I think I think it's uh it's

774
00:46:08,940 --> 00:46:14,780
a blindness outside the particular uh mechanism

775
00:46:15,020 --> 00:46:17,100
sort of of current focus.

776
00:46:17,260 --> 00:46:21,900
Uh and they wanna they say, okay, there's something here, let's come in and let's and and

777
00:46:21,900 --> 00:46:23,900
let's really sort of understand that.

778
00:46:24,060 --> 00:46:28,300
Um again, not realizing that there's all this other stuff out there uh that they're not

779
00:46:28,300 --> 00:46:28,620
seeing.

780
00:46:32,210 --> 00:46:36,370
thought that came to me about like how these people might be persuaded.

781
00:46:36,530 --> 00:46:41,570
You know, it seems to me like what they're trying to do is they're trying to fix a machine.

782
00:46:41,810 --> 00:46:43,490
Let's say, let's say it's a car.

783
00:46:43,730 --> 00:46:48,370
But um they're ignoring what the machine is and what its function is and what the different

784
00:46:48,370 --> 00:46:50,370
parts of it are designed to do.

785
00:46:50,530 --> 00:46:54,850
And you're gonna have a much harder time fixing a car if you don't know that what you're

786
00:46:54,850 --> 00:46:59,090
fixing is a car and the part you're f if you don't know what part what the function of the

787
00:46:59,090 --> 00:47:00,920
part you're looking at is, right?

788
00:47:01,080 --> 00:47:02,600
You're gonna have a really hard time.

789
00:47:02,760 --> 00:47:06,840
Um it so it seems like if you want to fix the car, you have to understand number one, that

790
00:47:06,840 --> 00:47:11,480
it is a car, and number two, that it has a set of functionally specialized parts that are

791
00:47:11,480 --> 00:47:13,160
designed to do different things.

792
00:47:13,320 --> 00:47:17,320
And you're gonna have, you know, uh imagine a mechanic who doesn't know what he's fixing

793
00:47:17,400 --> 00:47:20,360
and doesn't know the function of the things he's looking at, right?

794
00:47:20,680 --> 00:47:23,080
So that might be one argument you could give.

795
00:47:23,390 --> 00:47:28,350
Right, or d or doesn't understand what the what the relate so you're going in and you you

796
00:47:28,430 --> 00:47:32,350
even even if you understand sort of part of the part of the machine and you're going in to

797
00:47:32,350 --> 00:47:37,150
like fix a piston or something like that, uh, or you're trying to make it better or

798
00:47:37,150 --> 00:47:40,590
whatever you're trying to do, but you don't realize what the relationship between that

799
00:47:40,590 --> 00:47:42,590
piston is and these other things.

800
00:47:42,670 --> 00:47:45,790
And if it turns out if it yeah, you can get it cranking faster.

801
00:47:45,950 --> 00:47:48,590
If you get it cranking faster, you know the suspension's not going to hold.

802
00:47:48,820 --> 00:47:50,020
I'm making stuff up I don't know.

803
00:47:50,340 --> 00:47:50,420
Sure.

804
00:47:50,900 --> 00:47:50,980
Right.

805
00:47:51,220 --> 00:47:51,460
Right.

806
00:47:51,540 --> 00:47:51,860
Yeah.

807
00:47:52,100 --> 00:47:56,020
And uh and and and a and a real system wouldn't work like that, right?

808
00:47:56,900 --> 00:48:02,820
Sort of a real sort of uh adaptive system wouldn't have pistons that work in the kind

809
00:48:02,820 --> 00:48:06,260
of way that its suspension couldn't uh couldn't hold together.

810
00:48:06,340 --> 00:48:06,580
Right.

811
00:48:07,060 --> 00:48:12,900
I I also think there's it's really one cannot overestimate

812
00:48:13,380 --> 00:48:18,730
the sociology of the moral landscape of academia.

813
00:48:18,810 --> 00:48:24,090
And I really think that also if you grow up in a world where you're focused on a mechanism

814
00:48:24,330 --> 00:48:29,930
and people who are appealing to evolution are using that to essentialize or justify

815
00:48:30,250 --> 00:48:36,090
social or gender discrepancies, then it's not only a lack of

816
00:48:36,090 --> 00:48:41,960
curiosity, it's also a marker of there's another group of people

817
00:48:41,960 --> 00:48:47,400
who have an agenda that's not to figure out the mechanism, but to just

818
00:48:47,400 --> 00:48:50,600
essentialize the existing status quo.

819
00:48:51,160 --> 00:48:53,080
And that did that that did happen.

820
00:48:53,160 --> 00:48:58,120
And that's not what some evolutionary psychologists or most evolutionary psychologists are

821
00:48:58,120 --> 00:49:03,290
doing, but it does make sense why people would have that um perspective.

822
00:49:03,450 --> 00:49:09,210
And it's very much uh probably implicit thing of part of theory is sort of a marking, it's

823
00:49:09,210 --> 00:49:13,450
like a coalitional or coordination marker of like, who's my moral circle?

824
00:49:13,690 --> 00:49:16,490
We're all good, but there's other people who are up to no good.

825
00:49:16,570 --> 00:49:18,250
And theory is part of marking that.

826
00:49:18,330 --> 00:49:24,170
And so not wanting to adopt another theory has this like loyalty and moral tinge to

827
00:49:24,170 --> 00:49:24,490
it.

828
00:49:25,050 --> 00:49:26,410
I I think I think that's true.

829
00:49:26,490 --> 00:49:31,300
And I and I was if you would have if we would have had this conversation, you know, seven

830
00:49:31,300 --> 00:49:37,300
or eight years ago, what I would have said is that

831
00:49:37,700 --> 00:49:42,100
younger people, and I still think this is the case, that that younger scholars are way more

832
00:49:42,100 --> 00:49:47,940
open to what we're doing than older scholars, than folks of my generation and and

833
00:49:48,100 --> 00:49:49,940
uh and and beyond.

834
00:49:50,100 --> 00:49:55,890
Uh because they didn't grow up in the in the in the uh in the

835
00:49:55,890 --> 00:50:01,890
social activism and social constructivism sort of days of the sixties and the

836
00:50:01,890 --> 00:50:07,330
seventies and and and and all of that and have that be sort of part core of of their

837
00:50:07,330 --> 00:50:11,330
identities and of their affiliations or coalitions and and the like.

838
00:50:11,970 --> 00:50:17,200
And then the world got easier and simpler and okay now you know we we we can we can look at

839
00:50:17,200 --> 00:50:19,120
the world and we don't need these particular lenses.

840
00:50:19,200 --> 00:50:24,240
And I think you know younger psychologists were becoming more open to the evolutionary

841
00:50:24,240 --> 00:50:24,800
approach.

842
00:50:25,040 --> 00:50:31,040
I do wonder now, like over the last five years or so, whether that's taken uh as

843
00:50:31,040 --> 00:50:32,480
taken a hit again.

844
00:50:32,720 --> 00:50:38,080
You know, younger younger scientists are different now than uh uh than they were.

845
00:50:38,240 --> 00:50:42,970
Uh they're more sensitive to a lot of things, I think they feel more vulnerable.

846
00:50:43,210 --> 00:50:49,210
Uh uh they are uh even more cynical of of

847
00:50:49,210 --> 00:50:55,050
what they view as power structures which are defined by things that are very

848
00:50:55,050 --> 00:50:58,570
much sort of extra sci extra scientific, right?

849
00:50:58,970 --> 00:51:04,840
Uh and uh yeah and and and part of so i i think

850
00:51:04,840 --> 00:51:10,760
it'll be interesting over these next five or ten years to see you know whether you know the

851
00:51:10,760 --> 00:51:15,880
sort of the growth in the acceptance of evolutionary psychology takes a little bit of a a

852
00:51:15,880 --> 00:51:21,480
dip a little bit of a of a hit uh i think i think eventually you know the

853
00:51:21,720 --> 00:51:27,690
uh uh the science is gonna win out but i'm an optimist uh Uh

854
00:51:27,930 --> 00:51:28,810
but yeah, we'll see.

855
00:51:28,970 --> 00:51:34,570
And and and and part of part of my my local pessimism about this might have been I was

856
00:51:34,570 --> 00:51:35,530
chair for six years.

857
00:51:35,690 --> 00:51:41,610
I was chair during, you know, sort of the COVID George Floyd times where uh young

858
00:51:41,610 --> 00:51:47,050
people especially, sort of grad students especially, right, uh just became very, very

859
00:51:47,050 --> 00:51:52,970
activated and uh very, very sensitive to things that could be seen as uh uh oppressive in

860
00:51:52,970 --> 00:51:54,010
one way or another.

861
00:51:54,360 --> 00:51:59,560
And so uh I wonder whether we're gonna we're gonna be fall back into being stereotyped in

862
00:51:59,640 --> 00:52:01,480
and in in those ways again.

863
00:52:01,800 --> 00:52:01,960
Yeah.

864
00:52:02,280 --> 00:52:07,800
Or or we're part of the uh anti oppression um articulation.

865
00:52:08,040 --> 00:52:13,800
So uh I I I I feel like the last five or six years, I feel like uh um

866
00:52:14,690 --> 00:52:18,690
I don't know if it's COVID or I don't know if it's the political climate, like not to get

867
00:52:18,690 --> 00:52:19,730
political about things.

868
00:52:19,970 --> 00:52:24,290
I do feel like as an academic, I'm sort of living through a dying institution.

869
00:52:24,690 --> 00:52:26,770
You know, like journals.

870
00:52:27,090 --> 00:52:31,570
Uh I mean, I don't know what how David feels about this, but you know, I'm old enough that

871
00:52:31,570 --> 00:52:37,330
I feel like I was at the tail end of the golden era of um you could

872
00:52:37,330 --> 00:52:41,330
publish an article that didn't have fancy, glossy figures in it.

873
00:52:41,620 --> 00:52:42,900
people would read the articles.

874
00:52:43,060 --> 00:52:46,900
Maybe I was a kid, and maybe this was all maybe this is just a thing of when you're a kid,

875
00:52:46,980 --> 00:52:49,860
the world is ideal, and when you grow up, you realize it's not.

876
00:52:50,020 --> 00:52:55,220
Um, but you know, like I'm I'm old enough that I didn't have like as much internet science,

877
00:52:55,300 --> 00:52:58,740
and it wasn't as much like glossy photos.

878
00:52:58,980 --> 00:53:04,980
Um, and now it just feels like, especially sped up with like AI and and these things where

879
00:53:04,980 --> 00:53:10,670
it's just sort of funding, publishing, um, teaching all of these things

880
00:53:10,830 --> 00:53:16,750
just feel like there's it's sort of a dying institution and so even myself like the last

881
00:53:16,750 --> 00:53:22,750
five or six years I feel like there is more um more extra scientific

882
00:53:22,750 --> 00:53:28,430
garbage um or you're sort of aware of um uh all the ways in which

883
00:53:28,430 --> 00:53:34,190
science is being harmed um from all these outside forces and I I feel um

884
00:53:34,350 --> 00:53:37,710
I feel more oppressed in the last five or six years.

885
00:53:39,160 --> 00:53:40,600
Yeah, that's interesting.

886
00:53:40,840 --> 00:53:43,480
Uh holding myself constant.

887
00:53:43,640 --> 00:53:47,480
I'm uh I'm uh it's a within participant, uh within subjects effect.

888
00:53:47,560 --> 00:53:48,040
Yeah.

889
00:53:48,600 --> 00:53:49,240
Right.

890
00:53:49,720 --> 00:53:55,160
Uh yeah, I I I I you know share that that vibe, I think.

891
00:53:55,320 --> 00:53:58,040
I th there is a sense that something is decaying.

892
00:53:58,280 --> 00:54:00,680
Um maybe it's it's just an illusion.

893
00:54:00,760 --> 00:54:01,960
And I'm and I don't know.

894
00:54:02,120 --> 00:54:04,570
But curious if you if you share that feeling, Steve.

895
00:54:04,810 --> 00:54:08,170
Yeah, I don't know if it's a co I don't know if it's just you get older as a scientist and

896
00:54:08,170 --> 00:54:13,770
you realize the ways you you were ideal idealizing the process and then you see the

897
00:54:13,770 --> 00:54:17,130
warts and sausage being made, and that's always true.

898
00:54:17,450 --> 00:54:23,290
Or if it's really that um, you know, there's there's just a very different

899
00:54:23,290 --> 00:54:29,240
experience um That older faculty in my department, for example, didn't have to deal

900
00:54:29,240 --> 00:54:34,440
with a lot of these things that now current faculty, especially young faculty, are dealing

901
00:54:34,440 --> 00:54:36,120
with that are really new problems.

902
00:54:36,280 --> 00:54:41,800
I mean, maybe they had other new problems back in the day, but I think there's a

903
00:54:45,080 --> 00:54:48,040
this may be sort of orthogonal to what you guys are talking about.

904
00:54:48,200 --> 00:54:54,170
I think uh Science

905
00:54:54,490 --> 00:55:00,410
among serious scientists is getting there's like a

906
00:55:00,410 --> 00:55:04,250
pressure to be safer in it, right?

907
00:55:04,570 --> 00:55:09,850
Uh and I think part of this came out of uh a lot of very legitimate criticisms, you know,

908
00:55:09,930 --> 00:55:15,850
having to do with reproducibility and uh and uh how we were doing, uh how we were analyzing

909
00:55:15,850 --> 00:55:18,970
data and and and all of that, you know.

910
00:55:19,130 --> 00:55:22,500
Uh and I so I think there's some really legitimate criticism.

911
00:55:22,740 --> 00:55:24,900
I think we're doing a lot of that better now, right?

912
00:55:25,300 --> 00:55:30,980
Uh but I think people are scientists are uh

913
00:55:31,460 --> 00:55:36,900
becoming more afraid of making mistakes and getting caught in mistakes.

914
00:55:37,140 --> 00:55:43,030
Uh we've become uh you know science by Arthur Anderson versus by

915
00:55:43,270 --> 00:55:44,470
Magellan, right?

916
00:55:44,550 --> 00:55:46,950
That we're so we're concerned with these type one errors, right?

917
00:55:47,030 --> 00:55:49,990
We don't want to we don't want to have any false positives.

918
00:55:50,070 --> 00:55:55,190
But in and and so we get safe and the science gets narrower and we get more specialized and

919
00:55:55,270 --> 00:55:58,470
you know we don't swing for the fences as much, right?

920
00:55:58,710 --> 00:56:02,630
Uh but I think there's a huge cost to that, right?

921
00:56:02,950 --> 00:56:07,110
Uh you know, you have to head out into the into the open seas.

922
00:56:07,190 --> 00:56:12,940
I mean, otherwise the the science gets uh it's what it gets

923
00:56:12,940 --> 00:56:13,900
small, right?

924
00:56:14,380 --> 00:56:20,380
And uh if you think about times when you don't need small science, I think now times

925
00:56:20,380 --> 00:56:22,620
you don't need small science, right?

926
00:56:22,700 --> 00:56:28,220
And I and I and I think uh there there have been a lot of concerns in terms of you know

927
00:56:28,620 --> 00:56:33,310
what people are willing to do and what people are willing to sort of put out there and what

928
00:56:33,310 --> 00:56:34,990
risks they're willing to take.

929
00:56:35,950 --> 00:56:40,910
And partially because the criticism can be so fierce and it can be so quick and it can be

930
00:56:40,910 --> 00:56:41,950
so ad hominem.

931
00:56:53,200 --> 00:56:57,200
I'm actually not gonna mention her name because this was a really horrible experience for

932
00:56:57,200 --> 00:56:57,360
her.

