WEBVTT 00:00:00.320 --> 00:00:06.080 So David, um, I wonder if people think that we have been screwing up on purpose or if 00:00:06.080 --> 00:00:08.480 we're doing it for real in the beginning. 00:00:08.960 --> 00:00:13.760 No, I can I can assure you all, for those listening, our screw-ups are genuine and sincere. 00:00:13.840 --> 00:00:16.160 We really are as incompetent as we sound. 00:00:17.280 --> 00:00:21.520 Well, I am uh not David Pinsoff, and you are not. 00:00:22.080 --> 00:00:25.200 I'm definitely not George Clooney, sadly. 00:00:29.710 --> 00:00:33.150 Okay, uh today Okay, keep going. 00:00:33.310 --> 00:00:33.950 I'm really bad at this. 00:00:34.030 --> 00:00:35.230 Uh I'm David Pinsov. 00:00:35.550 --> 00:00:37.070 I'm David Petrozowski. 00:00:37.390 --> 00:00:43.070 And this is Evolutionary Psychology, the podcast actually features evolutionary psychology 00:00:44.030 --> 00:00:46.670 by actual evolutionary psychologists. 00:00:46.990 --> 00:00:47.710 That's right. 00:00:48.190 --> 00:00:49.150 So yeah. 00:00:49.630 --> 00:00:50.590 Enjoy 00:00:58.700 --> 00:01:00.460 Um David, good to see you. 00:01:00.540 --> 00:01:05.020 I'm really excited that uh I get to see you I got to see you at HBES, Human Behavior 00:01:05.180 --> 00:01:06.300 Evolution Society. 00:01:06.380 --> 00:01:11.740 Uh love going to HBES and it's was lovely to just spend some time with you in person. 00:01:12.140 --> 00:01:14.620 Yeah, uh it was it was a a really fun time. 00:01:14.780 --> 00:01:20.230 Um and uh after HBES, we have a wonderful guest, uh, Annie 00:01:20.230 --> 00:01:24.710 Wirtz, who is a professor of psychology at University of California, Santa Barbara. 00:01:24.790 --> 00:01:30.550 Uh, we cover uh some really fascinating new stuff that Annie has been pioneering on the 00:01:30.550 --> 00:01:34.310 study of infant learning and uh how we think about plants. 00:01:34.630 --> 00:01:39.510 Yeah, totally new area, really unusual for somebody in our sort of generation of science to 00:01:39.510 --> 00:01:43.190 kind of develop a whole new area and a really lovely example of somebody taking 00:01:43.270 --> 00:01:48.680 evolutionary perspective on development and learning and generating completely new 00:01:48.680 --> 00:01:53.160 knowledge in an area where people really didn't think to look before, especially from a 00:01:53.160 --> 00:01:55.320 psychological experimental perspective. 00:01:55.480 --> 00:01:57.800 So it's a really fun, interesting conversation. 00:01:57.880 --> 00:01:59.480 I think you'll really enjoy it. 00:01:59.960 --> 00:02:02.280 And yeah, enjoy the episode. 00:02:02.600 --> 00:02:03.320 Enjoy. 00:02:06.440 --> 00:02:12.360 Today we have Annie Wirtz, who is professor at UC 00:02:12.440 --> 00:02:13.640 Santa Barbara. 00:02:14.750 --> 00:02:20.510 and Annie, prior to UCSB, uh where where were you? 00:02:21.630 --> 00:02:23.630 Uh how far back should I go? 00:02:24.030 --> 00:02:26.030 Uh the snowy day. 00:02:26.110 --> 00:02:28.430 Uh Dan told us he was born in August. 00:02:28.590 --> 00:02:31.710 So uh you can go back all the way to the day of your childhood. 00:02:31.870 --> 00:02:37.710 So uh well, how about I I can go in reverse and then uh and then we 00:02:37.710 --> 00:02:38.190 can go. 00:02:38.430 --> 00:02:44.260 So uh prior to UCSB, so I started here in March of 2024, And 00:02:44.260 --> 00:02:50.180 then prior to that, I was at the Max Planck Institute for Human Development in Berlin for 00:02:50.980 --> 00:02:55.140 almost 10 years, like nine and a half-ish years. 00:02:55.540 --> 00:03:00.580 That I was there, I had an independent research group called the Max Planck Research Group, 00:03:00.660 --> 00:03:02.420 Naturalistic Social Cognition. 00:03:02.900 --> 00:03:08.500 And then before that, I was a postdoc at the Infant Cognition Center at 00:03:08.500 --> 00:03:08.980 Yale. 00:03:09.170 --> 00:03:11.970 And then before that, I was actually at UCSB. 00:03:12.050 --> 00:03:13.890 So I have looped again. 00:03:15.090 --> 00:03:21.090 I was at here for graduate school with Tams and German, and 00:03:21.170 --> 00:03:25.090 of course had Lita Cosmodies and John Tuby on my committee. 00:03:25.330 --> 00:03:28.610 And then before that, I was at Boston University. 00:03:29.010 --> 00:03:33.730 And before that, I was in uh Robozonia, Pennsylvania. 00:03:33.890 --> 00:03:37.440 Um until the day of my birth. 00:03:38.400 --> 00:03:40.000 And then before that, we don't know. 00:03:40.720 --> 00:03:41.520 We don't know, yeah. 00:03:41.920 --> 00:03:46.320 And we actually had Jamie Krems on, and she mentioned there's a whole bunch of people from 00:03:46.480 --> 00:03:52.480 eastern and apologies to western Pennsylvania, but eastern Pennsylvania, like um apparently 00:03:52.640 --> 00:03:58.480 Lita grew up in Philly, uh Jamie, um, and 00:03:58.480 --> 00:03:59.280 Joe Henrik. 00:03:59.440 --> 00:04:02.000 And then David, do you remember who else she mentioned? 00:04:02.530 --> 00:04:03.330 Oh, Mike Gervin. 00:04:03.410 --> 00:04:06.290 Mike Gervin is from the Mike on. 00:04:06.370 --> 00:04:06.450 Yeah. 00:04:06.530 --> 00:04:09.170 So there's a parent, she she thinks there's something in the water. 00:04:09.330 --> 00:04:12.610 So congratulations on being from it's a good pedigree. 00:04:12.770 --> 00:04:16.130 Um hailing from eastern Pennsylvania. 00:04:16.290 --> 00:04:18.770 Um we'll get into all of that path. 00:04:18.850 --> 00:04:24.610 And one of the things we always ask people is um is how they got interested in 00:04:24.610 --> 00:04:26.850 evolutionary um psychology. 00:04:27.010 --> 00:04:31.160 But before we do that, can you tell people a little bit about what an independent research 00:04:31.160 --> 00:04:34.600 group leader is at the Mox Planck or what the Mox Planck is? 00:04:34.680 --> 00:04:39.240 Because I know lots of people, um, our audiences diverse may not know what that is. 00:04:39.320 --> 00:04:40.920 So can you talk a little bit about that? 00:04:41.400 --> 00:04:41.640 Sure. 00:04:41.880 --> 00:04:47.160 Yes, so it is um, it's the Max Planck Society 00:04:47.800 --> 00:04:50.760 is the overarching uh institution. 00:04:51.810 --> 00:04:57.810 And in Germany, the Max Planck Society has over, I mean, I'm not sure what 00:04:57.810 --> 00:05:03.730 the current count is, but it's somewhere over 70 different research institutes throughout 00:05:04.130 --> 00:05:05.730 Germany, the EU. 00:05:06.450 --> 00:05:07.810 There had been one in Florida. 00:05:07.890 --> 00:05:10.210 I don't know if there's still one in Florida, Italy. 00:05:10.290 --> 00:05:12.610 So they're dispersed all over the place. 00:05:12.850 --> 00:05:15.640 And they all focus on different topics. 00:05:16.120 --> 00:05:22.040 And the it runs the gamut from physics and chemistry 00:05:22.280 --> 00:05:27.400 to empirical aesthetics and history of science and all kinds of fascinating questions. 00:05:27.480 --> 00:05:33.400 And they build them around the the particular sets of people who they bring in 00:05:33.400 --> 00:05:39.370 to be directors, who are kind of the the um the people who are in charge of the 00:05:39.370 --> 00:05:40.170 big centers. 00:05:40.330 --> 00:05:43.210 And there's usually several directors within an institute. 00:05:43.930 --> 00:05:49.530 And those are high-powered people with tons of money behind them and uh research 00:05:49.530 --> 00:05:53.450 scientists, postdocs, pre-docs, um, the whole thing. 00:05:53.610 --> 00:05:59.210 And then their system, they have what's equivalent to an assistant professor position 00:05:59.210 --> 00:06:04.760 within that, which are there's several different kinds, but um the kind that I had was an 00:06:04.760 --> 00:06:09.240 independent research group, um, so equivalent to an assistant professor position. 00:06:09.320 --> 00:06:13.880 And basically what that was is there's a call that goes out uh almost every year in the 00:06:13.880 --> 00:06:19.560 fall where you can apply for these positions and you pitch a research idea that you could 00:06:19.560 --> 00:06:22.510 do for around five-ish years. 00:06:23.150 --> 00:06:28.990 And I was successful in that application, and they gave me a bunch of money to do my work, 00:06:29.550 --> 00:06:34.830 working on how infants, the the um how infants learn about plants, um, but the kind of 00:06:34.830 --> 00:06:38.910 underlying psychology for how babies learn about the natural world. 