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So David, um, I wonder if people think that we have been screwing up on purpose or if

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we're doing it for real in the beginning.

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No, I can I can assure you all, for those listening, our screw-ups are genuine and sincere.

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We really are as incompetent as we sound.

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Well, I am uh not David Pinsoff, and you are not.

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I'm definitely not George Clooney, sadly.

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Okay, uh today Okay, keep going.

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I'm really bad at this.

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Uh I'm David Pinsov.

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I'm David Petrozowski.

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And this is Evolutionary Psychology, the podcast actually features evolutionary psychology

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by actual evolutionary psychologists.

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That's right.

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So yeah.

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Enjoy

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Um David, good to see you.

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I'm really excited that uh I get to see you I got to see you at HBES, Human Behavior

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Evolution Society.

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Uh love going to HBES and it's was lovely to just spend some time with you in person.

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Yeah, uh it was it was a a really fun time.

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Um and uh after HBES, we have a wonderful guest, uh, Annie

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Wirtz, who is a professor of psychology at University of California, Santa Barbara.

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Uh, we cover uh some really fascinating new stuff that Annie has been pioneering on the

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study of infant learning and uh how we think about plants.

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Yeah, totally new area, really unusual for somebody in our sort of generation of science to

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kind of develop a whole new area and a really lovely example of somebody taking

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evolutionary perspective on development and learning and generating completely new

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knowledge in an area where people really didn't think to look before, especially from a

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psychological experimental perspective.

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So it's a really fun, interesting conversation.

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I think you'll really enjoy it.

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And yeah, enjoy the episode.

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Enjoy.

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Today we have Annie Wirtz, who is professor at UC

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Santa Barbara.

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and Annie, prior to UCSB, uh where where were you?

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Uh how far back should I go?

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Uh the snowy day.

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Uh Dan told us he was born in August.

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So uh you can go back all the way to the day of your childhood.

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So uh well, how about I I can go in reverse and then uh and then we

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can go.

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So uh prior to UCSB, so I started here in March of 2024, And

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then prior to that, I was at the Max Planck Institute for Human Development in Berlin for

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almost 10 years, like nine and a half-ish years.

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That I was there, I had an independent research group called the Max Planck Research Group,

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Naturalistic Social Cognition.

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And then before that, I was a postdoc at the Infant Cognition Center at

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Yale.

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And then before that, I was actually at UCSB.

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So I have looped again.

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I was at here for graduate school with Tams and German, and

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of course had Lita Cosmodies and John Tuby on my committee.

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And then before that, I was at Boston University.

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And before that, I was in uh Robozonia, Pennsylvania.

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Um until the day of my birth.

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And then before that, we don't know.

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We don't know, yeah.

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And we actually had Jamie Krems on, and she mentioned there's a whole bunch of people from

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eastern and apologies to western Pennsylvania, but eastern Pennsylvania, like um apparently

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Lita grew up in Philly, uh Jamie, um, and

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Joe Henrik.

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And then David, do you remember who else she mentioned?

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Oh, Mike Gervin.

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Mike Gervin is from the Mike on.

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Yeah.

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So there's a parent, she she thinks there's something in the water.

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So congratulations on being from it's a good pedigree.

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Um hailing from eastern Pennsylvania.

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Um we'll get into all of that path.

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And one of the things we always ask people is um is how they got interested in

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evolutionary um psychology.

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But before we do that, can you tell people a little bit about what an independent research

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group leader is at the Mox Planck or what the Mox Planck is?

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Because I know lots of people, um, our audiences diverse may not know what that is.

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So can you talk a little bit about that?

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Sure.

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Yes, so it is um, it's the Max Planck Society

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is the overarching uh institution.

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And in Germany, the Max Planck Society has over, I mean, I'm not sure what

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the current count is, but it's somewhere over 70 different research institutes throughout

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Germany, the EU.

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There had been one in Florida.

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I don't know if there's still one in Florida, Italy.

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So they're dispersed all over the place.

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And they all focus on different topics.

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And the it runs the gamut from physics and chemistry

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to empirical aesthetics and history of science and all kinds of fascinating questions.

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And they build them around the the particular sets of people who they bring in

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to be directors, who are kind of the the um the people who are in charge of the

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big centers.

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And there's usually several directors within an institute.

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And those are high-powered people with tons of money behind them and uh research

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scientists, postdocs, pre-docs, um, the whole thing.

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And then their system, they have what's equivalent to an assistant professor position

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within that, which are there's several different kinds, but um the kind that I had was an

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independent research group, um, so equivalent to an assistant professor position.

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And basically what that was is there's a call that goes out uh almost every year in the

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fall where you can apply for these positions and you pitch a research idea that you could

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do for around five-ish years.

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And I was successful in that application, and they gave me a bunch of money to do my work,

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working on how infants, the the um how infants learn about plants, um, but the kind of

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underlying psychology for how babies learn about the natural world.

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Um, and so they gave me uh money to do that.

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Um, and I had uh I had my own PhD students, I had master's students, I had

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a team of student research assistants.

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I was lucky enough to have two paid lab manager, and then a person whose position was

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foreign language secretary who worked for me and were just wonderful professional science,

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uh science support staff.

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It was a fantastic position.

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Um, the biggest problem with it though is it's time limited.

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So even though there's an initial five year period for it, then uh after that you

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can apply for extensions of various kinds.

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And I did that successfully along the way.

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Um, but uh outside of a few constrained things, typically they expect you that they've

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given you all these resources, they expect you to move on.

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Um, and so I did, and I was very lucky to then get the position here at UCSV.

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Right.

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And so it's sort of the the Mox Planck thing, it's sort of a high risk, as I understand it,

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it's sort of there's a high risk new question to be asked.

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And they give you sort of a temporary pot of money to say, look, here's this really new

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idea.

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And uh maybe not all of them work, but uh they're important big

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picture new ideas that challenge existing wisdom.

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And uh it's it's uh it's it's this really cool sort of like scientific um,

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I don't know, what would you call that?

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Almost like a what is it when an entrepreneur throws money at things?

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I don't know anything about this.

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Startup or startup, yeah.

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It's sort of like a or a go, it's almost like a scientific startup or GoFundMe, or sort of

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like a thing up where, you know, it's just sort of an engine for like new innovative

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research ideas where, yeah, the ideas maybe some percentage or even high percentage fail,

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but then some are successful.

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And as far as we know, and I mean, this is when whenever we have guests on, I always think

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about like what to say about a person.

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There's very few people I know in our cohort who came up with a whole new area of research.

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Um and I think you're one of those people where the combination of babies and plants,

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um, and I know it's more complicated, but I'm just we're being super adductive now.

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Like that's a when people hear that, they sort of do a double take.

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Um, and we can get into and sort of what that is, but I mean, was it but what you're saying

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is that you know you were one of these high risk people in this really cool program

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in Germany.

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And it by all accounts, based on the papers and based on the fact that you're UCSB, it it

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worked, right?

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Yes.

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Yeah.

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It did.

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Yeah.

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And I think you know that's it's it's another example in your work.

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And we've talked about, we've alluded to your work uh a bunch that um you know we've talked

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a little bit about innate versus learned, and we can get to that too.

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And your work is a good example of that.

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But we've also talked about how taking an evolutionary approach um gives you new insights

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uh and questions to ask that you've never would have gotten without an evolutionary

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approach.

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And I think your work is a really good example of that to the point where when people hear

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about it, it sounds like a crazy idea, unless you sort of explain it.

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Yeah.

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Yeah, that's right.

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And I mean, to just to put a button on the Max Planck thing, the the um the idea behind

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these independent research groups is it's really promising ideas that are potentially too

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new to be a a sure bet for traditional funding agencies.

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So they give you the money to really establish the idea if it's got something to it,

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um, and with the idea that later on down the line you can get money from traditional

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funding agencies as well.

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And that's that's how it worked in my case.

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That's awesome.

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I I wish we had something like that here in the US.

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It sounds uh very cool.

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Um but I I I want to get into um the origin story behind um

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this topic uh of of plants, because I don't I don't think I've heard it or or or know how

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you got into this.

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So as far as I'm aware, like you're the first person to start studying this

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topic, you basically pioneered this new field of research.

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Um and that raises a lot of questions like how how did you discover that this was uh uh an

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underexplored topic?

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How did you uh uh move in this direction?

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Uh did did you slip on a plant and then uh

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like like what happened there?

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Yeah.

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Um, well, uh there uh several things kind of came together.

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So when I was in graduate school at UCSB, um I guess this it sort of uh

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intersects with the origin story of how I ended up in evolutionary psychology too, because

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coming out, I I'm my kind of deep time history as a scientist is in cognitive

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development.

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Um and I that's what I was doing when I was in undergrad.

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Um uh in addition to working in a behavior genetics lab.

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Um And so I was reading a lot of the work.

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This was early 2000s.

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I was reading a lot of the infant cognition work that was coming out at the time.

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People, you know, like Karen Wynne, Elizabeth Stalke, Susan Carey,

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Alan Leslie, people like that, talking about the kinds of

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systems you would expect to see in infant minds.

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And that was a very uh it remains, it's a domain-specific view that there are

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there are these um different people have different flavors of this, but to use uh Liz

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Felke's uh exam uh Liz Felke's framework, there are these different core knowledge systems,

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right, that are for different kinds of things.

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Um and so uh I had been working or thinking in in that um

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in that kind of way of, or I've been kind of steeped in that way of thinking.

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And when I applied to graduate school, I applied to work with Tams and German here to do

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theory of mind work.

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I was very interested in kind of thinking about thinking.

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But one of the other things that had always grabbed me in that work is there's a whole

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section on folk biology and intuitive biology and uh the kind of common

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sense understanding of the biological world, which basically boils down to plants and

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animals, but also includes things like how kids think about disease or other kinds of

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biological processes.

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There's just a really, there's a really interesting literature there that was very active

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in the late 90s and early 2000s.

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And uh so I had been kind of I had been familiar with that work.

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Um I uh back when I started graduate school was the days where you were

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accepted and then you were brought out for a recruitment weekend.

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So um I had been accepted to UCSB.

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I came for the recruitment weekend, uh, and I was among many other uh interesting

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conversations that I had, and of course the really good fit with my advisor, um, I was

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lucky enough to meet with Lita Cosmodies.

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And I did not know that she was Lita Cosmodies, you know.

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I uh because I had you heard had you heard of her at that point?

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No, uh-uh.

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No, because I I didn't know anything about evolutionary psychology and uh what I had the uh

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well that's not entirely true.

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The only thing I had heard about it was that it was all basically like

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fake and wrong.

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Garbage, yeah.

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Yeah, just in passing, that was what I had heard about it.

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And I but I I didn't hear enough of it to form an opinion one way or the other.

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Um I just really didn't know.

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So I I I came I here I was uh for the for the recruitment weekend I was talking to Lita and

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she asked me about um well what are you thinking about?

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And one of the things that I had been thinking about at that point when I had been reading

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is well how do you know what domains there should be?

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you know, because there's the at the time, it's there's objects, there's number, there's

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agency.

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Um, but why those and how would you carve them up?

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And so I said that to Lita, and she basically said, uh, I can teach you that.

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Um, and and so I came here and she did.

237
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Uh, and the other graduate students in the program here, and and my advisor.

238
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Um, and it was uh so that's I when I first got here, I knew

239
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nothing about evolutionary psychology.

240
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I remember um and if you ever do talk to Tams and German uh in in this, she can tell

241
00:15:00,510 --> 00:15:05,310
you, I remember going to her office early in graduate school and saying, It feels like

242
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they're all talking a different language and I have no idea what they're saying uh in the i

243
00:15:10,350 --> 00:15:12,590
in talking to the other graduate students here.

244
00:15:12,750 --> 00:15:18,680
Um so I had a lot of kind of catching up to do in terms of how you do

245
00:15:18,680 --> 00:15:19,880
an evolutionary approach.

246
00:15:19,960 --> 00:15:24,840
But it just seemed when Lita explained so Lita basically gave me the short version of how

247
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you do evolutionary psychology and an adaptationist approach.

248
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And it just seemed like it must be true, right?

249
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That if you are, if you want to understand the structure of the mind of

250
00:15:37,960 --> 00:15:43,960
a particular kind of organism, why wouldn't you want to know about and use the process

251
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that built the organism as a way of deriving predictions for what should be or

252
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what might be in what might be systems in the mind, right?

253
00:15:53,330 --> 00:15:58,850
So this it just it just seemed, it seemed like it, it at that broad level it had to be

254
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true.

255
00:15:59,330 --> 00:16:02,690
And then the question was learning how, how to do that.

256
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Um, and so that's what I did.

257
00:16:05,410 --> 00:16:08,050
I was reading a ton, I was working on theory of mind.

258
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I did my dissertation on theory of mind, which is still a topic I find absolutely

259
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fascinating.

260
00:16:14,140 --> 00:16:18,220
And just for people who do may not know, because we have a diverse audience, what is just

261
00:16:18,220 --> 00:16:20,860
theory of mind is the ability to sort of yeah.

262
00:16:21,260 --> 00:16:26,700
The the theory of mind is uh is the common sense understanding of that

263
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other people have mental states like beliefs, desires, um uh

264
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uh that basically motivate their behavior and that you can use to uh to interpret, predict,

265
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and explain their behavior.

266
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So you know it's almost it's it's such a weird.

267
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I remember when I first heard about theory of mine, I was like, that's weird.

268
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And I had this experience with almost everything, like vision or mechanisms.

269
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I had sort of this initial reaction of like, well, why do you need a mechanism for that?

270
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Because and I realized in retrospect, it was in David, I have talked about instinct

271
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blindness, where it was just instinct blindness, where it seems so obvious that it just

272
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happens.

273
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Like you never even think to think, oh, I think about people as having mental states, but

274
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you know, as John and Lead, I think, wrote one time, like bubble a bowl of oatmeal can't do

275
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that, you know.

276
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So, like, right, so that but it always felt like sort of alien.

277
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And I think like that's part of being a scientist is sort of thinking about there are these

278
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mechanisms.

279
00:17:24,920 --> 00:17:29,080
And that's interesting that you did you started out in theory of mind and thinking about

280
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mechanisms for these very obvious systems.

281
00:17:32,840 --> 00:17:33,160
Right.

282
00:17:33,400 --> 00:17:34,010
Well, yeah.

283
00:17:34,090 --> 00:17:37,370
Well what's what's interesting to me is that this was sort of this is sort of a different

284
00:17:37,370 --> 00:17:40,970
entryway into evolutionary psychology than we've heard from some of our other guests who

285
00:17:40,970 --> 00:17:44,250
sort of encountered it directly and saw the insights that it offered.

286
00:17:44,410 --> 00:17:49,290
This is an interesting case where you had a question that you were trying to answer, which

287
00:17:49,290 --> 00:17:54,570
is you know, how how do we figure out how to carve the mind up at the joints?

288
00:17:54,730 --> 00:17:59,290
What is the you know, we have these seems to have these intuitions about say minds, say

289
00:17:59,450 --> 00:18:03,680
agents, uh, number, but like why those categories?

290
00:18:03,840 --> 00:18:05,520
Why not another set of categories?

291
00:18:05,680 --> 00:18:07,600
And that was the question that you were bringing to the table.

292
00:18:07,760 --> 00:18:10,560
Like where you were basically asking a deeper why question.

293
00:18:10,720 --> 00:18:15,440
Uh and what's interesting is that uh Leda is right in that really you need an evolutionary

294
00:18:15,440 --> 00:18:17,360
approach to even begin to answer that question.

295
00:18:17,520 --> 00:18:21,440
So your entry point seems to be that you were asking this question that evolutionary

296
00:18:21,440 --> 00:18:26,130
psychology really had was the only field that had the answer to, the only way of going

297
00:18:26,130 --> 00:18:27,170
about answering it.

298
00:18:27,250 --> 00:18:31,490
Uh and that was sort of how you how you uh entered into the field was that it it was it was

299
00:18:31,490 --> 00:18:37,410
a way of delivering an answer to a question that you had um uh that you didn't even know

300
00:18:37,410 --> 00:18:37,890
existed.

301
00:18:38,290 --> 00:18:38,690
That's right.

302
00:18:38,850 --> 00:18:39,890
Yeah, that's exactly right.

303
00:18:40,050 --> 00:18:46,040
And it was it was very uh at the time I don't think I quite understood How

304
00:18:46,280 --> 00:18:52,280
lucky I was to literally stumble into Lita's office, basically, to find this out.

305
00:18:52,520 --> 00:18:57,640
Because, you know, at the time coming out of undergrad and reading things and coming out of

306
00:18:57,640 --> 00:19:03,320
an undergrad mindset where you're reading all kinds of things, and there's somebody out

307
00:19:03,320 --> 00:19:06,840
there who knows the answer and they're testing you on the thing.

308
00:19:06,920 --> 00:19:11,590
And you you just, if you don't know it it's because you just haven't been assigned the

309
00:19:11,590 --> 00:19:17,590
right thing yet or like you haven't um you haven't hit upon the right way the right set of

310
00:19:17,590 --> 00:19:23,590
things to read right to basically find the answer um and uh I was lucky that

311
00:19:23,910 --> 00:19:29,830
I ran into Lita and she could tell me basically the way to do this where it's not as

312
00:19:29,830 --> 00:19:34,950
you say it's not clear how else you could go about really

313
00:19:36,240 --> 00:19:41,680
really truly digging apart or really truly digging into what is uh

314
00:19:42,640 --> 00:19:45,920
why there would be certain systems in the mind, right?

315
00:19:46,000 --> 00:19:50,960
You can dig pretty far into the details of what's there and how it's done without an

316
00:19:50,960 --> 00:19:56,240
evolutionary approach, but it's really hard to think about in an a priori way what should

317
00:19:56,240 --> 00:19:58,400
be there without an evolutionary approach.

318
00:19:58,480 --> 00:20:02,850
Or what I mean, you know, should is is is strong, but I mean like if you're doing

319
00:20:02,850 --> 00:20:08,210
predictions, what might be there, and then uh to to be able to test whether or not your

320
00:20:08,210 --> 00:20:10,850
predictions about that are are correct.

321
00:20:11,330 --> 00:20:12,610
So yeah, it was it was luck.

322
00:20:12,690 --> 00:20:17,090
I mean, really, it was it was luck that I I ended up talking to Lita about it.

323
00:20:17,250 --> 00:20:21,330
But once it was clear, it was this, it was uh having talked to other people about the way

324
00:20:21,330 --> 00:20:25,170
they get to evolutionary psychology, there's usually this kind of like aha moment of like,

325
00:20:25,250 --> 00:20:27,330
oh, right, this just makes sense.

326
00:20:27,490 --> 00:20:31,970
And it was very clear uh talking to Lita, this just made sense.

327
00:20:32,600 --> 00:20:37,640
And then as uh and then, you know, getting into the details of it, like I said, when I

328
00:20:37,640 --> 00:20:41,000
started talking to all these other grad students who had read all the things before I got

329
00:20:41,000 --> 00:20:44,440
there, because they had been doing this for a year or two in undergrad or they had made

330
00:20:44,440 --> 00:20:50,360
this discovery of evolutionary psychology before me, it made no sense for a while

331
00:20:50,520 --> 00:20:51,880
as I was learning.

332
00:20:52,520 --> 00:20:58,280
And what I found is that and I don't know, I mean, I don't know if this is just the

333
00:20:58,370 --> 00:21:01,010
perspective I came from or if this is a common experience.

334
00:21:01,170 --> 00:21:06,770
But what I found is that in truly learning how to do an

335
00:21:06,770 --> 00:21:12,690
adaptationist approach, how to do evolutionary psychology the way that I do it, I

336
00:21:12,690 --> 00:21:16,290
would have these moments of, okay, this makes this completely makes sense.

337
00:21:16,450 --> 00:21:17,170
I get this.

338
00:21:17,410 --> 00:21:20,500
And then I would read more and then it would all kind of crumble apart, right?

339
00:21:20,580 --> 00:21:22,740
Or I'd think more and it would all kind of crumble apart.

340
00:21:22,820 --> 00:21:27,460
And then I would have to kind of push forward, and then it would kind of go back to making

341
00:21:27,460 --> 00:21:31,300
sense again as I was reading more things and thinking through things more deeply.

342
00:21:31,380 --> 00:21:33,300
And then it would kind of crumble again, right?

343
00:21:33,380 --> 00:21:39,380
And this is what I find about ideas that um, you know, these things are controversial for a

344
00:21:39,380 --> 00:21:41,380
reason, these things are hard for a reason.

345
00:21:41,540 --> 00:21:47,110
It takes to truly grasp what's going on, you really do have to do the mental work um and

346
00:21:47,110 --> 00:21:52,630
the reading work and uh and and the thinking and talking to other people and and talking

347
00:21:52,630 --> 00:21:58,470
things through um because it's it's not the caricature of just thinking, oh hey,

348
00:21:58,710 --> 00:22:04,470
back in uh back when we were living in caves, it must be probably we could have

349
00:22:04,470 --> 00:22:05,670
done X, Y, and Z.

350
00:22:05,750 --> 00:22:08,230
And now I'm gonna make predictions based on that.

351
00:22:08,310 --> 00:22:10,230
It's actually a lot more complicated than that.

352
00:22:10,310 --> 00:22:12,070
There's a lot more that goes into that.

353
00:22:12,420 --> 00:22:15,140
does take actual training and it's hard.

354
00:22:15,220 --> 00:22:20,900
Um I don't want to detract from the getting to plants, but just really quick, the the like

355
00:22:20,980 --> 00:22:22,740
you think you got it and then you don't.