933
00:56:57,520 --> 00:57:00,960
But who who had some papers who got seriously criticized.

934
00:57:01,120 --> 00:57:07,040
Uh and and some might have been legitimate criticisms, but not based on the morality of the

935
00:57:07,040 --> 00:57:08,320
scientists, right?

936
00:57:08,720 --> 00:57:12,400
Uh and uh and you know, Susan's dad was Donald Fisk.

937
00:57:12,640 --> 00:57:16,000
I don't know if that name rings a bell to you guys, but Fisk and Campbell, he was a very,

938
00:57:16,160 --> 00:57:21,360
very sort of important methodologist way back when uh in the University of Chicago.

939
00:57:21,600 --> 00:57:27,530
Uh uh and you know, there was a person who like threw out there on social media, you know,

940
00:57:27,690 --> 00:57:32,090
uh Donald Fisk would be spinning in his grave looking at this stuff, right?

941
00:57:32,410 --> 00:57:34,890
And it just just cruel, right?

942
00:57:35,130 --> 00:57:40,410
And and so I I I think there's this environment out there that the world can see what you

943
00:57:40,410 --> 00:57:44,410
do, they can misinterpret what they do, they can label it how they want to.

944
00:57:44,650 --> 00:57:46,660
Recovering is way harder, right?

945
00:57:46,820 --> 00:57:51,940
Tearing something down right and recovering from accusations is really, really hard.

946
00:57:52,260 --> 00:57:55,380
And so I think we're getting a little bit safer.

947
00:57:55,780 --> 00:58:01,780
And uh and and I think for people who feel compelled

948
00:58:01,780 --> 00:58:04,260
to be safer, right?

949
00:58:04,660 --> 00:58:08,070
I think I think uh that has to feel lousy.

950
00:58:08,230 --> 00:58:13,030
I think it has to uh feel stifling, or maybe you just get used to it a while and then

951
00:58:13,110 --> 00:58:13,670
science changes.

952
00:58:13,750 --> 00:58:16,950
And if that's the case, that's you know, that's sort of heartbreaking.

953
00:58:17,190 --> 00:58:20,550
Uh you know, I have a I have a thing.

954
00:58:21,670 --> 00:58:26,310
I have I have I have a couple couple things that that you'll that you can see around my

955
00:58:26,310 --> 00:58:27,910
office if you wander in.

956
00:58:28,070 --> 00:58:33,190
You know, one is uh quote by Einstein, not all that relevant here, but really it's a it's a

957
00:58:33,270 --> 00:58:39,160
it's a little bit of a it's a it's a it's a critique of sort of over parsimony right uh

958
00:58:39,320 --> 00:58:43,320
that sometimes we way oversimplify things you still have to account for the data right and

959
00:58:43,320 --> 00:58:49,320
what and what nature uh says but I have this thing here that's a story about Enrico Fermi

960
00:58:49,560 --> 00:58:54,680
who's used who's taking a tour of uh of someone other physicist lab and he's asked

961
00:58:54,760 --> 00:58:59,000
afterwards essentially hey so what do you think and uh I

962
00:59:01,610 --> 00:59:06,890
Research appears to be technically impeccable, but theoretically unexciting.

963
00:59:07,130 --> 00:59:11,930
But maybe so, but these are like bricks, bricks in the wall of uh in the edifice of

964
00:59:11,930 --> 00:59:12,730
science, right?

965
00:59:12,890 --> 00:59:16,570
You know, the uh the person comes back to them and says, well, no, we know most of them are

966
00:59:16,570 --> 00:59:19,210
just bricks laying around in a in a brickyard.

967
00:59:19,370 --> 00:59:21,690
And and the message for that is like, no bricks.

968
00:59:21,770 --> 00:59:26,810
We shouldn't be, we shouldn't be, you know, just uh just making bricks, right?

969
00:59:26,890 --> 00:59:29,210
They they have to be about something.

970
00:59:29,520 --> 00:59:33,840
And uh you know, there's another metaphor I sort of like, especially with students as

971
00:59:33,840 --> 00:59:38,320
they're at the stage where it's now time for them to sort of think about an identity, think

972
00:59:38,320 --> 00:59:41,120
about what your thing is going to be, you know, start doing this.

973
00:59:41,200 --> 00:59:43,840
Uh and it's the metaphor of a shot across a bow.

974
00:59:44,000 --> 00:59:48,240
And that, you know, the very first piece of work you do and sort of in with a new question,

975
00:59:48,320 --> 00:59:53,520
a new area, it should be designed to be a shot across the bow.

976
00:59:53,600 --> 00:59:59,390
And that is in the sense that if you're right and if the data turn out that people have to

977
00:59:59,390 --> 01:00:02,990
say, whoa, huh, this uh this this would change things.

978
01:00:03,150 --> 01:00:07,550
If this is right, this sort of if and if I decide I'm gonna take this seriously, right, as

979
01:00:07,550 --> 01:00:10,670
a scientist, this has to change things, right?

980
01:00:10,910 --> 01:00:15,790
And I think we need to be doing more of that as opposed to I mean I think a lot of people

981
01:00:15,790 --> 01:00:17,310
add bricks to their own edifices.

982
01:00:17,390 --> 01:00:18,350
I guess that's okay.

983
01:00:18,590 --> 01:00:24,460
Adding bricks to someone else's edifice, okay, that that that's fine, but that that to me

984
01:00:24,620 --> 01:00:30,620
is uh that's minor league science that what we really need more people doing is and and I

985
01:00:30,620 --> 01:00:31,900
don't care if you're wrong, right?

986
01:00:31,980 --> 01:00:34,940
I mean here's the other thing about science that that's incredible, right?

987
01:00:35,020 --> 01:00:37,900
I mean, if it's about something important, right?

988
01:00:38,300 --> 01:00:42,220
Uh it's people are gonna try to replicate it, they're gonna try to build on it and we'll

989
01:00:42,220 --> 01:00:43,580
discover that it's wrong, right?

990
01:00:43,740 --> 01:00:49,530
That to me is such a lesser cost than not to go out there and to take the risks and

991
01:00:49,610 --> 01:00:54,570
and and and and try to generate something that that would make a difference, right?

992
01:00:54,650 --> 01:00:56,170
And how we understand things.

993
01:00:56,570 --> 01:00:56,810
Yeah.

994
01:00:57,130 --> 01:00:59,690
Derek Gigerenzer has a very similar thing.

995
01:00:59,770 --> 01:01:05,770
It's like an older theory and psychology paper where he's at a lunch with students and

996
01:01:05,770 --> 01:01:11,450
there's faculty and the young students are asking faculty for advice and the faculty are

997
01:01:11,450 --> 01:01:15,930
saying, well, you really want a safe topic that you know you're going to get about three or

998
01:01:15,930 --> 01:01:18,560
four papers worth of data from.

999
01:01:18,960 --> 01:01:23,280
Um and then you know you can have your sort of speculative idea you can pursue later when

1000
01:01:23,280 --> 01:01:24,400
you're a faculty member.

1001
01:01:24,480 --> 01:01:30,400
And then Gerton is uh Gert style honesty is like that's fine if you want to be mediocre but

1002
01:01:30,400 --> 01:01:33,680
really you should so it's a similar similar sentiment.

1003
01:01:33,920 --> 01:01:37,760
Um I hear that but yeah no David yeah go ahead.

1004
01:01:38,320 --> 01:01:41,680
No no it was so but but but the thing is

1005
01:01:44,870 --> 01:01:49,430
If if if it's an interesting question, the data are going to be valuable no matter what.

1006
01:01:49,510 --> 01:01:54,710
You'll still get those three or four papers, you know, worth of you know uh data if you're

1007
01:01:54,790 --> 01:01:57,510
if you're asking important questions, right?

1008
01:01:57,590 --> 01:02:00,870
Yeah and uh and you're designing the studies well, right?

1009
01:02:02,550 --> 01:02:02,870
Yeah.

1010
01:02:03,110 --> 01:02:04,540
I mean I think that's an important thing.

1011
01:02:04,700 --> 01:02:10,060
Yeah, we we we have to be asking questions that are interesting enough that no matter you

1012
01:02:10,060 --> 01:02:12,540
know what the answer is, it's going to be interesting.

1013
01:02:12,780 --> 01:02:13,260
Right?

1014
01:02:13,580 --> 01:02:17,900
Where we uh it's bad when we get into a place where the questions we're asking, they only

1015
01:02:17,900 --> 01:02:19,580
matter if the if the data come out one way.

1016
01:02:19,660 --> 01:02:23,020
And if they don't come out that way, then whatever, we'll put it in the file drawer.

1017
01:02:23,260 --> 01:02:25,020
Like that's a bad place to be for science.

1018
01:02:25,260 --> 01:02:30,220
We want to be asking questions that really give you interesting data however they come out.

1019
01:02:30,750 --> 01:02:30,990
Yeah.

1020
01:02:31,150 --> 01:02:36,350
I I I also like, I mean, I everybody has their own sort of personal situation that they're

1021
01:02:36,430 --> 01:02:40,510
and I think one's expression of sort of what's going on in science is a readout of that.

1022
01:02:40,590 --> 01:02:43,790
And I'm aware that like what I'm about to say is largely my experience.

1023
01:02:44,030 --> 01:02:49,790
But I also think uh, you know, I also grew up with the theory

1024
01:02:49,790 --> 01:02:50,190
crisis.

1025
01:02:50,270 --> 01:02:54,910
Like I actually was submitting, I had a paper out at JPSP under Chick Judd at the same time

1026
01:02:55,070 --> 01:02:59,200
this the Daryl Bem, the infamous Daryl Bem paper came out.

1027
01:02:59,440 --> 01:03:05,360
Um and uh I think one of the other problems

1028
01:03:05,680 --> 01:03:11,120
is there's still we're still this is all a symptom still of the theory crisis

1029
01:03:11,520 --> 01:03:17,120
because there from a young from a young pers from a younger person's perspective

1030
01:03:17,360 --> 01:03:22,880
there was a view of the the older guard, which is probably

1031
01:03:22,880 --> 01:03:28,670
unfair, was uh the currency was like, is it

1032
01:03:28,670 --> 01:03:29,710
surprising?

1033
01:03:30,190 --> 01:03:35,310
And if you wanted to do sort of slower science where you just publish like a dirt

1034
01:03:35,310 --> 01:03:40,990
derivation of what we should be looking for in the mind, or a theory that isn't

1035
01:03:40,990 --> 01:03:46,510
surprising but is true and hasn't been documented, that's sort of more incremental, but I

1036
01:03:46,510 --> 01:03:52,030
would argue more profound because it's it's it's but it wasn't in the currency of

1037
01:03:52,030 --> 01:03:53,070
surprising.

1038
01:03:53,310 --> 01:03:58,840
Um that that was that was a generational

1039
01:03:59,160 --> 01:04:00,040
conflict.

1040
01:04:00,280 --> 01:04:06,280
And I think some of the I know who you're talking about, you know, the the the Susan Fix

1041
01:04:06,600 --> 01:04:07,800
student, and it was horrible.

1042
01:04:08,040 --> 01:04:10,360
I know, I know um her pretty well.

1043
01:04:10,600 --> 01:04:16,440
Um uh I think some of those were the growing pains, and where I think we're still in the

1044
01:04:16,440 --> 01:04:21,960
growing pains of as a science, psychology is still not figured out,

1045
01:04:22,120 --> 01:04:28,090
sort of it hasn't figured out the division of labor of who's doing what and what are

1046
01:04:28,090 --> 01:04:29,690
all the things that need to be done.

1047
01:04:29,930 --> 01:04:35,130
And I think some a lot of people feel like victims be in that

1048
01:04:35,450 --> 01:04:36,570
miscoordination.

1049
01:04:36,650 --> 01:04:42,410
And then people feel justified to harm other people because they're like, I wasn't valued.

1050
01:04:42,570 --> 01:04:45,690
I'm a statistician and I see how everybody's doing everything wrong.

1051
01:04:45,770 --> 01:04:46,730
And I wasn't valued.

1052
01:04:46,810 --> 01:04:51,880
So I'm gonna hurt somebody else, or I'm an evolutionary psychologist, and people don't

1053
01:04:51,880 --> 01:04:53,080
value adaptationism.

1054
01:04:53,320 --> 01:04:54,920
So I'm gonna hurt somebody else.

1055
01:04:55,080 --> 01:05:00,200
Or I wanna be shoot for the fences in a phenomenon, but nobody cares about that anymore.

1056
01:05:00,280 --> 01:05:02,680
So I'm gonna, I think everybody is correct.

1057
01:05:02,840 --> 01:05:08,680
I think it's just we there that we we're not coordinated enough yet as a science.

1058
01:05:10,680 --> 01:05:15,750
Yeah, that's I'm I'm trying to think about what coordinated science looks like.

1059
01:05:15,910 --> 01:05:20,150
I mean so in physics they have you know, they make a distinction between sort of

1060
01:05:20,150 --> 01:05:23,510
theoreticians and uh and empiricists, right?

1061
01:05:23,990 --> 01:05:29,670
Uh and uh and and rarely do they do they do they meet, rarely do they do

1062
01:05:29,670 --> 01:05:30,790
both things.

1063
01:05:31,110 --> 01:05:36,640
Uh yeah, I d I d I do think the surprising thing was a was a big

1064
01:05:37,120 --> 01:05:42,480
and and a and it was a it was a criterion in a lot of journals and and I think it was a big

1065
01:05:42,480 --> 01:05:42,800
problem.

1066
01:05:43,200 --> 01:05:48,800
Uh but I think it was a it was it was the version of

1067
01:05:48,800 --> 01:05:51,360
surprising that was the big problem.

1068
01:05:51,600 --> 01:05:56,800
That is that it had to surprise your your well evolved intuitions, right?

1069
01:05:57,040 --> 01:05:59,760
Which also meant that that a lot of those things were gonna be wrong.

1070
01:05:59,950 --> 01:06:00,270
Exactly.

1071
01:06:00,510 --> 01:06:01,310
I mean right.

1072
01:06:01,470 --> 01:06:02,350
Uh but there's a lot of things.

1073
01:06:04,350 --> 01:06:09,710
It was like I think there's a c it's a Kurt Gray and uh Dan Gilbert paper.

1074
01:06:09,790 --> 01:06:10,590
Uh how to do that.

1075
01:06:10,750 --> 01:06:11,550
Dan Wagner, maybe.

1076
01:06:11,710 --> 01:06:12,750
Dan Wagner, that's right.

1077
01:06:12,910 --> 01:06:13,390
Yeah, yeah, yeah.

1078
01:06:13,870 --> 01:06:14,190
Yeah.

1079
01:06:14,590 --> 01:06:14,750
Yeah.

1080
01:06:14,990 --> 01:06:17,150
And we forget that your grandmother knows a lot of things.

1081
01:06:17,230 --> 01:06:17,950
She's pretty smart.

1082
01:06:18,430 --> 01:06:18,910
Well, you know what?

1083
01:06:19,230 --> 01:06:21,630
But she knows she knows everything.

1084
01:06:21,790 --> 01:06:26,800
She knows she knows that absent makes the heart grow fonder and she knows that out of s she

1085
01:06:26,800 --> 01:06:27,920
knows out of sight, out of mind.

1086
01:06:28,080 --> 01:06:29,280
She actually knows both of those things.

1087
01:06:29,600 --> 01:06:33,040
Does she know when when those are gonna be she can see but she doesn't know how she sees.

1088
01:06:33,120 --> 01:06:38,880
That's also that there is a kind of surprising that I think

1089
01:06:38,880 --> 01:06:39,840
is really important.