00:06:39.070 --> 00:06:42.350 Um, and so they gave me uh money to do that. 00:06:42.510 --> 00:06:48.460 Um, and I had uh I had my own PhD students, I had master's students, I had 00:06:48.460 --> 00:06:49.980 a team of student research assistants. 00:06:50.140 --> 00:06:55.420 I was lucky enough to have two paid lab manager, and then a person whose position was 00:06:55.500 --> 00:07:01.260 foreign language secretary who worked for me and were just wonderful professional science, 00:07:01.340 --> 00:07:03.420 uh science support staff. 00:07:03.660 --> 00:07:05.660 It was a fantastic position. 00:07:05.820 --> 00:07:08.730 Um, the biggest problem with it though is it's time limited. 00:07:08.890 --> 00:07:14.890 So even though there's an initial five year period for it, then uh after that you 00:07:14.890 --> 00:07:17.370 can apply for extensions of various kinds. 00:07:17.530 --> 00:07:20.170 And I did that successfully along the way. 00:07:20.330 --> 00:07:26.010 Um, but uh outside of a few constrained things, typically they expect you that they've 00:07:26.010 --> 00:07:28.730 given you all these resources, they expect you to move on. 00:07:28.810 --> 00:07:33.290 Um, and so I did, and I was very lucky to then get the position here at UCSV. 00:07:33.560 --> 00:07:33.720 Right. 00:07:33.880 --> 00:07:38.360 And so it's sort of the the Mox Planck thing, it's sort of a high risk, as I understand it, 00:07:38.440 --> 00:07:41.640 it's sort of there's a high risk new question to be asked. 00:07:41.720 --> 00:07:46.760 And they give you sort of a temporary pot of money to say, look, here's this really new 00:07:46.760 --> 00:07:47.400 idea. 00:07:47.800 --> 00:07:53.560 And uh maybe not all of them work, but uh they're important big 00:07:53.560 --> 00:07:56.920 picture new ideas that challenge existing wisdom. 00:07:57.240 --> 00:08:03.170 And uh it's it's uh it's it's this really cool sort of like scientific um, 00:08:03.410 --> 00:08:04.610 I don't know, what would you call that? 00:08:04.770 --> 00:08:07.890 Almost like a what is it when an entrepreneur throws money at things? 00:08:07.970 --> 00:08:08.850 I don't know anything about this. 00:08:09.170 --> 00:08:10.210 Startup or startup, yeah. 00:08:10.290 --> 00:08:14.290 It's sort of like a or a go, it's almost like a scientific startup or GoFundMe, or sort of 00:08:14.370 --> 00:08:19.170 like a thing up where, you know, it's just sort of an engine for like new innovative 00:08:19.170 --> 00:08:24.690 research ideas where, yeah, the ideas maybe some percentage or even high percentage fail, 00:08:24.770 --> 00:08:26.370 but then some are successful. 00:08:26.640 --> 00:08:30.240 And as far as we know, and I mean, this is when whenever we have guests on, I always think 00:08:30.240 --> 00:08:31.680 about like what to say about a person. 00:08:31.840 --> 00:08:36.960 There's very few people I know in our cohort who came up with a whole new area of research. 00:08:37.280 --> 00:08:43.120 Um and I think you're one of those people where the combination of babies and plants, 00:08:43.200 --> 00:08:47.040 um, and I know it's more complicated, but I'm just we're being super adductive now. 00:08:47.280 --> 00:08:50.400 Like that's a when people hear that, they sort of do a double take. 00:08:50.560 --> 00:08:55.590 Um, and we can get into and sort of what that is, but I mean, was it but what you're saying 00:08:55.590 --> 00:09:01.030 is that you know you were one of these high risk people in this really cool program 00:09:01.350 --> 00:09:02.630 in Germany. 00:09:02.950 --> 00:09:08.870 And it by all accounts, based on the papers and based on the fact that you're UCSB, it it 00:09:08.870 --> 00:09:09.430 worked, right? 00:09:09.670 --> 00:09:09.910 Yes. 00:09:10.390 --> 00:09:10.630 Yeah. 00:09:10.950 --> 00:09:11.590 It did. 00:09:11.750 --> 00:09:12.150 Yeah. 00:09:12.710 --> 00:09:15.430 And I think you know that's it's it's another example in your work. 00:09:15.510 --> 00:09:20.680 And we've talked about, we've alluded to your work uh a bunch that um you know we've talked 00:09:20.680 --> 00:09:24.120 a little bit about innate versus learned, and we can get to that too. 00:09:24.280 --> 00:09:26.120 And your work is a good example of that. 00:09:26.200 --> 00:09:31.800 But we've also talked about how taking an evolutionary approach um gives you new insights 00:09:31.960 --> 00:09:37.640 uh and questions to ask that you've never would have gotten without an evolutionary 00:09:37.640 --> 00:09:38.120 approach. 00:09:38.360 --> 00:09:42.520 And I think your work is a really good example of that to the point where when people hear 00:09:42.520 --> 00:09:46.440 about it, it sounds like a crazy idea, unless you sort of explain it. 00:09:46.520 --> 00:09:46.840 Yeah. 00:09:47.270 --> 00:09:48.070 Yeah, that's right. 00:09:48.230 --> 00:09:53.910 And I mean, to just to put a button on the Max Planck thing, the the um the idea behind 00:09:53.910 --> 00:09:58.630 these independent research groups is it's really promising ideas that are potentially too 00:09:58.630 --> 00:10:02.950 new to be a a sure bet for traditional funding agencies. 00:10:03.110 --> 00:10:09.110 So they give you the money to really establish the idea if it's got something to it, 00:10:09.270 --> 00:10:13.190 um, and with the idea that later on down the line you can get money from traditional 00:10:13.190 --> 00:10:14.310 funding agencies as well. 00:10:14.470 --> 00:10:16.150 And that's that's how it worked in my case. 00:10:16.600 --> 00:10:17.080 That's awesome. 00:10:17.240 --> 00:10:19.240 I I wish we had something like that here in the US. 00:10:19.400 --> 00:10:21.560 It sounds uh very cool. 00:10:21.800 --> 00:10:27.320 Um but I I I want to get into um the origin story behind um 00:10:27.640 --> 00:10:31.720 this topic uh of of plants, because I don't I don't think I've heard it or or or know how 00:10:31.720 --> 00:10:32.280 you got into this. 00:10:32.440 --> 00:10:38.040 So as far as I'm aware, like you're the first person to start studying this 00:10:38.190 --> 00:10:42.030 topic, you basically pioneered this new field of research. 00:10:42.190 --> 00:10:47.710 Um and that raises a lot of questions like how how did you discover that this was uh uh an 00:10:47.710 --> 00:10:48.750 underexplored topic? 00:10:48.910 --> 00:10:52.510 How did you uh uh move in this direction? 00:10:52.750 --> 00:10:56.750 Uh did did you slip on a plant and then uh 00:10:58.830 --> 00:11:00.110 like like what happened there? 00:11:00.580 --> 00:11:00.900 Yeah. 00:11:01.060 --> 00:11:04.340 Um, well, uh there uh several things kind of came together. 00:11:04.500 --> 00:11:10.260 So when I was in graduate school at UCSB, um I guess this it sort of uh 00:11:10.260 --> 00:11:15.060 intersects with the origin story of how I ended up in evolutionary psychology too, because 00:11:15.220 --> 00:11:21.220 coming out, I I'm my kind of deep time history as a scientist is in cognitive 00:11:21.220 --> 00:11:22.020 development. 00:11:22.180 --> 00:11:25.620 Um and I that's what I was doing when I was in undergrad. 00:11:25.780 --> 00:11:29.460 Um uh in addition to working in a behavior genetics lab. 00:11:29.700 --> 00:11:33.390 Um And so I was reading a lot of the work. 00:11:33.790 --> 00:11:35.470 This was early 2000s. 00:11:35.790 --> 00:11:39.230 I was reading a lot of the infant cognition work that was coming out at the time. 00:11:39.390 --> 00:11:44.670 People, you know, like Karen Wynne, Elizabeth Stalke, Susan Carey, 00:11:45.230 --> 00:11:51.070 Alan Leslie, people like that, talking about the kinds of 00:11:51.070 --> 00:11:54.590 systems you would expect to see in infant minds. 00:11:54.750 --> 00:12:00.620 And that was a very uh it remains, it's a domain-specific view that there are 00:12:01.100 --> 00:12:05.900 there are these um different people have different flavors of this, but to use uh Liz 00:12:05.980 --> 00:12:11.100 Felke's uh exam uh Liz Felke's framework, there are these different core knowledge systems, 00:12:11.180 --> 00:12:14.300 right, that are for different kinds of things. 00:12:14.460 --> 00:12:19.740 Um and so uh I had been working or thinking in in that um 00:12:20.300 --> 00:12:25.790 in that kind of way of, or I've been kind of steeped in that way of thinking. 00:12:26.110 --> 00:12:30.750 And when I applied to graduate school, I applied to work with Tams and German here to do 00:12:30.750 --> 00:12:31.630 theory of mind work. 00:12:31.710 --> 00:12:34.430 I was very interested in kind of thinking about thinking. 