356
00:22:22,980 --> 00:22:25,220
Have you thought about what that what was that?

357
00:22:25,380 --> 00:22:28,900
Like, do you have an idea of sort of what I don't know.

358
00:22:28,980 --> 00:22:34,260
I mean, it's something that it's something that I experienced in not just in evolutionary

359
00:22:34,260 --> 00:22:34,580
things.

360
00:22:34,660 --> 00:22:39,530
It's something that with kind of tr counterintuitive concepts.

361
00:22:40,170 --> 00:22:40,490
Right?

362
00:22:40,730 --> 00:22:46,570
Like concepts that it takes training to flip out of the way you normally

363
00:22:46,570 --> 00:22:49,050
think about things to overcome your instinct blindness.

364
00:22:49,290 --> 00:22:51,290
Since we've talked about instinct blindness.

365
00:22:51,450 --> 00:22:57,370
Um it's just anything that requires uh reframing how you would kind of, I don't know,

366
00:22:57,450 --> 00:23:00,120
for lack of a better word, naturally approach a question.

367
00:23:00,440 --> 00:23:01,800
Um, it just slips in and out.

368
00:23:01,880 --> 00:23:02,760
I mean, I find this a lot.

369
00:23:02,920 --> 00:23:07,240
I teach developmental psychology now, and I find this happens a lot, excuse me, a lot with

370
00:23:07,240 --> 00:23:11,240
um uh uh heritability, right?

371
00:23:11,400 --> 00:23:13,160
Or like genes and environment.

372
00:23:13,320 --> 00:23:18,840
Like it just takes it, it it you can kind of get it at a surface level, and then you start

373
00:23:18,840 --> 00:23:21,880
thinking through another question and you realize, oh wait, this is actually very

374
00:23:21,880 --> 00:23:26,290
complicated, and you have to kind of like work at training yourself and how to keep kind of

375
00:23:26,290 --> 00:23:32,290
different conceptual levels uh clear and what the boundary conditions of what you're

376
00:23:32,290 --> 00:23:32,850
thinking about.

377
00:23:32,930 --> 00:23:36,130
So it just is, yeah, it just slips, it slipped in and out.

378
00:23:36,370 --> 00:23:36,450
Right.

379
00:23:36,770 --> 00:23:36,930
Yeah.

380
00:23:37,010 --> 00:23:38,530
Like nobody was starting from zero.

381
00:23:38,850 --> 00:23:38,930
Yeah.

382
00:23:39,090 --> 00:23:43,890
No, I should say like starting from zero with like, I didn't know about I didn't know about

383
00:23:43,890 --> 00:23:44,770
selection pressures.

384
00:23:44,930 --> 00:23:49,800
I didn't know about, you know, the whole literature, the like hunter-gatherer studies and

385
00:23:49,800 --> 00:23:50,840
behavioral ecology.

386
00:23:51,160 --> 00:23:52,200
I didn't know that stuff.

387
00:23:52,280 --> 00:23:57,720
And so I was also adding these new pieces and adding these entire new pieces.

388
00:23:57,960 --> 00:24:03,800
It would help this process of really reframing how I was approaching the study of the

389
00:24:03,800 --> 00:24:06,920
human mind, but it would just like crumble briefly.

390
00:24:07,000 --> 00:24:08,600
And then you kind of put it back together.

391
00:24:08,680 --> 00:24:10,840
It was anyway, that's my experience of it.

392
00:24:11,370 --> 00:24:11,610
Yeah.

393
00:24:11,850 --> 00:24:16,570
Well, I'm glad you had um the humility to know when it was crumbling instead of sort of

394
00:24:16,570 --> 00:24:22,090
blundering through uh in an overconfident way, which I see is unfortunately uh a trend

395
00:24:22,730 --> 00:24:26,650
uh in some uh corners of the internet regarding evolutionary psychology.

396
00:24:27,050 --> 00:24:29,690
Um I'm I'm unaware David, do you have references?

397
00:24:29,850 --> 00:24:30,410
I'm unaware of this.

398
00:24:30,490 --> 00:24:31,050
No, I'm kidding.

399
00:24:31,290 --> 00:24:31,770
Oh yeah.

400
00:24:33,930 --> 00:24:39,440
We've spent several episodes going through this stuff, but yeah, um i it it's surprising to

401
00:24:39,440 --> 00:24:41,440
me how easy people think it is.

402
00:24:41,680 --> 00:24:42,000
Yeah.

403
00:24:42,160 --> 00:24:47,040
Uh and how people think they can do it after learning about it for two minutes.

404
00:24:47,280 --> 00:24:47,440
Yeah.

405
00:24:47,760 --> 00:24:52,560
Um there's a lot of like really lazy amateur evolutionary psychology out there.

406
00:24:52,800 --> 00:24:58,640
I'm not sure w where that comes from or why people think it's so easy and it requires so

407
00:24:58,640 --> 00:25:00,720
little training and so little depth of thought.

408
00:25:00,970 --> 00:25:04,170
Uh I mean, do you have any uh is it is it just instinct blind?

409
00:25:04,250 --> 00:25:05,610
I mean it can't just be that.

410
00:25:07,130 --> 00:25:08,250
That's a good question.

411
00:25:08,410 --> 00:25:10,250
I mean it's something I have thought about.

412
00:25:10,330 --> 00:25:13,450
I think it's just I don't know.

413
00:25:15,530 --> 00:25:21,290
So I don't think anyone would think about becoming a cognitive neuroscientist

414
00:25:21,290 --> 00:25:26,650
as something you could do just by thinking about it for a few minutes, right?

415
00:25:27,240 --> 00:25:27,560
Yeah.

416
00:25:28,120 --> 00:25:33,720
And but that's something that's kind of that's a method, right?

417
00:25:34,440 --> 00:25:40,440
Uh and I wonder if I wonder if the fact that at least from

418
00:25:40,440 --> 00:25:46,280
my perspective, what evolutionary psychology offers is a really rigorous, you know, logical

419
00:25:46,920 --> 00:25:48,600
theoretical framework.

420
00:25:49,000 --> 00:25:49,400
Right.

421
00:25:49,640 --> 00:25:55,160
And the complexity of the theoretical framework, I think, is something that

422
00:25:55,800 --> 00:26:01,730
um you can overlook right like you

423
00:26:01,730 --> 00:26:07,730
can't overlook that you're sticking someone in an MRI and you have to know how to like deal

424
00:26:07,730 --> 00:26:13,490
with the machine and the the data that come out of it and that this clearly takes huge

425
00:26:13,490 --> 00:26:18,880
amounts of training to figure out how to do these things the right way um and that it's

426
00:26:18,880 --> 00:26:21,760
something that's specialized and does require training, right?

427
00:26:21,920 --> 00:26:27,120
Um but I think when there's certain there seem to be certain kinds of theoretical

428
00:26:27,120 --> 00:26:33,040
structures and even certain kinds of uh uh ways of doing science that people have uh

429
00:26:33,360 --> 00:26:37,120
are more likely to think are easier than they actually are.

430
00:26:37,280 --> 00:26:40,000
I actually find this, I mean this happens sometimes with baby stuff too.

431
00:26:40,160 --> 00:26:45,710
Like because I work with babies is sometimes people think it's just, you know, you just do

432
00:26:45,710 --> 00:26:46,910
a study with babies.

433
00:26:46,990 --> 00:26:52,110
Um, but it that's also something that takes quite a bit of training to learn how to use

434
00:26:52,110 --> 00:26:52,910
that method.

435
00:26:53,070 --> 00:26:58,510
Um, so I don't know, I'm not sure why evolutionary psychology falls into this category of

436
00:26:58,510 --> 00:27:03,950
it's easy to overlook how complicated it actually is and how difficult it actually is, but

437
00:27:03,950 --> 00:27:04,830
it certainly does.

438
00:27:05,470 --> 00:27:06,280
That's that's really interesting.

439
00:27:06,360 --> 00:27:10,040
I wonder, like this is, I think this is what Annie you were just saying, and you can tell

440
00:27:10,040 --> 00:27:13,640
me if I'm wrong, but like it's sort of like the difference between you drive past somebody

441
00:27:13,640 --> 00:27:17,240
building a bridge versus you you like see somebody writing a book.

442
00:27:17,480 --> 00:27:21,560
And you're sort of like the bridge thing, it's like I don't have a crane.

443
00:27:21,640 --> 00:27:23,160
I don't have huge things of cement.

444
00:27:23,320 --> 00:27:24,360
Like that seems really hard.

445
00:27:24,440 --> 00:27:28,600
So you can kind of see the method and the in the discrepancy between what you have and what

446
00:27:28,600 --> 00:27:29,400
is required.

447
00:27:29,590 --> 00:27:32,550
But for writing a book, like I think there's this trope like everybody thinks they can

448
00:27:32,550 --> 00:27:34,710
write a book until they sit down and try to.

449
00:27:34,870 --> 00:27:38,550
And it's because all of the difficulty is abstract and hidden.

450
00:27:38,790 --> 00:27:43,110
And I think like one of the themes of this podcast has been like humility about how

451
00:27:43,110 --> 00:27:48,710
complicated things are that might seem superficially not even worthy of notice, let alone

452
00:27:48,710 --> 00:27:54,340
consideration, let alone respect, like babies or like field work or like the

453
00:27:54,340 --> 00:27:55,860
difficulty of adaptationism.

454
00:27:55,940 --> 00:28:01,060
So it sounds like that's sort of what you're saying is that the the abstractness of this

455
00:28:01,220 --> 00:28:05,460
maybe combined with things like, you know, scientists who are, you know, kind of like, oh,

456
00:28:05,700 --> 00:28:09,940
babies, that's not scientific, you know, which is a different issue or a related issue.

457
00:28:10,100 --> 00:28:12,260
But but yeah, no, I I totally buy that.

458
00:28:12,340 --> 00:28:18,020
That it's a um the abstraction, it's it's this, it's this sort of silly thing of

459
00:28:18,020 --> 00:28:22,100
everyone who just thinks they can write a bestseller book until they sit down to to the

460
00:28:22,420 --> 00:28:25,850
well, it's not a typewriter anymore but you you get the the proverbial typewriter.

461
00:28:25,930 --> 00:28:26,170
Yeah.

462
00:28:26,490 --> 00:28:26,810
Yeah.

463
00:28:27,050 --> 00:28:31,930
And I mean I do think it it is the kind of thing like you can do a bad version of it

464
00:28:31,930 --> 00:28:32,730
easily.

465
00:28:33,130 --> 00:28:33,610
Oh yeah.

466
00:28:33,770 --> 00:28:34,010
Right.

467
00:28:34,250 --> 00:28:37,210
I mean I think also do a bad version of cognitive neuroscience easily.

468
00:28:37,690 --> 00:28:39,210
Bang someone over the head with a hammer.

469
00:28:39,850 --> 00:28:40,170
Yes.

470
00:28:40,490 --> 00:28:41,930
Yeah that's true.

471
00:28:42,970 --> 00:28:44,490
Well I impaired your cognition.

472
00:28:44,570 --> 00:28:45,850
Wow I've new discovery.

473
00:28:46,250 --> 00:28:46,650
That's true.

474
00:28:47,130 --> 00:28:51,120
Um We once in grad school somebody did an MRI analysis.

475
00:28:51,200 --> 00:28:54,560
This is like back in the old days where you'd used an abacus, not for real, but like you

476
00:28:54,560 --> 00:28:58,960
had to hand code the analysis and like the uh the pixels were like away from the head.

477
00:28:59,120 --> 00:29:01,280
And so somebody like had discovered the soul.

478
00:29:01,360 --> 00:29:05,280
Like we we joked that like somebody had discovered the soul because you know there was like

479
00:29:05,280 --> 00:29:07,760
brain activation outside of the skull.

480
00:29:07,920 --> 00:29:11,280
Um neuroscience joke.

481
00:29:11,520 --> 00:29:17,470
Not sure how So uh you're you're learning about what

482
00:29:17,470 --> 00:29:22,510
has been called core knowledge or the intuitions that uh babies bring to the table when

483
00:29:22,510 --> 00:29:23,390
they're learning about the world.

484
00:29:23,550 --> 00:29:26,350
So they don't just they're not blank slates, they don't come to the world with no

485
00:29:26,350 --> 00:29:29,070
preconceptions and no intuitions about anything.

486
00:29:29,230 --> 00:29:33,550
They often have uh very clear expectations about how the world works, and there's a whole

487
00:29:33,550 --> 00:29:38,750
literature of studies that basically surprise babies by violating their expectations or

488
00:29:38,750 --> 00:29:42,350
violating their intuitions by essentially doing magic tricks for them.

489
00:29:43,280 --> 00:29:47,760
And you can study this scientifically by looking at how long a baby will stare at

490
00:29:47,760 --> 00:29:48,000
something.

491
00:29:48,160 --> 00:29:51,680
So it's been shown that babies will look at something when they're surprised by it, and

492
00:29:51,680 --> 00:29:55,200
they'll they'll look at that for a longer time, kind of puzzling over how it works.

493
00:29:55,360 --> 00:29:59,920
And using that simple premise, you can study all these things about how babies think and

494
00:30:00,000 --> 00:30:02,960
and the intuitions that babies have about the world.

495
00:30:03,120 --> 00:30:09,050
So you're um uh at Santa Barbara, you're you're learning about core knowledge and

496
00:30:09,210 --> 00:30:13,450
these intuitions that we bring to the table and how babies are smarter than than we think

497
00:30:13,450 --> 00:30:14,090
they are.

498
00:30:14,570 --> 00:30:20,090
At what point does the light bulb go off and you think about uh plants as a

499
00:30:20,090 --> 00:30:22,170
potential uh area of inquiry?

500
00:30:22,570 --> 00:30:28,330
Yeah, well, so that was so I was going along doing my learning how to do evolutionary

501
00:30:28,330 --> 00:30:34,090
psychology, doing my work on theory of mind, and um my work on theory of mind

502
00:30:34,900 --> 00:30:40,180
um uh was very heavily informed by alan leslie's work.

503
00:30:40,420 --> 00:30:46,260
And uh that was a lot of, you know, task analysis work of how do you

504
00:30:46,260 --> 00:30:49,780
build a successful model of theory of mind performance?

505
00:30:50,340 --> 00:30:56,020
How does that how how and how would different models explain the kind of

506
00:30:56,020 --> 00:31:01,410
data that you see when you test young kids at the time on

507
00:31:02,050 --> 00:31:03,170
theory of mind tasks.

508
00:31:03,330 --> 00:31:09,330
So I was learning not only kind of these broader questions or thinking

509
00:31:09,330 --> 00:31:15,330
about these broader questions of what are kind of core knowledge systems and what are

510
00:31:15,330 --> 00:31:19,490
the set of core knowledge systems, but I was very focused on this kind of like how do you

511
00:31:19,490 --> 00:31:25,260
do the nitty-gritty of unpacking what would successful performance look like on a

512
00:31:25,260 --> 00:31:26,060
particular task.

513
00:31:26,140 --> 00:31:26,300
Right.

514
00:31:26,460 --> 00:31:28,380
So that was extremely useful.

515
00:31:28,460 --> 00:31:34,060
And that was something, you know, this was uh what I was thinking about a lot in my

516
00:31:34,060 --> 00:31:34,940
day-to-day stuff.

517
00:31:35,020 --> 00:31:36,540
I really like theory of mind work.

518
00:31:36,700 --> 00:31:40,300
I should preface what I'm about to say with I really like theory of mind work.

519
00:31:40,620 --> 00:31:43,340
Um I really, it was fascinating to think about.

520
00:31:43,420 --> 00:31:49,310
I learned a huge amount, and uh I have a huge amount of respect

521
00:31:49,310 --> 00:31:55,070
for the people working in the field, but at the time I was doing it, it was a hot topic

522
00:31:55,230 --> 00:31:57,230
and everybody was working on it.

523
00:31:57,470 --> 00:32:03,470
And I had the uh experience of submitting papers and getting the kind of like,

524
00:32:03,550 --> 00:32:09,150
well, this all looks great, the science is fine, but you're not adhering to my particular

525
00:32:09,150 --> 00:32:12,880
version of theory of mind, my particular theoretical structure.

526
00:32:12,960 --> 00:32:16,880
So we're going to reject the paper, which, you know, it's a standard thing that happens,

527
00:32:16,960 --> 00:32:18,880
but that was sort of grading on me.

528
00:32:19,280 --> 00:32:25,280
And at the same time, I'm sitting in on these on the Center for Evolutionary

529
00:32:25,280 --> 00:32:26,560
Psychology meetings.

530
00:32:27,040 --> 00:32:30,080
And at the time when I was a graduate student, I really was just sitting there.

531
00:32:30,160 --> 00:32:31,040
I was very shy.

532
00:32:31,200 --> 00:32:35,110
I did not talk for most of my graduate career.

533
00:32:35,270 --> 00:32:39,750
Um, and uh so I was just absorbing everything that was coming through when I started going

534
00:32:39,750 --> 00:32:45,110
to HBus uh and uh connecting with um, you know,

535
00:32:45,590 --> 00:32:51,190
uh uh biological anthropologists and behavioral ecologists and primatologists and seeing

536
00:32:51,190 --> 00:32:52,630
the kind of work they were doing.

537
00:32:52,790 --> 00:32:58,740
And uh one of the things that came up was uh seeing a lot of Mike Gervin's

538
00:32:58,740 --> 00:33:02,820
work uh and looking at human life history trajectories.

539
00:33:03,060 --> 00:33:08,180
And a lot of the focus on that, um the data that he was presenting at the time was about uh

540
00:33:08,180 --> 00:33:14,100
caloric returns for hunting uh and kind of the age curves for when you

541
00:33:14,100 --> 00:33:18,730
finally start to bring in more calories than you're using through hunting.

542
00:33:19,130 --> 00:33:20,010
And when when is that point?

543
00:33:20,090 --> 00:33:24,410
I always I find that fact fascinating and reassuring in in for me in my personal life.

544
00:33:26,890 --> 00:33:28,570
Yeah, I think it's 40s or 50s, right?

545
00:33:28,650 --> 00:33:28,890
I think it's a good thing.

546
00:33:33,050 --> 00:33:34,810
Remember the remember Mike Irvin's work.

547
00:33:34,970 --> 00:33:35,130
I know.

548
00:33:35,530 --> 00:33:35,850
I know.

549
00:33:36,170 --> 00:33:38,810
I'm really glad you said that, David, because I feel the same way too.

550
00:33:38,890 --> 00:33:44,640
And I'm like And I mean this was uh I the I am pulling that from, you know,

551
00:33:44,800 --> 00:33:46,400
twenty years ago probably at this point.

552
00:33:46,480 --> 00:33:50,560
But yeah, it was uh um yeah, so it's it's quite late, which is good.

553
00:33:50,640 --> 00:33:56,480
So he but you know, he's talking about the the great data that he has and the theoretical

554
00:33:56,480 --> 00:33:56,720
work.

555
00:33:56,880 --> 00:34:00,880
And at some point it or often it would be kind of mentioned like, okay, so there's this

556
00:34:00,880 --> 00:34:05,440
variability in the calories that come in from hunting, but the kind of basis of the diet is

557
00:34:05,440 --> 00:34:07,840
plants, it's gathered plant resources.

558
00:34:08,290 --> 00:34:10,130
Dot move back to hunting.

559
00:34:10,290 --> 00:34:14,610
And I was like thinking, I'm like, hang on, how do you do that?

560
00:34:14,850 --> 00:34:20,370
Like what are the set of cognitive skills that are required to do that?

561
00:34:20,450 --> 00:34:25,250
Because that actually, even though it's reliable, that actually doesn't seem easy if you

562
00:34:25,250 --> 00:34:26,610
start thinking about it.

563
00:34:26,770 --> 00:34:30,370
And so that kind of grabbed my attention and I started thinking about it.

564
00:34:30,450 --> 00:34:35,020
And at the time, I mean, I don't know, I don't know if you like Dave and I are married.

565
00:34:35,100 --> 00:34:35,980
Uh we were both.

566
00:34:36,460 --> 00:34:37,100
News to me.

567
00:34:38,860 --> 00:34:39,100
I know.

568
00:34:39,180 --> 00:34:39,820
I don't know about it.

569
00:34:41,660 --> 00:34:42,460
Yeah, thanks.

570
00:34:42,700 --> 00:34:48,540
Um, and at the time we were, you know, doing a lot of trail running here in Santa

571
00:34:48,540 --> 00:34:49,020
Barbara.

572
00:34:49,100 --> 00:34:51,180
And so we were up in the mountains.

573
00:34:51,420 --> 00:34:53,100
This was basically parents.

574
00:34:53,260 --> 00:34:54,140
So we had time to do it.

575
00:34:54,380 --> 00:34:56,140
Yes, this is preparenting.

576
00:34:56,220 --> 00:34:57,980
Now we don't go in the mountains.

577
00:34:58,220 --> 00:35:03,660
Um, but uh but we had time to do these long runs in the mountains on the weekends.

578
00:35:03,830 --> 00:35:08,070
Um, and we did some runs where we'd go back over into the backcountry and stuff.

579
00:35:08,310 --> 00:35:13,270
And there's a this is also pre like um pre uh

580
00:35:14,150 --> 00:35:18,630
earbuds and like listening to stuff while you're while you're going, it was just quiet and

581
00:35:18,630 --> 00:35:21,430
we would uh we would run with our with our friends.

582
00:35:21,590 --> 00:35:25,110
Um and there were a lot of times when I was out there and it was like, okay, if we got

583
00:35:25,110 --> 00:35:27,270
stuck this far out, I would die.

584
00:35:27,750 --> 00:35:30,820
Um but people did this.