1090
01:06:40,240 --> 01:06:45,600
And that is uh surprising relative to the dominant

1091
01:06:45,600 --> 01:06:47,990
theoretical frames of the time.

1092
01:06:48,070 --> 01:06:48,550
Yeah right.

1093
01:06:48,630 --> 01:06:50,310
And the challenging of the frames.

1094
01:06:50,470 --> 01:06:55,510
And so sometimes the response that I get to some of my research is uh

1095
01:06:56,870 --> 01:06:58,070
this hindsight thing.

1096
01:06:58,230 --> 01:07:01,270
Oh yeah of of of course there are these different kind of prejudices or whatever.

1097
01:07:01,430 --> 01:07:04,230
And I and I and uh and so okay so what?

1098
01:07:04,390 --> 01:07:04,630
Right?

1099
01:07:04,790 --> 01:07:07,190
And I'd say okay well look at every one of your theories.

1100
01:07:07,340 --> 01:07:10,700
Give me show me one theory that actually can generate this set of predictions.

1101
01:07:10,940 --> 01:07:12,300
It's like, oh, right.

1102
01:07:12,540 --> 01:07:15,900
That's the kind of that's that's sort of the shot across the bow.

1103
01:07:15,980 --> 01:07:19,580
That's the kind of surprising thing that we that we do need, right?

1104
01:07:19,820 --> 01:07:25,660
The things that challenge the standard frames that we have, uh and that's

1105
01:07:25,820 --> 01:07:28,390
and that's where the advances that come from.

1106
01:07:28,550 --> 01:07:32,790
The problem is that the kind of surprising that we were going after was was the you know

1107
01:07:32,870 --> 01:07:36,390
grandma Bubba, you know, uh, you know, surprising.

1108
01:07:36,710 --> 01:07:37,030
Yeah.

1109
01:07:37,190 --> 01:07:37,430
Yeah.

1110
01:07:37,510 --> 01:07:42,070
I think my my mean my opinion is that the journals are not adequately organized or

1111
01:07:42,070 --> 01:07:47,030
articulate what I want um and where to send this kind of paper.

1112
01:07:47,110 --> 01:07:52,560
Like I think the journal landscape is um is really bad right now.

1113
01:07:52,720 --> 01:07:58,000
And I think there's I there's so many people I talk to who send papers out to different

1114
01:07:58,000 --> 01:08:02,160
journals and they're just desk rejected because this is not the kind of paper we want, but

1115
01:08:02,160 --> 01:08:03,680
there's no articulation of where.

1116
01:08:03,840 --> 01:08:09,840
And if it's not the the the operationalization of sort of this is where you do

1117
01:08:09,920 --> 01:08:12,880
this kind of paper is not articulated.

1118
01:08:13,040 --> 01:08:18,830
And I think editors with no guile or malicious intent are

1119
01:08:18,830 --> 01:08:21,950
nervous and they want their journal to look sciencey.

1120
01:08:22,190 --> 01:08:27,470
And if something looks out of place or different than what is usual, then they'll just sort

1121
01:08:27,470 --> 01:08:32,590
of say, Well, I don't want to be under the tutelage of this journal taking weird looking,

1122
01:08:32,750 --> 01:08:34,670
less sciencey looking things.

1123
01:08:34,990 --> 01:08:35,550
Right.

1124
01:08:35,870 --> 01:08:41,700
So that I I think that I think that's right and again it it leads to safe

1125
01:08:41,700 --> 01:08:46,420
science and I think you know the funding agencies, you know, NIH would I mean you pretty

1126
01:08:46,420 --> 01:08:50,420
much have finished all the studies that you'd be proposing in an NIH proposal, you know,

1127
01:08:50,500 --> 01:08:55,220
and and provide you know enough of that sort of pilot data on it uh you know before NIH

1128
01:08:55,300 --> 01:08:57,540
would say, okay, we'll we'll we'll spend money on this now.

1129
01:08:57,700 --> 01:08:57,940
Right?

1130
01:08:58,100 --> 01:09:04,050
I mean it you know it it it you know just uh just very, very uh uh safe and

1131
01:09:04,050 --> 01:09:07,170
i guess that's you know i think we can think about scarcity in different kinds of ways we

1132
01:09:07,170 --> 01:09:11,810
can think about in terms of money you know i guess for the journal it's you know is it is

1133
01:09:11,810 --> 01:09:17,170
it scarcity of sort of reputation or or just the concern of making a mistake and getting

1134
01:09:17,170 --> 01:09:23,170
caught and when when I I was associate editor of JESP a long

1135
01:09:23,170 --> 01:09:28,940
time ago uh, with with Russ Fazio as the editor, and and we instituted a thing at the

1136
01:09:29,100 --> 01:09:32,620
it may have been one of the very first versions of this, which were short papers.

1137
01:09:32,860 --> 01:09:38,300
So there'd be a long and and and I can see in some ways why this would be viewed as

1138
01:09:38,300 --> 01:09:40,060
outrageous now, right?

1139
01:09:40,140 --> 01:09:45,820
Uh, this is before the replication crisis and everything, where the notion was:

1140
01:09:46,060 --> 01:09:49,530
no, we don't want to spend 30 pages on this, right?

1141
01:09:50,010 --> 01:09:55,850
Uh you know, you got four studies and whatever, and yep, stuff, but it's a really cool

1142
01:09:55,850 --> 01:09:56,330
idea.

1143
01:09:56,970 --> 01:10:02,810
So let's pull out the the the study that's the best exemplar of the idea,

1144
01:10:03,050 --> 01:10:08,410
and we'll give you seven pages or whatever, whatever the the number was, and uh

1145
01:10:08,970 --> 01:10:11,760
and let's get that out there so the world can see it.

1146
01:10:12,000 --> 01:10:12,640
Right.

1147
01:10:12,880 --> 01:10:18,480
Now, what that sort of meant was okay, you were and this is before the the age of

1148
01:10:18,480 --> 01:10:20,480
computer, you know, online supplements.

1149
01:10:22,240 --> 01:10:25,200
So people wouldn't see all the other stuff that was out there, right?

1150
01:10:25,440 --> 01:10:29,040
Uh and so yeah, I can see why that would get critiqued now.

1151
01:10:29,440 --> 01:10:35,130
But the but the notion was again that it's an idea that's worth having out there.

1152
01:10:35,290 --> 01:10:39,610
And if it's an important idea and it turns out to be wrong, we're gonna discover it.

1153
01:10:39,850 --> 01:10:41,130
And that's okay.

1154
01:10:41,290 --> 01:10:44,330
That's the way I mean we we should be thrilled by that.

1155
01:10:44,490 --> 01:10:46,090
That's the way science works.

1156
01:10:46,250 --> 01:10:48,970
I'd rather have an idea that turns out to be wrong.

1157
01:10:49,130 --> 01:10:52,730
I'd rather generate an idea, have it out there for a while, and then have someone say, you

1158
01:10:52,730 --> 01:10:57,460
know, it's really this, it's not that, and say, okay.

1159
01:10:57,620 --> 01:11:01,140
I think I I think you know, under that circumstance, I will still have made a contribution

1160
01:11:01,220 --> 01:11:05,060
because I would have had an idea out there that would have been significant enough that

1161
01:11:05,060 --> 01:11:08,900
could have, and now, boom, we got we got people talking, we learned something.

1162
01:11:09,060 --> 01:11:13,060
Uh yes, this is now off the table, and we're going, we're going here.

1163
01:11:13,220 --> 01:11:14,980
That's that's science moving forward.

1164
01:11:15,140 --> 01:11:18,340
I think that's a hard thing, and maybe that's easier because I'm old, right?

1165
01:11:18,420 --> 01:11:24,210
And my my my career is set, you know, I'm a folk professor, I'm tenured, I make a

1166
01:11:24,210 --> 01:11:26,930
good salary, I I'm not forced to retire at any age.

1167
01:11:27,010 --> 01:11:29,890
I can sort of do this however uh however I want.

1168
01:11:29,970 --> 01:11:33,410
And so that's that's easy for me to to I think to say that.

1169
01:11:33,490 --> 01:11:38,370
I think for a young untenured person that's a way harder uh thing to say, uh especially

1170
01:11:38,370 --> 01:11:43,970
these days and especially again how quickly one can get devastated by uh by the

1171
01:11:44,130 --> 01:11:48,690
commentariat out there in the you know out there in the in the world.

1172
01:11:48,850 --> 01:11:51,900
So yeah.

1173
01:11:52,300 --> 01:11:53,420
That's this is very meta.

1174
01:11:53,740 --> 01:11:54,220
This is good though.

1175
01:11:54,540 --> 01:11:54,860
I know.

1176
01:11:55,500 --> 01:11:56,140
Yeah.

1177
01:11:56,460 --> 01:12:00,940
Maybe we should talk about what Steve Newberg, the evolutionary psychology you do.

1178
01:12:01,660 --> 01:12:03,260
Uh no, but this is wonderful.

1179
01:12:03,340 --> 01:12:08,220
I yeah, it but the last it reminds me there's a Jerry Fodor um when Jerry Fodor passed

1180
01:12:08,220 --> 01:12:13,900
away, there was a um a memorial service and somebody talked about how uh they remembered

1181
01:12:14,060 --> 01:12:19,330
um going up to Jerry Fodor and saying, you know, this one idea I think you have is actually

1182
01:12:19,330 --> 01:12:20,450
pretty reasonable.

1183
01:12:20,690 --> 01:12:24,050
And he looked shocked and he's like, but it's still pretty unreasonable, right?

1184
01:12:24,130 --> 01:12:30,130
Like he wanted to he wanted to be the the the contrarian or to provoke people to get them

1185
01:12:30,130 --> 01:12:30,450
to think.

1186
01:12:30,610 --> 01:12:33,410
And I think that's you know, yeah, I think that's really important.

1187
01:12:33,570 --> 01:12:36,840
And I I think a science that doesn't encourage that.

1188
01:12:36,920 --> 01:12:42,120
I think it's a litmus test of we're probably incentivizing the wrong thing.

1189
01:12:42,280 --> 01:12:47,560
Um, if we can't be like, hey, this is this, let's what what if this is true?

1190
01:12:47,800 --> 01:12:48,920
Let's figure this out.

1191
01:12:49,080 --> 01:12:49,880
Like, yeah.

1192
01:12:50,600 --> 01:12:55,800
Or or we just need to be, is ecumenical the right term, in terms of the different kind of

1193
01:12:55,880 --> 01:12:59,400
sciences and the different kind of scholarship that we're open to, right?

1194
01:12:59,560 --> 01:12:59,720
Yeah.

1195
01:12:59,880 --> 01:13:03,870
Uh I mean, I've got colleagues in in the department and and the work to me is totally

1196
01:13:03,870 --> 01:13:08,190
uninspiring, but it's important in certain kind of ways because it helps people with mental

1197
01:13:08,190 --> 01:13:09,150
illnesses, right?

1198
01:13:09,310 --> 01:13:10,510
Deal with their challenges, right?

1199
01:13:10,590 --> 01:13:14,590
It's not interesting to me, but it's it's really useful and there and there needs to be

1200
01:13:14,590 --> 01:13:15,150
space for that.

1201
01:13:15,310 --> 01:13:15,470
Yeah.

1202
01:13:15,550 --> 01:13:20,990
You know, I also want them to be to to look at stuff that uh that I and some of my

1203
01:13:20,990 --> 01:13:25,230
colleagues are doing where, you know, there this it's way further you know to to get to

1204
01:13:25,230 --> 01:13:28,910
application, but it's about how the mind works and that's really an important thing, right?

1205
01:13:29,150 --> 01:13:30,430
And let's understand that.

1206
01:13:30,510 --> 01:13:36,380
And so, you know, and I I think if uh we're a little bit less sort of uh you know sort of

1207
01:13:36,380 --> 01:13:42,300
intradisciplinarily tribal or whatever, uh that that's uh something that would be good

1208
01:13:42,300 --> 01:13:42,780
for us.

1209
01:13:43,020 --> 01:13:43,340
Yeah.

1210
01:13:44,620 --> 01:13:44,940
Yeah.

1211
01:13:45,180 --> 01:13:50,140
I mean I mean this goes to Dave's point, which I think is very well articulated that it's

1212
01:13:50,140 --> 01:13:54,140
about, you know, coordination failures among you know, we're we're just not rowing in the

1213
01:13:54,140 --> 01:13:54,780
same direction.

1214
01:13:54,860 --> 01:13:56,860
It's more like every man for himself.

1215
01:13:57,020 --> 01:13:59,730
Uh there's no cohesive paradigm.

1216
01:13:59,810 --> 01:14:05,010
There's no shared goal or shared uh philosophy about what we're doing and why we're doing

1217
01:14:05,010 --> 01:14:09,490
it and what we're looking for and how our science should be.

1218
01:14:09,890 --> 01:14:15,890
Um, I mean, maybe the solution to that is to have more you know broad conferences where

1219
01:14:15,890 --> 01:14:20,690
people from diverse parts of the social sciences come together and get on the same page,

1220
01:14:20,850 --> 01:14:26,290
but you know, that has its own challenges, and and that's also hard in in in different

1221
01:14:26,290 --> 01:14:26,770
ways.

1222
01:14:27,010 --> 01:14:28,660
Um yeah, I don't know.

1223
01:14:28,740 --> 01:14:29,860
I mean there's a great quote.

1224
01:14:29,940 --> 01:14:34,820
I can't remember who said it that um the best interdisciplinary work is done within one's

1225
01:14:34,820 --> 01:14:35,140
own mind.

1226
01:14:35,460 --> 01:14:36,900
I think you said it was Jerry Fodor back in the middle.

1227
01:14:36,980 --> 01:14:38,100
Yeah, I think it was Jerry Fodor, yeah.

1228
01:14:38,180 --> 01:14:39,300
I could I could be wrong, but yeah.

1229
01:14:39,700 --> 01:14:41,540
Sounds like something Jerry Fodor would say.

1230
01:14:42,340 --> 01:14:44,420
You attribute it to Jerry Fodor early in an earlier.

1231
01:14:45,140 --> 01:14:48,900
The best interdisciplinary work happens within one's own mind.

1232
01:14:49,140 --> 01:14:54,810
Yeah, see, I yeah, I don't I don't I don't buy it.

1233
01:14:54,970 --> 01:15:00,810
I th I think, you know, what you actually need are people who come at things

1234
01:15:00,810 --> 01:15:06,330
from very different perspectives but have an ethos of of listening and learning from one

1235
01:15:06,330 --> 01:15:06,810
another.

1236
01:15:06,970 --> 01:15:08,250
And and and it's it's hard.

1237
01:15:08,330 --> 01:15:14,170
It takes a I've I've done several interdisciplinary uh kinds of uh uh sort of

1238
01:15:14,140 --> 01:15:15,580
bigger projects.

1239
01:15:15,740 --> 01:15:18,380
And uh it's hard because it takes a while to get the language.

1240
01:15:18,540 --> 01:15:23,180
And and you and I know I remember one instance doing this project on religion and conflict

1241
01:15:23,340 --> 01:15:27,740
where it took a full year before I realized that two of us were using the same term in very

1242
01:15:27,740 --> 01:15:28,380
different ways.

1243
01:15:28,540 --> 01:15:28,780
Yeah.

1244
01:15:28,940 --> 01:15:29,340
Right.

1245
01:15:29,980 --> 01:15:32,860
You know, because you know the disciplines used them in different ways.

1246
01:15:33,020 --> 01:15:36,300
And uh and that we didn't even realize that we had sort of been talking.

1247
01:15:36,460 --> 01:15:39,130
We finally realized this is why we're talking past each other.

1248
01:15:39,370 --> 01:15:39,610
Right.