00:12:34.750 --> 00:12:38.430 But one of the other things that had always grabbed me in that work is there's a whole 00:12:38.430 --> 00:12:43.820 section on folk biology and intuitive biology and uh the kind of common 00:12:43.980 --> 00:12:49.980 sense understanding of the biological world, which basically boils down to plants and 00:12:49.980 --> 00:12:54.540 animals, but also includes things like how kids think about disease or other kinds of 00:12:54.540 --> 00:12:55.820 biological processes. 00:12:55.980 --> 00:12:59.820 There's just a really, there's a really interesting literature there that was very active 00:12:59.820 --> 00:13:02.620 in the late 90s and early 2000s. 00:13:03.590 --> 00:13:07.830 And uh so I had been kind of I had been familiar with that work. 00:13:08.070 --> 00:13:13.590 Um I uh back when I started graduate school was the days where you were 00:13:13.590 --> 00:13:16.950 accepted and then you were brought out for a recruitment weekend. 00:13:17.110 --> 00:13:19.670 So um I had been accepted to UCSB. 00:13:19.830 --> 00:13:25.750 I came for the recruitment weekend, uh, and I was among many other uh interesting 00:13:25.750 --> 00:13:31.110 conversations that I had, and of course the really good fit with my advisor, um, I was 00:13:31.110 --> 00:13:33.660 lucky enough to meet with Lita Cosmodies. 00:13:33.740 --> 00:13:37.660 And I did not know that she was Lita Cosmodies, you know. 00:13:37.820 --> 00:13:40.940 I uh because I had you heard had you heard of her at that point? 00:13:41.260 --> 00:13:41.820 No, uh-uh. 00:13:41.900 --> 00:13:46.460 No, because I I didn't know anything about evolutionary psychology and uh what I had the uh 00:13:46.700 --> 00:13:47.820 well that's not entirely true. 00:13:47.980 --> 00:13:53.500 The only thing I had heard about it was that it was all basically like 00:13:53.810 --> 00:13:55.170 fake and wrong. 00:13:55.570 --> 00:13:56.130 Garbage, yeah. 00:13:56.850 --> 00:13:59.570 Yeah, just in passing, that was what I had heard about it. 00:13:59.650 --> 00:14:04.370 And I but I I didn't hear enough of it to form an opinion one way or the other. 00:14:04.610 --> 00:14:06.770 Um I just really didn't know. 00:14:06.930 --> 00:14:12.610 So I I I came I here I was uh for the for the recruitment weekend I was talking to Lita and 00:14:12.610 --> 00:14:15.570 she asked me about um well what are you thinking about? 00:14:15.810 --> 00:14:19.250 And one of the things that I had been thinking about at that point when I had been reading 00:14:19.330 --> 00:14:23.010 is well how do you know what domains there should be? 00:14:23.260 --> 00:14:28.220 you know, because there's the at the time, it's there's objects, there's number, there's 00:14:28.220 --> 00:14:29.100 agency. 00:14:29.420 --> 00:14:33.420 Um, but why those and how would you carve them up? 00:14:33.580 --> 00:14:37.820 And so I said that to Lita, and she basically said, uh, I can teach you that. 00:14:38.060 --> 00:14:41.980 Um, and and so I came here and she did. 00:14:42.060 --> 00:14:46.700 Uh, and the other graduate students in the program here, and and my advisor. 00:14:46.860 --> 00:14:52.750 Um, and it was uh so that's I when I first got here, I knew 00:14:52.750 --> 00:14:54.430 nothing about evolutionary psychology. 00:14:54.590 --> 00:15:00.510 I remember um and if you ever do talk to Tams and German uh in in this, she can tell 00:15:00.510 --> 00:15:05.310 you, I remember going to her office early in graduate school and saying, It feels like 00:15:05.310 --> 00:15:10.350 they're all talking a different language and I have no idea what they're saying uh in the i 00:15:10.350 --> 00:15:12.590 in talking to the other graduate students here. 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 00:15:18.680 --> 00:15:19.880 an evolutionary approach. 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 00:15:24.840 --> 00:15:28.200 you do evolutionary psychology and an adaptationist approach. 00:15:28.360 --> 00:15:31.960 And it just seemed like it must be true, right? 00:15:32.040 --> 00:15:37.960 That if you are, if you want to understand the structure of the mind of 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 00:15:43.960 --> 00:15:49.730 that built the organism as a way of deriving predictions for what should be or 00:15:49.730 --> 00:15:53.170 what might be in what might be systems in the mind, right? 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 00:15:58.850 --> 00:15:59.170 true. 00:15:59.330 --> 00:16:02.690 And then the question was learning how, how to do that. 00:16:03.250 --> 00:16:05.250 Um, and so that's what I did. 00:16:05.410 --> 00:16:08.050 I was reading a ton, I was working on theory of mind. 00:16:08.130 --> 00:16:12.610 I did my dissertation on theory of mind, which is still a topic I find absolutely 00:16:12.620 --> 00:16:13.420 fascinating. 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 00:16:18.220 --> 00:16:20.860 theory of mind is the ability to sort of yeah. 00:16:21.260 --> 00:16:26.700 The the theory of mind is uh is the common sense understanding of that 00:16:27.020 --> 00:16:32.940 other people have mental states like beliefs, desires, um uh 00:16:33.740 --> 00:16:39.580 uh that basically motivate their behavior and that you can use to uh to interpret, predict, 00:16:39.660 --> 00:16:40.780 and explain their behavior. 00:16:41.260 --> 00:16:43.970 So you know it's almost it's it's such a weird. 00:16:44.210 --> 00:16:46.690 I remember when I first heard about theory of mine, I was like, that's weird. 00:16:46.770 --> 00:16:49.890 And I had this experience with almost everything, like vision or mechanisms. 00:16:49.970 --> 00:16:54.050 I had sort of this initial reaction of like, well, why do you need a mechanism for that? 00:16:54.370 --> 00:16:58.210 Because and I realized in retrospect, it was in David, I have talked about instinct 00:16:58.210 --> 00:17:03.970 blindness, where it was just instinct blindness, where it seems so obvious that it just 00:17:03.970 --> 00:17:04.450 happens. 00:17:04.530 --> 00:17:09.960 Like you never even think to think, oh, I think about people as having mental states, but 00:17:10.120 --> 00:17:14.600 you know, as John and Lead, I think, wrote one time, like bubble a bowl of oatmeal can't do 00:17:14.600 --> 00:17:15.160 that, you know. 00:17:15.320 --> 00:17:18.920 So, like, right, so that but it always felt like sort of alien. 00:17:19.000 --> 00:17:24.200 And I think like that's part of being a scientist is sort of thinking about there are these 00:17:24.200 --> 00:17:24.840 mechanisms. 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 00:17:29.160 --> 00:17:32.120 mechanisms for these very obvious systems. 00:17:32.840 --> 00:17:33.160 Right. 00:17:33.400 --> 00:17:34.010 Well, yeah. 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 00:17:37.370 --> 00:17:40.970 entryway into evolutionary psychology than we've heard from some of our other guests who 00:17:40.970 --> 00:17:44.250 sort of encountered it directly and saw the insights that it offered. 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 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? 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 00:17:59.450 --> 00:18:03.680 agents, uh, number, but like why those categories? 00:18:03.840 --> 00:18:05.520 Why not another set of categories? 00:18:05.680 --> 00:18:07.600 And that was the question that you were bringing to the table. 00:18:07.760 --> 00:18:10.560 Like where you were basically asking a deeper why question. 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 00:18:15.440 --> 00:18:17.360 approach to even begin to answer that question. 00:18:17.520 --> 00:18:21.440 So your entry point seems to be that you were asking this question that evolutionary 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 00:18:26.130 --> 00:18:27.170 about answering it. 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 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 00:18:37.410 --> 00:18:37.890 existed. 00:18:38.290 --> 00:18:38.690 That's right. 00:18:38.850 --> 00:18:39.890 Yeah, that's exactly right. 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 00:18:46.280 --> 00:18:52.280 lucky I was to literally stumble into Lita's office, basically, to find this out. 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 00:18:57.640 --> 00:19:03.320 an undergrad mindset where you're reading all kinds of things, and there's somebody out 00:19:03.320 --> 00:19:06.840 there who knows the answer and they're testing you on the thing. 