585
00:35:30,980 --> 00:35:32,500
Like people did this here.

586
00:35:32,660 --> 00:35:36,740
They did this here successfully for thousands and thousands of years.

587
00:35:37,060 --> 00:35:38,660
How do you do this?

588
00:35:38,820 --> 00:35:41,460
And so I was just kind of thinking about all of these things.

589
00:35:41,620 --> 00:35:43,700
And I just, I just started thinking through the problem.

590
00:35:43,780 --> 00:35:44,980
It just was interesting to me.

591
00:35:45,060 --> 00:35:47,060
I've kind of always kind of liked plants.

592
00:35:47,140 --> 00:35:49,780
I find them interesting and fruits and things like that.

593
00:35:49,940 --> 00:35:55,630
Um, I never have gotten into being a a super gardener yet, but I

594
00:35:55,710 --> 00:35:59,390
I I can see that coming someday.

595
00:36:00,350 --> 00:36:06,190
I see the TED talk in your future, Annie Words, plants and you are maybe I can

596
00:36:06,270 --> 00:36:08,830
see you writing some self-help book about the wisdom of flowers.

597
00:36:09,470 --> 00:36:10,030
Something like that.

598
00:36:10,190 --> 00:36:11,950
I think that could bring in some money for you.

599
00:36:12,430 --> 00:36:14,190
I'll I'll I'll keep that in mind for the title.

600
00:36:14,430 --> 00:36:15,310
Thanks to it.

601
00:36:16,360 --> 00:36:17,960
Um yeah, but it was so much.

602
00:36:19,880 --> 00:36:21,880
Oh, uh it's so ripe for puns.

603
00:36:21,960 --> 00:36:27,000
It's just you know, I do it it is, and I have to say I've used a bunch of puns in my titles

604
00:36:27,000 --> 00:36:29,320
because I find it I I just I don't know.

605
00:36:29,800 --> 00:36:30,360
No, it's a contention.

606
00:36:30,840 --> 00:36:31,480
Life is hard enough.

607
00:36:31,560 --> 00:36:32,440
You might as well have puns now.

608
00:36:32,840 --> 00:36:33,560
No, I'm pro pun.

609
00:36:33,720 --> 00:36:35,880
I'm I'm firmly on the pro pun side.

610
00:36:35,960 --> 00:36:38,760
I think we me need more levity uh in in our science.

611
00:36:39,080 --> 00:36:39,560
Oh yes.

612
00:36:39,960 --> 00:36:42,920
Some people disagree with me, but I'm I'm firmly on the side of fun.

613
00:36:43,650 --> 00:36:44,370
Me too.

614
00:36:45,810 --> 00:36:49,570
But yeah, so I just I had the luxury though of like I started thinking about that.

615
00:36:49,730 --> 00:36:54,850
I don't remember exactly when, but a few years into grad school, maybe three years in.

616
00:36:54,930 --> 00:37:00,290
So I had like three years of just thinking about this for fun while I was frustrated about

617
00:37:00,290 --> 00:37:01,410
theory of mind stuff.

618
00:37:01,570 --> 00:37:03,330
So I was thinking about theory of mind stuff.

619
00:37:03,410 --> 00:37:04,530
I was doing the theory of mind stuff.

620
00:37:04,610 --> 00:37:05,970
I was doing my dissertation.

621
00:37:06,050 --> 00:37:10,930
Um, I was working on the papers for that, um, and just getting intensely frustrated.

622
00:37:11,170 --> 00:37:15,220
Um, And uh but then I just had the time to think and I could.

623
00:37:15,700 --> 00:37:21,700
And I um then when we got our PhDs, Dave and I,

624
00:37:21,940 --> 00:37:27,940
uh he got the uh the job to go work with Karen Wynne at the Infant Cognition

625
00:37:27,940 --> 00:37:33,460
Center at Yale because this was the time when um she was looking at social relationship

626
00:37:33,550 --> 00:37:37,630
stuff and group kinds of things and his work fit really well.

627
00:37:37,790 --> 00:37:43,550
Um and I I did they had some money um for me to come along too, but there

628
00:37:43,550 --> 00:37:46,430
wasn't a specific project that it was tied to.

629
00:37:46,670 --> 00:37:52,190
And so I had a a meeting, Karen Wynne was here in Santa

630
00:37:52,190 --> 00:37:52,830
Barbara.

631
00:37:52,990 --> 00:37:58,000
Um think she was a sage fellow or something like that with one of our speaker series with

632
00:37:58,160 --> 00:38:02,880
have people um stay for at the time anyway, had people stay for a little bit in town.

633
00:38:03,120 --> 00:38:08,400
So I met with her here uh and she basically asked, well, you know, what do you want to do

634
00:38:08,400 --> 00:38:09,840
for your postdoc project?

635
00:38:10,000 --> 00:38:14,160
And it was wide open, like it wasn't tied to a specific grant, it could be anything.

636
00:38:14,320 --> 00:38:20,210
And so I talked about some action perception and theory of mind kind of

637
00:38:20,210 --> 00:38:23,490
uh ideas that I had been thinking about and that I found very interesting.

638
00:38:23,650 --> 00:38:29,170
And they also said, but I also have been thinking about this thing that babies might there

639
00:38:29,170 --> 00:38:32,450
might be design in the human mind for learning about plants.

640
00:38:32,610 --> 00:38:34,290
And we could look at that in babies.

641
00:38:34,450 --> 00:38:39,330
And she, I mean, this is you know, condensing down the conversation, but she was basically

642
00:38:39,330 --> 00:38:41,090
like, Oh, yes, go do that.

643
00:38:41,250 --> 00:38:45,490
Uh, and so that's how we started working on that.

644
00:38:45,650 --> 00:38:50,500
Um, she taught me how to do the actual baby studies.

645
00:38:50,820 --> 00:38:55,940
And this is also when Kylie Hamlin was a PhD student in the lab.

646
00:38:56,020 --> 00:39:01,380
And I learned a ton about how to test babies from Karen and from Kylie Hamlin, just

647
00:39:01,380 --> 00:39:02,500
watching her do her thing.

648
00:39:02,660 --> 00:39:05,620
Kylie is a baby testing master.

649
00:39:06,260 --> 00:39:11,850
And so I learned a ton from that and basically supplied like here's here's the

650
00:39:11,850 --> 00:39:17,130
theoretical stuff, here's what I think uh is our places we here are places I think we could

651
00:39:17,130 --> 00:39:19,290
start that may be fruitful, huh?

652
00:39:19,530 --> 00:39:21,130
For uh for looking at.

653
00:39:21,290 --> 00:39:27,130
Um, and uh and so we started with some of these basic questions about you know,

654
00:39:27,450 --> 00:39:33,260
a very basic level of is there evidence that babies are sensitive to the kind

655
00:39:33,260 --> 00:39:37,020
of harm that plants can inflict on humans.

656
00:39:37,180 --> 00:39:42,700
And is there evidence that they seem to that they may have social learning systems that are

657
00:39:42,700 --> 00:39:45,260
set up for learning about plants?

658
00:39:45,820 --> 00:39:51,580
And so that was the focus of my postdoc, was kind of would basically resulted in a

659
00:39:51,580 --> 00:39:54,060
couple papers looking at those questions.

660
00:39:54,140 --> 00:39:58,460
And then it was on the basis of that work that I pitched to the Max Planck Society to say,

661
00:39:58,540 --> 00:39:59,740
hey, here's this new idea.

662
00:39:59,900 --> 00:40:05,830
There's a couple, you know, there's a couple papers on this, and they said, yes, please go

663
00:40:05,830 --> 00:40:06,230
do this.

664
00:40:06,390 --> 00:40:09,510
And that's what I did for like almost a decade.

665
00:40:09,590 --> 00:40:15,430
Um, and have really been lucky enough to have the opportunity to expand out uh into all

666
00:40:15,430 --> 00:40:17,430
kinds of different aspects of that question.

667
00:40:17,510 --> 00:40:20,070
And that's what I'm continuing to do here.

668
00:40:20,390 --> 00:40:23,510
Um, but yeah, and I there's a ton to do.

669
00:40:23,590 --> 00:40:27,030
It turns out plants are really complicated, it's very fun to think about.

670
00:40:27,800 --> 00:40:28,120
Totally.

671
00:40:28,280 --> 00:40:34,200
I mean, so it seems like uh what what drove you into this area was a combination of two

672
00:40:34,200 --> 00:40:34,760
things.

673
00:40:34,920 --> 00:40:40,120
Um, one is a frustration with the sort of faddishness in in social science.

674
00:40:40,280 --> 00:40:44,680
So, like people were really into theory of mind, that was the hot topic, uh, as you said.

675
00:40:44,840 --> 00:40:50,440
And uh there are big problems with entering into a hot topic area and that you have a lot

676
00:40:50,440 --> 00:40:50,920
of competition.

677
00:40:51,000 --> 00:40:55,470
A lot of people have their own pet theories and their own pet ways of doing things.

678
00:40:55,550 --> 00:40:57,310
Uh, it's hard to break in.

679
00:40:57,470 --> 00:41:00,830
Um and so that uh i i is inherently limiting.

680
00:41:00,910 --> 00:41:06,110
So a continued frustration with that and trying to find something new um that you could

681
00:41:06,110 --> 00:41:07,470
carve out for yourself.

682
00:41:07,710 --> 00:41:13,310
And the other was um, I think a uh a glimpse of

683
00:41:13,500 --> 00:41:15,100
of the wave of a hand.

684
00:41:15,420 --> 00:41:19,660
So uh you mentioned Mike Gervin Gervin's work, um, and he was talking about how, you know,

685
00:41:19,740 --> 00:41:23,340
uh uh uh gathering plant food as a as a source of calories.

686
00:41:23,420 --> 00:41:27,180
Uh and and and you just saw that and and said, wait, wait a second, what what's what's

687
00:41:27,180 --> 00:41:29,900
going on there with that wave of the hand about plant food?

688
00:41:29,980 --> 00:41:33,020
That's there's a lot in there that's being dismissed.

689
00:41:33,180 --> 00:41:39,170
Um and um what I really like about the evolutionary way of thinking is that it it

690
00:41:39,170 --> 00:41:43,170
teaches you how to spot those waves of the hand and say, wait, wait, wait, hold on.

691
00:41:43,250 --> 00:41:45,330
You can't just you can't just wave your hand like there.

692
00:41:45,730 --> 00:41:48,770
There's there's something underneath there, there's something more complicated.

693
00:41:48,930 --> 00:41:54,690
Uh it teaches you to be uh to have a better eye about, you know, uh

694
00:41:55,010 --> 00:42:00,740
what what questions have not been asked, what uh what answers have not been given,

695
00:42:00,900 --> 00:42:05,060
um, and it helps you go uh in in a in a really good direction.

696
00:42:05,220 --> 00:42:09,140
Um so is is that a fair characterization of how you you ended up here?

697
00:42:09,220 --> 00:42:15,140
Uh you know, a a a frustration of of faddishness and a um and I

698
00:42:15,140 --> 00:42:19,860
guess a vigilance against having, you know, the wool pulled over your eyes or or a

699
00:42:19,860 --> 00:42:24,750
vigilance against just glib uh answers to questions that don't really get into the

700
00:42:24,750 --> 00:42:25,310
complexity.

701
00:42:25,870 --> 00:42:27,070
Yeah, I mean I it's close.

702
00:42:27,230 --> 00:42:32,910
I would say that the uh the for the first part um it makes me it makes it sound

703
00:42:32,910 --> 00:42:34,190
better than it actually was.

704
00:42:34,270 --> 00:42:39,950
I was frustrated and I was like it because for the part about um about the the the kind of

705
00:42:39,950 --> 00:42:45,940
working in a fad area was really like uh okay well I it w I was young, you

706
00:42:45,940 --> 00:42:50,580
know, so I was kind of like, okay, you're going to tell me that I am not adhering to your

707
00:42:50,580 --> 00:42:50,980
theory.

708
00:42:51,140 --> 00:42:55,140
I'm gonna go do something that nobody's done before and I'm gonna build my own theory.

709
00:42:55,300 --> 00:42:56,100
Thank you very much.

710
00:42:56,340 --> 00:43:00,980
Like it was kind of like, I mean, I didn't say this out loud again because I was extremely

711
00:43:00,980 --> 00:43:06,580
shy, but that is what was that that more kind of um maybe uh

712
00:43:06,820 --> 00:43:10,420
juvenile motivation was was behind that.

713
00:43:11,300 --> 00:43:12,340
Thank goodness you had it.

714
00:43:12,450 --> 00:43:16,530
You know, I like we we we know n next to nothing about plant cognition.

715
00:43:16,690 --> 00:43:21,970
We know um I uh I we still don't know enough about theory of mind, but I think uh it's it's

716
00:43:21,970 --> 00:43:25,090
good to have a diversified approach to the discovery of knowledge.

717
00:43:25,170 --> 00:43:27,490
Uh we don't wanna all be studying the same thing.

718
00:43:27,810 --> 00:43:28,450
No, it's true.

719
00:43:29,730 --> 00:43:34,240
Yeah, and I I mean I taught a grad class this uh this past spring quarter here, and I

720
00:43:34,240 --> 00:43:38,320
described, and I it did feel at the time it was kind of like in doing theory of mind stuff.

721
00:43:38,400 --> 00:43:40,240
It was sort of like I took my ball and went home.

722
00:43:40,400 --> 00:43:41,280
You know what I mean?

723
00:43:41,520 --> 00:43:46,720
Um, but uh, and then for the second part, I think, I mean, what I so I I completely agree

724
00:43:46,800 --> 00:43:52,560
that it's it's looking for, well, hang on, you just passed over something there that

725
00:43:52,560 --> 00:43:54,320
is actually really complicated.

726
00:43:54,560 --> 00:44:00,010
And I you're exactly right, there's a vigilance for that is a problem

727
00:44:00,650 --> 00:44:05,130
that people have been solving, and it's actually pretty a lot more complex.

728
00:44:05,290 --> 00:44:10,330
I would say in Mike Irvin, I would not say he was he wasn't being gliding.

729
00:44:10,570 --> 00:44:10,810
Oh, yeah.

730
00:44:10,970 --> 00:44:13,210
Don't mean to just Mike Irvin by any stretch of the imagination.

731
00:44:13,530 --> 00:44:13,930
No, no, no.

732
00:44:14,250 --> 00:44:17,130
And you know, we all focus on what we focus on, right?

733
00:44:17,290 --> 00:44:22,650
So, but it was, it was just, it was the vigilance for like, oh, hang on, that is hard,

734
00:44:22,810 --> 00:44:23,050
right?

735
00:44:23,210 --> 00:44:29,200
And right now, that is, you know, either it's being overlooked or it's in the bin for

736
00:44:29,280 --> 00:44:33,280
like, I'll deal with this later, you know, but I'm focusing on this other thing.

737
00:44:33,440 --> 00:44:38,640
Um, but it was very much that vigilance for like, okay, yes, this this requires an

738
00:44:38,640 --> 00:44:39,600
explanation.

739
00:44:39,840 --> 00:44:42,800
And how is that how is that happening?

740
00:44:42,960 --> 00:44:48,800
And then critically, having been trained in how to do an adaptationist approach,

741
00:44:48,880 --> 00:44:54,560
it gave me the theoretical toolkit to basically be like, well, nobody's done this before in

742
00:44:54,630 --> 00:44:58,870
the way that I, in this like kind of holistic way that I'm thinking about it, or thinking,

743
00:44:58,950 --> 00:45:02,390
not I mean holistic is the wrong word, but in a focused way, right?

744
00:45:02,550 --> 00:45:06,470
Because people have gotten to pieces of this.

745
00:45:06,550 --> 00:45:12,470
You know, like there are people like um Liz Cashton had some work looking in in

746
00:45:12,470 --> 00:45:18,420
the uh mid 90s, looking at why kids are neophobic about um

747
00:45:18,740 --> 00:45:20,020
about vegetables, right?

748
00:45:20,100 --> 00:45:22,420
Like why do little kids not want to eat their vegetables?

749
00:45:22,660 --> 00:45:28,340
And um uh uh um Margie Prophet in the adapted mind

750
00:45:28,580 --> 00:45:32,020
has the whole thing about plant toxins and uh pregnancy.

751
00:45:32,260 --> 00:45:38,260
Susan Gelman um had uh had work actually looking at how young kids think

752
00:45:38,260 --> 00:45:39,110
about plants.

753
00:45:39,750 --> 00:45:41,910
Again, that was in the kind of mid-90s.

754
00:45:41,990 --> 00:45:45,590
This was, as I said, there's that whole intuitive biology literature, right?

755
00:45:45,750 --> 00:45:51,430
So people had studied what do young kids think about plants, but it was, with the exception

756
00:45:51,430 --> 00:45:57,110
of Susan Gelman's work, as far as I'm aware, almost all of it was

757
00:45:57,750 --> 00:46:00,440
how are plants and animals the same, right?

758
00:46:00,840 --> 00:46:04,520
So, like, uh, how do living things work, right?

759
00:46:04,600 --> 00:46:09,400
And so, and you can you can learn quite a lot from that by looking at that question for

760
00:46:09,400 --> 00:46:09,720
plants.

761
00:46:09,880 --> 00:46:15,480
So, like little preschool age kids, um you know, three to three to five-year-old kids, four

762
00:46:15,480 --> 00:46:21,190
to six, can know things like um plants like animals grow, Plants like

763
00:46:21,190 --> 00:46:24,710
animals can uh need food and water to grow.

764
00:46:24,870 --> 00:46:30,230
They can get heal themselves after they get damaged and they can die.

765
00:46:30,390 --> 00:46:35,430
Like they know these kinds of things about both both sets of entities.

766
00:46:35,750 --> 00:46:40,870
But there again, that's another place where the evolutionary approach, you look at that and

767
00:46:40,870 --> 00:46:44,230
you're like, okay, sure, there's commonalities between plants and animals, but if you're

768
00:46:44,230 --> 00:46:50,120
thinking adaptive problem first, of what how are you as uh either a young human or

769
00:46:50,120 --> 00:46:52,520
even an adult, how are you engaging with these things?

770
00:46:52,680 --> 00:46:57,000
The way that you engage with plants is very different than the way that you engage with

771
00:46:57,000 --> 00:47:03,000
animals because a lot of my work kind of uh now you've got me on puns, it stems

772
00:47:03,000 --> 00:47:08,840
from this, um, which is that uh it is uh plants are plants

773
00:47:08,840 --> 00:47:11,110
are rooted to the ground, right?

774
00:47:11,190 --> 00:47:16,230
And because plants are rooted to the ground, that's a very different thing than animals

775
00:47:16,390 --> 00:47:17,430
that can move around.

776
00:47:17,590 --> 00:47:23,430
So, like the example of dangerous plants and dangerous animals, um a dangerous spider,

777
00:47:23,590 --> 00:47:29,430
a poisonous spider, a poisonous snake, um, a uh a lion, whatever,

778
00:47:29,670 --> 00:47:34,550
big dangerous animals, small dangerous animals, all of those things can come to you.

779
00:47:34,720 --> 00:47:37,520
You have to be vigilant about them in different ways.

780
00:47:37,760 --> 00:47:43,360
A dangerous plant, you can have a poison oak plant that you're gonna get a horrible rash,

781
00:47:43,520 --> 00:47:48,000
or you can have a deadly toxic plant that if you take a bite of it, you will die.

782
00:47:48,160 --> 00:47:51,200
But none of that happens unless you go to the plant.

783
00:47:51,680 --> 00:47:52,000
Right.

784
00:47:52,800 --> 00:47:58,800
So even though the danger, you the danger of injury or the danger of death

785
00:47:58,800 --> 00:48:02,870
is there in both cases, it's very different how it plays out.

786
00:48:02,950 --> 00:48:07,990
So if you're thinking about how systems should be designed to deal with those dangers, they

787
00:48:07,990 --> 00:48:11,670
likely have different characteristics and different design features.

788
00:48:11,750 --> 00:48:17,670
And so that's that's where I really that's that's how I started thinking about that too.

789
00:48:17,750 --> 00:48:23,590
Um so there's there's pieces in the literature, but not from the standpoint of

790
00:48:23,700 --> 00:48:29,620
what is what are the broader adaptive problems really of humans dealing with plants and how

791
00:48:29,620 --> 00:48:34,900
would you see what what would the cognitive systems for those kinds of problems look like

792
00:48:34,900 --> 00:48:40,820
in babies and in uh young kids right so it's that

793
00:48:40,900 --> 00:48:46,580
that uh instead of all the infinite ways you could carve up plants as a thing sort of in a

794
00:48:46,580 --> 00:48:50,750
school book, you know, it's thinking of this privilege class of what would there be

795
00:48:50,750 --> 00:48:52,990
selection pressures for for people.

796
00:48:53,150 --> 00:48:58,270
And I mean, one of the things that I whenever I see your talks is that the first few slides

797
00:48:58,270 --> 00:49:03,070
are sort of, you know, the way that we think of plants now is this sort of backdrop and

798
00:49:03,070 --> 00:49:03,950
wallpaper.

799
00:49:04,110 --> 00:49:05,870
But that's very unusual.

800
00:49:06,030 --> 00:49:09,950
And our brains are really evolved for this world where we didn't have grocery stores and

801
00:49:09,950 --> 00:49:15,240
where everything really is, you know, you you have to go out and actually like get food.

802
00:49:15,320 --> 00:49:17,160
And that is super not trivial.

803
00:49:17,320 --> 00:49:20,040
Um, as you said, like I'm sure all of us would die.

804
00:49:20,200 --> 00:49:23,880
Um, probably Annie, you would probably survive the longest of the three of us.