1249
01:15:39,770 --> 01:15:41,210
And it took a year, right?

1250
01:15:41,370 --> 01:15:46,890
Uh and so so so doing doing that kind of work is hard, but no one can be an

1251
01:15:46,890 --> 01:15:49,530
expert in in tons of things, right?

1252
01:15:49,610 --> 01:15:54,730
And so you you you want you want folks who have the depth of expertise and then you want to

1253
01:15:54,730 --> 01:16:00,490
be willing to listen and to let the ideas uh collide and converge and uh you know

1254
01:16:00,730 --> 01:16:04,250
meld and uh and everything I think.

1255
01:16:04,810 --> 01:16:05,130
Yeah.

1256
01:16:05,450 --> 01:16:07,220
And it's hard to get the benefit of the doubt.

1257
01:16:07,300 --> 01:16:11,780
I mean, I remember, I mean, Steve, I think you're doing exactly what David is describing

1258
01:16:11,780 --> 01:16:14,420
here, which is you're helping coordinate, right?

1259
01:16:14,660 --> 01:16:20,020
But it's it's hard because number one, and I think students really feel this, is that if

1260
01:16:20,020 --> 01:16:25,220
you go, for example, to a social psychology pre-conference and you don't use the same

1261
01:16:25,220 --> 01:16:30,260
terminology or you're you're coming from a different perspective, we all absorb these norms

1262
01:16:30,340 --> 01:16:32,820
of this is the way I usually do this.

1263
01:16:33,370 --> 01:16:38,010
And I think to their credit and detriment, social psychology is a very norm heavy

1264
01:16:38,010 --> 01:16:38,730
discipline.

1265
01:16:38,890 --> 01:16:42,570
I think there's there's lots of anecdotal data.

1266
01:16:42,730 --> 01:16:46,890
You know, for a while you couldn't get a paper published without a path diagram, a path

1267
01:16:47,050 --> 01:16:47,450
diagram.

1268
01:16:47,530 --> 01:16:51,530
I mean, it was very, you know, they were like, I remember working with social

1269
01:16:51,530 --> 01:16:54,730
psychologists, and they're like, no, you have to say this thing in this way.

1270
01:16:54,890 --> 01:16:57,610
You have to have this kind of figure, you have to have this kind of statistic.

1271
01:16:57,690 --> 01:16:59,340
I was like, but you don't even know what the study is about.

1272
01:16:59,420 --> 01:17:00,460
It just doesn't matter.

1273
01:17:00,540 --> 01:17:01,500
This is the norm.

1274
01:17:01,820 --> 01:17:06,700
And you know, and so I think like going up in front of a group of people, violating the

1275
01:17:06,700 --> 01:17:11,260
norm, knowing you're doing that by having a different approach, it's a vulnerability.

1276
01:17:11,340 --> 01:17:15,260
It would be hard for a young student, especially if it's hard for young people and for

1277
01:17:15,260 --> 01:17:20,140
women or anybody, like you know, for example, like if if you're not the kind of phenotype

1278
01:17:20,300 --> 01:17:26,250
or the that is given the benefit of the doubt for for multiple reasons, then

1279
01:17:26,250 --> 01:17:31,610
there's this additional problem of in order for me to even cr facilitate

1280
01:17:31,850 --> 01:17:34,970
coordination, the people, the audience has to give me the benefit of the doubt.

1281
01:17:35,130 --> 01:17:37,690
In a 15 minute talk, are they going to?

1282
01:17:38,010 --> 01:17:42,570
So I think like it's very courageous for everybody to do it, but I think it's really good

1283
01:17:42,570 --> 01:17:47,530
when people do it like you, Steve, because it opens the door for other people who may not

1284
01:17:47,530 --> 01:17:48,970
even be able to do that.

1285
01:17:49,700 --> 01:17:51,780
Well, I'd never thought about that, but thank you.

1286
01:17:52,020 --> 01:17:57,940
Uh I I I do think that, you know, one of the this is this is not only,

1287
01:17:58,020 --> 01:18:03,380
you know, part of the problem in in in doing the science, but maybe in our broader

1288
01:18:03,380 --> 01:18:06,980
societies is that we've moved away from giving people the benefit of the doubt.

1289
01:18:07,220 --> 01:18:07,700
Right.

1290
01:18:07,940 --> 01:18:11,780
And uh and that has just humongous uh costs.

1291
01:18:12,020 --> 01:18:17,970
Uh it it has costs, you know, for when that when that benefit isn't given, but it

1292
01:18:17,970 --> 01:18:22,530
has huge costs in people knowing that that they're not going to be given it, and therefore

1293
01:18:22,610 --> 01:18:28,050
they're spending all this time and all this effort to uh uh to

1294
01:18:28,770 --> 01:18:34,690
overexplain is not quite the right word, but uh but to avoid the potential cost of of

1295
01:18:34,690 --> 01:18:36,130
being misinterpreted.

1296
01:18:36,290 --> 01:18:39,490
Uh and that's that's uh just a heavy weight, right?

1297
01:18:39,820 --> 01:18:44,940
Uh to to know that I can't go and and have a five minute conversation with someone uh you

1298
01:18:44,940 --> 01:18:49,580
know that that is that is that is just totally play right because I could be

1299
01:18:49,580 --> 01:18:55,100
misinterpreted, I could do this, uh to have to, you know, think about exactly how I'm gonna

1300
01:18:55,100 --> 01:19:00,700
say every single thing, that I don't leave this out, that I what be I mean that's that's a

1301
01:19:00,700 --> 01:19:01,260
heavy weight.

1302
01:19:01,340 --> 01:19:06,140
And that's a weight that takes away from uh doing uh a lot of creative good things.

1303
01:19:06,300 --> 01:19:10,910
You know, I'd I'd rather, you know, if if you think uh and I see this actually in some

1304
01:19:10,910 --> 01:19:14,590
communication, I've been talking to some colleagues about this, you know, you I see

1305
01:19:14,590 --> 01:19:19,630
sometimes tensions arise where, you know, someone will write an email, right?

1306
01:19:19,870 --> 01:19:24,590
Not even about so they'll write an email and someone will have an interpretation of that.

1307
01:19:24,670 --> 01:19:29,310
And instead of asking a question, let me understand, are you saying this or are you saying

1308
01:19:29,310 --> 01:19:29,630
this?

1309
01:19:29,790 --> 01:19:32,580
They presume that they're saying that.

1310
01:19:33,220 --> 01:19:37,540
And uh and now all of a sudden you have a conflict where there's never any need to have a

1311
01:19:37,540 --> 01:19:37,940
conflict.

1312
01:19:38,020 --> 01:19:40,500
And now people are going they're they're cycling on this.

1313
01:19:40,820 --> 01:19:45,300
It's now the person who's been accused of something that they didn't do, now they're

1314
01:19:45,300 --> 01:19:46,900
offended and everyone's offended.

1315
01:19:47,060 --> 01:19:48,660
Uh yeah, I think those two things.

1316
01:19:48,820 --> 01:19:51,220
We don't give people the benefit of the doubt and we're too easily offended.

1317
01:19:51,300 --> 01:19:55,780
You put those two things together and it's hard to do it's hard to do really good science.

1318
01:19:55,940 --> 01:20:01,690
Uh to it's hard it's hard to communicate uh really good uh uh science and uh

1319
01:20:01,770 --> 01:20:02,810
and to take risks.

1320
01:20:03,130 --> 01:20:03,370
Yeah.

1321
01:20:03,610 --> 01:20:08,970
Yeah, or even if we're not more offended, there's uh the selection for

1322
01:20:09,290 --> 01:20:10,810
attention, right?

1323
01:20:10,970 --> 01:20:16,170
Like there's just new coordination devices like social media, or you know, I I if you're

1324
01:20:16,250 --> 01:20:18,490
I'm just doing my science, nobody's paying attention to me.

1325
01:20:18,650 --> 01:20:22,890
But boy, I just said something controversial, or that could be interpreted, or I just knock

1326
01:20:22,970 --> 01:20:28,160
somebody down, all of a sudden I've got you know thousands of people looking at me.

1327
01:20:28,240 --> 01:20:29,200
That felt good.

1328
01:20:29,360 --> 01:20:30,720
I'm gonna do more of that, right?

1329
01:20:30,800 --> 01:20:36,560
So even if people um individually are no different, there's now like a select uh

1330
01:20:36,720 --> 01:20:41,120
institutional selection for for these things, yeah.

1331
01:20:41,680 --> 01:20:47,440
Yeah, and I and I actually think that and the knocking down, I think we saw a lot of that

1332
01:20:47,680 --> 01:20:51,920
uh for young people who are sort of trying to be on their way up.

1333
01:20:52,080 --> 01:20:57,190
I mean, it's uh it's uh it's it's it's exciting, it's a drug, right?

1334
01:20:57,350 --> 01:20:59,270
And it you know it can really be reinforcing.

1335
01:20:59,350 --> 01:21:02,870
And and so I'll tell you something that I have a little bit of shame about.

1336
01:21:03,190 --> 01:21:09,190
So uh not because I think I did the science wrong, but because of how I felt

1337
01:21:09,590 --> 01:21:11,670
you know with the communication of it.

1338
01:21:11,830 --> 01:21:15,750
So I was in a controversy uh I don't know if I should be even saying this.

1339
01:21:15,910 --> 01:21:21,590
I was in a controversy with an article Kru Kruglanski uh in the mid nineteen eighties

1340
01:21:21,830 --> 01:21:27,520
about this uh uh about this individual difference uh construct uh personal need for

1341
01:21:27,520 --> 01:21:33,120
structure uh and need for cognitive uh closure that he was doing some work on

1342
01:21:33,360 --> 01:21:39,200
and uh I don't need to go into the content of it but we ended up uh I

1343
01:21:39,200 --> 01:21:45,010
I ended up learning around two months before we were

1344
01:21:45,010 --> 01:21:50,130
both me and a student of his were gonna be on a panel together talking about sort of need

1345
01:21:50,290 --> 01:21:55,010
for structure kind of ideas and and how they shape cognition and all sorts of other things.

1346
01:21:55,170 --> 01:21:55,490
Okay.

1347
01:21:55,890 --> 01:22:01,810
So uh what I dis what I discovered in the couple months before, because I got an email from

1348
01:22:01,810 --> 01:22:05,890
a student at another place that says, you know, you this scale over here that that that you

1349
01:22:06,050 --> 01:22:11,820
felt uh you know advanced done by other people, not by me, uh, but that I published on it.

1350
01:22:11,900 --> 01:22:15,900
And this scale over here by Kruglanski and his colleagues, you know they're correlated like

1351
01:22:15,900 --> 01:22:16,460
point eight.

1352
01:22:16,700 --> 01:22:19,020
It's like no that and I I was a reviewer on that crew.

1353
01:22:19,100 --> 01:22:21,660
I said, no, they couldn't be correlated.8, right?

1354
01:22:21,900 --> 01:22:25,020
They uh you know they're correlated point two.

1355
01:22:25,180 --> 01:22:26,940
It says, no no no look I here are my data.

1356
01:22:27,100 --> 01:22:31,660
So we ran a thing here and yes it's point eight and attenuating for over whatever.

1357
01:22:31,820 --> 01:22:35,580
Uh it's essentially they're essentially the same scales, but one's way longer and has a lot

1358
01:22:35,580 --> 01:22:37,580
of bad items in it, and one is shorter.

1359
01:22:37,830 --> 01:22:39,750
but all those items were overlap.

1360
01:22:39,990 --> 01:22:41,430
And logically, of course, they were correlated.

1361
01:22:41,590 --> 01:22:45,510
And we like I had like four colleagues around the country in your own sample.

1362
01:22:45,670 --> 01:22:46,150
So go ahead.

1363
01:22:46,230 --> 01:22:47,030
You know what is it?

1364
01:22:47,750 --> 01:22:51,670
And then we dove deeper and we were looking at the structure of these, and and and we had a

1365
01:22:51,670 --> 01:22:54,070
sort of a legitimate sort of critique.

1366
01:22:54,310 --> 01:23:00,150
And the problem was from the science perspective, was that they were the

1367
01:23:00,200 --> 01:23:04,440
way they were doing it, they were taking two independent constructs, but it was making it

1368
01:23:04,440 --> 01:23:06,200
look like it was just one construct.

1369
01:23:06,440 --> 01:23:08,840
And that was going to lead to a lot.

1370
01:23:11,000 --> 01:23:17,000
I'm a splitter as opposed to a lumper, uh theoretically, and uh it was going to lead to

1371
01:23:17,000 --> 01:23:21,240
a lot of wrong inferences about about really what was going on with with all these social

1372
01:23:21,240 --> 01:23:23,240
cognitive processes it was being used for.

1373
01:23:23,480 --> 01:23:29,130
And so at this conference, and this was uh it was I think the one time that S E S P and the

1374
01:23:29,130 --> 01:23:32,810
European Association had a joint conflict, I think it was in DC.

1375
01:23:33,210 --> 01:23:34,730
Uh, and we were on this panel together.

1376
01:23:34,810 --> 01:23:37,850
So around a month before, I said, you know what, I'm gonna change the topic of my talk.

1377
01:23:37,930 --> 01:23:38,970
I think this is really important.

1378
01:23:39,130 --> 01:23:42,330
I'm gonna talk about this stuff because it's about the construct.

1379
01:23:42,490 --> 01:23:44,090
But here's what I'm gonna say.

1380
01:23:44,250 --> 01:23:46,330
I'm gonna uh everyone has a heads up.

1381
01:23:46,490 --> 01:23:48,170
Here's what I'm gonna say beforehand.

1382
01:23:48,330 --> 01:23:53,340
No one's gonna get, and you know if you want to put me at the end, right, so that you don't

1383
01:23:53,340 --> 01:23:57,580
feel the need to sort of respond to what I'm gonna say in your own talks, absolutely fine.

1384
01:23:57,740 --> 01:23:58,940
They put me at the end.

1385
01:23:59,100 --> 01:24:02,540
They actually try to have me not be allowed to talk about that.

1386
01:24:02,700 --> 01:24:05,900
And to their credit, the conference organizers said this is science.

1387
01:24:05,980 --> 01:24:08,540
Conferences are about the cutting edge stuff at the front end.

1388
01:24:08,700 --> 01:24:13,100
You know, yes, he can he can change his mind about what he's gonna uh talk about.

1389
01:24:13,340 --> 01:24:19,070
Uh there was uh the sort of his

1390
01:24:19,070 --> 01:24:23,310
allies on the panel sort of filibustered by the time it got to Schaller was also on the

1391
01:24:23,310 --> 01:24:24,910
panel uh talking about other stuff.

1392
01:24:25,070 --> 01:24:29,310
By the time it got to me, there were like seven minutes left for my you know 17-minute

1393
01:24:29,550 --> 01:24:30,110
talk.

1394
01:24:30,430 --> 01:24:33,550
And uh and and there was no time for nuance.

1395
01:24:33,630 --> 01:24:35,870
And this is back in the days of overhead projectors.

1396
01:24:36,190 --> 01:24:40,670
And so Shaler's like slapping the the things down on the thing, and I'm just going boom,

1397
01:24:40,750 --> 01:24:41,310
boom, boom.

1398
01:24:41,390 --> 01:24:44,580
No no nuance, no politically political sensitivity.

1399
01:24:44,900 --> 01:24:50,340
And at the end of the talk, you know, RE is in the audience because a student had

1400
01:24:50,340 --> 01:24:54,100
presented, and he said, I've got some I've got some things to say.

1401
01:24:54,260 --> 01:24:56,180
So he says the one thing I start to answer.

1402
01:24:56,260 --> 01:24:57,460
He says, No, no, no, no, no.