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 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 00:19:17.590 --> 00:19:23.590 things to read right to basically find the answer um and uh I was lucky that 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 00:19:29.830 --> 00:19:34.950 you say it's not clear how else you could go about really 00:19:36.240 --> 00:19:41.680 really truly digging apart or really truly digging into what is uh 00:19:42.640 --> 00:19:45.920 why there would be certain systems in the mind, right? 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 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 00:19:56.240 --> 00:19:58.400 be there without an evolutionary approach. 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 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 00:20:08.210 --> 00:20:10.850 predictions about that are are correct. 00:20:11.330 --> 00:20:12.610 So yeah, it was it was luck. 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. 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 00:20:21.330 --> 00:20:25.170 they get to evolutionary psychology, there's usually this kind of like aha moment of like, 00:20:25.250 --> 00:20:27.330 oh, right, this just makes sense. 00:20:27.490 --> 00:20:31.970 And it was very clear uh talking to Lita, this just made sense. 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 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 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 00:20:44.440 --> 00:20:50.360 this discovery of evolutionary psychology before me, it made no sense for a while 00:20:50.520 --> 00:20:51.880 as I was learning. 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 00:20:58.370 --> 00:21:01.010 perspective I came from or if this is a common experience. 00:21:01.170 --> 00:21:06.770 But what I found is that in truly learning how to do an 00:21:06.770 --> 00:21:12.690 adaptationist approach, how to do evolutionary psychology the way that I do it, I 00:21:12.690 --> 00:21:16.290 would have these moments of, okay, this makes this completely makes sense. 00:21:16.450 --> 00:21:17.170 I get this. 00:21:17.410 --> 00:21:20.500 And then I would read more and then it would all kind of crumble apart, right? 00:21:20.580 --> 00:21:22.740 Or I'd think more and it would all kind of crumble apart. 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 00:21:27.460 --> 00:21:31.300 sense again as I was reading more things and thinking through things more deeply. 00:21:31.380 --> 00:21:33.300 And then it would kind of crumble again, right? 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 00:21:39.380 --> 00:21:41.380 reason, these things are hard for a reason. 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 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 00:21:52.630 --> 00:21:58.470 things through um because it's it's not the caricature of just thinking, oh hey, 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 00:22:04.470 --> 00:22:05.670 done X, Y, and Z. 00:22:05.750 --> 00:22:08.230 And now I'm gonna make predictions based on that. 00:22:08.310 --> 00:22:10.230 It's actually a lot more complicated than that. 00:22:10.310 --> 00:22:12.070 There's a lot more that goes into that. 00:22:12.420 --> 00:22:15.140 does take actual training and it's hard. 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 00:22:20.980 --> 00:22:22.740 you think you got it and then you don't. 00:22:22.980 --> 00:22:25.220 Have you thought about what that what was that? 00:22:25.380 --> 00:22:28.900 Like, do you have an idea of sort of what I don't know. 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 00:22:34.260 --> 00:22:34.580 things. 00:22:34.660 --> 00:22:39.530 It's something that with kind of tr counterintuitive concepts. 00:22:40.170 --> 00:22:40.490 Right? 00:22:40.730 --> 00:22:46.570 Like concepts that it takes training to flip out of the way you normally 00:22:46.570 --> 00:22:49.050 think about things to overcome your instinct blindness. 00:22:49.290 --> 00:22:51.290 Since we've talked about instinct blindness. 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, 00:22:57.450 --> 00:23:00.120 for lack of a better word, naturally approach a question. 00:23:00.440 --> 00:23:01.800 Um, it just slips in and out. 00:23:01.880 --> 00:23:02.760 I mean, I find this a lot. 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 00:23:07.240 --> 00:23:11.240 um uh uh heritability, right? 00:23:11.400 --> 00:23:13.160 Or like genes and environment. 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 00:23:18.840 --> 00:23:21.880 thinking through another question and you realize, oh wait, this is actually very 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 00:23:26.290 --> 00:23:32.290 different conceptual levels uh clear and what the boundary conditions of what you're 00:23:32.290 --> 00:23:32.850 thinking about. 00:23:32.930 --> 00:23:36.130 So it just is, yeah, it just slips, it slipped in and out. 00:23:36.370 --> 00:23:36.450 Right. 00:23:36.770 --> 00:23:36.930 Yeah. 00:23:37.010 --> 00:23:38.530 Like nobody was starting from zero. 00:23:38.850 --> 00:23:38.930 Yeah. 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 00:23:43.890 --> 00:23:44.770 selection pressures. 00:23:44.930 --> 00:23:49.800 I didn't know about, you know, the whole literature, the like hunter-gatherer studies and 00:23:49.800 --> 00:23:50.840 behavioral ecology. 00:23:51.160 --> 00:23:52.200 I didn't know that stuff. 00:23:52.280 --> 00:23:57.720 And so I was also adding these new pieces and adding these entire new pieces. 00:23:57.960 --> 00:24:03.800 It would help this process of really reframing how I was approaching the study of the 00:24:03.800 --> 00:24:06.920 human mind, but it would just like crumble briefly. 00:24:07.000 --> 00:24:08.600 And then you kind of put it back together. 00:24:08.680 --> 00:24:10.840 It was anyway, that's my experience of it. 00:24:11.370 --> 00:24:11.610 Yeah. 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 00:24:16.570 --> 00:24:22.090 blundering through uh in an overconfident way, which I see is unfortunately uh a trend 00:24:22.730 --> 00:24:26.650 uh in some uh corners of the internet regarding evolutionary psychology. 00:24:27.050 --> 00:24:29.690 Um I'm I'm unaware David, do you have references? 00:24:29.850 --> 00:24:30.410 I'm unaware of this. 00:24:30.490 --> 00:24:31.050 No, I'm kidding. 00:24:31.290 --> 00:24:31.770 Oh yeah. 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 00:24:39.440 --> 00:24:41.440 me how easy people think it is. 00:24:41.680 --> 00:24:42.000 Yeah. 00:24:42.160 --> 00:24:47.040 Uh and how people think they can do it after learning about it for two minutes. 00:24:47.280 --> 00:24:47.440 Yeah. 00:24:47.760 --> 00:24:52.560 Um there's a lot of like really lazy amateur evolutionary psychology out there. 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 00:24:58.640 --> 00:25:00.720 little training and so little depth of thought. 00:25:00.970 --> 00:25:04.170 Uh I mean, do you have any uh is it is it just instinct blind? 00:25:04.250 --> 00:25:05.610 I mean it can't just be that. 00:25:07.130 --> 00:25:08.250 That's a good question. 00:25:08.410 --> 00:25:10.250 I mean it's something I have thought about. 00:25:10.330 --> 00:25:13.450 I think it's just I don't know. 00:25:15.530 --> 00:25:21.290 So I don't think anyone would think about becoming a cognitive neuroscientist 00:25:21.290 --> 00:25:26.650 as something you could do just by thinking about it for a few minutes, right? 00:25:27.240 --> 00:25:27.560 Yeah. 00:25:28.120 --> 00:25:33.720 And but that's something that's kind of that's a method, right? 00:25:34.440 --> 00:25:40.440 Uh and I wonder if I wonder if the fact that at least from 00:25:40.440 --> 00:25:46.280 my perspective, what evolutionary psychology offers is a really rigorous, you know, logical 00:25:46.920 --> 00:25:48.600 theoretical framework. 00:25:49.000 --> 00:25:49.400 Right. 00:25:49.640 --> 00:25:55.160 And the complexity of the theoretical framework, I think, is something that 00:25:55.800 --> 00:26:01.730 um you can overlook right like you 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 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 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 00:26:18.880 --> 00:26:21.760 something that's specialized and does require training, right? 