805
00:49:24,040 --> 00:49:24,760
David, I don't know.

806
00:49:24,840 --> 00:49:27,800
Who do you think if we were in the wilderness, who would go first?

807
00:49:28,200 --> 00:49:29,800
Oh, I would go first, definitely.

808
00:49:31,000 --> 00:49:33,000
I didn't want to say it, but I don't know.

809
00:49:33,240 --> 00:49:33,720
We'll we'll see.

810
00:49:34,120 --> 00:49:35,640
We we've been through this many times.

811
00:49:36,680 --> 00:49:42,050
Every time we bring on an anthropologist, I'm like shivering with fear to describe what

812
00:49:42,050 --> 00:49:42,690
they've been through.

813
00:49:44,770 --> 00:49:49,250
But uh but yeah, but no, but but the point of like, you know, you really, you know, this

814
00:49:49,250 --> 00:49:50,610
thing of affordances, right?

815
00:49:50,690 --> 00:49:52,290
Like what does this thing afford?

816
00:49:52,450 --> 00:49:57,730
And we had Ed Hagan on already too, and he talked about how like this this, you know, these

817
00:49:57,730 --> 00:50:01,890
secondary compounds, these pesticides, like there's just a ton of these chemicals.

818
00:50:01,970 --> 00:50:03,410
And I I just love that.

819
00:50:03,570 --> 00:50:09,540
You know, this your your talks are incredibly logical in the sense of plants, even though

820
00:50:09,540 --> 00:50:11,860
they look like wallpaper, are fundamentally important.

821
00:50:11,940 --> 00:50:16,900
They literally are like life and death for eating and also other stuff like you know,

822
00:50:17,140 --> 00:50:17,780
construction.

823
00:50:18,340 --> 00:50:21,380
But then they're super, super dangerous.

824
00:50:21,540 --> 00:50:26,660
And I think even as much as I thought I appreciated just hearing all the details from you

825
00:50:26,660 --> 00:50:31,060
about even like tomatoes, like the leaves of the tomato plant, it's like a deadly

826
00:50:31,060 --> 00:50:31,940
nightshade family.

827
00:50:32,020 --> 00:50:37,090
So even though it's been artificially selected, even though you know it's still yeah, yeah,

828
00:50:37,170 --> 00:50:38,930
it's still like super dangerous, right?

829
00:50:39,010 --> 00:50:40,770
Like plants are just super dangerous.

830
00:50:41,010 --> 00:50:41,330
Yeah.

831
00:50:41,570 --> 00:50:44,610
Don't eat tomato leaves, don't eat potato leaves.

832
00:50:44,930 --> 00:50:46,370
Don't eat raw potatoes, also.

833
00:50:46,930 --> 00:50:48,130
Don't eat raw potatoes, yeah.

834
00:50:48,290 --> 00:50:48,690
Yeah.

835
00:50:48,930 --> 00:50:49,250
Yeah.

836
00:50:49,490 --> 00:50:55,250
I mean, this is what's it's uh plants are really complicated and

837
00:50:55,330 --> 00:51:00,140
and it's it's really, it's always very interesting to talk to people about this because

838
00:51:00,380 --> 00:51:05,420
when I give the few-word description of I study babies and plants, Dave's right, everybody

839
00:51:05,420 --> 00:51:06,140
goes, huh?

840
00:51:06,380 --> 00:51:11,900
And I mean, now it's it happens less because I've been doing it long enough that people

841
00:51:11,900 --> 00:51:12,700
sort of expect that.

842
00:51:12,780 --> 00:51:15,020
And sometimes now they go, oh, you're the one.

843
00:51:15,180 --> 00:51:20,540
Um, but uh, but um there's usually kind of like,

844
00:51:21,100 --> 00:51:22,490
well, I get asked a lot of things.

845
00:51:22,650 --> 00:51:26,570
One thing I get asked a lot is what were you really looking for when you found this?

846
00:51:27,130 --> 00:51:29,610
It's something I get asked a lot.

847
00:51:29,690 --> 00:51:31,770
And I said, Well, I was looking for this.

848
00:51:31,930 --> 00:51:36,090
Like I started out, I mean, I was thinking about this for literal years before I started

849
00:51:36,090 --> 00:51:37,290
looking for this.

850
00:51:37,530 --> 00:51:43,130
Um, and uh and then the the second thing is kind of a oh, well, okay,

851
00:51:43,210 --> 00:51:48,880
maybe I guess, but you know, people have this idea very much built on their own

852
00:51:48,880 --> 00:51:51,680
experience that plants are just like not that important.

853
00:51:52,080 --> 00:51:57,920
Um, and then when you start to when you start to get people thinking about,

854
00:51:58,400 --> 00:52:04,320
first of all, as Dave mentioned, in worlds where people are living in wild

855
00:52:04,320 --> 00:52:08,720
environments, and you can't go to the grocery store, you can't go to a restaurant, how are

856
00:52:08,720 --> 00:52:11,040
you gonna get your plant foods, right?

857
00:52:11,200 --> 00:52:14,800
Um, you have to go out and you have to actually identify these things, but plants are

858
00:52:14,800 --> 00:52:20,590
really tricky because they all have, as you heard from Ed, they all have these toxic

859
00:52:20,590 --> 00:52:22,510
secondary compounds in them.

860
00:52:22,830 --> 00:52:26,830
Um, they all have toxic secondary compounds.

861
00:52:26,910 --> 00:52:32,030
And then some of those exist in forms and in concentrations that can be really bad for

862
00:52:32,030 --> 00:52:32,590
humans.

863
00:52:32,750 --> 00:52:36,990
Um, and Ed probably talked about how we have enzymatic pathways.

864
00:52:37,070 --> 00:52:39,790
There's all kinds of defenses that we have against plants.

865
00:52:39,870 --> 00:52:45,230
Like our physiology is really adapted to these things, and not just us, but

866
00:52:45,320 --> 00:52:51,160
existing off of uh of um wild forage plant resources, this is

867
00:52:51,160 --> 00:52:56,760
something that applies to all kinds of other animals, arguably most other

868
00:52:56,760 --> 00:52:57,560
animals, right?

869
00:52:57,800 --> 00:52:57,960
Right.

870
00:52:58,120 --> 00:53:02,040
If you were to do like a pie chart of likely selection pressures, yes.

871
00:53:02,360 --> 00:53:07,960
Plants, contrary to the intuition, like this probably the most certain

872
00:53:08,280 --> 00:53:14,040
stable feature that that like animals have been, you know, dealing

873
00:53:14,040 --> 00:53:19,770
with for really really long time well well prior to um you know whatever

874
00:53:19,930 --> 00:53:25,690
what what what mammals I mean right like even yeah I mean yeah insects do this right most

875
00:53:25,770 --> 00:53:31,530
of plants is like plants and insects um and it's uh it's

876
00:53:31,930 --> 00:53:37,130
it is a really long-standing problem and so I think I mean of the the the

877
00:53:37,800 --> 00:53:43,720
one of the benefits of also doing this and starting this in my 20s is I

878
00:53:44,200 --> 00:53:46,920
I just knew this had to be true.

879
00:53:47,240 --> 00:53:47,560
Right.

880
00:53:47,800 --> 00:53:50,440
Like it now I think I'd be more risk averse.

881
00:53:50,520 --> 00:53:55,880
And even if I knew it had to be true, I don't know that I would either counsel my students

882
00:53:55,880 --> 00:54:01,800
or allow myself to just like, no, no, just go do a whole new area based on this logic that

883
00:54:01,800 --> 00:54:02,760
you have, right?

884
00:54:03,080 --> 00:54:05,870
Um, but uh but it had to be true.

885
00:54:05,950 --> 00:54:11,790
There had it, they they why would an entity that

886
00:54:12,110 --> 00:54:17,550
lives off of these things out in the world, like yeah, even just if you take the

887
00:54:17,550 --> 00:54:22,910
fundamental that just like consumes these things, eats these things, why would there not be

888
00:54:23,070 --> 00:54:26,190
psychology for engaging with plants?

889
00:54:26,350 --> 00:54:31,310
How could there not be psychology for the kind of thing, one of the main kinds of things

890
00:54:31,310 --> 00:54:33,630
that this kind of organism exists on?

891
00:54:33,880 --> 00:54:34,200
right?

892
00:54:34,440 --> 00:54:40,120
Um, and so I, from that perspective, it yeah, it it it had to be true.

893
00:54:40,200 --> 00:54:46,120
So I started doing it with the certainty that, you know, I might be, I might be wrong about

894
00:54:46,120 --> 00:54:47,480
the details, right?

895
00:54:47,560 --> 00:54:53,560
So I might be wrong about the way that the uh psychology is

896
00:54:53,560 --> 00:54:55,320
set up to deal with plants.

897
00:54:55,570 --> 00:54:57,250
that's entirely possible.

898
00:54:57,490 --> 00:55:03,010
I don't think I'm wrong that the psychology is set up to deal with plants.

899
00:55:03,250 --> 00:55:03,490
Right.

900
00:55:03,650 --> 00:55:03,890
Right.

901
00:55:04,050 --> 00:55:04,690
In some way.

902
00:55:04,850 --> 00:55:10,130
Like some aspects of human psychology must be set up to deal with plants.

903
00:55:10,210 --> 00:55:10,450
Yeah.

904
00:55:10,610 --> 00:55:15,730
Maybe not the way I think, maybe not the way I've interpreted my data, but there's there's

905
00:55:15,970 --> 00:55:18,600
there there should, and it's a good place you should.

906
00:55:18,680 --> 00:55:20,520
Like there should be something there for that.

907
00:55:20,680 --> 00:55:26,120
If an insect is set up that way, if a gorilla is set up that way, why not humans?

908
00:55:26,280 --> 00:55:26,520
Right.

909
00:55:26,760 --> 00:55:27,640
Um yeah.

910
00:55:27,800 --> 00:55:29,480
So it seemed like a safe bet.

911
00:55:29,560 --> 00:55:34,360
And I mean it's worked out, but it was in in retrospect, like later on in my postdoc

912
00:55:34,360 --> 00:55:39,960
career, I had a kind of passing conversation with Paul Bloom, who was uh who was

913
00:55:40,270 --> 00:55:43,470
uh kind of a co-advisor at the at the time.

914
00:55:43,630 --> 00:55:47,310
Um and he said something like, Yeah, this was actually brave to do this.

915
00:55:47,550 --> 00:55:49,710
I thought and it was the first time I thought about it.

916
00:55:49,790 --> 00:55:53,310
And I was like, oh no, this this could have been a huge mistake.

917
00:55:54,190 --> 00:55:56,990
But uh but yeah, it it ended up working out.

918
00:55:57,150 --> 00:55:58,430
Um all right.

919
00:55:58,590 --> 00:56:00,750
So you took this uh this leap of faith.

920
00:56:00,910 --> 00:56:03,070
Well I it's actually it's a more of a leap of logic, I think.

921
00:56:03,150 --> 00:56:05,390
I think there's really rigorous and solid logic.

922
00:56:05,470 --> 00:56:07,630
So I don't think it was a leap at all.

923
00:56:07,950 --> 00:56:13,400
Um and uh so after you you take this leap and you do this brave thing of, you know

924
00:56:14,040 --> 00:56:19,960
walking out onto a new field, another plant metaphor, um, uh, you know, ten years

925
00:56:19,960 --> 00:56:24,680
later or so, uh you have harvested uh uh you know, another plant metaphor, uh a lot of

926
00:56:24,680 --> 00:56:26,040
empirical evidence.

927
00:56:26,280 --> 00:56:31,640
Um could you give us uh a sketch of some of the discoveries you found, some of the design

928
00:56:31,640 --> 00:56:33,000
features of this the system?

929
00:56:33,160 --> 00:56:35,640
What have you learned uh in the past decade or so?

930
00:56:36,070 --> 00:56:36,710
Yeah, sure.

931
00:56:36,870 --> 00:56:41,270
So the the overarching thing is the that um

932
00:56:42,150 --> 00:56:48,070
fundamentally because humans are i uh huh well here

933
00:56:48,230 --> 00:56:49,270
let me just step back.

934
00:56:49,430 --> 00:56:55,190
So the the the logic, the the core of the logic about the design of plant systems is that

935
00:56:55,510 --> 00:57:01,110
a large portion of what is going on in humans is likely to involve social learning,

936
00:57:01,300 --> 00:57:01,620
right?

937
00:57:01,780 --> 00:57:07,780
And the reason for this is because uh so as we've talked about, plants are many things.

938
00:57:08,020 --> 00:57:13,700
They are edible, um, but they are also dangerous and they can be that in very

939
00:57:13,700 --> 00:57:14,660
specific ways.

940
00:57:14,900 --> 00:57:20,660
So most cases plants are um only edible uh or like it's certain

941
00:57:20,660 --> 00:57:26,660
parts of plants are edible at certain times of the year, basically, because that's you know

942
00:57:26,820 --> 00:57:31,390
how that's not entirely the case, but that's that's how it works.

943
00:57:31,550 --> 00:57:36,270
For humans, we also do this thing where we uh process our food and we cook our food.

944
00:57:36,430 --> 00:57:42,110
And so that unlocks a lot of plant resources that are otherwise toxic.

945
00:57:42,350 --> 00:57:46,510
So there's a lot of things, the kinds of foods that humans specialize in, like fruits,

946
00:57:46,590 --> 00:57:52,510
roots, and nuts, a lot of the roots and nuts that humans rely on and that are the kind

947
00:57:52,510 --> 00:57:54,270
of staples of human diets.

948
00:57:54,350 --> 00:58:00,280
If you look in uh in small scale and small scale indigenous societies you see

949
00:58:00,280 --> 00:58:06,280
that they they are uh they're plant resources that are not edible unless you do some kind

950
00:58:06,280 --> 00:58:10,680
of processing to them so they're toxic until they're processed and then they are food and

951
00:58:10,680 --> 00:58:16,600
they're the they are these um staple kind of core basis of and of

952
00:58:16,600 --> 00:58:22,600
the of the caloric intake um so what that means though is that as a

953
00:58:22,600 --> 00:58:27,770
human being when you are dropped, when you're born, you're basically dropped into a

954
00:58:27,770 --> 00:58:29,370
particular environment.

955
00:58:30,010 --> 00:58:34,810
You can't know in advance what the plant life around you is going to be.

956
00:58:35,130 --> 00:58:41,050
Um, so because we are omnivores and we don't specialize in like one or

957
00:58:41,050 --> 00:58:46,820
two particular plants, like some species do, you can't build in something

958
00:58:46,820 --> 00:58:49,940
that's more like a template for like find this particular plant.

959
00:58:50,100 --> 00:58:55,140
And if you find this particular plant or this particular features of plants, then you know

960
00:58:55,220 --> 00:58:56,980
you're fine, go ahead and eat it.

961
00:58:57,140 --> 00:58:58,420
We're not set up that way.

962
00:58:58,580 --> 00:59:04,100
We have this large diet breadth, and because we specialize in these higher caloric

963
00:59:04,100 --> 00:59:09,700
density parts that require processing beforehand, it means

964
00:59:09,940 --> 00:59:15,590
that any individual human can't construct a human diet on their own,

965
00:59:15,830 --> 00:59:16,150
right?

966
00:59:16,550 --> 00:59:22,230
So if you as a baby are born to a particular place, if you were by trial and

967
00:59:22,230 --> 00:59:26,630
error to kind of just even figure out which plants are around you are edible, and you just

968
00:59:26,630 --> 00:59:31,990
start eating particular plants and seeing what happens based on what happens to you when

969
00:59:31,990 --> 00:59:37,760
you eat it, at best, you're going to spend a lot of time sick and uh and

970
00:59:37,920 --> 00:59:39,200
and out of commission.

971
00:59:39,360 --> 00:59:41,120
At worst, you're going to die.

972
00:59:41,360 --> 00:59:46,480
And so instead, what you see, and now I've done this with some

973
00:59:46,480 --> 00:59:52,480
collaborators, is when you run selection dynamic models, when you run the math

974
00:59:52,480 --> 00:59:58,150
on this, these circumstances select for the evolution of social learning mechanisms

975
00:59:58,390 --> 01:00:04,390
where instead of trial and error learning the information for yourself, you instead

976
01:00:04,470 --> 01:00:10,310
the mechanisms are set up to learn the information from the people in your local

977
01:00:10,310 --> 01:00:12,790
environment who already know it, right?

978
01:00:13,110 --> 01:00:18,070
So I know and this is one of these places where there's a little there's a little bit of a

979
01:00:18,070 --> 01:00:22,630
gloss over, like it does gloss over how do you get that knowledge in the first place,

980
01:00:22,820 --> 01:00:23,140
right?

981
01:00:23,460 --> 01:00:28,980
Again, this is this is it clearly there is a process there by which the first

982
01:00:28,980 --> 01:00:33,380
individual figured out that you could eat this, and then the the individuals along the way

983
01:00:33,460 --> 01:00:37,940
across generations figured out, for example, the processing techniques and things like that

984
01:00:38,020 --> 01:00:42,900
that you could do, and you have this kind of cumulative cultural evolution of these kinds

985
01:00:42,900 --> 01:00:45,060
of uh of these aspects of things.

986
01:00:45,220 --> 01:00:48,930
For right now, for me, that stuff is black boxed, right?

987
01:00:49,010 --> 01:00:53,810
I know it's there, I know it's something to be explained, but I'm assuming that that is

988
01:00:53,810 --> 01:00:54,130
there.

989
01:00:54,450 --> 01:01:00,370
And then given that babies are dropped into a world where that exists, then the

990
01:01:00,370 --> 01:01:04,850
argument is that their their psychology, particularly our psychology, human psychology,

991
01:01:04,930 --> 01:01:10,930
especially when we're we're uh when we're in the earliest parts of our lives, is

992
01:01:10,930 --> 01:01:15,720
really geared towards getting that information from watching what other people do, Right.

993
01:01:16,040 --> 01:01:21,960
So what we have found is at a broad level

994
01:01:22,280 --> 01:01:28,120
is that infants show evidence of a psychology that is designed

995
01:01:28,120 --> 01:01:34,040
for balancing the costs and benefits of plants, such that when infants are first

996
01:01:34,040 --> 01:01:40,030
confronted with unfamiliar plants, they show a reluctance to

997
01:01:40,030 --> 01:01:43,710
reach out and touch plants compared to other things.

998
01:01:43,950 --> 01:01:49,230
So we do this by uh we test babies with a series of different objects.

999
01:01:49,390 --> 01:01:54,830
We have real plants, we have artificial plants that look very realistic, but we

1000
01:01:54,830 --> 01:01:56,750
include them for two reasons.

1001
01:01:56,910 --> 01:02:02,540
And first we include them because uh they don't grow or change or die over the course of

1002
01:02:02,540 --> 01:02:04,380
testing, and the real plants do.

1003
01:02:04,540 --> 01:02:09,420
And then secondly, we include them because they don't have a scent and the real plants do.

1004
01:02:09,580 --> 01:02:13,500
And scent is important, but when we were testing this, we wanted to make sure that we

1005
01:02:13,500 --> 01:02:18,540
weren't just getting babies responding to stuff that smelled one way versus things that

1006
01:02:18,540 --> 01:02:19,580
don't smell at all.

1007
01:02:19,740 --> 01:02:25,420
So we have real plants, artificial plants, and then we make a bunch of control objects to

1008
01:02:25,530 --> 01:02:31,290
examine whether babies are responding to plants per se, or are they responding to

1009
01:02:31,290 --> 01:02:32,090
particular features?

1010
01:02:32,170 --> 01:02:38,170
Like is it a broader class of anything that's green or anything that has

1011
01:02:38,170 --> 01:02:41,770
some a particular kind, particular kinds of shapes?

1012
01:02:42,250 --> 01:02:44,250
So we build these artifacts.

1013
01:02:44,810 --> 01:02:50,120
I don't have any in my office, or I would pull one over, but we we uh we we build these

1014
01:02:50,120 --> 01:02:54,440
artifacts that share features of the plants, but they when you see them especially up

1015
01:02:54,440 --> 01:02:56,680
close, they are definitely not plants.

1016
01:02:56,920 --> 01:03:02,440
Um we also include familiar objects, objects that are both things that

1017
01:03:02,440 --> 01:03:07,320
babies would uh would use all the time themselves, like little board books, and then

1018
01:03:07,320 --> 01:03:12,280
objects that would also be things that parents would caution babies about using.

1019
01:03:12,360 --> 01:03:17,710
So we have like cooking pots, we have uh uh a knife, it's an infant-safe

1020
01:03:17,870 --> 01:03:23,470
3D printed knife, but it is a knife, and uh and and other kinds of objects like that.

1021
01:03:23,630 --> 01:03:29,550
And then we have another category of stimuli that are other inanimate natural kinds that

1022
01:03:29,550 --> 01:03:30,350
are not plants.

1023
01:03:30,430 --> 01:03:36,110
So shells, stones, like a dried-out sea sponge, these kinds of things, so that um we can

1024
01:03:36,110 --> 01:03:41,920
examine whether it's a broader category potentially of natural versus human-made, right?

1025
01:03:42,160 --> 01:03:47,600
So we we have this whole set of different objects and uh we put them down in front of

1026
01:03:47,600 --> 01:03:53,200
infants uh one at a time in a randomized order and then what we see is that infants take

1027
01:03:53,200 --> 01:03:58,640
longer to reach out and touch the plants versus all of the other object types we tested.

1028
01:03:58,800 --> 01:04:01,440
So we see this plant specific response.