1403
01:24:57,620 --> 01:25:00,260
You've had your chance to talk now, it's my turn.

1404
01:25:00,500 --> 01:25:03,460
And and it's at the end of a session.

1405
01:25:03,830 --> 01:25:05,270
people aren't leaving the room.

1406
01:25:05,350 --> 01:25:06,710
We're going overtime, right?

1407
01:25:06,790 --> 01:25:10,790
The rooms people are coming in, and instead of trying to kick us off, this is like the

1408
01:25:10,790 --> 01:25:14,310
coolest thing they've ever seen at a conference because we're going back and forth.

1409
01:25:14,630 --> 01:25:18,310
And uh and I got a buzz off of it.

1410
01:25:18,470 --> 01:25:18,790
Yeah.

1411
01:25:19,030 --> 01:25:19,670
Right.

1412
01:25:19,990 --> 01:25:25,030
And uh and I feel some shame for the buzz I got off of it.

1413
01:25:25,190 --> 01:25:27,030
A young guy, I was a young guy at the time.

1414
01:25:27,110 --> 01:25:32,980
I in fact, uh before I went and I did that, I I was I had I was

1415
01:25:33,140 --> 01:25:34,580
I had just gotten tenure.

1416
01:25:34,740 --> 01:25:40,660
In fact I asked, you know, Bob and Doug, Taldini and and Kenrick, uh whether I

1417
01:25:40,660 --> 01:25:41,540
should do this or not.

1418
01:25:41,620 --> 01:25:43,700
And they said, you know, this is what tenure's for, right?

1419
01:25:43,860 --> 01:25:45,060
This is this is what tenure's for.

1420
01:25:45,140 --> 01:25:48,980
If you believe the data, if you believe then then you should do this.

1421
01:25:49,220 --> 01:25:54,690
Uh so I I under but but I it it it got it went

1422
01:25:54,690 --> 01:25:58,530
beyond the science uh at that point for me.

1423
01:25:58,690 --> 01:25:59,410
And that was wrong.

1424
01:25:59,570 --> 01:26:00,290
And that was wrong.

1425
01:26:00,450 --> 01:26:04,050
He and I didn't chat for a long, we didn't talk, and we had been we hadn't known each other

1426
01:26:04,050 --> 01:26:09,490
well, and he in fact been a supporter of me when I was very young uh for like 10-15 years.

1427
01:26:09,730 --> 01:26:12,930
Uh to to put a bring a happy end to the story.

1428
01:26:13,170 --> 01:26:16,820
Uh we're in a lobby at another conference.

1429
01:26:16,900 --> 01:26:21,540
I'm sitting at I'm sort of standing chatting with someone and I see him walking down.

1430
01:26:21,620 --> 01:26:23,780
He's gonna he's gonna pass right in front of me.

1431
01:26:24,020 --> 01:26:25,620
And I don't know what it was.

1432
01:26:25,780 --> 01:26:27,220
I grabbed him as he walked by.

1433
01:26:27,300 --> 01:26:29,220
I said, you know, we should talk.

1434
01:26:29,540 --> 01:26:31,540
He said, Yeah, we should talk.

1435
01:26:31,780 --> 01:26:36,910
Happy hour later, down in the down in the poster session, whatever the thing was.

1436
01:26:39,870 --> 01:26:42,030
We're there two minutes into the conversation.

1437
01:26:42,910 --> 01:26:47,310
I sort of explained, you know, why I did what I did, and then we we publ we went back and

1438
01:26:47,310 --> 01:26:48,270
forth in the literature too.

1439
01:26:48,350 --> 01:26:50,990
I mean, it turned into a series of papers, uh, which was good.

1440
01:26:51,070 --> 01:26:52,270
I think it was good for the field.

1441
01:26:52,430 --> 01:26:57,070
Uh two minutes later he says, You know, I'm the new editor of this series on these on these

1442
01:26:57,150 --> 01:26:59,310
uh on these monographs about stereotyping prejudice.

1443
01:26:59,470 --> 01:27:00,030
You want to do one?

1444
01:27:00,270 --> 01:27:01,550
It's like you know.

1445
01:27:01,710 --> 01:27:07,280
So it's it's sort of, I mean, at that the space gave us the ability to take the the person

1446
01:27:07,920 --> 01:27:10,800
the personal aspects out of it, right?

1447
01:27:11,040 --> 01:27:12,960
But the personal aspects get in there.

1448
01:27:13,200 --> 01:27:18,720
And I think as a young person, you know, there there there's there's a buzz to going after

1449
01:27:18,720 --> 01:27:24,240
senior people and uh the f folks who are who have the power and stuff and it's uh

1450
01:27:24,400 --> 01:27:26,640
it's natural uh and it's not good.

1451
01:27:26,970 --> 01:27:27,210
Yeah.

1452
01:27:27,370 --> 01:27:32,010
I mean I think to your credit, I don't think it wasn't like you were pursuing it.

1453
01:27:32,090 --> 01:27:36,970
You felt experienced it and you know, it you didn't then go, Oh, this is great, I'm gonna

1454
01:27:36,970 --> 01:27:37,850
keep doing it, you know.

1455
01:27:37,930 --> 01:27:40,170
So I yeah, but I but we did write the papers.

1456
01:27:40,330 --> 01:27:45,530
We did go back and forth in the journals and um which I thought w was was useful.

1457
01:27:45,690 --> 01:27:46,010
Yeah.

1458
01:27:46,250 --> 01:27:52,220
Um But but I I did I did get a buzz and I got a buzz off of young other young people coming

1459
01:27:52,220 --> 01:27:54,940
up and saying that's the coolest thing we've ever seen at the conference, right?

1460
01:27:55,100 --> 01:27:55,260
Yeah.

1461
01:27:55,980 --> 01:27:56,940
Yeah, why wouldn't you?

1462
01:27:57,020 --> 01:27:57,740
It makes sense.

1463
01:27:57,820 --> 01:27:58,300
Yeah.

1464
01:27:59,820 --> 01:28:00,220
Yeah.

1465
01:28:00,460 --> 01:28:01,020
Yeah.

1466
01:28:01,500 --> 01:28:01,820
Yeah.

1467
01:28:01,980 --> 01:28:07,740
No, it reminds me of um uh one of my favorite Robert Trivers quotes, which is that uh the

1468
01:28:07,740 --> 01:28:10,940
greater the social content of a discipline, the slower its progress.

1469
01:28:11,180 --> 01:28:15,580
Um and that there are you know real challenges and difficulties to being, you know, a bunch

1470
01:28:15,580 --> 01:28:20,990
of people studying people because we have all you know all the all the flaws of people.

1471
01:28:21,310 --> 01:28:23,310
You know yeah.

1472
01:28:24,190 --> 01:28:29,070
We're humans with you know Trivers having more than a healthy dose of those flaws for

1473
01:28:30,190 --> 01:28:33,070
absolutely of people ness.

1474
01:28:33,470 --> 01:28:38,350
As a side note, there's an entire no journalist I can't believe just as quick aside,

1475
01:28:38,510 --> 01:28:40,030
Trivers passed away recently.

1476
01:28:40,190 --> 01:28:43,790
I looked through all of these think pieces about Trivers.

1477
01:28:44,460 --> 01:28:46,380
They're all by men, by the way.

1478
01:28:46,620 --> 01:28:51,020
Um, which you should also think, why might that be?

1479
01:28:51,260 --> 01:28:55,420
Uh there's an enormous story about Trivers that is not yet.

1480
01:28:55,580 --> 01:29:01,180
Um there like all the all the all the reporters uh who did Trivers research did not do

1481
01:29:01,180 --> 01:29:02,220
their homework.

1482
01:29:03,580 --> 01:29:05,420
Yeah, not not a good not a good man.

1483
01:29:05,580 --> 01:29:09,970
Very good scientist, very good thinker, uh brilliant contributions to the field, but yeah,

1484
01:29:10,050 --> 01:29:11,010
not not a good person.

1485
01:29:15,890 --> 01:29:20,450
This is something somebody said, I won't say who said it because I don't wanna I'm not sure

1486
01:29:20,450 --> 01:29:21,250
if it's accurate.

1487
01:29:21,410 --> 01:29:27,330
But what I heard was a lot of Trivers' papers were written in Irv Devore's um kitchen

1488
01:29:27,410 --> 01:29:28,530
with Irv Devore.

1489
01:29:29,010 --> 01:29:32,130
Um so that's also something to look into.

1490
01:29:32,290 --> 01:29:34,130
I don't I don't know the full story there.

1491
01:29:34,210 --> 01:29:34,690
Yeah.

1492
01:29:35,730 --> 01:29:39,420
I've been I've been told uh, who have I heard this from?

1493
01:29:39,660 --> 01:29:45,660
Uh that may maybe from Lita, that Irv Devour is probably

1494
01:29:45,660 --> 01:29:51,500
the most significant uh mentor and grower of evolutionary

1495
01:29:51,500 --> 01:29:52,620
psychologists.

1496
01:29:52,780 --> 01:29:54,860
Uh evolutionists terms.

1497
01:29:55,180 --> 01:29:55,500
Yeah.

1498
01:29:55,900 --> 01:30:01,830
We we in in this my cohort of uh at least UCSB of psych people, we refer

1499
01:30:01,830 --> 01:30:07,350
to like an Irv Devor as this sort of a puppet master person who's not sort of well known

1500
01:30:07,350 --> 01:30:13,270
outside the area, but is the originator or the the salon keeper, maybe is

1501
01:30:13,590 --> 01:30:17,110
the right way of sort of sort of like the the George Harrison of uh evolutionary

1502
01:30:17,110 --> 01:30:21,910
psychology, the underrated compositional backbone.

1503
01:30:23,270 --> 01:30:24,390
Very good, very good.

1504
01:30:24,870 --> 01:30:28,310
Um Steve, um we've had Keila Williams on.

1505
01:30:28,700 --> 01:30:31,580
And she talked a lot about the the work.

1506
01:30:31,980 --> 01:30:37,740
Um, is there stuff that you're currently chewing on or thinking about that you

1507
01:30:37,740 --> 01:30:39,020
find really exciting?

1508
01:30:39,180 --> 01:30:43,980
Or is there something that if people are listening that don't know your work and you've

1509
01:30:43,980 --> 01:30:49,740
done you've done so much and you know, like the the there's affordances or stereotypes are

1510
01:30:49,740 --> 01:30:51,660
specific to these different groups?

1511
01:30:51,900 --> 01:30:57,770
Um out of all of that, you know, set, is there something either that already

1512
01:30:57,770 --> 01:31:03,770
exists or that is going to exist in the future that you feel like you know, if somebody

1513
01:31:03,770 --> 01:31:09,370
had four minutes to spend with Steve Newberg, what science do you think they want should

1514
01:31:09,370 --> 01:31:09,690
know?

1515
01:31:11,530 --> 01:31:12,810
So wow.

1516
01:31:13,050 --> 01:31:17,420
Uh you have three and a half minutes now, sorry.

1517
01:31:17,660 --> 01:31:19,100
Yeah, no, I got three and a half minutes.

1518
01:31:20,540 --> 01:31:26,220
So there's a line of stuff that comes out of the sort of the

1519
01:31:26,220 --> 01:31:32,220
affordance management approach to stereotypes framework that I'm really excited about that

1520
01:31:32,380 --> 01:31:38,380
that Oliver Sung is doing working on and that Becca Neal is

1521
01:31:38,380 --> 01:31:44,250
working on in a in a at sort of a broader sort of pulling together other sort of sub

1522
01:31:44,890 --> 01:31:47,530
sort of sub-phenomena as well.

1523
01:31:47,850 --> 01:31:51,530
And that's the idea of directed stereotypes.

1524
01:31:51,690 --> 01:31:55,530
And we we could think about this, and I don't know if you've seen this work by Oliver or

1525
01:31:55,530 --> 01:31:55,690
not.

1526
01:31:55,850 --> 01:32:00,890
There's a paper in JPSB this past year on it, with I think Becca in Kila.

1527
01:32:02,120 --> 01:32:07,960
But the idea here is that we tend to think about, you know, when we think about

1528
01:32:08,040 --> 01:32:12,040
you know making inferences about people that we make inferences about their traits or their

1529
01:32:12,040 --> 01:32:13,800
capacities or something like that.

1530
01:32:13,880 --> 01:32:19,240
And so and some of these traits are, you know, you know, someone is friendly, right?

1531
01:32:19,400 --> 01:32:25,000
Or someone's competitive or whatever, caring, uh aggressive.

1532
01:32:26,190 --> 01:32:31,470
As if we we presume that people have these uh these

1533
01:32:31,630 --> 01:32:34,990
non-directed behavioral inclinations towards folks.

1534
01:32:35,230 --> 01:32:36,990
But of course they don't, right?

1535
01:32:37,150 --> 01:32:42,270
What I really care about, if I wanna if I wanna manage the potential affordances that you

1536
01:32:42,270 --> 01:32:47,390
have for me or the or the people I'm invested in, is I want to know what you're gonna do to

1537
01:32:47,400 --> 01:32:48,120
me, right?

1538
01:32:48,200 --> 01:32:49,960
Or or to these other folks, right?

1539
01:32:50,120 --> 01:32:54,200
I don't really care what you're gonna what whether this right, because I if I have to

1540
01:32:54,200 --> 01:32:58,120
predict your behavior towards me, I need to predict your behavior towards me.

1541
01:32:58,280 --> 01:33:03,640
And so it turns out that what people actually have in their minds, uh, which we don't

1542
01:33:03,640 --> 01:33:05,960
discover because we never ask the questions, right?

1543
01:33:06,040 --> 01:33:09,080
This is part of our measurement problem and because we don't have theory that sort of

1544
01:33:09,080 --> 01:33:14,760
suggests this, is that uh we actually have these really uh nuanced

1545
01:33:14,760 --> 01:33:20,470
notions of of uh you know people having inclinations towards other kinds of

1546
01:33:20,470 --> 01:33:22,710
specific other kinds of people, right?

1547
01:33:23,110 --> 01:33:28,950
So uh you know some of the stuff that came out of Oliver's uh uh work with his

1548
01:33:28,950 --> 01:33:33,030
collaborators, you know, who's more competitive, you know, men or women.

1549
01:33:33,190 --> 01:33:35,670
Well of course men are are more competitive.

1550
01:33:35,830 --> 01:33:38,230
You know, who's more competitive towards young women?

1551
01:33:38,390 --> 01:33:39,510
Young men or young women?

1552
01:33:39,670 --> 01:33:42,550
It's like, well young women are more oh, right?

1553
01:33:42,860 --> 01:33:44,460
Young women are more okay.

1554
01:33:44,620 --> 01:33:44,940
Right.

1555
01:33:45,100 --> 01:33:50,860
As soon as you add the towards whom, all of a sudden there's all these things that swap.

1556
01:33:51,020 --> 01:33:52,060
They look very different.

1557
01:33:52,140 --> 01:33:56,060
And of course, those are the that's the level of of representation that people need to have

1558
01:33:56,060 --> 01:33:59,980
in their heads if they're in fact going to predict other people's behaviors.

1559
01:34:00,140 --> 01:34:05,180
And so, you know, I I think, you know, Becca gave a a talk at uh

1560
01:34:05,900 --> 01:34:08,430
uh was it SPSP?

1561
01:34:09,150 --> 01:34:15,070
Uh yeah, I think it was at I think it was at SPSP uh uh where she sort of

1562
01:34:15,070 --> 01:34:21,070
expanded on this toward whom notion of that there that they're classes of characteristics

1563
01:34:21,070 --> 01:34:25,390
that really are fundamentally relational and they're about towards whom and we need to have

1564
01:34:25,390 --> 01:34:29,470
those represent those that's the level of representation you need to have for those things.