00:26:21.920 --> 00:26:27.120 Um but I think when there's certain there seem to be certain kinds of theoretical 00:26:27.120 --> 00:26:33.040 structures and even certain kinds of uh uh ways of doing science that people have uh 00:26:33.360 --> 00:26:37.120 are more likely to think are easier than they actually are. 00:26:37.280 --> 00:26:40.000 I actually find this, I mean this happens sometimes with baby stuff too. 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 00:26:45.710 --> 00:26:46.910 a study with babies. 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 00:26:52.110 --> 00:26:52.910 that method. 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 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 00:27:03.950 --> 00:27:04.830 it certainly does. 00:27:05.470 --> 00:27:06.280 That's that's really interesting. 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 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 00:27:13.640 --> 00:27:17.240 building a bridge versus you you like see somebody writing a book. 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. 00:27:21.640 --> 00:27:23.160 I don't have huge things of cement. 00:27:23.320 --> 00:27:24.360 Like that seems really hard. 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 00:27:28.600 --> 00:27:29.400 is required. 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 00:27:32.550 --> 00:27:34.710 write a book until they sit down and try to. 00:27:34.870 --> 00:27:38.550 And it's because all of the difficulty is abstract and hidden. 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 00:27:43.110 --> 00:27:48.710 complicated things are that might seem superficially not even worthy of notice, let alone 00:27:48.710 --> 00:27:54.340 consideration, let alone respect, like babies or like field work or like the 00:27:54.340 --> 00:27:55.860 difficulty of adaptationism. 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 00:28:01.220 --> 00:28:05.460 maybe combined with things like, you know, scientists who are, you know, kind of like, oh, 00:28:05.700 --> 00:28:09.940 babies, that's not scientific, you know, which is a different issue or a related issue. 00:28:10.100 --> 00:28:12.260 But but yeah, no, I I totally buy that. 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 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 00:28:22.420 --> 00:28:25.850 well, it's not a typewriter anymore but you you get the the proverbial typewriter. 00:28:25.930 --> 00:28:26.170 Yeah. 00:28:26.490 --> 00:28:26.810 Yeah. 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 00:28:31.930 --> 00:28:32.730 easily. 00:28:33.130 --> 00:28:33.610 Oh yeah. 00:28:33.770 --> 00:28:34.010 Right. 00:28:34.250 --> 00:28:37.210 I mean I think also do a bad version of cognitive neuroscience easily. 00:28:37.690 --> 00:28:39.210 Bang someone over the head with a hammer. 00:28:39.850 --> 00:28:40.170 Yes. 00:28:40.490 --> 00:28:41.930 Yeah that's true. 00:28:42.970 --> 00:28:44.490 Well I impaired your cognition. 00:28:44.570 --> 00:28:45.850 Wow I've new discovery. 00:28:46.250 --> 00:28:46.650 That's true. 00:28:47.130 --> 00:28:51.120 Um We once in grad school somebody did an MRI analysis. 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 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. 00:28:59.120 --> 00:29:01.280 And so somebody like had discovered the soul. 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 00:29:05.280 --> 00:29:07.760 brain activation outside of the skull. 00:29:07.920 --> 00:29:11.280 Um neuroscience joke. 00:29:11.520 --> 00:29:17.470 Not sure how So uh you're you're learning about what 00:29:17.470 --> 00:29:22.510 has been called core knowledge or the intuitions that uh babies bring to the table when 00:29:22.510 --> 00:29:23.390 they're learning about the world. 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 00:29:26.350 --> 00:29:29.070 preconceptions and no intuitions about anything. 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 00:29:33.550 --> 00:29:38.750 literature of studies that basically surprise babies by violating their expectations or 00:29:38.750 --> 00:29:42.350 violating their intuitions by essentially doing magic tricks for them. 00:29:43.280 --> 00:29:47.760 And you can study this scientifically by looking at how long a baby will stare at 00:29:47.760 --> 00:29:48.000 something. 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 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. 00:29:55.360 --> 00:29:59.920 And using that simple premise, you can study all these things about how babies think and 00:30:00.000 --> 00:30:02.960 and the intuitions that babies have about the world. 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 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 00:30:13.450 --> 00:30:14.090 they are. 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 00:30:20.090 --> 00:30:22.170 potential uh area of inquiry? 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 00:30:28.330 --> 00:30:34.090 psychology, doing my work on theory of mind, and um my work on theory of mind 00:30:34.900 --> 00:30:40.180 um uh was very heavily informed by alan leslie's work. 00:30:40.420 --> 00:30:46.260 And uh that was a lot of, you know, task analysis work of how do you 00:30:46.260 --> 00:30:49.780 build a successful model of theory of mind performance? 00:30:50.340 --> 00:30:56.020 How does that how how and how would different models explain the kind of 00:30:56.020 --> 00:31:01.410 data that you see when you test young kids at the time on 00:31:02.050 --> 00:31:03.170 theory of mind tasks. 00:31:03.330 --> 00:31:09.330 So I was learning not only kind of these broader questions or thinking 00:31:09.330 --> 00:31:15.330 about these broader questions of what are kind of core knowledge systems and what are 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 00:31:19.490 --> 00:31:25.260 do the nitty-gritty of unpacking what would successful performance look like on a 00:31:25.260 --> 00:31:26.060 particular task. 00:31:26.140 --> 00:31:26.300 Right. 00:31:26.460 --> 00:31:28.380 So that was extremely useful. 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 00:31:34.060 --> 00:31:34.940 day-to-day stuff. 00:31:35.020 --> 00:31:36.540 I really like theory of mind work. 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. 00:31:40.620 --> 00:31:43.340 Um I really, it was fascinating to think about. 00:31:43.420 --> 00:31:49.310 I learned a huge amount, and uh I have a huge amount of respect 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 00:31:55.230 --> 00:31:57.230 and everybody was working on it. 00:31:57.470 --> 00:32:03.470 And I had the uh experience of submitting papers and getting the kind of like, 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 00:32:09.150 --> 00:32:12.880 version of theory of mind, my particular theoretical structure. 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, 00:32:16.960 --> 00:32:18.880 but that was sort of grading on me. 00:32:19.280 --> 00:32:25.280 And at the same time, I'm sitting in on these on the Center for Evolutionary 00:32:25.280 --> 00:32:26.560 Psychology meetings. 00:32:27.040 --> 00:32:30.080 And at the time when I was a graduate student, I really was just sitting there. 00:32:30.160 --> 00:32:31.040 I was very shy. 00:32:31.200 --> 00:32:35.110 I did not talk for most of my graduate career. 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 00:32:39.750 --> 00:32:45.110 to HBus uh and uh connecting with um, you know, 00:32:45.590 --> 00:32:51.190 uh uh biological anthropologists and behavioral ecologists and primatologists and seeing 00:32:51.190 --> 00:32:52.630 the kind of work they were doing. 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 00:32:58.740 --> 00:33:02.820 work uh and looking at human life history trajectories. 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 00:33:08.180 --> 00:33:14.100 caloric returns for hunting uh and kind of the age curves for when you 00:33:14.100 --> 00:33:18.730 finally start to bring in more calories than you're using through hunting. 00:33:19.130 --> 00:33:20.010 And when when is that point? 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. 00:33:26.890 --> 00:33:28.570 Yeah, I think it's 40s or 50s, right? 00:33:28.650 --> 00:33:28.890 I think it's a good thing. 00:33:33.050 --> 00:33:34.810 Remember the remember Mike Irvin's work. 00:33:34.970 --> 00:33:35.130 I know. 00:33:35.530 --> 00:33:35.850 I know. 00:33:36.170 --> 00:33:38.810 I'm really glad you said that, David, because I feel the same way too. 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, 00:33:44.800 --> 00:33:46.400 twenty years ago probably at this point. 