1029
01:04:01,680 --> 01:04:07,410
They treat the real and the artificial plants similarly And show this

1030
01:04:07,410 --> 01:04:08,450
reluctance to touch.

1031
01:04:08,690 --> 01:04:13,810
And we've replicated that now, I think, seven times in different

1032
01:04:13,810 --> 01:04:19,810
contexts, including some work with collaborators looking at indigenous

1033
01:04:19,890 --> 01:04:25,170
small scale societies, where we see aspects of this also in those societies as well.

1034
01:04:25,810 --> 01:04:31,730
And what we see in addition to that initial reluctance to touch is at least in the

1035
01:04:31,730 --> 01:04:37,160
US and the German populations that we've looked at in the time before babies touch, they

1036
01:04:37,160 --> 01:04:43,080
actually look up to the adult to see the way we interpret that is to it's

1037
01:04:43,160 --> 01:04:48,760
it's a if you are geared to get social information, you have to look at the person

1038
01:04:49,000 --> 01:04:50,760
to see what they're doing, right?

1039
01:04:51,000 --> 01:04:56,680
So in these studies, the adult experimenters across the table from the baby, they put these

1040
01:04:56,680 --> 01:04:58,440
uh stimulus objects down.

1041
01:04:58,600 --> 01:05:04,130
And what we see is that if you on my computer screen, if you're the experimenter and you

1042
01:05:04,130 --> 01:05:09,730
hand me the baby an object, uh if it's a plant, what I do is I look to you first

1043
01:05:10,050 --> 01:05:12,450
and then I will go ahead and try and touch it.

1044
01:05:12,610 --> 01:05:16,690
If it's one of these other non-plant objects, I'll touch it first, and then I'll look to

1045
01:05:16,690 --> 01:05:17,890
you to see what to do.

1046
01:05:18,130 --> 01:05:23,740
So we see this kind of like social information gathering thing, and then we also have

1047
01:05:23,740 --> 01:05:29,180
evidence that in addition to looking for social information prior to making contact with

1048
01:05:29,180 --> 01:05:35,100
plants, we we see that babies appear to be geared to learn that particular

1049
01:05:35,100 --> 01:05:36,140
plants are edible.

1050
01:05:36,220 --> 01:05:39,420
So we see kind of selective learning of plant edibility.

1051
01:05:39,900 --> 01:05:44,220
We see that that information that babies learn about plants is

1052
01:05:45,930 --> 01:05:51,610
when it's generalized to new things, they're really careful about how they generalize

1053
01:05:51,610 --> 01:05:55,050
information about plants, especially edibility information.

1054
01:05:55,130 --> 01:06:00,330
They seem to generalize that more tightly than they do, say, toxicity information.

1055
01:06:00,490 --> 01:06:05,130
And when they're generalizing just information like name information about plants, they use

1056
01:06:05,210 --> 01:06:09,530
or when they're generalizing name information when it's about a plant, they focus on these

1057
01:06:09,530 --> 01:06:14,410
little fine grain features more than when it's a human made artifact.

1058
01:06:14,620 --> 01:06:20,060
So we see that there seems to be, because one of the thinking adaptive problem first, one

1059
01:06:20,060 --> 01:06:25,180
of the problems is after you learn about a particular plant in your environment, you have

1060
01:06:25,180 --> 01:06:27,820
to be able to apply that information in new settings.

1061
01:06:28,060 --> 01:06:33,980
And the because many plants look very similar and they have

1062
01:06:34,220 --> 01:06:38,860
that high cost of making a mistake as even very similar looking plants, one can be edible,

1063
01:06:38,940 --> 01:06:44,850
one can be toxic, it suggests that there should be selection on the mechanisms to use all

1064
01:06:44,850 --> 01:06:48,290
available features to make these kind of fine-grained distinctions.

1065
01:06:48,450 --> 01:06:54,050
And we're seeing some evidence about that in babies and some in

1066
01:06:54,050 --> 01:06:55,010
adults too.

1067
01:06:55,410 --> 01:06:59,490
So that's that's kind of like that's a gloss, but that's one of the that's kind of the

1068
01:06:59,490 --> 01:07:01,490
large, the big picture at this point.

1069
01:07:01,650 --> 01:07:06,880
Initial reluctance, look uh evidence of looking for social information, and then

1070
01:07:07,520 --> 01:07:12,080
gathering social information in specific ways, and then generalizing that information in

1071
01:07:12,080 --> 01:07:13,600
specific ways as well.

1072
01:07:14,480 --> 01:07:15,200
Fascinating.

1073
01:07:15,520 --> 01:07:21,520
I mean it it it makes uh good logical sense um what you're talking about,

1074
01:07:21,600 --> 01:07:27,290
because with with a physical artifact, like say a chair, chairs vary uh quite substantially

1075
01:07:27,290 --> 01:07:29,050
in terms of how big they are, their shape.

1076
01:07:29,210 --> 01:07:33,690
You know, any man-made artifact or human-made artifact can uh you know have have different

1077
01:07:33,930 --> 01:07:39,050
have you know vary in in size, um, but what what is constant is is the function.

1078
01:07:39,130 --> 01:07:40,010
Like what is the purpose?

1079
01:07:40,170 --> 01:07:43,770
You know, chairs are for sitting and um hammers are for hammering nails.

1080
01:07:43,930 --> 01:07:49,520
Um and so you wouldn't necessarily expect such a a focused attention on the details of a

1081
01:07:49,520 --> 01:07:53,680
physical artifact if you want to learn how to use that artifact or what its its function

1082
01:07:53,680 --> 01:07:53,920
is.

1083
01:07:54,080 --> 01:07:59,520
But with plants, on the other hand, uh the the the tiny subtle details actually matter a

1084
01:07:59,520 --> 01:08:03,600
great deal in terms of differentiating um one plant from another plant.

1085
01:08:03,760 --> 01:08:08,000
Um with with a plant, you know, the size, shape, texture really uh is is hugely important

1086
01:08:08,160 --> 01:08:12,880
and could could mean the difference between uh you know uh getting sick or dying and uh

1087
01:08:12,960 --> 01:08:14,480
eating something that is edible.

1088
01:08:14,560 --> 01:08:19,530
So I think that's a really fascinating uh example of how uh fine-grained the learning

1089
01:08:19,530 --> 01:08:20,890
psychology is.

1090
01:08:21,770 --> 01:08:27,770
Um I also think it's fascinating how laser specific uh these mechanisms are.

1091
01:08:27,930 --> 01:08:32,330
So it's not it's not just green things, it's not just pointy things, it's not just you know

1092
01:08:32,490 --> 01:08:33,130
sharp things.

1093
01:08:33,290 --> 01:08:39,130
Uh it's it's a it's a like really the the specific features of a plant are are what's uh

1094
01:08:39,130 --> 01:08:44,580
triggering this psychology and this reluctance to touch this curiosity about what other

1095
01:08:44,580 --> 01:08:47,540
adults think of this thing and whether they think it's safe?

1096
01:08:48,500 --> 01:08:49,860
It's truly fascinating.

1097
01:08:50,980 --> 01:08:55,940
Given that you've uh uh gathered all this evidence about this, you know, seemingly

1098
01:08:55,940 --> 01:09:01,700
laser-focused psychology uh on plants, how would you refer to this

1099
01:09:01,940 --> 01:09:04,970
uh uh This system, this collection of mechanisms.

1100
01:09:05,130 --> 01:09:08,730
I know you and Dave have written a lot about modularity and how you don't like that term.

1101
01:09:09,450 --> 01:09:13,610
To me, this sounds like maybe module is a is a good way of thinking about it.

1102
01:09:14,410 --> 01:09:15,930
If it's not a module, what is it?

1103
01:09:16,090 --> 01:09:17,930
How do you talk about this system?

1104
01:09:18,330 --> 01:09:24,250
Yeah, I mean, though so the way that I think about it is that what

1105
01:09:24,250 --> 01:09:29,780
I'm looking at is a collection of sort of

1106
01:09:29,780 --> 01:09:33,940
related but uh overlapping systems, right?

1107
01:09:34,100 --> 01:09:39,940
So I think about this as uh there are systems, I what I what I've called them to have kind

1108
01:09:39,940 --> 01:09:45,940
of a a single label for everything that I'm doing, is that I'm looking at a collection of

1109
01:09:45,940 --> 01:09:51,060
systems for plant learning and avoiding natural toxins or plant systems.

1110
01:09:51,220 --> 01:09:56,910
Um, but I don't think about this as there is a single module for

1111
01:09:56,910 --> 01:09:57,950
plants, right?

1112
01:09:58,190 --> 01:10:04,190
First because I think that, as I mean, probably you've discussed with Dave, I think that

1113
01:10:04,270 --> 01:10:10,110
use the the use of module and modularity gets tied up in implications

1114
01:10:10,110 --> 01:10:14,190
of Fodorian modularity, and I certainly do not mean that.

1115
01:10:14,430 --> 01:10:15,310
Um I understand.

1116
01:10:16,880 --> 01:10:22,800
Yeah, to Jerry Fodor, who was funny, uh scathing um and pretty controversial philosopher of

1117
01:10:22,800 --> 01:10:25,760
mine at Rutgers, who was actually a colleague of Alan Leslie's, right?

1118
01:10:25,840 --> 01:10:27,040
If I'm is that right, Andy?

1119
01:10:27,840 --> 01:10:29,680
But but he basically the idea is like a module.

1120
01:10:29,760 --> 01:10:32,640
I don't know how much we talked about what Fodor meant about module, but basically the idea

1121
01:10:32,640 --> 01:10:38,240
is like sort of that um it's things that are you as like an intuitive agent can't control.

1122
01:10:38,320 --> 01:10:40,880
You know, like seeing an illusion is a classic example.

1123
01:10:40,960 --> 01:10:45,270
Like you know that two lines and an illusion, You've measured them with a ruler, they're

1124
01:10:45,270 --> 01:10:49,350
both the same length, but you can't help but see them as different length because of the

1125
01:10:49,350 --> 01:10:50,790
other parts of the scene.

1126
01:10:51,270 --> 01:10:55,350
And so the idea is something like visual perception is modular in the sense of like you,

1127
01:10:55,430 --> 01:10:59,030
the little person in your head who has sort of beliefs, desires, goals to throw back to

1128
01:10:59,030 --> 01:10:59,670
theory mind.

1129
01:10:59,910 --> 01:11:03,590
Like that theory of mind parts of you can't control something.

1130
01:11:03,750 --> 01:11:07,990
And so for Fodor, that was in for, I mean, there's a whole other, you can, you know,

1131
01:11:08,070 --> 01:11:09,430
there's a whole paper on it you can read.

1132
01:11:09,510 --> 01:11:14,140
But basically, the idea is like Fodor had a reason for differentiating like the stuff you

1133
01:11:14,220 --> 01:11:17,820
quote unquote the little person can control versus those other things.

1134
01:11:18,060 --> 01:11:23,660
Evolutionary psychology really never meant that evolved stuff are those things that you

1135
01:11:23,660 --> 01:11:26,860
can't control, but it kind of got tied together.

1136
01:11:27,020 --> 01:11:31,340
And David and I did talk about sort of like the way people misunderstand it and how they

1137
01:11:31,340 --> 01:11:34,220
often want to compartmentalize it to some things.

1138
01:11:34,380 --> 01:11:36,620
And it is often the things you can't control.

1139
01:11:36,700 --> 01:11:42,230
And even in the podcast and popular spaces that's often the way it's sort of framed is like

1140
01:11:42,310 --> 01:11:47,350
there's this there's you and then there's like this additional stuff where it's not coming

1141
01:11:47,350 --> 01:11:51,750
from you but it's coming from evolution and so I think it's a very pre-potent thing.

1142
01:11:51,910 --> 01:11:56,310
But that I just wanted to fill in like that's the Fedorian version but that's but what

1143
01:11:56,310 --> 01:11:59,510
Annie's saying correct me if I'm wrong but you're saying like that's not what you're

1144
01:11:59,510 --> 01:12:00,390
talking about here.

1145
01:12:00,710 --> 01:12:01,110
That's right.

1146
01:12:01,270 --> 01:12:06,150
And I mean there's even if you read the he his the uh if you read photos work there's even

1147
01:12:06,150 --> 01:12:11,920
like a list of of criteria that a system has if you're claiming that

1148
01:12:11,920 --> 01:12:15,040
it's modular and it's things like fast, automatic, encapsulated.

1149
01:12:16,880 --> 01:12:22,880
And uh when when it when as Dave said, when evolutionary psychologists talk about

1150
01:12:22,880 --> 01:12:26,640
modularity, they're talking about a functionally specif specialized system, right?

1151
01:12:26,800 --> 01:12:32,240
And maybe it's fast, maybe it's slow, maybe it's automatic, maybe it's not, maybe it's

1152
01:12:32,240 --> 01:12:33,680
encapsulated, maybe it's not.

1153
01:12:33,760 --> 01:12:39,230
It's the the it's the George Williams adaptationism, the form follows the function, right?

1154
01:12:39,310 --> 01:12:44,030
And it depends on the it depends on the function and on the problem the thing is designed

1155
01:12:44,030 --> 01:12:45,630
to solve, the function that it has.

1156
01:12:45,790 --> 01:12:47,390
Those are the design criteria it has.

1157
01:12:47,470 --> 01:12:50,350
It's Clark Barrett's thing of it depends, right?

1158
01:12:50,830 --> 01:12:56,270
And uh and uh so um that's why I would not say

1159
01:12:56,270 --> 01:12:58,280
it's a module.

1160
01:12:58,680 --> 01:13:01,480
Well, that's why I would say it's not a module, right?

1161
01:13:01,560 --> 01:13:06,520
I would say that I'm looking at systems that are functionally uh

1162
01:13:07,000 --> 01:13:11,960
functionally specialized around the problems that people face with respect to plants.

1163
01:13:12,120 --> 01:13:15,240
And I'm you may also hear I'm also saying there's multiple, right?

1164
01:13:15,400 --> 01:13:19,400
So I don't think that there is just one problem with respect to plants.

1165
01:13:19,480 --> 01:13:24,750
And I also find just in thinking through doing the task analysis and what and making

1166
01:13:24,750 --> 01:13:30,750
predictions about the design that, and again, this is maybe where my approach to

1167
01:13:30,750 --> 01:13:35,870
this might be wrong and potentially leading me astray, but I find it easier to think about,

1168
01:13:35,950 --> 01:13:41,550
you know, this that there's at best there's sort of

1169
01:13:41,550 --> 01:13:47,150
subcomponents to the problem of plants, but more likely I think there are

1170
01:13:47,550 --> 01:13:53,240
these the that the problems, the adaptive problems, uh are to some degree

1171
01:13:53,400 --> 01:13:55,000
distinct within plants.

1172
01:13:55,080 --> 01:14:00,840
And I think there's also areas where the problem that I'm thinking of from the perspective

1173
01:14:00,840 --> 01:14:05,160
of being interested in plants is actually larger than just plants, right?

1174
01:14:05,480 --> 01:14:10,680
So, like there's there's a lot of things for foraging, for example, for plant foraging,

1175
01:14:10,760 --> 01:14:15,960
that there's probably actually a larger category of stationary resource foraging, which

1176
01:14:15,960 --> 01:14:21,330
would include things like honey, and it would include things like probably marine life,

1177
01:14:21,410 --> 01:14:22,930
aspects of marine life.

1178
01:14:23,490 --> 01:14:29,170
And so then a psychology designed for that is not really plant specific, but

1179
01:14:29,170 --> 01:14:31,330
plants, there would be a lot of overlap.

1180
01:14:31,650 --> 01:14:36,210
You could get to thinking about that psychology from starting with plants and then seeing

1181
01:14:36,210 --> 01:14:37,730
commonalities with other things.

1182
01:14:37,970 --> 01:14:43,090
So when I think about the systems that I'm studying, I really do think that it's a fuzzy

1183
01:14:43,090 --> 01:14:49,040
set of cognitive mechanisms that have overlap with

1184
01:14:49,040 --> 01:14:54,960
these other systems and other problems that are functionally

1185
01:14:54,960 --> 01:14:56,960
specialized for those problems.

1186
01:14:57,120 --> 01:15:00,880
And so in a way, it's an unsatisfying answer because it's complicated, right?

1187
01:15:00,960 --> 01:15:05,920
Like it basically comes down to it's complicated, but the way that I approach it in my

1188
01:15:05,920 --> 01:15:10,400
science and the way that I prefer, the way that I just like to think about it because I'm

1189
01:15:10,470 --> 01:15:15,830
interested in thinking about plants is I think kind of the plant problems first, right?

1190
01:15:16,070 --> 01:15:21,190
And then seeing that there is often overlap with other things.

1191
01:15:21,910 --> 01:15:22,070
Yeah.

1192
01:15:22,390 --> 01:15:28,310
Yeah, it's actually a beautiful example of how you wouldn't uh necessarily expect a

1193
01:15:28,310 --> 01:15:33,510
well-designed system for solving the problem of finding edible plants and avoiding toxic

1194
01:15:33,510 --> 01:15:33,750
plants.

1195
01:15:33,910 --> 01:15:38,980
You wouldn't expect that system to be fast automatic and encapsulated from the rest of

1196
01:15:38,980 --> 01:15:39,460
cognition.

1197
01:15:39,540 --> 01:15:42,820
In fact, if it was, it would serve its function extremely poorly.

1198
01:15:43,300 --> 01:15:46,020
You want to be open to other kinds of social information.

1199
01:15:46,180 --> 01:15:50,340
You want to be looking at the social cues you get, the the mental states that you can infer

1200
01:15:50,340 --> 01:15:52,820
other adults around you are having with regard to the plant.

1201
01:15:53,140 --> 01:15:56,580
If they're making a grossed-out face or a fearful face, that's going to be important

1202
01:15:56,580 --> 01:15:58,660
information that should feed into the system.

1203
01:15:58,980 --> 01:16:03,470
So there's a rich variety of information that should that this learning system should be

1204
01:16:03,470 --> 01:16:04,350
connected to.

1205
01:16:04,750 --> 01:16:07,630
And it doesn't necessarily need to be fast or automatic.

1206
01:16:08,590 --> 01:16:14,430
And what the the modularity, the Fodorian modularity

1207
01:16:14,430 --> 01:16:19,310
approach, I think, misleads us into doing is to thinking that

1208
01:16:19,630 --> 01:16:25,630
adaptations have one shape, or that they that uh instead of looking at what

1209
01:16:25,700 --> 01:16:28,980
is the actual problem that needs to be solved and what is the best way to solve it.

1210
01:16:29,300 --> 01:16:34,340
And then just abandoning all your preconceptions about what a good solution would be and

1211
01:16:34,340 --> 01:16:39,380
just and just looking at uh how how would you actually solve this in practice in a way that

1212
01:16:39,460 --> 01:16:40,980
that would be fitness promoting.

1213
01:16:42,420 --> 01:16:43,540
Yeah, that's exactly right.

1214
01:16:43,620 --> 01:16:46,580
That's like I mean we used to, Dave and I, I don't we've kind of moved away from this, but

1215
01:16:46,580 --> 01:16:47,860
we used to call that binning.

1216
01:16:48,020 --> 01:16:52,250
You know, like that it would like create it was like it's calling something module it like

1217
01:16:52,250 --> 01:16:57,210
puts it in the module calling something modular it puts it in the module bin and then by

1218
01:16:57,210 --> 01:17:02,890
virtue of being in the module bin then it has it entails all of these different criteria

1219
01:17:03,050 --> 01:17:07,530
and then people try to say well this thing you're claiming it's an adaptation and you're

1220
01:17:07,530 --> 01:17:12,010
saying there's a module and then so you have to show all of these things in photos list

1221
01:17:12,250 --> 01:17:17,300
right and as you said that's if from an adaptationist perspective that's just kind of the

1222
01:17:17,300 --> 01:17:20,900
wrong way to go about it because the form follows the functions.

1223
01:17:20,980 --> 01:17:26,740
So it's really thinking about what is the problem, what what are the design

1224
01:17:26,740 --> 01:17:32,180
features that could solve the problem, and then test for the presence of those design

1225
01:17:32,180 --> 01:17:32,580
features.

1226
01:17:32,660 --> 01:17:35,700
And if if there if there's evidence for them, great.

1227
01:17:35,860 --> 01:17:38,500
If there's not, then you've made an error somewhere along the way.

1228
01:17:38,580 --> 01:17:42,980
You can falsify your predictions and you can go back and really think about the structure

1229
01:17:43,190 --> 01:17:47,190
independent of kind of having to worry about whether you've ticked all the boxes for that

1230
01:17:47,190 --> 01:17:48,470
particular bin, right?

1231
01:17:48,630 --> 01:17:48,790
Yeah.

1232
01:17:49,670 --> 01:17:55,670
And it it another downside of this is that it it uh distracts us into having this really

1233
01:17:55,670 --> 01:17:59,670
silly and pointless debate about whether something counts as a module.

1234
01:17:59,830 --> 01:17:59,990
Yes.

1235
01:18:00,230 --> 01:18:04,550
Like that is the absolutely the wrong question that we should be asking and the wrong

1236
01:18:04,550 --> 01:18:05,910
debate to be having.

1237
01:18:06,070 --> 01:18:06,230
Yeah.

1238
01:18:06,470 --> 01:18:11,620
It's what we should be asking is how the mind works, how it solves the particular problems

1239
01:18:11,620 --> 01:18:16,420
that we know that our ancestors would have needed to solve to survive and reproduce, and

1240
01:18:16,420 --> 01:18:19,460
just going about and figuring out how those systems work.

1241
01:18:20,180 --> 01:18:25,300
Whether something you know fits some definition of a module is just the wrong question to

1242
01:18:25,300 --> 01:18:25,940
be asking.