1565
01:34:29,630 --> 01:34:29,870
Right?

1566
01:34:30,110 --> 01:34:34,920
Intelligence isn't uh isn't uh relational, right?

1567
01:34:35,160 --> 01:34:38,680
You had to have just to know whether someone is has the ability to process information

1568
01:34:38,680 --> 01:34:41,880
effectively and efficiently, whatever, that's that's good.

1569
01:34:42,280 --> 01:34:43,720
But aggressive?

1570
01:34:44,040 --> 01:34:44,360
No.

1571
01:34:44,680 --> 01:34:47,400
Yeah, that that that that that that doesn't do the job.

1572
01:34:47,560 --> 01:34:52,040
And so I think that's a really interesting sort of next implication that sort of falls

1573
01:34:52,040 --> 01:34:55,400
right out of the logic of the affordance management.

1574
01:34:55,560 --> 01:34:59,480
You know, so if we're doing first principles, then we start with the first principle of of

1575
01:34:59,770 --> 01:35:05,370
of of of the basics of evolutionary uh of of affordance management then and you work that

1576
01:35:05,370 --> 01:35:09,450
through you're gonna get to the idea that some of these things have to be directed and so

1577
01:35:09,450 --> 01:35:14,090
i'm i'm i'm really excited to see what that's gonna pop out coming out of out of their work

1578
01:35:14,330 --> 01:35:20,090
there's some work i'm doing with uh a student of mine tiffany chin uh where we're applying

1579
01:35:20,090 --> 01:35:25,450
this this this broader uh uh affordance management perspective to prejudices uh

1580
01:35:25,740 --> 01:35:30,780
against immigrants uh and you know to let me say towards immigrants because some are

1581
01:35:30,780 --> 01:35:35,500
actually quite fair and and sort of again that you know if you if you look at gallup

1582
01:35:35,500 --> 01:35:39,180
polling, if you look at politicians, you look at all the discussion, it's like there's

1583
01:35:39,180 --> 01:35:40,060
immigrants, right?

1584
01:35:40,220 --> 01:35:43,260
Well no, they're actually immigrants and they're here for they're different kinds of

1585
01:35:43,580 --> 01:35:44,940
they're here for very different reasons.

1586
01:35:45,020 --> 01:35:48,620
And depending on what your own vulnerabilities and goals are, those characteristics that

1587
01:35:48,620 --> 01:35:51,100
you think that they're they bring different characteristics with them.

1588
01:35:51,260 --> 01:35:56,410
The characteristics might have might pose opportunities for you, they may pose threats uh

1589
01:35:56,410 --> 01:35:57,290
uh to you.

1590
01:35:57,610 --> 01:36:03,610
Uh one of the interesting implications that we've never uh and so elabor using that

1591
01:36:03,610 --> 01:36:09,130
as a case to sort of uh look again greater new people uh

1592
01:36:09,290 --> 01:36:14,090
different kinds of groups, but one of the interesting things here is that uh

1593
01:36:15,320 --> 01:36:20,360
most of our feelings towards people, most of our prejudices are are probably

1594
01:36:20,680 --> 01:36:21,880
ambivalences.

1595
01:36:22,040 --> 01:36:26,680
And I know ambivalence is a single dimension, and so ambivalence has to be positive and

1596
01:36:26,680 --> 01:36:27,160
negative.

1597
01:36:27,240 --> 01:36:30,760
But the fact is, we have these different kinds of negative negative ambivalences.

1598
01:36:30,840 --> 01:36:32,280
We'll need a different word for it, right?

1599
01:36:32,360 --> 01:36:36,600
There, folks that you're that they they both make you angry and they and they make you

1600
01:36:36,600 --> 01:36:37,240
afraid.

1601
01:36:37,480 --> 01:36:41,170
And uh, well, fear leads you to want to go away.

1602
01:36:41,250 --> 01:36:46,770
And if, you know, uh and and angry makes you want to go forward and uh and to recalibrate

1603
01:36:46,770 --> 01:36:49,090
their their their behaviors, right, and the like.

1604
01:36:49,250 --> 01:36:52,050
Well, people they they they emerge.

1605
01:36:52,130 --> 01:36:57,570
If if you if you believe that that that our impressions that are stereotypes about groups

1606
01:36:57,570 --> 01:37:01,410
can be profiles of different kinds of threats, then you have to acknowledge that you've got

1607
01:37:01,410 --> 01:37:05,620
profiles of emotional responses and there are all these ambivalences that again are getting

1608
01:37:05,620 --> 01:37:11,060
masked by the typical ways in which we and you can have different kinds of sort of positive

1609
01:37:11,220 --> 01:37:15,220
putting air quotes around positive and negative, because I think it's a really problematic

1610
01:37:15,220 --> 01:37:16,980
word when we're thinking about affect.

1611
01:37:17,220 --> 01:37:22,820
Uh to be thinking about some as positive and some as negative, it just it it it totally

1612
01:37:22,820 --> 01:37:25,220
masks what what these affects are for.

1613
01:37:25,460 --> 01:37:26,740
Uh uh.

1614
01:37:27,850 --> 01:37:31,050
But there are all sorts of different flavors of these ambivalences.

1615
01:37:31,130 --> 01:37:36,410
And I think uh there'll be a lot of traction as as we sort of as we sort of unpack that and

1616
01:37:36,410 --> 01:37:39,050
demonstrate that and and show where the different ones come from.

1617
01:37:39,210 --> 01:37:42,970
Again, if you're interested, if you're interested in fixing the car engine, you better

1618
01:37:42,970 --> 01:37:46,570
understand what this actually what's actually going on inside this.

1619
01:37:46,730 --> 01:37:51,370
You want to do interventions to reduce prejudices that you're that you're not uh uh that

1620
01:37:51,450 --> 01:37:52,970
that you're opposed to, right?

1621
01:37:53,130 --> 01:37:56,440
Well you better understand actually what these what these prejudices actually look like and

1622
01:37:56,440 --> 01:37:57,000
what these feel.

1623
01:37:57,160 --> 01:38:01,080
And so I I I think that that's I think there's some really interesting stuff in that.

1624
01:38:01,160 --> 01:38:05,000
You know, so of the things that are coming out of sort of that perspective that I've taken,

1625
01:38:05,160 --> 01:38:08,840
I think those are two of the things that uh that I'm sort of most interested in right now.

1626
01:38:09,080 --> 01:38:14,520
We're also applying uh Barlev and I are applying this framework to be thinking about

1627
01:38:14,520 --> 01:38:18,600
anti-Semitism because I think it's actually another one of these groups where there's a lot

1628
01:38:18,600 --> 01:38:24,450
of ambivalence, there's a lot of uh competing uh uh uh sort of

1629
01:38:24,450 --> 01:38:27,970
different kind of affordance stereotypes of opportunities threats and qualitatively

1630
01:38:27,970 --> 01:38:29,090
different kind of threats.

1631
01:38:29,250 --> 01:38:30,530
And I think that would benefit.

1632
01:38:30,770 --> 01:38:35,010
So it's it's another it's both a case study and something that's uh that's of interest uh

1633
01:38:35,170 --> 01:38:36,930
uh to me for other reasons.

1634
01:38:37,090 --> 01:38:42,210
But I I think I think there might be some very nice leverage uh there as well.

1635
01:38:42,530 --> 01:38:47,700
Uh uh David's doing very some interesting stuff on uh on on

1636
01:38:47,700 --> 01:38:49,540
anti-semitism and coalitions.

1637
01:38:49,700 --> 01:38:53,620
Uh and I'm I'm very interested to see what what what ends up coming out of all that.

1638
01:38:54,260 --> 01:38:58,660
Yeah, and I've worked with uh Barlov and um and and Jamie and Sneezer.

1639
01:38:58,740 --> 01:39:02,420
It's sort of a bit on the hiatus, but we have some really interesting data on anti-Semitism

1640
01:39:02,500 --> 01:39:06,900
looking at the alliance structure and and who people think the allies of Jews are

1641
01:39:06,900 --> 01:39:10,260
politically and who people think the enemies of Jews are politically.

1642
01:39:12,450 --> 01:39:17,650
and we're looking at w if they're the ally of one of my enemies, is that gonna predict uh

1643
01:39:17,730 --> 01:39:18,610
anti Semitism?

1644
01:39:18,690 --> 01:39:22,370
Or if they're the enemy of one of my uh enemies, is that gonna predict more positive

1645
01:39:22,370 --> 01:39:23,330
attitudes toward Jews?

1646
01:39:23,490 --> 01:39:29,090
And it turns out that um just these indirect relationships of of of who you s view the

1647
01:39:29,090 --> 01:39:32,610
allies of Jews and and the enemies of Jews and how you feel about those allies and enemies,

1648
01:39:32,770 --> 01:39:36,130
just those indirect pathways are explaining something like forty percent of the variation

1649
01:39:36,130 --> 01:39:39,890
in anti Semitism, and then it's all interact and like indirect in in terms of like where

1650
01:39:39,890 --> 01:39:43,640
are Jews situated in the political alliance structure, And that is uh

1651
01:39:48,040 --> 01:39:50,760
just who you where you think they're situated in the alliance structure.

1652
01:39:51,000 --> 01:39:51,880
So I'm excited about that.

1653
01:39:51,960 --> 01:39:55,640
And it's you know obviously inspired by a lot of Steve's work in terms of understanding

1654
01:39:55,640 --> 01:39:58,200
prejudice in a more nuanced and and functional way.

1655
01:39:58,360 --> 01:40:03,640
That um, you know, it's not just uh you know uh um a single continuum of positive and

1656
01:40:03,640 --> 01:40:05,240
negative, it's much more complicated.

1657
01:40:05,400 --> 01:40:10,680
Um and uh yeah, I I I I love this work because it it um

1658
01:40:11,750 --> 01:40:15,510
It unearths the complexity that we didn't know was there.

1659
01:40:15,670 --> 01:40:21,270
And it's it's interesting and functionally organized complexity that ought to be of of

1660
01:40:21,270 --> 01:40:26,390
interest to evolutionary researchers and anyone who's interested in in prejudice itself.

1661
01:40:27,110 --> 01:40:32,950
Yeah, you know, uh Oliver Sung has this uh uh great little line that he likes to use

1662
01:40:33,030 --> 01:40:36,630
that we've been uh we've been stereotyping, right?

1663
01:40:36,950 --> 01:40:42,080
That that that we that we pres we're presuming that this is all sort of really simple,

1664
01:40:42,320 --> 01:40:42,640
right?

1665
01:40:42,960 --> 01:40:48,960
And people are so much people are so much more complex and for and for and for really

1666
01:40:48,960 --> 01:40:53,280
good reasons and way more interesting than than we've been giving them credit for.

1667
01:40:53,440 --> 01:40:58,240
And you know, I understand you know you start your model simple and you start with uh but

1668
01:40:58,320 --> 01:41:04,320
you know we're we're too mature of a of a of a behavioral science to be still living in

1669
01:41:04,320 --> 01:41:05,680
those in those old models.

1670
01:41:06,000 --> 01:41:06,160
Yeah.

1671
01:41:06,240 --> 01:41:10,080
Do you think there's a little bit of wishful thinking that's probably like well intended

1672
01:41:10,160 --> 01:41:15,970
which is that if prejudice or stereotyping is simple or unitary, then maybe there's like

1673
01:41:15,970 --> 01:41:17,730
an intervention we can do.

1674
01:41:17,970 --> 01:41:22,850
But if it turns out that it's multifaceted and more to the point, which I think a lot of

1675
01:41:22,850 --> 01:41:28,610
your work is pointing towards, it's also largely rational to the extent that it's in

1676
01:41:28,610 --> 01:41:30,050
response to structural issues.

1677
01:41:30,210 --> 01:41:35,490
It's pointing towards the way you reduce prejudice or discrimination are largely structural

1678
01:41:35,490 --> 01:41:35,730
things.

1679
01:41:35,810 --> 01:41:39,090
They're not really things where you can just like have this pill or like, you know, you

1680
01:41:39,200 --> 01:41:42,320
know, hit your head ten times against a board and now you're not prejudiced.

1681
01:41:42,400 --> 01:41:46,080
I mean, I'm being f facetious, but I mean it's kind of in that category.

1682
01:41:46,240 --> 01:41:52,080
Do you think that some of that is that there is a resistance because it when you get

1683
01:41:52,080 --> 01:41:57,840
more truthful, uh it points to harder to fix or more structural things?

1684
01:41:58,640 --> 01:42:03,830
I mean, I I think that I I suspect that that's not uh

1685
01:42:05,750 --> 01:42:08,310
consciously what people would it would admit to themselves.

1686
01:42:10,230 --> 01:42:13,270
I suspect that uh that that may be part of it.

1687
01:42:13,350 --> 01:42:19,110
It also may be part of that it says something uh that well well maybe our field isn't

1688
01:42:19,110 --> 01:42:20,950
the field to fix this.

1689
01:42:21,270 --> 01:42:21,510
Right.

1690
01:42:21,750 --> 01:42:27,580
So right so you know if the solutions are you know uh you know change changing the

1691
01:42:27,580 --> 01:42:33,580
environments in which people are growing up and if they if they are uh uh other

1692
01:42:33,580 --> 01:42:38,620
kinds of things you need to do to you know create opportunities and reduce threats and the

1693
01:42:38,620 --> 01:42:44,620
like and that that moves the solutions then require politics and they require

1694
01:42:44,620 --> 01:42:49,420
community organization and they require an investment of money and well that's not what's

1695
01:42:49,580 --> 01:42:51,180
that's not what psychologists do, right?

1696
01:42:52,460 --> 01:42:58,210
Yeah that that's uh and and so you know you know, and in some ways the the irony there is

1697
01:42:58,210 --> 01:43:04,050
that, you know, psychologists, I think, you know, even way more than sociologists

1698
01:43:04,290 --> 01:43:10,050
are the ones that sort of sort of uncovered and turned, you know, the explorations of

1699
01:43:10,050 --> 01:43:14,930
prejudice and a group conflict into uh you know into into a science, right?

1700
01:43:15,410 --> 01:43:20,960
Uh and in the end may not be, you know, the you know the largest

1701
01:43:20,960 --> 01:43:23,920
contributor to uh uh to to the solutions.

1702
01:43:24,160 --> 01:43:25,280
Um yeah.

1703
01:43:25,520 --> 01:43:31,440
Or at least uh I mean the charitable t version is that you can't solve the world like

1704
01:43:31,440 --> 01:43:32,800
you said by yourself.

1705
01:43:32,960 --> 01:43:38,240
And so you it's it's like, oh we realize we need all this other stuff, like like you all

1706
01:43:38,240 --> 01:43:40,000
the things you articulately listed.

1707
01:43:40,240 --> 01:43:46,190
Um yeah, and until you you're just like a lowly PI in a lab, you know,

1708
01:43:46,270 --> 01:43:48,030
and you're like, Well, how am I gonna do that?

1709
01:43:48,110 --> 01:43:48,430
you know.

1710
01:43:48,590 --> 01:43:49,790
So um right.

1711
01:43:49,950 --> 01:43:52,030
Again, I think it comes back to a coronation problem.

1712
01:43:52,110 --> 01:43:57,150
But I think to the credit, to your credit, I mean, I think like sticking to the guns of we

1713
01:43:57,390 --> 01:44:02,030
we are being accurate about what the psychology is, and therefore if it is a structural

1714
01:44:02,030 --> 01:44:07,940
problem, like maybe, maybe it will provoke um or you know, I like I think that's

1715
01:44:07,940 --> 01:44:09,140
good to stick with, right?