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. 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 00:33:56.480 --> 00:33:56.720 work. 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 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 00:34:05.440 --> 00:34:07.840 plants, it's gathered plant resources. 00:34:08.290 --> 00:34:10.130 Dot move back to hunting. 00:34:10.290 --> 00:34:14.610 And I was like thinking, I'm like, hang on, how do you do that? 00:34:14.850 --> 00:34:20.370 Like what are the set of cognitive skills that are required to do that? 00:34:20.450 --> 00:34:25.250 Because that actually, even though it's reliable, that actually doesn't seem easy if you 00:34:25.250 --> 00:34:26.610 start thinking about it. 00:34:26.770 --> 00:34:30.370 And so that kind of grabbed my attention and I started thinking about it. 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. 00:34:35.100 --> 00:34:35.980 Uh we were both. 00:34:36.460 --> 00:34:37.100 News to me. 00:34:38.860 --> 00:34:39.100 I know. 00:34:39.180 --> 00:34:39.820 I don't know about it. 00:34:41.660 --> 00:34:42.460 Yeah, thanks. 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 00:34:48.540 --> 00:34:49.020 Barbara. 00:34:49.100 --> 00:34:51.180 And so we were up in the mountains. 00:34:51.420 --> 00:34:53.100 This was basically parents. 00:34:53.260 --> 00:34:54.140 So we had time to do it. 00:34:54.380 --> 00:34:56.140 Yes, this is preparenting. 00:34:56.220 --> 00:34:57.980 Now we don't go in the mountains. 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. 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. 00:35:08.310 --> 00:35:13.270 And there's a this is also pre like um pre uh 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 00:35:18.630 --> 00:35:21.430 we would uh we would run with our with our friends. 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 00:35:25.110 --> 00:35:27.270 stuck this far out, I would die. 00:35:27.750 --> 00:35:30.820 Um but people did this. 00:35:30.980 --> 00:35:32.500 Like people did this here. 00:35:32.660 --> 00:35:36.740 They did this here successfully for thousands and thousands of years. 00:35:37.060 --> 00:35:38.660 How do you do this? 00:35:38.820 --> 00:35:41.460 And so I was just kind of thinking about all of these things. 00:35:41.620 --> 00:35:43.700 And I just, I just started thinking through the problem. 00:35:43.780 --> 00:35:44.980 It just was interesting to me. 00:35:45.060 --> 00:35:47.060 I've kind of always kind of liked plants. 00:35:47.140 --> 00:35:49.780 I find them interesting and fruits and things like that. 00:35:49.940 --> 00:35:55.630 Um, I never have gotten into being a a super gardener yet, but I 00:35:55.710 --> 00:35:59.390 I I can see that coming someday. 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 00:36:06.270 --> 00:36:08.830 see you writing some self-help book about the wisdom of flowers. 00:36:09.470 --> 00:36:10.030 Something like that. 00:36:10.190 --> 00:36:11.950 I think that could bring in some money for you. 00:36:12.430 --> 00:36:14.190 I'll I'll I'll keep that in mind for the title. 00:36:14.430 --> 00:36:15.310 Thanks to it. 00:36:16.360 --> 00:36:17.960 Um yeah, but it was so much. 00:36:19.880 --> 00:36:21.880 Oh, uh it's so ripe for puns. 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 00:36:27.000 --> 00:36:29.320 because I find it I I just I don't know. 00:36:29.800 --> 00:36:30.360 No, it's a contention. 00:36:30.840 --> 00:36:31.480 Life is hard enough. 00:36:31.560 --> 00:36:32.440 You might as well have puns now. 00:36:32.840 --> 00:36:33.560 No, I'm pro pun. 00:36:33.720 --> 00:36:35.880 I'm I'm firmly on the pro pun side. 00:36:35.960 --> 00:36:38.760 I think we me need more levity uh in in our science. 00:36:39.080 --> 00:36:39.560 Oh yes. 00:36:39.960 --> 00:36:42.920 Some people disagree with me, but I'm I'm firmly on the side of fun. 00:36:43.650 --> 00:36:44.370 Me too. 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. 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. 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 00:37:00.290 --> 00:37:01.410 theory of mind stuff. 00:37:01.570 --> 00:37:03.330 So I was thinking about theory of mind stuff. 00:37:03.410 --> 00:37:04.530 I was doing the theory of mind stuff. 00:37:04.610 --> 00:37:05.970 I was doing my dissertation. 00:37:06.050 --> 00:37:10.930 Um, I was working on the papers for that, um, and just getting intensely frustrated. 00:37:11.170 --> 00:37:15.220 Um, And uh but then I just had the time to think and I could. 00:37:15.700 --> 00:37:21.700 And I um then when we got our PhDs, Dave and I, 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 00:37:27.940 --> 00:37:33.460 Center at Yale because this was the time when um she was looking at social relationship 00:37:33.550 --> 00:37:37.630 stuff and group kinds of things and his work fit really well. 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 00:37:43.550 --> 00:37:46.430 wasn't a specific project that it was tied to. 00:37:46.670 --> 00:37:52.190 And so I had a a meeting, Karen Wynne was here in Santa 00:37:52.190 --> 00:37:52.830 Barbara. 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 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. 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 00:38:08.400 --> 00:38:09.840 for your postdoc project? 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. 00:38:14.320 --> 00:38:20.210 And so I talked about some action perception and theory of mind kind of 00:38:20.210 --> 00:38:23.490 uh ideas that I had been thinking about and that I found very interesting. 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 00:38:29.170 --> 00:38:32.450 might be design in the human mind for learning about plants. 00:38:32.610 --> 00:38:34.290 And we could look at that in babies. 00:38:34.450 --> 00:38:39.330 And she, I mean, this is you know, condensing down the conversation, but she was basically 00:38:39.330 --> 00:38:41.090 like, Oh, yes, go do that. 00:38:41.250 --> 00:38:45.490 Uh, and so that's how we started working on that. 00:38:45.650 --> 00:38:50.500 Um, she taught me how to do the actual baby studies. 00:38:50.820 --> 00:38:55.940 And this is also when Kylie Hamlin was a PhD student in the lab. 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 00:39:01.380 --> 00:39:02.500 watching her do her thing. 00:39:02.660 --> 00:39:05.620 Kylie is a baby testing master. 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 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 00:39:17.130 --> 00:39:19.290 start that may be fruitful, huh? 00:39:19.530 --> 00:39:21.130 For uh for looking at. 00:39:21.290 --> 00:39:27.130 Um, and uh and so we started with some of these basic questions about you know, 00:39:27.450 --> 00:39:33.260 a very basic level of is there evidence that babies are sensitive to the kind 00:39:33.260 --> 00:39:37.020 of harm that plants can inflict on humans. 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 00:39:42.700 --> 00:39:45.260 set up for learning about plants? 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 00:39:51.580 --> 00:39:54.060 couple papers looking at those questions. 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, 00:39:58.540 --> 00:39:59.740 hey, here's this new idea. 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 00:40:05.830 --> 00:40:06.230 do this. 00:40:06.390 --> 00:40:09.510 And that's what I did for like almost a decade. 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 00:40:15.430 --> 00:40:17.430 kinds of different aspects of that question. 00:40:17.510 --> 00:40:20.070 And that's what I'm continuing to do here. 00:40:20.390 --> 00:40:23.510 Um, but yeah, and I there's a ton to do. 00:40:23.590 --> 00:40:27.030 It turns out plants are really complicated, it's very fun to think about. 00:40:27.800 --> 00:40:28.120 Totally. 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 00:40:34.200 --> 00:40:34.760 things. 00:40:34.920 --> 00:40:40.120 Um, one is a frustration with the sort of faddishness in in social science. 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. 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 00:40:50.440 --> 00:40:50.920 of competition. 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. 00:40:55.550 --> 00:40:57.310 Uh, it's hard to break in. 00:40:57.470 --> 00:41:00.830 Um and so that uh i i is inherently limiting. 