1243
01:18:26,180 --> 01:18:27,380
And it's a distraction.

1244
01:18:27,700 --> 01:18:28,180
Exactly.

1245
01:18:28,340 --> 01:18:29,380
That's exactly right.

1246
01:18:29,540 --> 01:18:35,270
And and in in addition to that, with my work, the fact that what I'm predicting is an

1247
01:18:35,270 --> 01:18:41,030
evolved learning system is something that I hope is a

1248
01:18:41,030 --> 01:18:42,310
contribution of this work.

1249
01:18:42,390 --> 01:18:48,390
Because you have uh in in many areas of psychology, you have a misconception

1250
01:18:48,390 --> 01:18:51,270
that evolved things are somehow opposite.

1251
01:18:52,150 --> 01:18:54,070
Evolution is the opposite of learning, right?

1252
01:18:54,150 --> 01:18:56,070
That either it's evolved or it's learned.

1253
01:18:56,150 --> 01:19:01,750
And I think it does come in part from this Fodorian from a from

1254
01:19:01,750 --> 01:19:05,160
thinking that things follow Fodorian modularity, right?

1255
01:19:05,240 --> 01:19:09,400
So that there can't be learning if you have a Fodorian module.

1256
01:19:09,720 --> 01:19:15,320
But for an evolved system, there's no reason that part of the design can't be

1257
01:19:15,320 --> 01:19:15,800
learning.

1258
01:19:15,960 --> 01:19:18,280
And in fact, there should be learning here.

1259
01:19:18,440 --> 01:19:21,080
And then of course there's the whole you talk to Christina Moya.

1260
01:19:21,160 --> 01:19:25,800
I mean, there's the whole, you know, there's there's big research traditions within the

1261
01:19:25,800 --> 01:19:31,370
evolutionary social sciences about this, but it's not clear that um

1262
01:19:31,930 --> 01:19:37,610
that information makes it out into the wider world, the it or at least to

1263
01:19:37,850 --> 01:19:43,850
the the the the other scientific communities that I care very much about

1264
01:19:43,850 --> 01:19:49,210
and uh have a lot of contact with that you know evolution and learning are not in conflict.

1265
01:19:49,370 --> 01:19:51,450
Evolution can design a learning system.

1266
01:19:51,900 --> 01:19:52,220
Right.

1267
01:19:52,460 --> 01:19:54,060
And and even needs to, right?

1268
01:19:54,140 --> 01:19:59,260
I mean like even the point of just, you know, even just as David said, the specifics of the

1269
01:19:59,260 --> 01:20:00,060
plants, right?

1270
01:20:00,140 --> 01:20:06,140
And like your the whole point of your research is is is as you're saying is that uh and I

1271
01:20:06,140 --> 01:20:07,980
like what you're saying because there's like kind of two things.

1272
01:20:08,060 --> 01:20:09,820
One is like in its affordance base.

1273
01:20:10,060 --> 01:20:14,450
Like you know, as you talked about, like it's something can hurt you, you can eat it.

1274
01:20:14,530 --> 01:20:20,130
And so you're privileging all the ways to categorize a research program into what are

1275
01:20:20,130 --> 01:20:22,530
likely the evolutionarily relevant affordances.

1276
01:20:22,770 --> 01:20:27,010
And people just weren't looking at these things psychologically or developmentally.

1277
01:20:27,490 --> 01:20:31,090
But then it's also respecting the entity itself.

1278
01:20:31,330 --> 01:20:34,210
And plants have just have specific properties, right?

1279
01:20:34,450 --> 01:20:39,880
And so that combination of like respecting the entity and its properties and the

1280
01:20:39,880 --> 01:20:41,880
affordances that are evolutionary.

1281
01:20:41,960 --> 01:20:46,920
It's that combination that I think it's it's very striking that that's sort of like the

1282
01:20:46,920 --> 01:20:48,520
north star of the work you're doing.

1283
01:20:48,600 --> 01:20:50,120
And it's really interesting.

1284
01:20:50,360 --> 01:20:53,480
You alluded to some of the affordances or like the different systems.

1285
01:20:53,640 --> 01:20:57,800
Like what do humans, for people who might not have thought about this, like what do humans

1286
01:20:57,800 --> 01:21:03,650
use plants for other than food and occasionally failing to misidentify

1287
01:21:03,650 --> 01:21:05,730
a toxic plant and sources of death.

1288
01:21:06,130 --> 01:21:10,290
Like so, other than like having a full stomach or dying, what else do plants provide

1289
01:21:10,290 --> 01:21:10,530
people?

1290
01:21:10,690 --> 01:21:14,370
I mean, I I know I'm sure people have some intuition, but maybe not, especially if they're

1291
01:21:14,370 --> 01:21:18,530
not talking to like human behavioral ecologists who are out in the out in the world.

1292
01:21:18,690 --> 01:21:19,170
Um yeah.

1293
01:21:19,650 --> 01:21:19,810
Yeah.

1294
01:21:19,890 --> 01:21:23,730
I mean, if you're thinking about humans in a hunter-gatherer world and you're thinking

1295
01:21:23,730 --> 01:21:29,720
about um making a living in a world where you need to gather all of your food,

1296
01:21:29,880 --> 01:21:35,800
you need to get all of your food, and also you need to make all the stuff that enables your

1297
01:21:35,800 --> 01:21:36,440
life.

1298
01:21:36,920 --> 01:21:38,920
Plants are a huge part of that as well.

1299
01:21:39,160 --> 01:21:44,120
So plants are a huge part of human material culture.

1300
01:21:44,680 --> 01:21:50,600
Plants don't fossilize, which is, or they don't fossilize, they don't fossilize the

1301
01:21:50,600 --> 01:21:51,240
same way.

1302
01:21:51,320 --> 01:21:55,890
They are preserved in the archaeological record in the same way a lot of other things are

1303
01:21:56,050 --> 01:22:01,810
so things like um things like ropes and baskets and

1304
01:22:01,810 --> 01:22:07,650
clothing and uh and um like shelters and the

1305
01:22:08,210 --> 01:22:14,210
uh you know you see all this you you see all of the spear points but you're missing like

1306
01:22:14,210 --> 01:22:19,940
the wooden spear right that's uh that that the the the point

1307
01:22:20,020 --> 01:22:21,700
made it, but the spirit didn't.

1308
01:22:22,020 --> 01:22:27,140
And when you read, when you read the literature, the people who are looking and the

1309
01:22:27,140 --> 01:22:30,660
archaeological record for plants, this is something that comes up a lot.

1310
01:22:31,060 --> 01:22:36,500
That you have these issues of like it just can be, it's not preserved in the same way.

1311
01:22:36,660 --> 01:22:42,580
But if you look at modern populations and people living in societies

1312
01:22:42,580 --> 01:22:48,550
today that still use subsistence practices that include hunting and gathering and

1313
01:22:48,550 --> 01:22:51,270
small scale, small-scale horticulture.

1314
01:22:51,510 --> 01:22:55,270
You see, plants are used to build all kinds of different things.

1315
01:22:55,350 --> 01:22:58,390
They're also used for their underlying chemical properties.

1316
01:22:58,630 --> 01:23:04,230
So there's a lot of kind of medicinal plant use, and there's a lot of using plants for

1317
01:23:04,230 --> 01:23:10,180
ritual things and making dyes and making face paints and making uh like

1318
01:23:10,500 --> 01:23:13,060
making making the things you make pretty.

1319
01:23:13,220 --> 01:23:18,580
Uh so there's kind of like these function uh uh it's maybe it's not right to call it

1320
01:23:18,580 --> 01:23:24,580
exactly functional uses versus versus more kind of decorative uses, but

1321
01:23:24,580 --> 01:23:26,420
there is that as well.

1322
01:23:26,580 --> 01:23:30,100
Um so yeah, plants get used for pretty much everything.

1323
01:23:30,260 --> 01:23:35,710
Um yeah, interesting folk uh chemistry, or maybe not even folk chemistry, just sort of

1324
01:23:35,710 --> 01:23:36,430
different cultural.

1325
01:23:36,750 --> 01:23:38,510
I mean, that's a really interesting thing.

1326
01:23:38,990 --> 01:23:39,150
Yeah.

1327
01:23:39,230 --> 01:23:43,950
I mean, going back to Mike Gervin, like they one of the things that uh the Chimane use is

1328
01:23:43,950 --> 01:23:48,430
they um use uh uh they do barbosco fishing.

1329
01:23:48,590 --> 01:23:54,220
So it's you there's a plant that you use that you poison the river

1330
01:23:54,540 --> 01:23:59,820
with the plant and then that kills the fish and you uh you get the fish out of the river.

1331
01:24:00,300 --> 01:24:04,940
So uh you're there are um and you can eat them meat, right?

1332
01:24:05,020 --> 01:24:06,460
Like that's important too, right?

1333
01:24:06,540 --> 01:24:12,140
It kills the fish in a particular way such that you don't I I think that they they

1334
01:24:12,140 --> 01:24:14,430
suffocate Yes, they suffocate it.

1335
01:24:14,750 --> 01:24:18,910
But it doesn't like it stops the oxygen oxygen uptake in the gills, I think, or something.

1336
01:24:19,470 --> 01:24:21,790
But I mean it's just such an a a lovely example, right?

1337
01:24:21,870 --> 01:24:24,910
Of like, you know, it's so improbable.

1338
01:24:25,070 --> 01:24:29,630
And it is across this diffuse like trial and error um thing, or just like, you know, social

1339
01:24:29,630 --> 01:24:30,750
learning as you're putting it.

1340
01:24:30,910 --> 01:24:34,840
But I just love that example of like even the way it kills the fish, you know.

1341
01:24:35,080 --> 01:24:38,760
Somebody I guess had to take that first little bite, you know, to be like, I guess it's

1342
01:24:38,760 --> 01:24:39,000
okay.

1343
01:24:39,080 --> 01:24:39,320
Yeah.

1344
01:24:39,560 --> 01:24:40,200
Yeah.

1345
01:24:41,560 --> 01:24:47,320
But yeah, so and and people use uh uh plant toxins to poison

1346
01:24:47,320 --> 01:24:49,160
arrows for hunting.

1347
01:24:49,400 --> 01:24:55,160
Um, so I mean it we are an ingenious bunch, us humans, and people

1348
01:24:55,160 --> 01:24:56,590
exploit plants.

1349
01:24:56,750 --> 01:25:02,670
Uh even you have a plant that part of it is toxic, part of it is edible, the edible part is

1350
01:25:02,670 --> 01:25:04,990
eaten, the toxic part is used for something else.

1351
01:25:05,550 --> 01:25:05,790
Interesting.

1352
01:25:05,950 --> 01:25:10,350
But there's also interesting things about for when you look at the kinds of plants that are

1353
01:25:10,350 --> 01:25:10,830
eaten.

1354
01:25:11,070 --> 01:25:16,830
There uh this um this literature, maybe Ed Hagen might know, probably knows

1355
01:25:16,830 --> 01:25:22,440
more about this than than I do, but the number of edible plants that or the number of

1356
01:25:22,440 --> 01:25:28,120
plants that are in fact edible in an environment is usually a lot higher than the set of

1357
01:25:28,120 --> 01:25:30,920
plants that people in that particular environment eat.

1358
01:25:32,360 --> 01:25:38,120
And what I'm uh and so you could think about that that's kind of that could be evidence for

1359
01:25:38,120 --> 01:25:41,800
these social learning systems like shunting people in particular ways.

1360
01:25:42,360 --> 01:25:48,070
There's probably also the uh the the kind of cultural learning, cultural

1361
01:25:48,070 --> 01:25:53,910
evolution part of specializing in the plants that end up having the highest nutritional

1362
01:25:53,910 --> 01:25:55,990
yield over time.

1363
01:25:56,070 --> 01:26:02,070
And so there's, I think there's something very interesting there to be

1364
01:26:02,070 --> 01:26:03,030
dug into.

1365
01:26:04,470 --> 01:26:09,350
That yeah, it's one of the one of the things in my bin of at some point I'm really

1366
01:26:09,350 --> 01:26:11,750
interested in looking into what's going on with that.

1367
01:26:12,200 --> 01:26:12,440
Yeah.

1368
01:26:12,600 --> 01:26:16,280
And that's also a reason, I mean, just talking about like the the stuff that you can eat,

1369
01:26:16,360 --> 01:26:19,240
the other materials could be used for like material construction.

1370
01:26:19,320 --> 01:26:22,920
That would be another reason for it to not be modular in this quote unquote encapsulated

1371
01:26:22,920 --> 01:26:26,760
way, which is that as you're interfacing with this object, what are all the other

1372
01:26:26,760 --> 01:26:32,680
affordances sort of as a byproduct, you know, as like you're just like tearing apart this

1373
01:26:32,680 --> 01:26:38,650
thing to to get the food, well, what are the other things that could this thing

1374
01:26:38,650 --> 01:26:39,530
could afford, right?

1375
01:26:39,610 --> 01:26:43,210
Like I mean, evolved organisms are really non-entropic.

1376
01:26:43,450 --> 01:26:49,450
And so plants, you know, like I'm I guess I mean like I'm sitting on a wooden building,

1377
01:26:49,530 --> 01:26:50,650
you know, essentially, right?

1378
01:26:50,730 --> 01:26:53,930
Like, you know, like we're many of us, like David, would fall through the floor right now

1379
01:26:53,930 --> 01:26:59,160
if it wasn't for the fact that trees um, you know, have selection pressures to like grow

1380
01:26:59,160 --> 01:26:59,720
tall, right?

1381
01:26:59,800 --> 01:27:01,160
And that's what makes wood strong.

1382
01:27:01,320 --> 01:27:04,760
So like there's there's all these I don't think this is wood.

1383
01:27:06,040 --> 01:27:11,480
I realized yeah I'm I I I'm actually realizing this is like a veneered uh

1384
01:27:12,680 --> 01:27:14,360
I mean we we have similar offices.

1385
01:27:14,600 --> 01:27:15,080
I don't know.

1386
01:27:15,160 --> 01:27:16,200
Maybe the door is wooden.

1387
01:27:16,440 --> 01:27:22,360
But I mean but yeah but the point is right and this is where I think one of

1388
01:27:22,360 --> 01:27:28,210
the so because I was starting with infants, and because I wanted to start with the

1389
01:27:28,210 --> 01:27:32,930
very, very basic questions of looking at uh

1390
01:27:33,250 --> 01:27:37,330
avoiding danger, learning that it could be eaten.

1391
01:27:37,570 --> 01:27:43,170
There's this whole category of thing of uh how do plants intersect with artifact psychology

1392
01:27:43,250 --> 01:27:47,170
and actually the building and making of artifacts, because artifact psychology is very

1393
01:27:47,170 --> 01:27:48,130
interesting.

1394
01:27:48,700 --> 01:27:54,700
that it it was something that again that had that was a big research focus in the late

1395
01:27:54,700 --> 01:28:00,140
90s early 2000s is a really fascinating um topic it's kind of

1396
01:28:00,140 --> 01:28:06,060
fallen out of the out it's fallen by the wayside a bit um in the scientific

1397
01:28:06,060 --> 01:28:11,530
literature but it's really interesting to think about how plants factor into

1398
01:28:11,530 --> 01:28:16,570
artifact psychology and how using materials from plants, and also this is an area where

1399
01:28:16,570 --> 01:28:18,010
this is wider than plants, right?

1400
01:28:18,090 --> 01:28:23,290
If you've killed an animal and you are butchering the animal for meat, you also see all of

1401
01:28:23,290 --> 01:28:28,410
these parts inside of that thing that you can use and people do use for all kinds of

1402
01:28:28,410 --> 01:28:29,210
different things.

1403
01:28:29,370 --> 01:28:34,650
And so this is where the overlap between I think about it from plants, but if you're

1404
01:28:34,650 --> 01:28:40,480
thinking about how to build artifacts and the psychology for building material culture in

1405
01:28:40,480 --> 01:28:45,920
a hunter-gatherer world, there's probably a huge overlap in that between plants and animals

1406
01:28:46,000 --> 01:28:48,160
and in how that psychology is set up.

1407
01:28:48,240 --> 01:28:49,920
Um it'd be very interesting to look at.

1408
01:28:50,160 --> 01:28:50,240
Yeah.

1409
01:28:50,480 --> 01:28:54,080
It's a very cool way to think about like our evolved architecture where it's sort of like

1410
01:28:54,160 --> 01:28:58,320
we have this, I mean I at least have this idea sort of even now, like of sort of, you know,

1411
01:28:58,400 --> 01:29:01,680
like there's people who specialize in like carpentry or there's like chemists or

1412
01:29:01,680 --> 01:29:05,610
physicists, you know, and like there's just these different things, but like, you know, we

1413
01:29:05,610 --> 01:29:09,930
have software for doing chemistry and physical construction and like thinking about

1414
01:29:09,930 --> 01:29:10,490
artifacts.

1415
01:29:10,570 --> 01:29:14,330
And you know, if you I think if you watch kids or like even think about like I love playing

1416
01:29:14,330 --> 01:29:18,410
with like I even like randomly, I don't know if you guys did this, but like when I would

1417
01:29:18,410 --> 01:29:21,450
talk to my friends and I would just be out in the woods, I would just like grab a stick and

1418
01:29:21,450 --> 01:29:22,810
just peel the bark off randomly.

1419
01:29:22,890 --> 01:29:27,690
Like it's almost like there's this placeholder for like processing plants as just one of

1420
01:29:27,690 --> 01:29:32,010
the repertoire behavioral motor repertoires of what we do, even to the point where I'll

1421
01:29:32,010 --> 01:29:34,640
just do it even when it's for no purpose.

1422
01:29:35,120 --> 01:29:39,680
It's just, it's such an interesting thing to think about where there is this just

1423
01:29:40,080 --> 01:29:46,000
discrepancy between sort of this job has been taken care of for us by the division

1424
01:29:46,000 --> 01:29:50,560
of labor in a modern environment, but yet the software still exists in us.

1425
01:29:50,720 --> 01:29:56,490
And maybe to the extent we don't understand it, we're actually possibly not

1426
01:29:56,490 --> 01:29:58,330
doing as well as we could be.

1427
01:29:58,410 --> 01:30:00,490
Um, you know, like that's that's another thing.

1428
01:30:00,650 --> 01:30:03,850
I know you're starting to think about also like food and nutrition.

1429
01:30:04,090 --> 01:30:04,330
Yes.

1430
01:30:04,490 --> 01:30:09,690
And just also like there there are consequences of this mismatch that are both health and

1431
01:30:09,690 --> 01:30:11,290
physical and also maybe mental.

1432
01:30:11,530 --> 01:30:13,770
Can you maybe talk a little bit about that?

1433
01:30:14,330 --> 01:30:14,570
Yeah.

1434
01:30:14,730 --> 01:30:20,410
I mean, I think one of the what you describe of being a kid and walking through the woods

1435
01:30:20,570 --> 01:30:26,200
and actually engaging with plants and with the with with the natural world

1436
01:30:26,200 --> 01:30:27,160
around you.

1437
01:30:27,400 --> 01:30:33,160
That's kind of the being immersed in the natural world and growing up, having

1438
01:30:33,160 --> 01:30:39,160
this rich first-person experience, not only with the natural world, but with watching

1439
01:30:39,160 --> 01:30:44,840
other people who have this rich knowledge, manufacturing the kinds of things you need to

1440
01:30:44,840 --> 01:30:49,960
survive, getting the food you need to survive, processing the food you need to survive.

1441
01:30:50,190 --> 01:30:53,230
All of those things are things we're just really missing.

1442
01:30:54,110 --> 01:30:59,870
And it it with respect to food, the way that I have looked at

1443
01:30:59,950 --> 01:31:05,950
um uh plant edibility so far with babies is largely with showing

1444
01:31:05,950 --> 01:31:07,150
them an adult.

1445
01:31:07,310 --> 01:31:13,310
Sometimes it's been Dave acting in my stimuli, but then after Dave it was my my students

1446
01:31:13,310 --> 01:31:14,030
in Berlin.

1447
01:31:14,190 --> 01:31:19,860
Um, but uh but picking a piece of fruit off of a plant and sticking it in the mouth,

1448
01:31:20,020 --> 01:31:20,260
right?

1449
01:31:20,340 --> 01:31:22,820
And that is a cue of edibility.

1450
01:31:22,980 --> 01:31:28,900
Um, and it seems to be something that uh plants are selectively seen as edible, even

1451
01:31:28,900 --> 01:31:34,100
if you if you show babies somebody eating a piece of fruit off of a plant and then eating a

1452
01:31:34,100 --> 01:31:38,420
similar thing off of a human-made object, they'll make the inference that the plant is

1453
01:31:38,420 --> 01:31:40,980
edible, um, even though the action is the same.

1454
01:31:41,140 --> 01:31:46,630
So the social information is uh is is uh is processed

1455
01:31:46,630 --> 01:31:50,710
differently when depending on what is being acted upon.

1456
01:31:50,870 --> 01:31:55,110
Um but the thing about plants it's true that there are plants that where you can pick stuff

1457
01:31:55,110 --> 01:31:59,030
off of it and eat it but like I was talking about earlier there's a lot of plants where you

1458
01:31:59,030 --> 01:32:03,580
can't eat it until you do a lot of other things to it first.

1459
01:32:03,980 --> 01:32:09,740
And so not only do you as a human need to learn that this plant is edible,

1460
01:32:09,980 --> 01:32:14,860
you also need to learn all of the things you need to do to make it edible in order to feed

1461
01:32:14,860 --> 01:32:18,380
yourself and your family and the other people in your community.