1716
01:44:09,220 --> 01:44:11,140
Even if even if we can't fix it.

1717
01:44:11,540 --> 01:44:14,420
But by the way, I don't I don't I don't think it I don't think it's just a structural

1718
01:44:14,420 --> 01:44:14,900
problem, right?

1719
01:44:15,060 --> 01:44:20,820
I mean I think I think with with even within if we look within whatever sort of uh

1720
01:44:21,220 --> 01:44:26,890
you know uh you know cells of interacting structural things, you

1721
01:44:27,210 --> 01:44:31,370
still you still find a lot of variation uh with how people responding.

1722
01:44:31,610 --> 01:44:36,330
So so I think I think that I think there's plenty of work uh to be done if if one has an

1723
01:44:36,330 --> 01:44:40,810
aim of uh of addressing some of those uh uh some of those challenges.

1724
01:44:40,970 --> 01:44:46,410
Uh I I think another part of it is uh is actually even uh

1725
01:44:49,060 --> 01:44:54,580
simpler in the way in the sense of you know

1726
01:44:55,940 --> 01:45:01,380
people most scientists get used to using certain tools you know and and they're they they

1727
01:45:01,380 --> 01:45:05,300
may be methodological they may be conceptual and that's sort of what and they and they they

1728
01:45:05,300 --> 01:45:09,220
have an identity around those tools this is what I do this is what I know I'm good at this

1729
01:45:09,220 --> 01:45:15,060
is what I've been rewarded for and you know I think challenges like mine which sort of say

1730
01:45:15,620 --> 01:45:17,470
you need, you know, the tools are wrong.

1731
01:45:17,550 --> 01:45:21,150
You you keep using a tool that's too simple to understand your phenomenon that you're

1732
01:45:21,150 --> 01:45:21,710
interested in.

1733
01:45:21,870 --> 01:45:24,510
But now you gotta change, you gotta shift, right?

1734
01:45:24,590 --> 01:45:27,550
You got you have to use different measures and they're more complicated.

1735
01:45:27,710 --> 01:45:32,270
Uh, you know, you have to analyze your data uh uh differently.

1736
01:45:32,430 --> 01:45:36,560
Uh, you know, the the stories sometimes aren't so simple, right?

1737
01:45:36,640 --> 01:45:40,880
When you're when you're sort of trying to articulate something, it's not it's not as easy

1738
01:45:40,960 --> 01:45:44,480
uh, you know, when you're getting from the eighth floor of the elevator down to the lobby

1739
01:45:44,640 --> 01:45:49,120
to to explain what it is that you uh what it what it is that you're uh doing and what it

1740
01:45:49,120 --> 01:45:52,800
what exactly it is that you're finding and so I mean that's pushing people out of their

1741
01:45:52,800 --> 01:45:57,270
comfort zones, which is why, you know, who is it that said that, you know, you know science

1742
01:45:57,270 --> 01:46:00,310
advances by the by the by the death of old scientists.

1743
01:46:01,270 --> 01:46:02,470
It's a mox punc.

1744
01:46:02,550 --> 01:46:04,790
It's uh science progresses one funeral at a time.

1745
01:46:05,590 --> 01:46:06,310
Okay, that's right.

1746
01:46:06,390 --> 01:46:11,910
Right and and so uh you know we we we're we're all uh you know somewhat

1747
01:46:11,910 --> 01:46:15,350
constrained by what we know and what we're used to doing and what we think is good and what

1748
01:46:15,350 --> 01:46:16,390
what our identities are.

1749
01:46:16,550 --> 01:46:22,260
And so uh you know uh which which is why you know I think we

1750
01:46:22,260 --> 01:46:28,100
always need to be looking I I'm way more interested in in uh in convincing

1751
01:46:28,100 --> 01:46:33,540
and getting the it the attention and the interest uh of young people than I am of

1752
01:46:33,860 --> 01:46:39,620
people of of my uh my generation right uh you know the people of my generation

1753
01:46:39,780 --> 01:46:45,410
you know uh you know can give me uh what's

1754
01:46:47,010 --> 01:46:52,930
uh it's uh benefits or status in a kind of way that young folks

1755
01:46:52,930 --> 01:46:53,170
can.

1756
01:46:53,410 --> 01:46:58,690
But in the long run, it's the it's it's it's it's the young folks that are actually gonna

1757
01:46:58,770 --> 01:47:03,010
uh you know you know determine whether whether the ideas are right and where they can go

1758
01:47:03,170 --> 01:47:05,570
and uh uh and the like.

1759
01:47:05,730 --> 01:47:11,100
It's it's actually, you know, in my mind what the what sort of the biggest joy of mentoring

1760
01:47:11,100 --> 01:47:11,260
is.

1761
01:47:11,420 --> 01:47:13,100
I I I like mentoring.

1762
01:47:13,180 --> 01:47:19,100
Uh it's an important part of my identity and the the idea of of young people going off

1763
01:47:19,100 --> 01:47:23,420
and I mean and taking things in these incredibly cool different kind of directions that I

1764
01:47:23,420 --> 01:47:24,860
never would have thought about.

1765
01:47:24,940 --> 01:47:30,220
But but knowing that you were sort of a part of that, I think is uh is is is maybe the most

1766
01:47:30,220 --> 01:47:30,780
rewarding.

1767
01:47:31,010 --> 01:47:36,290
I I suspect that my impact on the field, whatever it ends up being, will be way greater as

1768
01:47:36,290 --> 01:47:41,330
mediated by my students than anything that I end up uh that ends up having my name on it.

1769
01:47:41,650 --> 01:47:44,930
I hope anyway, that's maybe maybe that's maybe that's just a hope.

1770
01:47:45,250 --> 01:47:50,130
But it's almost like differential reproductive success you can have.

1771
01:47:53,940 --> 01:47:56,660
No, I mean i if any I mean you have a good track record thus far.

1772
01:47:56,740 --> 01:48:02,580
I think you know you've Jamie Oliver and Keela and there's just so many I can't

1773
01:48:02,820 --> 01:48:08,660
Beck and forgetting so or not forgetting, but I I can't I'm not

1774
01:48:08,660 --> 01:48:09,620
gonna list everybody.

1775
01:48:09,860 --> 01:48:10,180
Yes.

1776
01:48:10,340 --> 01:48:13,220
Um but yeah, it's like Tom Gilovich or Brenda Major too, right?

1777
01:48:13,460 --> 01:48:18,100
Even you had your own st story um and the people that influenced you.

1778
01:48:18,340 --> 01:48:24,170
Um yeah so so yeah if you feel like you're um being uh being

1779
01:48:24,330 --> 01:48:28,490
your science is being ignored the people you should be worrying about are are what the

1780
01:48:28,490 --> 01:48:29,530
young people think about you.

1781
01:48:29,930 --> 01:48:30,410
That's right.

1782
01:48:30,570 --> 01:48:31,210
That's right.

1783
01:48:31,450 --> 01:48:36,090
Uh and and and just uh you know you know I I think their

1784
01:48:36,650 --> 01:48:42,170
open-minded attention is probably the I th yeah so I'll throw this out there.

1785
01:48:42,250 --> 01:48:43,130
I don't know if this is right or not.

1786
01:48:43,210 --> 01:48:44,490
I've never really thought about this before.

1787
01:48:44,650 --> 01:48:50,100
That the that the open-minded attention of young

1788
01:48:50,580 --> 01:48:56,260
scientists is probably the most important resource uh uh that there is out there for the

1789
01:48:56,260 --> 01:48:58,260
advancement of of science.

1790
01:48:58,580 --> 01:49:00,900
Um I don't know.

1791
01:49:01,060 --> 01:49:05,700
Does that does that sound Yeah I mean there is they're probably the closest thing we can

1792
01:49:06,020 --> 01:49:09,990
get to a you know an impartial jury to evaluate these ideas.

1793
01:49:19,670 --> 01:49:23,990
And they can just evaluate all these different ideas with with fresh eyes in a way that's

1794
01:49:23,990 --> 01:49:29,190
less biased by, you know, years of building coalitions with different people.

1795
01:49:30,950 --> 01:49:36,780
And then they have the capacity and the time to actually if if the if the ideas grab uh

1796
01:49:37,020 --> 01:49:40,780
to actually make like you know important things happen with them yeah they have time to

1797
01:49:40,780 --> 01:49:45,900
read the whole paper uh yeah um uh Lita I was thinking in terms of years

1798
01:49:46,860 --> 01:49:49,420
not in terms of like no but they also have the time to read the whole paper.

1799
01:49:49,580 --> 01:49:54,620
Uh Lita always said um you should be writing to young graduate students and I think it was

1800
01:49:54,620 --> 01:49:59,730
exactly for this reason you described Steve is that when when they're and I think even I

1801
01:49:59,730 --> 01:50:02,050
asked, like I was like, you know, who were you writing to?

1802
01:50:02,130 --> 01:50:05,810
And it was like to young graduate students, and it was for all these reasons we're talking

1803
01:50:05,810 --> 01:50:06,050
about.

1804
01:50:06,210 --> 01:50:11,810
So I think that that's always been really helpful for me, too, is like you're and I think

1805
01:50:11,810 --> 01:50:17,730
sometimes we over some graduate students really get uh to put it in a

1806
01:50:17,730 --> 01:50:22,530
hokey way, a bee in their bonnet about like some theory, and they really go after it and

1807
01:50:22,600 --> 01:50:24,760
they want to convince like the senior person.

1808
01:50:24,840 --> 01:50:28,440
And I think sometimes that's a mistake, you know, like that's not the right way to write

1809
01:50:28,440 --> 01:50:28,760
the paper.

1810
01:50:28,920 --> 01:50:32,280
The right way to paper is as David just said, like it's you know, you're writing to the

1811
01:50:32,280 --> 01:50:37,480
jury of young students, and and that should be the tone and the approach.

1812
01:50:37,720 --> 01:50:43,400
And you don't have to convince this person who's who's living, as Steve put it,

1813
01:50:43,640 --> 01:50:48,290
was you know, their salary depends on hanging on to this idea.

1814
01:50:48,450 --> 01:50:53,730
They're probably not gonna let go unless they're very rare and special um

1815
01:50:54,210 --> 01:50:54,530
people.

1816
01:50:54,930 --> 01:50:55,250
Yeah.

1817
01:50:55,650 --> 01:50:57,730
Yeah, you don't want to insult them if you don't have to.

1818
01:50:57,970 --> 01:50:58,610
No, that's true.

1819
01:50:59,410 --> 01:51:00,210
What what was it?

1820
01:51:00,290 --> 01:51:06,290
Is it uh Dan Dennett, who's got this uh sort of philosophy of how to

1821
01:51:06,290 --> 01:51:08,370
write a great review, right?

1822
01:51:08,820 --> 01:51:14,100
Uh you know, and and and and what it's it starts with you know understanding the uh you

1823
01:51:14,100 --> 01:51:19,300
know the position so well that they would just be overjoyed as you sort of explain it back

1824
01:51:19,620 --> 01:51:20,660
uh to them.

1825
01:51:20,740 --> 01:51:23,460
And that's sort of the the the the first thing.

1826
01:51:23,940 --> 01:51:26,660
You know, not offended you're you're looking it up right now.

1827
01:51:26,740 --> 01:51:31,700
Uh it says first and more important you should attempt to express your target's position so

1828
01:51:31,700 --> 01:51:36,420
clearly, vividly, and fairly that your target says things like, I wish I had thought of

1829
01:51:36,420 --> 01:51:37,380
putting it that way.

1830
01:51:37,850 --> 01:51:38,010
Yeah.

1831
01:51:38,170 --> 01:51:38,330
Yeah.

1832
01:51:38,570 --> 01:51:38,890
Exactly.

1833
01:51:39,210 --> 01:51:44,890
And and so and so that's uh you know so so beginning with uh beginning with respect and uh

1834
01:51:45,130 --> 01:51:50,570
generosity right of care I mean it's like it's a cue of that you care right about doing

1835
01:51:50,570 --> 01:51:56,410
this and I think that's uh a really useful uh thing so we don't want to

1836
01:51:56,570 --> 01:51:58,410
we don't want to offend the old folks.

1837
01:51:58,650 --> 01:52:04,380
Yeah but some some

1838
01:52:04,540 --> 01:52:09,180
but sometimes, you know no one should get offended.

1839
01:52:09,420 --> 01:52:09,580
Right.

1840
01:52:09,740 --> 01:52:11,820
I mean, I I think this is again the thing.

1841
01:52:11,980 --> 01:52:16,380
You know, some someone uh someone at attacks my perspective.

1842
01:52:16,540 --> 01:52:20,700
Uh yes, I'm gonna get irritable about it, but what I should do is I should appreciate it as

1843
01:52:20,700 --> 01:52:25,250
an opportun you first of all they paid attention so they gave me the gift of attention and

1844
01:52:25,250 --> 01:52:31,010
then the the second thing is that they uh they've given me an opportunity uh you know uh

1845
01:52:31,170 --> 01:52:37,090
to learn and and or and or defend right and to make my case better right if people

1846
01:52:37,090 --> 01:52:42,050
don't understand you know what I'm writing that's on me right this is actually one of the

1847
01:52:42,050 --> 01:52:46,130
really important lessons I think for grad students right you know if if they if they

1848
01:52:46,130 --> 01:52:50,130
misinterpret that's that's on you that's your job right uh

1849
01:52:51,920 --> 01:52:54,640
yeah, that's good good advice.

1850
01:52:54,960 --> 01:53:00,240
Um Steve, is there anything um about you that people might not know, like

1851
01:53:00,240 --> 01:53:03,680
hobbies or um hobbies.

1852
01:53:04,480 --> 01:53:05,680
Hobbies, you know.

1853
01:53:06,080 --> 01:53:09,680
I've I've had several people tell me recently that I need a hobby.

1854
01:53:09,920 --> 01:53:15,920
Uh so uh like you know, way back when I used

1855
01:53:15,920 --> 01:53:21,490
to be uh uh musician but stock while I was still too young to get really

1856
01:53:21,490 --> 01:53:22,290
serious about it.

1857
01:53:22,370 --> 01:53:28,290
But I I had talent way back when that that maybe that's uh a

1858
01:53:28,290 --> 01:53:29,170
little bit interesting.

1859
01:53:29,330 --> 01:53:34,290
I think uh well I'll I'll tell you really briefly something I'm doing right now that's very

1860
01:53:34,290 --> 01:53:35,810
different than than this.

1861
01:53:35,970 --> 01:53:41,520
And that is when I was chair of the Department of Psychology, uh We we

1862
01:53:41,520 --> 01:53:44,080
started something that's now evolved.

1863
01:53:44,320 --> 01:53:46,240
Uh we call it Psych for Life.

1864
01:53:46,320 --> 01:53:52,320
And it's an attempt to sort of bring the the uh it's it started when when I was chair

1865
01:53:52,320 --> 01:53:56,560
of the department, you know, you know, you know that 75% of psych majors don't do anything

1866
01:53:56,560 --> 01:53:57,200
psych related.

1867
01:53:57,360 --> 01:54:01,040
I mean they do everything is psych related, but they go into business or they go into

1868
01:54:01,040 --> 01:54:05,360
health or they go into law, or they do they don't go into you know become therapists or to

1869
01:54:05,440 --> 01:54:07,840
or to be or to be researchers or things like that.

1870
01:54:08,080 --> 01:54:12,270
And so when I was chair, I thought, well, you know, how what how do how do we serve them

1871
01:54:12,270 --> 01:54:12,510
well?

1872
01:54:12,670 --> 01:54:15,390
Because the system isn't designed for for that really.