00:41:00.910 --> 00:41:06.110 So a continued frustration with that and trying to find something new um that you could 00:41:06.110 --> 00:41:07.470 carve out for yourself. 00:41:07.710 --> 00:41:13.310 And the other was um, I think a uh a glimpse of 00:41:13.500 --> 00:41:15.100 of the wave of a hand. 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, 00:41:19.740 --> 00:41:23.340 uh uh uh gathering plant food as a as a source of calories. 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 00:41:27.180 --> 00:41:29.900 going on there with that wave of the hand about plant food? 00:41:29.980 --> 00:41:33.020 That's there's a lot in there that's being dismissed. 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 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. 00:41:43.250 --> 00:41:45.330 You can't just you can't just wave your hand like there. 00:41:45.730 --> 00:41:48.770 There's there's something underneath there, there's something more complicated. 00:41:48.930 --> 00:41:54.690 Uh it teaches you to be uh to have a better eye about, you know, uh 00:41:55.010 --> 00:42:00.740 what what questions have not been asked, what uh what answers have not been given, 00:42:00.900 --> 00:42:05.060 um, and it helps you go uh in in a in a really good direction. 00:42:05.220 --> 00:42:09.140 Um so is is that a fair characterization of how you you ended up here? 00:42:09.220 --> 00:42:15.140 Uh you know, a a a frustration of of faddishness and a um and I 00:42:15.140 --> 00:42:19.860 guess a vigilance against having, you know, the wool pulled over your eyes or or a 00:42:19.860 --> 00:42:24.750 vigilance against just glib uh answers to questions that don't really get into the 00:42:24.750 --> 00:42:25.310 complexity. 00:42:25.870 --> 00:42:27.070 Yeah, I mean I it's close. 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 00:42:32.910 --> 00:42:34.190 better than it actually was. 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 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 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 00:42:50.580 --> 00:42:50.980 theory. 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. 00:42:55.300 --> 00:42:56.100 Thank you very much. 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 00:43:00.980 --> 00:43:06.580 shy, but that is what was that that more kind of um maybe uh 00:43:06.820 --> 00:43:10.420 juvenile motivation was was behind that. 00:43:11.300 --> 00:43:12.340 Thank goodness you had it. 00:43:12.450 --> 00:43:16.530 You know, I like we we we know n next to nothing about plant cognition. 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 00:43:21.970 --> 00:43:25.090 good to have a diversified approach to the discovery of knowledge. 00:43:25.170 --> 00:43:27.490 Uh we don't wanna all be studying the same thing. 00:43:27.810 --> 00:43:28.450 No, it's true. 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 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. 00:43:38.400 --> 00:43:40.240 It was sort of like I took my ball and went home. 00:43:40.400 --> 00:43:41.280 You know what I mean? 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 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 00:43:52.560 --> 00:43:54.320 is actually really complicated. 00:43:54.560 --> 00:44:00.010 And I you're exactly right, there's a vigilance for that is a problem 00:44:00.650 --> 00:44:05.130 that people have been solving, and it's actually pretty a lot more complex. 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. 00:44:10.570 --> 00:44:10.810 Oh, yeah. 00:44:10.970 --> 00:44:13.210 Don't mean to just Mike Irvin by any stretch of the imagination. 00:44:13.530 --> 00:44:13.930 No, no, no. 00:44:14.250 --> 00:44:17.130 And you know, we all focus on what we focus on, right? 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, 00:44:22.810 --> 00:44:23.050 right? 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 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. 00:44:33.440 --> 00:44:38.640 Um, but it was very much that vigilance for like, okay, yes, this this requires an 00:44:38.640 --> 00:44:39.600 explanation. 00:44:39.840 --> 00:44:42.800 And how is that how is that happening? 00:44:42.960 --> 00:44:48.800 And then critically, having been trained in how to do an adaptationist approach, 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 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, 00:44:58.950 --> 00:45:02.390 not I mean holistic is the wrong word, but in a focused way, right? 00:45:02.550 --> 00:45:06.470 Because people have gotten to pieces of this. 00:45:06.550 --> 00:45:12.470 You know, like there are people like um Liz Cashton had some work looking in in 00:45:12.470 --> 00:45:18.420 the uh mid 90s, looking at why kids are neophobic about um 00:45:18.740 --> 00:45:20.020 about vegetables, right? 00:45:20.100 --> 00:45:22.420 Like why do little kids not want to eat their vegetables? 00:45:22.660 --> 00:45:28.340 And um uh uh um Margie Prophet in the adapted mind 00:45:28.580 --> 00:45:32.020 has the whole thing about plant toxins and uh pregnancy. 00:45:32.260 --> 00:45:38.260 Susan Gelman um had uh had work actually looking at how young kids think 00:45:38.260 --> 00:45:39.110 about plants. 00:45:39.750 --> 00:45:41.910 Again, that was in the kind of mid-90s. 00:45:41.990 --> 00:45:45.590 This was, as I said, there's that whole intuitive biology literature, right? 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 00:45:51.430 --> 00:45:57.110 of Susan Gelman's work, as far as I'm aware, almost all of it was 00:45:57.750 --> 00:46:00.440 how are plants and animals the same, right? 00:46:00.840 --> 00:46:04.520 So, like, uh, how do living things work, right? 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 00:46:09.400 --> 00:46:09.720 plants. 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 00:46:15.480 --> 00:46:21.190 to six, can know things like um plants like animals grow, Plants like 00:46:21.190 --> 00:46:24.710 animals can uh need food and water to grow. 00:46:24.870 --> 00:46:30.230 They can get heal themselves after they get damaged and they can die. 00:46:30.390 --> 00:46:35.430 Like they know these kinds of things about both both sets of entities. 00:46:35.750 --> 00:46:40.870 But there again, that's another place where the evolutionary approach, you look at that and 00:46:40.870 --> 00:46:44.230 you're like, okay, sure, there's commonalities between plants and animals, but if you're 00:46:44.230 --> 00:46:50.120 thinking adaptive problem first, of what how are you as uh either a young human or 00:46:50.120 --> 00:46:52.520 even an adult, how are you engaging with these things? 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 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 00:47:03.000 --> 00:47:08.840 from this, um, which is that uh it is uh plants are plants 00:47:08.840 --> 00:47:11.110 are rooted to the ground, right? 00:47:11.190 --> 00:47:16.230 And because plants are rooted to the ground, that's a very different thing than animals 00:47:16.390 --> 00:47:17.430 that can move around. 00:47:17.590 --> 00:47:23.430 So, like the example of dangerous plants and dangerous animals, um a dangerous spider, 00:47:23.590 --> 00:47:29.430 a poisonous spider, a poisonous snake, um, a uh a lion, whatever, 00:47:29.670 --> 00:47:34.550 big dangerous animals, small dangerous animals, all of those things can come to you. 00:47:34.720 --> 00:47:37.520 You have to be vigilant about them in different ways. 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, 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. 00:47:48.160 --> 00:47:51.200 But none of that happens unless you go to the plant. 00:47:51.680 --> 00:47:52.000 Right. 00:47:52.800 --> 00:47:58.800 So even though the danger, you the danger of injury or the danger of death 00:47:58.800 --> 00:48:02.870 is there in both cases, it's very different how it plays out. 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 00:48:07.990 --> 00:48:11.670 likely have different characteristics and different design features. 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. 00:48:17.750 --> 00:48:23.590 Um so there's there's pieces in the literature, but not from the standpoint of 00:48:23.700 --> 00:48:29.620 what is what are the broader adaptive problems really of humans dealing with plants and how 00:48:29.620 --> 00:48:34.900 would you see what what would the cognitive systems for those kinds of problems look like 00:48:34.900 --> 00:48:40.820 in babies and in uh young kids right so it's that 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 00:48:46.580 --> 00:48:50.750 school book, you know, it's thinking of this privilege class of what would there be 00:48:50.750 --> 00:48:52.990 selection pressures for for people. 