1462
01:32:18,620 --> 01:32:24,380
And so oftentimes babies are just like along for the ride for foraging,

1463
01:32:24,540 --> 01:32:24,700
right?

1464
01:32:25,100 --> 01:32:28,220
They're when they're really little, they're carried along for foraging.

1465
01:32:28,540 --> 01:32:33,890
When uh children get a little bit older, they are tend to be kind of

1466
01:32:33,890 --> 01:32:39,810
together in these um uh multi-age groups of kids running around,

1467
01:32:39,970 --> 01:32:44,850
but there's still those little groups of kids go out and do their own foraging.

1468
01:32:45,010 --> 01:32:50,690
Um uh Karen Kramer gave a great talk at uh CWES recently at the at a

1469
01:32:50,690 --> 01:32:56,530
conference we we had here recently detailing all the ways that kids do this kind

1470
01:32:56,530 --> 01:32:57,490
of foraging.

1471
01:32:57,570 --> 01:33:01,760
Um, that I would encourage people to go look up what Karen Kramer has written about this.

1472
01:33:02,240 --> 01:33:08,160
And also people like uh Sheena Lou Levy is working on

1473
01:33:08,160 --> 01:33:08,320
this.

1474
01:33:08,480 --> 01:33:10,320
There's really, there's really great work.

1475
01:33:10,400 --> 01:33:15,200
And Barry Hewlett, of course, has all of this work on hunter-gatherer, children and

1476
01:33:15,200 --> 01:33:15,760
childhoods.

1477
01:33:15,840 --> 01:33:21,520
And that was something that had not been a big focus of the research for a while.

1478
01:33:22,320 --> 01:33:28,150
But it there now is starting to be some very, very interesting great

1479
01:33:28,150 --> 01:33:30,390
work looking at what kids actually do.

1480
01:33:30,790 --> 01:33:36,230
And this also includes that they're doing it themselves with their multi-age peers, but

1481
01:33:36,230 --> 01:33:41,830
they're also around while their parents are processing these various food items.

1482
01:33:42,070 --> 01:33:47,990
And so what my work suggests is the littlest babies, their initial response to

1483
01:33:47,990 --> 01:33:50,390
unknown plants is to kind of avoid them, right?

1484
01:33:50,870 --> 01:33:56,740
As a way of avoiding exposure to these potentially dangerous toxins until

1485
01:33:56,740 --> 01:33:59,780
they have some information about how to proceed.

1486
01:34:00,420 --> 01:34:06,260
But if you have this psychology that's basically like, just don't engage

1487
01:34:06,260 --> 01:34:10,500
with this thing until you have the social information that it's safe, until you have the

1488
01:34:10,500 --> 01:34:12,100
social information that it's edible.

1489
01:34:12,500 --> 01:34:16,580
If you're in a world where you're not getting the social information in the correct form

1490
01:34:16,660 --> 01:34:21,250
that this thing is safe and this thing is edible, it leads you to places like we see a lot

1491
01:34:21,330 --> 01:34:25,090
where you have a lot of very young kids who will not touch vegetables.

1492
01:34:25,250 --> 01:34:25,730
Right.

1493
01:34:26,370 --> 01:34:32,050
Um, and you that it's a it's a big struggle, and it makes sense that you would have kids

1494
01:34:32,690 --> 01:34:36,770
as they are developing their own motor skills and their own independence.

1495
01:34:36,850 --> 01:34:41,170
Um, this is what Liz Cashton talked about that it would make sense that you would ramp up

1496
01:34:41,170 --> 01:34:46,050
this neophobia, this food neophobia for these potentially dangerous things in the

1497
01:34:46,050 --> 01:34:47,010
environment.

1498
01:34:47,520 --> 01:34:53,120
but in hunter-gatherer kinds of situations, in these small-scale societies in which our

1499
01:34:53,120 --> 01:34:58,800
brains evolved, you would see the information that would show you, no, no, this is the

1500
01:34:58,800 --> 01:34:58,960
thing.

1501
01:34:59,120 --> 01:35:00,720
Like this, this is the thing we're processing.

1502
01:35:00,800 --> 01:35:02,240
This is the thing that everybody's eating.

1503
01:35:02,320 --> 01:35:03,920
This is the thing that's being gathered.

1504
01:35:04,160 --> 01:35:08,480
And the way we feed kids today, you know, we basically like plunk them down at a table and

1505
01:35:08,480 --> 01:35:14,010
we give them food that's already prepared that just looks like like messes of colors and

1506
01:35:14,010 --> 01:35:19,050
shapes and oftentimes it's different than what the adult is eating uh because it's the kid

1507
01:35:19,050 --> 01:35:21,130
food as opposed to the adult food.

1508
01:35:21,210 --> 01:35:25,130
Um and you know they haven't seen how it gets there.

1509
01:35:25,210 --> 01:35:27,770
And you're like, no no trust me, it's food, just eat it.

1510
01:35:27,850 --> 01:35:33,450
And you end up fighting this battle of getting a small child to accept something where

1511
01:35:33,840 --> 01:35:38,640
potentially from their mechanisms perspectives, they're like, why are you feeding me

1512
01:35:38,640 --> 01:35:39,200
poison?

1513
01:35:39,440 --> 01:35:40,000
Right.

1514
01:35:40,480 --> 01:35:46,480
So uh so there's this is one of the the areas now I'm almost have

1515
01:35:46,480 --> 01:35:49,440
my lab built here in uh Santa Barbara.

1516
01:35:49,520 --> 01:35:53,440
And one of the things that I'm very interested in doing going forward is to really start

1517
01:35:53,440 --> 01:35:59,230
unpacking what are the what is the entirety of the set of cues of

1518
01:35:59,230 --> 01:36:02,270
food learning, of how something becomes food.

1519
01:36:02,590 --> 01:36:07,070
And this is some work that I've already started doing with my former postdoc and now

1520
01:36:07,070 --> 01:36:12,830
collaborator Camille Rioux, who uh is uh who is in a

1521
01:36:12,830 --> 01:36:15,310
research center in Dijon in France.

1522
01:36:15,550 --> 01:36:20,960
Um She and I have started looking, doing some initial work looking at food

1523
01:36:20,960 --> 01:36:26,880
processing and how infants respond to signals that somebody

1524
01:36:26,880 --> 01:36:29,520
has uh it previously interacted with the food.

1525
01:36:29,600 --> 01:36:34,160
And we have a paper we're working on getting out the door now with my uh former PhD

1526
01:36:34,160 --> 01:36:39,600
student, Karula Schlegelmilch, and former postdoc as well, um, looking at what babies do

1527
01:36:39,680 --> 01:36:44,850
when they actually see somebody cutting up a novel plant food with a knife versus eating it

1528
01:36:45,010 --> 01:36:50,690
versus a control action of just touching it, but not in a way that processes it.

1529
01:36:51,090 --> 01:36:51,410
Interesting.

1530
01:36:51,570 --> 01:36:56,210
I another question I would be interested in is if once they see an adult preparing a

1531
01:36:56,210 --> 01:37:01,330
particular food, um, do they generalize to other adults or do they want that same adult to

1532
01:37:01,330 --> 01:37:02,130
prepare the food?

1533
01:37:02,370 --> 01:37:06,380
Because I have this problem with my daughter Whenever I I bring her food, she says, No, I

1534
01:37:06,380 --> 01:37:07,020
want Mama to do it.

1535
01:37:07,180 --> 01:37:08,540
I want Mama to put me the milk.

1536
01:37:11,100 --> 01:37:11,980
Is it though, David?

1537
01:37:12,060 --> 01:37:14,460
Are you is it is she saying you're bad cook?

1538
01:37:14,620 --> 01:37:15,980
Or are you just cutting out carrots?

1539
01:37:16,060 --> 01:37:17,260
Maybe you're bad cutting a sun.

1540
01:37:17,660 --> 01:37:22,060
Presumably at some point she saw, you know, my wife preparing the food and she and she knew

1541
01:37:22,060 --> 01:37:24,220
that like she didn't die when she ate that food.

1542
01:37:24,300 --> 01:37:26,140
So she's not gonna take a risk on me, I guess.

1543
01:37:26,220 --> 01:37:26,780
I don't know.

1544
01:37:27,980 --> 01:37:28,540
I don't know.

1545
01:37:28,700 --> 01:37:31,710
She she might have things to say about the your cooking house.

1546
01:37:34,190 --> 01:37:35,870
No, but it is it is really interesting.

1547
01:37:35,950 --> 01:37:40,430
I mean, and this is um my colleague here, Zoe Liberman, has been looking at social

1548
01:37:40,510 --> 01:37:42,670
inferences based on food, right?

1549
01:37:42,750 --> 01:37:48,590
Like so based on what people eat, but it is in and it's very clear that because for

1550
01:37:48,590 --> 01:37:53,790
humans food is social, there are a lot of social inferences that you can make based off of

1551
01:37:53,790 --> 01:37:57,220
what people are eating and food sharing and things like this.

1552
01:37:57,540 --> 01:38:02,980
And Ashley Thomas has some work touching on this as well of people who are like

1553
01:38:03,300 --> 01:38:07,380
uh uh well, people who are getting like their saliva and food and things like that.

1554
01:38:07,540 --> 01:38:12,980
But um but uh but it would be fascinating to actually look at

1555
01:38:13,620 --> 01:38:18,660
what happens when you have different kinds of people giving different kinds of information

1556
01:38:18,660 --> 01:38:19,300
about food.

1557
01:38:19,460 --> 01:38:25,310
And you might you could expect, for example, that something about information about whether

1558
01:38:25,310 --> 01:38:30,350
something is toxic or not, it might not matter who's telling you that, right?

1559
01:38:30,830 --> 01:38:36,190
So like if somebody who's, you know, somebody who is in some kind of

1560
01:38:36,190 --> 01:38:42,110
outgroup role for for lack of a better term tells you you will die if you eat

1561
01:38:42,110 --> 01:38:45,340
this thing, you might just accept that information no matter what.

1562
01:38:45,500 --> 01:38:51,500
But if it's something more something more nuanced about how a food is prepared or

1563
01:38:51,740 --> 01:38:56,540
um or something about how you build a particular artifact, something something like that,

1564
01:38:56,700 --> 01:39:00,300
that might matter a lot, who it is that's telling you what's going on there.

1565
01:39:00,460 --> 01:39:03,500
So yeah, it would be that's something that would be fascinating to look at.

1566
01:39:03,820 --> 01:39:05,170
We'll eat your cooking, David.

1567
01:39:06,290 --> 01:39:06,530
Okay, good.

1568
01:39:06,690 --> 01:39:07,490
That'll make me feel better.

1569
01:39:07,650 --> 01:39:10,450
Because uh yeah, my daughter has insulted me uh one too many times.

1570
01:39:10,610 --> 01:39:12,450
So I could use an ego boost.

1571
01:39:12,770 --> 01:39:17,810
Um another thing that occurred to me um, have you thought about how emotions might

1572
01:39:17,810 --> 01:39:19,010
interface with this system?

1573
01:39:19,250 --> 01:39:23,410
Because as I've been reflecting on this, it seems like this would be, you know, a really

1574
01:39:23,410 --> 01:39:28,130
good domain for disgust to be involved in because this is you know a contaminant, it could

1575
01:39:28,130 --> 01:39:30,530
involve toxins and poisons and make you sick.

1576
01:39:30,690 --> 01:39:34,680
Uh, but just reflecting on it in terms of the phenomenology of it, it's disgust isn't

1577
01:39:34,680 --> 01:39:38,840
really the emotion I feel when I think about a toxic plant.

1578
01:39:39,240 --> 01:39:43,960
It is not really analogous at all to when I think about like rotting garbage or feces or or

1579
01:39:44,040 --> 01:39:45,480
or something or rotting meat.

1580
01:39:46,600 --> 01:39:48,280
Which is really interesting to me.

1581
01:39:48,360 --> 01:39:53,480
And it and it ties into what you were saying before about all the different things that we

1582
01:39:53,480 --> 01:39:57,720
use plants for, you know, for making tools, for preparing food, even for hunting in some

1583
01:39:57,720 --> 01:39:58,360
cases.

1584
01:39:58,750 --> 01:40:04,110
So given that we depend on plants for so many different purposes, it kind of makes a

1585
01:40:04,110 --> 01:40:08,270
functional sense that we wouldn't feel disgust necessarily toward a plant.

1586
01:40:08,350 --> 01:40:12,830
I mean, you do want to feel caution and a certain amount of fear about, you know, not uh

1587
01:40:12,830 --> 01:40:14,910
engaging with the plant in a way that might make you sick.

1588
01:40:15,070 --> 01:40:20,830
But it seems like disgust might be too coarse grained of an emotion to apply to plants

1589
01:40:20,830 --> 01:40:24,910
because you don't want to necessarily avoid the plant at all times and keep keep your

1590
01:40:24,910 --> 01:40:26,510
distance from it in every way possible.

1591
01:40:26,670 --> 01:40:30,840
You might just want to avoid eating it, say, or or engaging with a particular part of it,

1592
01:40:31,080 --> 01:40:33,160
say, but you might want to use it for these other purposes.

1593
01:40:33,320 --> 01:40:38,920
So it it may be that um there there's a reason why disgust is not coming online when it

1594
01:40:38,920 --> 01:40:42,360
comes to plants and it's more of just a kind of caution or fear.

1595
01:40:42,520 --> 01:40:44,680
Uh have have you thought about that in any way?

1596
01:40:45,080 --> 01:40:45,640
Yeah, I have.

1597
01:40:45,720 --> 01:40:46,440
And I think you're right.

1598
01:40:46,600 --> 01:40:52,050
I think I think it's I mean, so to preface this by we have not

1599
01:40:52,050 --> 01:40:53,570
tested this yet.

1600
01:40:53,810 --> 01:40:57,010
So to try to distinguish between these things empirically.

1601
01:40:57,410 --> 01:41:03,330
Um, but what what my the way that I think about it is that

1602
01:41:03,490 --> 01:41:08,930
what makes sense for plants is basically just an avoidance, right?

1603
01:41:09,090 --> 01:41:13,260
It's not it's i I mean, watching the kids, it looks like boredom.

1604
01:41:13,500 --> 01:41:17,340
It looks like they kind of want to do anything else other than be there.

1605
01:41:17,500 --> 01:41:22,940
They're like curious, but they're looking at the person, you know, but it's not like I

1606
01:41:22,940 --> 01:41:28,460
don't see any evidence of them exhibiting a disgust reaction to plants.

1607
01:41:28,700 --> 01:41:34,540
I also don't think that fear per se is necessarily involved

1608
01:41:34,780 --> 01:41:40,570
because fear seems like the kind of thing that you would want to have for like a snake or a

1609
01:41:40,570 --> 01:41:44,490
spider, something that you need to like get up and move away from.

1610
01:41:44,730 --> 01:41:48,410
It's not clear that being afraid of a plant per se is necessary.

1611
01:41:48,570 --> 01:41:52,570
It really, I think, is this is why I talk about it as an avoidance mechanism.

1612
01:41:52,650 --> 01:41:58,100
It really is just as far as I am aware, um it's an avoidance, right?

1613
01:41:58,260 --> 01:42:00,180
It's like an and a caution, right?

1614
01:42:00,260 --> 01:42:03,220
And it particularly as you say, there's different parts of a plant.

1615
01:42:03,300 --> 01:42:09,140
So there's lots of plants that you have like raspberries or

1616
01:42:09,140 --> 01:42:12,100
blackberries or any of those kind of brambly plants.

1617
01:42:12,340 --> 01:42:17,460
You have to be very careful with how you go in and pick those fruits, but the fruits

1618
01:42:17,460 --> 01:42:19,380
themselves you don't have to be cautious of.

1619
01:42:19,460 --> 01:42:22,420
But the broader plant you have to exhibit caution around.

1620
01:42:22,660 --> 01:42:25,250
Yeah, I mean it's almost a a a a distinct emotion.

1621
01:42:25,410 --> 01:42:27,250
Like it's not disgust, it's not fear.

1622
01:42:27,410 --> 01:42:29,730
It really is this this caution state.

1623
01:42:29,810 --> 01:42:33,970
And and it would be interesting to look at that as a distinct emotional profile and how it

1624
01:42:33,970 --> 01:42:35,810
could be differentiated from fear and disgust.

1625
01:42:36,210 --> 01:42:36,450
Yeah.

1626
01:42:37,010 --> 01:42:37,730
I totally agree.

1627
01:42:37,890 --> 01:42:38,530
I totally agree.

1628
01:42:38,610 --> 01:42:42,850
And I mean I think in taking kind of a step back and thinking about the broader thing with

1629
01:42:42,850 --> 01:42:48,610
plant learning, the way I think about that is that it's gonna likely be a

1630
01:42:48,610 --> 01:42:50,850
largely observational system.

1631
01:42:51,200 --> 01:42:51,520
right?

1632
01:42:51,760 --> 01:42:57,360
So especially with what we what the literature says about the way that social

1633
01:42:57,760 --> 01:43:03,680
or the way that um kind of teaching unfolds in small-scale societies is

1634
01:43:03,760 --> 01:43:09,360
you know, this is some of the work of people like Michelle Klein, but um you you don't see

1635
01:43:09,600 --> 01:43:11,440
necessarily explicit teaching.

1636
01:43:11,520 --> 01:43:17,280
You don't see a lot of the kind of pedagogical stance uh that you see in is certainly in

1637
01:43:17,280 --> 01:43:22,470
the way we do things in the US and uh and in uh in other kind of

1638
01:43:22,630 --> 01:43:25,910
westernized cultures for lack of a better term.

1639
01:43:27,190 --> 01:43:33,030
But uh instead, what you see is that there's often kind of subtle changes that people make

1640
01:43:33,030 --> 01:43:36,790
when they know they have a naive learner who's there observing them.

1641
01:43:36,950 --> 01:43:42,230
Um, and so it could be that in some cases, maybe for some of the things around food

1642
01:43:42,230 --> 01:43:48,020
preparation or around artifact building, you would have kids just observing what the

1643
01:43:48,020 --> 01:43:51,700
adults or the older kids are doing when they're making these things.

1644
01:43:51,940 --> 01:43:57,300
They're not really being taught in any sort of specific way, but maybe the person is kind

1645
01:43:57,300 --> 01:44:00,980
of adjusting a little bit, the model is kind of adjusting a little bit what they're doing.

1646
01:44:01,140 --> 01:44:06,100
If it's a foraging thing and a baby's along, maybe the people who are going foraging aren't

1647
01:44:06,100 --> 01:44:08,740
bothering to do anything differently, but the baby's still there.

1648
01:44:08,820 --> 01:44:14,210
And so you can have the learning systems kind of like um like kind of zero in on

1649
01:44:14,530 --> 01:44:16,690
the relevant information, right?

1650
01:44:16,770 --> 01:44:22,370
And that was a lot of the basis behind uh why I was testing, are they particularly vigilant

1651
01:44:22,530 --> 01:44:24,690
for pick something off of a plant and eat it?

1652
01:44:24,770 --> 01:44:29,090
Like, because I think these are probably largely observational systems, and it's not

1653
01:44:29,090 --> 01:44:33,090
people, it's not adults or older kids sitting around being like, look, this is what you do

1654
01:44:33,090 --> 01:44:33,410
with this.

1655
01:44:33,490 --> 01:44:35,090
First you do this, first you do that.

1656
01:44:35,250 --> 01:44:39,660
Instead, there's people living their lives and doing these things, And it's a young

1657
01:44:39,660 --> 01:44:45,660
learner's problem basically to key in on what's happening and figure it out themselves and

1658
01:44:45,660 --> 01:44:49,020
practice it and in in safe ways.

1659
01:44:50,380 --> 01:44:51,020
Yeah.

1660
01:44:52,380 --> 01:44:52,940
Interesting.

1661
01:44:53,100 --> 01:44:53,340
Yeah.

1662
01:44:53,420 --> 01:44:55,820
There's a whole I mean, oh, and that's what I was sorry.

1663
01:44:55,900 --> 01:45:00,300
I just I I realized I I don't think you necessarily need a lot of emotion with that.

1664
01:45:00,470 --> 01:45:06,470
right so I don't think you necessarily need like big like ah or like uh or or big

1665
01:45:06,550 --> 01:45:12,310
like uh disgust sleep maybe it happens and certainly I bet plants are bitter right the

1666
01:45:12,310 --> 01:45:18,310
toxins in them are bitter so I'm sure there would be I'm sure you would uh

1667
01:45:18,470 --> 01:45:22,390
we haven't done it yet we should we we haven't done it yet where somebody tastes something

1668
01:45:22,470 --> 01:45:28,470
that's like um but the you would expect there might be vigilance for that but I don't know

1669
01:45:28,520 --> 01:45:32,200
that you need disgust as the input.

1670
01:45:32,360 --> 01:45:35,080
I mean, certainly our our our work suggests that you don't.

1671
01:45:35,160 --> 01:45:39,560
It just seems to be, as far as we can tell, it seems to be sort of the default response

1672
01:45:39,560 --> 01:45:41,240
before there's social information.

1673
01:45:41,720 --> 01:45:41,960
Right.

1674
01:45:42,200 --> 01:45:42,440
Yeah.

1675
01:45:42,600 --> 01:45:43,800
Fear is sort of like you're far.

1676
01:45:44,040 --> 01:45:45,880
Oh, sorry, David, you're like kind of far into it.

1677
01:45:46,040 --> 01:45:50,280
So, like if you totally, you know, if you're like you you've beaten a bunch and all of a

1678
01:45:50,280 --> 01:45:53,320
sudden you realize you use the poisonous plant, you might get afraid, right?