1873
01:54:15,550 --> 01:54:18,990
And so uh we we started this thing, we were calling it psych for life.

1874
01:54:19,070 --> 01:54:20,670
The psych department will be free for life.

1875
01:54:20,910 --> 01:54:24,910
That if we played with the premise that we were going to be with you and add value to your

1876
01:54:24,910 --> 01:54:26,830
life and for life, what would we do differently?

1877
01:54:26,990 --> 01:54:31,310
So we started doing a bunch of things having to do with careers and mentorships and and

1878
01:54:31,310 --> 01:54:31,870
whatever.

1879
01:54:32,110 --> 01:54:36,120
Uh we then asked the question, well, what do we do for our alums after they're out.

1880
01:54:36,520 --> 01:54:40,200
And the thing, and so here's the second meaning of Psych for Life, and that is we have an

1881
01:54:40,200 --> 01:54:46,040
evidence-based psychology, uh science, right, that says that has useful uh

1882
01:54:46,200 --> 01:54:51,800
useful lessons, useful insights about relationships and about, you know, raising your kids

1883
01:54:51,880 --> 01:54:55,240
and about well-being and about career and about community.

1884
01:54:55,400 --> 01:55:00,110
Can we figure out a way of really easily getting that into people's hands in ways that are

1885
01:55:00,110 --> 01:55:03,790
actionable, that are engaging, that that that could be effective.

1886
01:55:03,950 --> 01:55:07,950
And so, you know, we thought about this just in the terms of okay, can we can we send stuff

1887
01:55:07,950 --> 01:55:08,910
out to our alums?

1888
01:55:09,390 --> 01:55:14,190
Over time, it became clear that maybe there's sort of a broader value of this out there in

1889
01:55:14,190 --> 01:55:19,070
the world and people encouraging us, raised a good amount of philanthropy uh to sort of

1890
01:55:19,070 --> 01:55:20,030
start to build this.

1891
01:55:20,270 --> 01:55:21,710
We've now shifted it.

1892
01:55:21,820 --> 01:55:24,780
Uh, we're going to be rolling this out of ASU.

1893
01:55:24,860 --> 01:55:30,380
Uh, the first instantiation will be sort of as an app, uh, covering a bunch of topics, but

1894
01:55:30,380 --> 01:55:36,220
really helping people have skills, sort of life skills within these

1895
01:55:36,220 --> 01:55:41,020
different kinds of domains that they might now be able to integrate into their everyday

1896
01:55:41,020 --> 01:55:46,060
lives and uh and you know help solve you know little challenges before they become real

1897
01:55:46,060 --> 01:55:46,620
problems.

1898
01:55:46,860 --> 01:55:49,820
And so we're actually spinning this out as a startup.

1899
01:55:49,980 --> 01:55:55,830
And I am now the CEO president of this of this uh new startup that I'm gonna be

1900
01:55:55,830 --> 01:55:57,350
doing while I'm an academic.

1901
01:55:57,750 --> 01:55:58,870
We'll see how well that goes.

1902
01:55:58,950 --> 01:56:04,470
I should have a separate conversation with David uh about uh about being a about being a

1903
01:56:04,470 --> 01:56:05,430
business guy.

1904
01:56:05,670 --> 01:56:09,270
Uh but that's that's something that's sort of exciting to me.

1905
01:56:09,350 --> 01:56:14,790
Uh the challenge right I'm I'm trying to you know marry everything together and do both of

1906
01:56:14,790 --> 01:56:15,270
these things.

1907
01:56:15,430 --> 01:56:21,160
And uh but that's uh that's it's a it's you know as scientists we're problem solvers and

1908
01:56:21,240 --> 01:56:22,920
uh of of one sort.

1909
01:56:23,160 --> 01:56:29,080
And you know, getting these tools out to people in ways uh and to a lot of people in

1910
01:56:29,080 --> 01:56:34,200
ways that can be useful to them uh is uh is just another kind of problem to be solved, both

1911
01:56:34,200 --> 01:56:38,360
how do you design the systems, but how do you how do you you know find what the right

1912
01:56:38,360 --> 01:56:42,280
markets are and how do you engage in those markets and how do you how do you sell and all

1913
01:56:42,280 --> 01:56:42,600
those things.

1914
01:56:42,680 --> 01:56:47,130
So that's sort of been exciting uh uh to me as well and that's probably something that

1915
01:56:47,130 --> 01:56:52,330
people don't know that it's a it's sort of a very different side more of an applied uh uh

1916
01:56:52,330 --> 01:56:58,330
kind of side uh but uh trying to trying to uh you know have an impact in

1917
01:56:58,330 --> 01:57:02,810
in that kind of way as well that's fantastic it does it exist yet or is this coming out

1918
01:57:03,210 --> 01:57:07,610
it's so we we sort of have beta versions of it where we're in the midst of we we got some

1919
01:57:07,770 --> 01:57:12,170
we've been getting some feedback we're in the midst of sort of this next sort of like beta

1920
01:57:12,410 --> 01:57:18,300
plus version uh but we'll we we think we'll be ready to go out and to have

1921
01:57:18,300 --> 01:57:23,260
like real people using it, you know, come uh sort of end of summer or so.

1922
01:57:23,980 --> 01:57:29,580
We're sort of building some some new, I think, reasonably fundamental features into it that

1923
01:57:29,740 --> 01:57:35,580
that significantly raise the value of it, that bring it beyond sort of just psychoeducation

1924
01:57:35,580 --> 01:57:41,340
stuff, uh in in ways that uh people can integrate into their into their lives and uh make

1925
01:57:41,340 --> 01:57:42,300
it really more usable.

1926
01:57:42,380 --> 01:57:45,970
So and of course, you know, doing you know, doing the user research and all that.

1927
01:57:46,050 --> 01:57:48,850
I mean, it's just it's been a bunch of different challenges and they're all interesting.

1928
01:57:48,930 --> 01:57:50,450
So Yeah, that's fantastic.

1929
01:57:50,530 --> 01:57:55,170
And I mean, that's wonderful for social things, like if we have the data, it's again this

1930
01:57:55,170 --> 01:58:00,370
coordination problem and people want to know what do I do for my um uh what do I do with my

1931
01:58:00,370 --> 01:58:06,370
kid here or myself or my spouse, uh, if there's data and getting that to them without ads

1932
01:58:06,370 --> 01:58:09,570
or snake oil or some of them sell you selling something to them.

1933
01:58:09,810 --> 01:58:10,130
That's right.

1934
01:58:10,290 --> 01:58:10,930
That's fantastic.

1935
01:58:11,010 --> 01:58:15,000
And it's gonna make the science better to the degree that there's a market outside of

1936
01:58:15,000 --> 01:58:16,360
entertaining undergrads.

1937
01:58:16,760 --> 01:58:17,800
No big lecture hall.

1938
01:58:17,960 --> 01:58:18,120
Yeah.

1939
01:58:18,600 --> 01:58:19,240
We hope so.

1940
01:58:19,400 --> 01:58:19,800
We hope so.

1941
01:58:20,040 --> 01:58:23,240
Yeah, David, I'll probably reach out to you actually to you know what's what's the license

1942
01:58:23,320 --> 01:58:24,680
also to be run in a business.

1943
01:58:25,080 --> 01:58:25,800
Yeah, please do.

1944
01:58:25,960 --> 01:58:27,400
I wish I knew the answer to that question.

1945
01:58:29,560 --> 01:58:32,280
At least how you solve some of the challenges.

1946
01:58:33,160 --> 01:58:33,880
Business humor.

1947
01:58:34,040 --> 01:58:37,160
So well, Steve, this was wonderful.

1948
01:58:37,320 --> 01:58:39,080
Uh we really appreciate it.

1949
01:58:39,160 --> 01:58:44,810
Um and uh Yeah, it's it's it went by quick and uh yeah, it's always fun.

1950
01:58:44,890 --> 01:58:49,770
There's so much going on, uh so much throughput in your lab and your offspring, your

1951
01:58:49,770 --> 01:58:50,730
academic offspring.

1952
01:58:50,890 --> 01:58:52,650
It's uh thanks for being on.

1953
01:58:52,730 --> 01:58:53,850
Um it was lovely.

1954
01:58:54,170 --> 01:58:55,530
Well, well, thank you for having me.

1955
01:58:55,610 --> 01:58:59,850
It's been a pleasure and um I'm flattered, and it's been a lot of fun.

1956
01:59:04,490 --> 01:59:09,780
David, um Why do I always try to start the in the outros?

1957
01:59:10,020 --> 01:59:11,540
I never stop.

1958
01:59:13,140 --> 01:59:15,620
Well, we just we just had a conversation with Steve Newberg.

1959
01:59:15,780 --> 01:59:18,100
We just had a Steve had a lovely conversation with Steve Newberg.

1960
01:59:18,580 --> 01:59:19,380
Time flew.

1961
01:59:19,460 --> 01:59:23,540
Um there was We're still figuring out what we're still figuring out what this outro even

1962
01:59:23,540 --> 01:59:23,700
is.

1963
01:59:31,860 --> 01:59:33,380
I think that's it said that.

1964
01:59:33,690 --> 01:59:34,250
Oh yeah.

1965
01:59:34,330 --> 01:59:34,570
Okay.

1966
01:59:38,170 --> 01:59:41,290
Yeah, that fits in with like Bayesian models of cognition.

1967
01:59:41,610 --> 01:59:46,970
John John Tuby famously had a post-it note on his computer that was a little more direct,

1968
01:59:47,050 --> 01:59:50,250
and it said, Everything you think you know is wrong.

1969
01:59:52,250 --> 01:59:52,570
Okay.

1970
01:59:53,130 --> 01:59:53,930
I like that.

1971
01:59:54,140 --> 01:59:54,460
Yeah.

1972
01:59:54,700 --> 01:59:59,660
Um I mean I have a blog post coming up that's basically arguing that most of what you think

1973
01:59:59,660 --> 02:00:01,340
you believe you don't actually believe.

1974
02:00:01,660 --> 02:00:02,460
Awesome.

1975
02:00:02,780 --> 02:00:04,460
I'm really excited about that one.

1976
02:00:04,860 --> 02:00:05,660
I believe that.

1977
02:00:05,820 --> 02:00:06,220
Does it be a good one?

1978
02:00:06,380 --> 02:00:10,220
Yeah, I'm glad you that's a really, really good question.

1979
02:00:10,460 --> 02:00:11,820
You might not deep down.

1980
02:00:11,900 --> 02:00:12,460
Who knows?

1981
02:00:13,820 --> 02:00:16,780
That's kind of I feel like that's very freeing though, because then if somebody's like I

1982
02:00:16,780 --> 02:00:19,260
don't believe you, you can be like, well, okay.

1983
02:00:19,770 --> 02:00:20,090
Yeah.

1984
02:00:20,330 --> 02:00:24,970
No, I mean the thesis is that you you may believe you believe those things, but you don't

1985
02:00:24,970 --> 02:00:26,090
actually believe those things.

1986
02:00:26,170 --> 02:00:27,130
And there's a difference there.

1987
02:00:27,290 --> 02:00:29,690
Just because you believe you believe it doesn't mean you actually believe it.

1988
02:00:30,010 --> 02:00:30,250
Right.

1989
02:00:30,410 --> 02:00:31,130
Yeah, yeah.

1990
02:00:31,290 --> 02:00:31,690
Yeah.

1991
02:00:32,010 --> 02:00:35,850
Like like we've talked about, like if you actually the way people believe act when there's

1992
02:00:35,850 --> 02:00:39,850
a real conspiracy versus they say there's a conspiracy is very different.

1993
02:00:40,010 --> 02:00:41,530
I think we talked about Hugo Mercier.

1994
02:00:42,010 --> 02:00:43,210
Yeah, we talked about Hugo Mercier.

1995
02:00:43,290 --> 02:00:46,650
We also talked about it with Dan Williams, and I talked about pseudo-beliefs.

1996
02:00:46,730 --> 02:00:50,260
So I have a big post coming up on on pseudo beliefs.

1997
02:00:50,500 --> 02:00:52,580
And uh I think it's a really interesting topic.

1998
02:00:52,820 --> 02:00:56,020
Anyway, we I don't know how this fits in with anything.

1999
02:00:57,300 --> 02:01:03,220
Well, uh if you believe, David, that um that was uh yeah, I didn't even I didn't

2000
02:01:03,220 --> 02:01:04,660
even uh finish that.

2001
02:01:04,820 --> 02:01:08,500
Um well if you believe you like this podcast, what can people do?

2002
02:01:09,460 --> 02:01:14,990
Uh well, they can say nice things about us on social media, support us on Patreon, leave us

2003
02:01:14,990 --> 02:01:16,030
a kind review.

2004
02:01:16,270 --> 02:01:17,870
Those are the big three, right?

2005
02:01:18,190 --> 02:01:19,310
Can't think of any other ones.

2006
02:01:19,630 --> 02:01:20,750
Yeah, that's that's it.

2007
02:01:20,990 --> 02:01:24,110
Yeah, and some journalists out there get on the Robert Trivers thing.

2008
02:01:24,190 --> 02:01:24,750
My goodness.

2009
02:01:24,830 --> 02:01:26,030
It's ridiculous.

2010
02:01:26,350 --> 02:01:28,510
Yeah, I'm just beginning to hear some of the horror stories.

2011
02:01:28,590 --> 02:01:28,910
Yikes.

2012
02:01:29,310 --> 02:01:33,230
I met I'm I didn't meet him in personally, but I did I was for H best Rutgers.

2013
02:01:33,620 --> 02:01:36,980
I stayed in the student dorms and he was staying in the same hallway.

2014
02:01:37,060 --> 02:01:39,460
And he was, I just remember he was in the hallway.

2015
02:01:39,540 --> 02:01:41,940
I think like the showers was a college dorms.

2016
02:01:42,180 --> 02:01:45,140
So he just I just remember he was like peering out the wind, looking out the window with

2017
02:01:45,140 --> 02:01:46,980
like a towel around his neck, just sort of peering.

2018
02:01:47,300 --> 02:01:48,500
And I was like going into my room.

2019
02:01:48,580 --> 02:01:50,100
I was like, Oh, there's Robert Trivers.

2020
02:01:50,180 --> 02:01:52,100
And that was the only interaction I had with him.

2021
02:01:52,260 --> 02:01:57,540
But yeah, I've had I've I've never heard so many stories from people having interactions

2022
02:01:57,540 --> 02:02:02,180
with a human being that were so colorful, is the one way to put it.

2023
02:02:02,510 --> 02:02:02,990
Yes.

2024
02:02:03,150 --> 02:02:03,630
Yes.

2025
02:02:04,110 --> 02:02:04,750
Yeah.

2026
02:02:05,470 --> 02:02:09,390
Well anyway, on that note we can separate the ideas from the man, hopefully.

2027
02:02:09,790 --> 02:02:10,030
Exactly.

2028
02:02:10,190 --> 02:02:10,830
No, totally.

2029
02:02:10,990 --> 02:02:11,390
Absolutely.

2030
02:02:11,710 --> 02:02:12,590
Yes, exactly.

2031
02:02:12,670 --> 02:02:12,910
Yes.

2032
02:02:13,070 --> 02:02:17,070
Um but uh it was wonderful uh to uh to have Steve on.

2033
02:02:17,150 --> 02:02:17,870
Thank you for listening.

2034
02:02:17,950 --> 02:02:19,390
And David, I'll see you next week.

2035
02:02:19,630 --> 02:02:19,790
Yep.

2036
02:02:19,950 --> 02:02:20,270
See ya.

2037
02:02:20,670 --> 02:02:20,990
Bye.