1679
01:45:53,560 --> 01:45:57,240
But that's different, you know, like that's a different function, or like you're far into a

1680
01:45:57,270 --> 01:46:00,230
forest and you realize there's no way out, and you become afraid.

1681
01:46:00,390 --> 01:46:03,590
Like that, that's engaging that, but that's sort of incidental that it's plants.

1682
01:46:03,670 --> 01:46:07,990
But it's it's for like, as you said, Annie, it's like for this additional motivating, like

1683
01:46:08,070 --> 01:46:09,590
get out of this situation.

1684
01:46:09,990 --> 01:46:15,910
And typically, plants, it's sort of you don't have to, you don't get all that far in if

1685
01:46:15,910 --> 01:46:19,270
everything is going right, and you don't need those emotions exactly.

1686
01:46:19,350 --> 01:46:25,350
And I David, I love the idea of sort of this cautionary, um, distinct category.

1687
01:46:25,510 --> 01:46:26,230
Um, yeah.

1688
01:46:26,630 --> 01:46:31,060
I think yeah it could very well be its own distinct emotion with its distinct design

1689
01:46:31,060 --> 01:46:35,940
features and that it prompts attention to parts rather than holes and procedures and and

1690
01:46:35,940 --> 01:46:39,700
where you know uh uh prompts a greater attention toward you know how other people are

1691
01:46:39,700 --> 01:46:41,540
reacting to it and and social learning.

1692
01:46:41,700 --> 01:46:44,260
So yeah, it's an interesting underexplored topic.

1693
01:46:44,420 --> 01:46:45,220
But yeah, yeah.

1694
01:46:45,460 --> 01:46:50,410
And again, because you know, since long before we were humans, this was a problem, right?

1695
01:46:50,570 --> 01:46:55,930
So having something, having a motivational system that kind of shifts everything, all the

1696
01:46:55,930 --> 01:47:00,570
necessary uh different other systems into the right setting when you're engaging with it

1697
01:47:00,730 --> 01:47:02,090
makes a lot of sense, right?

1698
01:47:02,570 --> 01:47:06,890
So yeah, but I I can barely convince a lot of people that there should be any psychology

1699
01:47:06,890 --> 01:47:07,530
for plants.

1700
01:47:07,610 --> 01:47:12,250
I think convincing them that there might be a separate emotional component for plants would

1701
01:47:12,250 --> 01:47:15,770
be that's that's a lift, but that's something I mean that would be cool.

1702
01:47:16,000 --> 01:47:16,320
Right.

1703
01:47:16,480 --> 01:47:20,000
And and so it sounds like, I mean, just to sort, I mean, we we've David and I've talked a

1704
01:47:20,000 --> 01:47:25,040
lot about too, about not sort of like overselling results from studies or telling people

1705
01:47:25,040 --> 01:47:25,520
what to do.

1706
01:47:25,680 --> 01:47:28,160
You know, like I think we have to be humble about we don't know a lot.

1707
01:47:28,320 --> 01:47:33,280
But it sounds like what you're saying that as much as possible, like expose kids to food

1708
01:47:33,280 --> 01:47:36,160
preparation and the fact that they're not getting that.

1709
01:47:36,400 --> 01:47:41,710
Um, and there's like this whole category of like, you know, like plant uh

1710
01:47:42,030 --> 01:47:44,750
interactions of like cooking, like on YouTube.

1711
01:47:44,990 --> 01:47:48,190
If you just like there's all these things of like people building houses out of like plants

1712
01:47:48,270 --> 01:47:53,390
and people watch this or like cooking shows or right, like or just you know, the people

1713
01:47:53,390 --> 01:47:55,390
love watching like people make stuff.

1714
01:47:55,550 --> 01:48:01,150
And I wonder if to some extent that's sort of like a a a readout of the psychology that's

1715
01:48:01,150 --> 01:48:05,950
not getting the relevant cues for other for those of us who are not in in a place where

1716
01:48:05,950 --> 01:48:08,590
people are sort of physically interacting with the environment as much.

1717
01:48:08,830 --> 01:48:09,070
Yeah.

1718
01:48:09,280 --> 01:48:09,600
Yeah.

1719
01:48:09,760 --> 01:48:10,800
I mean, I think so.

1720
01:48:10,880 --> 01:48:14,000
As you say, you don't want to overread stuff, but I I think that's right.

1721
01:48:14,160 --> 01:48:20,160
And I and I mean, you know, one of the reasons that I'm interested in following up more

1722
01:48:20,160 --> 01:48:26,080
on this food learning thing is because I in an ideal world, I'd be able

1723
01:48:26,080 --> 01:48:29,840
to identify kind of what are these relevant cues.

1724
01:48:30,080 --> 01:48:35,930
And then how could we find ways of, you know, we're not going back to having

1725
01:48:36,090 --> 01:48:40,970
sitting, you know, we're not going back to a small-scale world in all likelihood.

1726
01:48:41,130 --> 01:48:46,970
Um, and but how could we provide aspects of those cues to toddlers,

1727
01:48:47,130 --> 01:48:52,890
to infants, to young kids in ways that could help to get them over some of

1728
01:48:52,890 --> 01:48:58,740
this very um reasonable reluctance towards the what what turn out to

1729
01:48:58,740 --> 01:49:04,740
be the healthiest foods yeah right um and so that's that's something I would I I I that's

1730
01:49:04,820 --> 01:49:09,300
that's next on the on the list is to really start digging into what that is.

1731
01:49:09,540 --> 01:49:11,460
Um and yeah we'll see.

1732
01:49:11,620 --> 01:49:17,300
I mean I've done a little bit of uh doing some gardening program stuff which is uh was

1733
01:49:17,460 --> 01:49:22,980
a a a big task um but but fun to do um and I think

1734
01:49:23,210 --> 01:49:29,050
there is a world where you could imagine like ways of designing things that you

1735
01:49:29,050 --> 01:49:33,850
could potentially target the design of these systems to get you kind of the biggest bang

1736
01:49:33,850 --> 01:49:36,330
for your buck in these kinds of systems.

1737
01:49:36,730 --> 01:49:39,210
Let let the kids plan the dirt and plant some things.

1738
01:49:39,610 --> 01:49:39,930
Exactly.

1739
01:49:40,090 --> 01:49:42,250
And and let them see where their food is coming from.

1740
01:49:42,330 --> 01:49:47,920
And I mean, this is uh Camille Ryu, my former postdoc now collaborator, she has some work

1741
01:49:47,920 --> 01:49:53,200
from her PhD actually showing that some of this food neophobia stuff seems maybe uh the

1742
01:49:53,200 --> 01:49:59,120
result of um having less or more immature categorization abilities.

1743
01:49:59,360 --> 01:50:05,360
So if you have a harder time knowing that the thing that you are encountering is in fact

1744
01:50:05,440 --> 01:50:10,160
the same kind of thing you've encountered before, you are more likely to show neophobia.

1745
01:50:10,240 --> 01:50:13,170
So if you're into categorization abilities, yeah, right.

1746
01:50:13,250 --> 01:50:17,410
If you're if your categorization abilities, if you score more high, uh highly on

1747
01:50:17,410 --> 01:50:21,890
categorization abilities, you're less likely to exhibit neophobia in some of her studies.

1748
01:50:22,290 --> 01:50:26,210
So this is why, yeah, be maybe you're just cutting the vegetables the wrong way for your

1749
01:50:26,210 --> 01:50:26,530
daughter.

1750
01:50:27,170 --> 01:50:28,690
Honestly, I think that might be it.

1751
01:50:28,770 --> 01:50:30,610
Yeah, I'm cutting them in the wrong shape or something.

1752
01:50:30,930 --> 01:50:36,100
Because she does have a hard time like when we're eating uh uh tortilla chips, I remember I

1753
01:50:36,100 --> 01:50:42,100
have this memory of uh she had a meltdown uh because she was upset that I ate

1754
01:50:42,100 --> 01:50:44,740
the the specific tortilla chip that she wanted.

1755
01:50:45,220 --> 01:50:45,540
Right.

1756
01:50:45,940 --> 01:50:50,100
Where she wasn't just saying they were all the same kind of thing, you know, it was they

1757
01:50:50,100 --> 01:50:54,420
were all they were distinct tortilla chips and she had her eye on that particular tortilla

1758
01:50:54,420 --> 01:50:58,190
chips, which suggests that she's having a hard time like treating it as a general category

1759
01:50:58,510 --> 01:51:00,830
of the same type of thing, and that and that could be driving this.

1760
01:51:00,990 --> 01:51:01,150
Yeah.

1761
01:51:01,390 --> 01:51:01,630
Yeah.

1762
01:51:01,710 --> 01:51:03,230
And I mean, food is one of those things.

1763
01:51:03,310 --> 01:51:05,950
Like, we look at it, this is a big instinct blindness thing, right?

1764
01:51:06,030 --> 01:51:08,110
Like we look at it and it's very clearly food.

1765
01:51:08,190 --> 01:51:09,870
And why can't you see that it's food?

1766
01:51:10,030 --> 01:51:15,550
But if you step back from it, it's just piles of shapes and colors and like textures.

1767
01:51:15,870 --> 01:51:18,350
And why should that be food and not something else?

1768
01:51:18,510 --> 01:51:18,590
Right.

1769
01:51:18,960 --> 01:51:22,720
Yeah, she wanted the one that was a particular shape of of a triangle and not the one that

1770
01:51:22,720 --> 01:51:26,080
was a different shape, you know, like she was paying attention to details that I completely

1771
01:51:26,080 --> 01:51:29,120
ignored that, you know, make sense if you're if you're trying to figure out how the world

1772
01:51:29,120 --> 01:51:32,160
works, like it's not obvious what details are worth paying attention to.

1773
01:51:32,640 --> 01:51:33,120
Exactly.

1774
01:51:33,600 --> 01:51:36,000
Yeah, build a robot that can identify food.

1775
01:51:36,160 --> 01:51:41,760
That's the uh but uh one of the questions we always

1776
01:51:41,760 --> 01:51:45,520
ask people is is there any question we should have asked you?

1777
01:51:46,850 --> 01:51:49,650
Oh, uh, I don't know.

1778
01:51:49,730 --> 01:51:51,890
I feel like you got them all.

1779
01:51:52,370 --> 01:51:54,610
Um, yeah.

1780
01:51:55,010 --> 01:51:59,250
Well, I mean, David sort of alluded to did I slip on a plant?

1781
01:51:59,330 --> 01:52:05,170
And there was, there is one like big plant experience that I did have uh

1782
01:52:05,170 --> 01:52:10,690
as a child that um probably so the the big plant experience as a child is I accidentally

1783
01:52:10,690 --> 01:52:16,460
climbed up a poison oak vine, not knowing that it was poison oak uh and

1784
01:52:16,780 --> 01:52:22,700
got huge poison oak rash on my face it was like summer so it was along

1785
01:52:22,700 --> 01:52:28,300
my my legs my whole body and got a really really really terrible rash so I

1786
01:52:28,300 --> 01:52:33,420
learned firsthand that plants can be really dangerous and really

1787
01:52:33,420 --> 01:52:37,100
unpleasant uh and that you might not want to touch them.

1788
01:52:38,110 --> 01:52:39,630
That's a great origin story.

1789
01:52:40,190 --> 01:52:43,950
Poison Oak would be a great supervillain name for you where you use your technology.

1790
01:52:44,510 --> 01:52:45,150
That's great.

1791
01:52:48,270 --> 01:52:49,470
Poison Oak strikes again.

1792
01:52:50,190 --> 01:52:53,630
It's also a good like folk fusion band name, Poison Oak, sort of.

1793
01:52:53,950 --> 01:52:54,350
Oh yeah.

1794
01:52:54,430 --> 01:52:54,670
Totally.

1795
01:52:54,990 --> 01:52:56,670
Maybe a little bit of rocking it too.

1796
01:52:56,750 --> 01:52:56,910
Yeah.

1797
01:52:56,990 --> 01:53:00,910
Um I want to see the movie where you seek revenge on Reviewer 2 by us.

1798
01:53:01,550 --> 01:53:02,510
As Poison Oak.

1799
01:53:02,990 --> 01:53:04,190
Yeah, Poison Oak.

1800
01:53:07,880 --> 01:53:09,480
The really good superpower, yeah.

1801
01:53:09,720 --> 01:53:11,560
Like harnessing the power of plants.

1802
01:53:11,640 --> 01:53:12,360
I mean that's yeah.

1803
01:53:12,760 --> 01:53:14,360
Um who was saying, David, do you remember?

1804
01:53:14,440 --> 01:53:18,680
I think it was either um Chris von Ruden or Ed Hagen was saying plants aren't your friends.

1805
01:53:18,760 --> 01:53:23,080
It might have been it was somebody who like was in the schmar, like with in the forest, or

1806
01:53:23,240 --> 01:53:25,960
like really just you know, no, they are not your friends.

1807
01:53:27,670 --> 01:53:29,750
They're building weapons factories.

1808
01:53:29,990 --> 01:53:31,030
I mean, really, they are.

1809
01:53:31,190 --> 01:53:32,550
That's how they defend themselves.

1810
01:53:32,710 --> 01:53:33,750
This is what they've come up with.

1811
01:53:33,830 --> 01:53:36,150
And they've come up with some very clever ways to do it.

1812
01:53:36,390 --> 01:53:37,270
Um yeah.

1813
01:53:37,510 --> 01:53:37,670
Yeah.

1814
01:53:37,830 --> 01:53:37,910
Yeah.

1815
01:53:38,150 --> 01:53:39,990
You gotta respect the plants.

1816
01:53:40,790 --> 01:53:41,030
Yeah.

1817
01:53:41,350 --> 01:53:42,310
Respect plants.

1818
01:53:42,550 --> 01:53:43,030
Yeah, yeah.

1819
01:53:43,110 --> 01:53:45,750
So respect the adaptations and respect plants.

1820
01:53:45,830 --> 01:53:47,270
And yeah.

1821
01:53:47,430 --> 01:53:50,470
So um yeah, but uh David, anything else?

1822
01:53:50,980 --> 01:53:53,940
No, I I think, you know, we we covered a lot of ground.

1823
01:53:54,100 --> 01:54:00,100
And uh yeah, we we harvested our our insights and we planted our seeds and we uh I'll

1824
01:54:00,100 --> 01:54:01,140
just keep rattling off.

1825
01:54:01,620 --> 01:54:02,580
Keep going, keep going.

1826
01:54:03,300 --> 01:54:05,220
And now we're out of time.

1827
01:54:05,780 --> 01:54:07,700
Oh T H Y M E.

1828
01:54:09,860 --> 01:54:14,430
Those are yeah, it's hard, it's harder to get those to can convey across this acoustic

1829
01:54:14,430 --> 01:54:14,830
modality.

1830
01:54:15,150 --> 01:54:16,190
Yeah, but you know.

1831
01:54:16,670 --> 01:54:17,790
But yeah, no, thank you so much.

1832
01:54:17,870 --> 01:54:23,310
And you know, genuinely, like, you know, personal bias aside, like the work that you're

1833
01:54:23,310 --> 01:54:28,990
doing, it's extremely important, not only because you're uncovering a new area of

1834
01:54:28,990 --> 01:54:33,950
adaptations people hadn't looked before, but because it's also an example of exactly what

1835
01:54:33,950 --> 01:54:39,200
you said, like learning is not opposed to evolutionary and the connection to development.

1836
01:54:39,280 --> 01:54:41,440
I mean, we had Deb Lieberman Deb Lieberman on.

1837
01:54:41,600 --> 01:54:46,320
She was really excited about the special issue with development, um, on development.

1838
01:54:46,480 --> 01:54:51,040
And I think it comes back to the initial thing that David mentioned about what you were

1839
01:54:51,040 --> 01:54:55,840
doing, which is that as a developmental psychologist, you were already asking like a good

1840
01:54:55,840 --> 01:54:58,560
question, and evolutionary psychology answered it.

1841
01:54:58,850 --> 01:55:04,690
And I do think that the connection between developmental and evolutionary approaches are

1842
01:55:04,690 --> 01:55:09,810
very much kindred because in many cases developmentalists are asking, and you can you're

1843
01:55:09,810 --> 01:55:13,810
nodding your head, so I I suggest you know you agree, but but yeah, because you have to

1844
01:55:13,810 --> 01:55:17,810
sort of respect that there are systems that because they're kids, you know, you have to

1845
01:55:17,810 --> 01:55:19,810
really think about what's the Q structure.

1846
01:55:20,290 --> 01:55:26,120
I think there's a lot of connections to integrating development evolutionary.

1847
01:55:26,200 --> 01:55:31,640
And so thank you for for doing that because I think it'll it's it's really gonna help keep

1848
01:55:31,640 --> 01:55:37,320
both development and evolutionary psychology sort of invigorated and um thriving

1849
01:55:37,480 --> 01:55:41,560
and flourishing uh to tiptoe towards a plant pun.

1850
01:55:42,840 --> 01:55:43,720
Well thank you.

1851
01:55:43,880 --> 01:55:44,760
Thank you for saying that.

1852
01:55:44,920 --> 01:55:46,310
That that that means a lot.

1853
01:55:46,390 --> 01:55:50,310
And I mean, you know, I'm standing on shoulders of giants with all of this stuff.

1854
01:55:50,390 --> 01:55:53,430
And I I uh I appreciate that.

1855
01:55:53,510 --> 01:55:58,710
And I hope that people who are interested in development and evolution, you know, I'm gonna

1856
01:55:58,710 --> 01:56:04,390
be looking for grad students for the next many years to come in this lab and research

1857
01:56:04,390 --> 01:56:04,950
assistance.

1858
01:56:05,030 --> 01:56:09,920
And so if you're if you're interested in that kind of thing, you know, keep an eye out for

1859
01:56:09,920 --> 01:56:10,880
me and my work.

1860
01:56:10,960 --> 01:56:16,480
Um, and hopefully we can bring development and uh evolution, evolutionary

1861
01:56:16,480 --> 01:56:17,920
approaches closer together.

1862
01:56:18,160 --> 01:56:20,960
Yeah, the lab name, it's a relatively new lab name.

1863
01:56:21,040 --> 01:56:21,840
What is the lab?

1864
01:56:22,240 --> 01:56:26,000
Uh the lab for infant learning and cognition or lilac.

1865
01:56:27,920 --> 01:56:28,560
Yeah, nice.

1866
01:56:28,800 --> 01:56:29,920
Plant puns.

1867
01:56:30,160 --> 01:56:30,880
All right, yeah.

1868
01:56:31,120 --> 01:56:32,800
Top, top that, yeah.

1869
01:56:33,950 --> 01:56:36,830
Uh but yeah, thank you so much both of you for having me on.

1870
01:56:36,910 --> 01:56:37,710
This is a real pleasure.

1871
01:56:37,790 --> 01:56:42,510
It's great to great to talk to you, even though I get to talk to one of you every day, but

1872
01:56:42,510 --> 01:56:43,790
this is a different format.

1873
01:56:44,510 --> 01:56:44,750
Exactly.

1874
01:56:44,830 --> 01:56:46,110
But we don't often get to talk to you.

1875
01:56:46,510 --> 01:56:47,070
So thank you.

1876
01:56:47,230 --> 01:56:47,710
Yeah.

1877
01:56:48,510 --> 01:56:49,310
Oh yeah.

1878
01:56:49,470 --> 01:56:50,110
All right.

1879
01:56:50,350 --> 01:56:50,750
All right.

1880
01:56:50,990 --> 01:56:56,750
David, we have ended another episode, this one full of the weird combination of

1881
01:56:56,750 --> 01:56:58,190
babies and plants.

1882
01:56:58,670 --> 01:56:59,230
Yes.

1883
01:56:59,470 --> 01:57:02,140
It was a uh wild ride.

1884
01:57:02,300 --> 01:57:07,820
Um a lot of seeds were planted, um, a lot of flowers of insight

1885
01:57:07,820 --> 01:57:08,380
bloomed.

1886
01:57:08,940 --> 01:57:12,380
And it was in but now it's time to end the episode.

1887
01:57:12,780 --> 01:57:14,540
O T H Y M E okay.

1888
01:57:15,500 --> 01:57:17,660
There's a lot of the homonyms really don't come across on podcasts.

1889
01:57:17,820 --> 01:57:18,460
I really don't know.

1890
01:57:18,540 --> 01:57:18,860
Yeah, exactly.

1891
01:57:19,260 --> 01:57:20,220
Not the ideal format.

1892
01:57:20,380 --> 01:57:26,090
But um if you want to support us, please uh leave us a kind review, give us some

1893
01:57:26,090 --> 01:57:30,170
feedback, uh tell us what you want to hear, you know, who you want to listen to, what

1894
01:57:30,170 --> 01:57:31,450
topics you want us to cover.

1895
01:57:31,610 --> 01:57:35,450
Uh if you're so inclined, you can uh support us on Patreon.

1896
01:57:35,610 --> 01:57:37,930
Uh anything else people can do, Dave?

1897
01:57:38,170 --> 01:57:43,930
Um, you know, just you know, look up uh interesting, important work in

1898
01:57:43,930 --> 01:57:45,930
evolutionary social sciences.

1899
01:57:46,090 --> 01:57:49,530
And if you come across stuff that we should cover, let us know.

1900
01:57:49,820 --> 01:57:50,700
Yeah, please do.

1901
01:57:50,940 --> 01:57:51,340
All right.

1902
01:57:51,500 --> 01:57:53,020
We'll see you guys next week.

1903
01:57:53,340 --> 01:57:53,660
See ya.

1904
01:57:54,060 --> 01:57:54,700
Bye.