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 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 00:49:03.070 --> 00:49:03.950 wallpaper. 00:49:04.110 --> 00:49:05.870 But that's very unusual. 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 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. 00:49:15.320 --> 00:49:17.160 And that is super not trivial. 00:49:17.320 --> 00:49:20.040 Um, as you said, like I'm sure all of us would die. 00:49:20.200 --> 00:49:23.880 Um, probably Annie, you would probably survive the longest of the three of us. 00:49:24.040 --> 00:49:24.760 David, I don't know. 00:49:24.840 --> 00:49:27.800 Who do you think if we were in the wilderness, who would go first? 00:49:28.200 --> 00:49:29.800 Oh, I would go first, definitely. 00:49:31.000 --> 00:49:33.000 I didn't want to say it, but I don't know. 00:49:33.240 --> 00:49:33.720 We'll we'll see. 00:49:34.120 --> 00:49:35.640 We we've been through this many times. 00:49:36.680 --> 00:49:42.050 Every time we bring on an anthropologist, I'm like shivering with fear to describe what 00:49:42.050 --> 00:49:42.690 they've been through. 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 00:49:49.250 --> 00:49:50.610 thing of affordances, right? 00:49:50.690 --> 00:49:52.290 Like what does this thing afford? 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 00:49:57.730 --> 00:50:01.890 secondary compounds, these pesticides, like there's just a ton of these chemicals. 00:50:01.970 --> 00:50:03.410 And I I just love that. 00:50:03.570 --> 00:50:09.540 You know, this your your talks are incredibly logical in the sense of plants, even though 00:50:09.540 --> 00:50:11.860 they look like wallpaper, are fundamentally important. 00:50:11.940 --> 00:50:16.900 They literally are like life and death for eating and also other stuff like you know, 00:50:17.140 --> 00:50:17.780 construction. 00:50:18.340 --> 00:50:21.380 But then they're super, super dangerous. 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 00:50:26.660 --> 00:50:31.060 about even like tomatoes, like the leaves of the tomato plant, it's like a deadly 00:50:31.060 --> 00:50:31.940 nightshade family. 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, 00:50:37.170 --> 00:50:38.930 it's still like super dangerous, right? 00:50:39.010 --> 00:50:40.770 Like plants are just super dangerous. 00:50:41.010 --> 00:50:41.330 Yeah. 00:50:41.570 --> 00:50:44.610 Don't eat tomato leaves, don't eat potato leaves. 00:50:44.930 --> 00:50:46.370 Don't eat raw potatoes, also. 00:50:46.930 --> 00:50:48.130 Don't eat raw potatoes, yeah. 00:50:48.290 --> 00:50:48.690 Yeah. 00:50:48.930 --> 00:50:49.250 Yeah. 00:50:49.490 --> 00:50:55.250 I mean, this is what's it's uh plants are really complicated and 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 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 00:51:05.420 --> 00:51:06.140 goes, huh? 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 00:51:11.900 --> 00:51:12.700 sort of expect that. 00:51:12.780 --> 00:51:15.020 And sometimes now they go, oh, you're the one. 00:51:15.180 --> 00:51:20.540 Um, but uh, but um there's usually kind of like, 00:51:21.100 --> 00:51:22.490 well, I get asked a lot of things. 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? 00:51:27.130 --> 00:51:29.610 It's something I get asked a lot. 00:51:29.690 --> 00:51:31.770 And I said, Well, I was looking for this. 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 00:51:36.090 --> 00:51:37.290 looking for this. 00:51:37.530 --> 00:51:43.130 Um, and uh and then the the second thing is kind of a oh, well, okay, 00:51:43.210 --> 00:51:48.880 maybe I guess, but you know, people have this idea very much built on their own 00:51:48.880 --> 00:51:51.680 experience that plants are just like not that important. 00:51:52.080 --> 00:51:57.920 Um, and then when you start to when you start to get people thinking about, 00:51:58.400 --> 00:52:04.320 first of all, as Dave mentioned, in worlds where people are living in wild 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 00:52:08.720 --> 00:52:11.040 you gonna get your plant foods, right? 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 00:52:14.800 --> 00:52:20.590 really tricky because they all have, as you heard from Ed, they all have these toxic 00:52:20.590 --> 00:52:22.510 secondary compounds in them. 00:52:22.830 --> 00:52:26.830 Um, they all have toxic secondary compounds. 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 00:52:32.030 --> 00:52:32.590 humans. 00:52:32.750 --> 00:52:36.990 Um, and Ed probably talked about how we have enzymatic pathways. 00:52:37.070 --> 00:52:39.790 There's all kinds of defenses that we have against plants. 00:52:39.870 --> 00:52:45.230 Like our physiology is really adapted to these things, and not just us, but 00:52:45.320 --> 00:52:51.160 existing off of uh of um wild forage plant resources, this is 00:52:51.160 --> 00:52:56.760 something that applies to all kinds of other animals, arguably most other 00:52:56.760 --> 00:52:57.560 animals, right? 00:52:57.800 --> 00:52:57.960 Right. 00:52:58.120 --> 00:53:02.040 If you were to do like a pie chart of likely selection pressures, yes. 00:53:02.360 --> 00:53:07.960 Plants, contrary to the intuition, like this probably the most certain 00:53:08.280 --> 00:53:14.040 stable feature that that like animals have been, you know, dealing 00:53:14.040 --> 00:53:19.770 with for really really long time well well prior to um you know whatever 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 00:53:25.770 --> 00:53:31.530 of plants is like plants and insects um and it's uh it's 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 00:53:37.800 --> 00:53:43.720 one of the benefits of also doing this and starting this in my 20s is I 00:53:44.200 --> 00:53:46.920 I just knew this had to be true. 00:53:47.240 --> 00:53:47.560 Right. 00:53:47.800 --> 00:53:50.440 Like it now I think I'd be more risk averse. 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 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 00:54:01.800 --> 00:54:02.760 you have, right? 00:54:03.080 --> 00:54:05.870 Um, but uh but it had to be true. 00:54:05.950 --> 00:54:11.790 There had it, they they why would an entity that 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 00:54:17.550 --> 00:54:22.910 fundamental that just like consumes these things, eats these things, why would there not be 00:54:23.070 --> 00:54:26.190 psychology for engaging with plants? 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 00:54:31.310 --> 00:54:33.630 that this kind of organism exists on? 00:54:33.880 --> 00:54:34.200 right? 00:54:34.440 --> 00:54:40.120 Um, and so I, from that perspective, it yeah, it it it had to be true. 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 00:54:46.120 --> 00:54:47.480 the details, right? 00:54:47.560 --> 00:54:53.560 So I might be wrong about the way that the uh psychology is 00:54:53.560 --> 00:54:55.320 set up to deal with plants. 00:54:55.570 --> 00:54:57.250 that's entirely possible. 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. 00:55:03.250 --> 00:55:03.490 Right. 00:55:03.650 --> 00:55:03.890 Right. 00:55:04.050 --> 00:55:04.690 In some way. 00:55:04.850 --> 00:55:10.130 Like some aspects of human psychology must be set up to deal with plants. 00:55:10.210 --> 00:55:10.450 Yeah. 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 00:55:15.970 --> 00:55:18.600 there there should, and it's a good place you should. 00:55:18.680 --> 00:55:20.520 Like there should be something there for that. 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? 00:55:26.280 --> 00:55:26.520 Right. 00:55:26.760 --> 00:55:27.640 Um yeah. 00:55:27.800 --> 00:55:29.480 So it seemed like a safe bet. 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 00:55:34.360 --> 00:55:39.960 career, I had a kind of passing conversation with Paul Bloom, who was uh who was 00:55:40.270 --> 00:55:43.470 uh kind of a co-advisor at the at the time. 00:55:43.630 --> 00:55:47.310 Um and he said something like, Yeah, this was actually brave to do this. 00:55:47.550 --> 00:55:49.710 I thought and it was the first time I thought about it. 00:55:49.790 --> 00:55:53.310 And I was like, oh no, this this could have been a huge mistake. 00:55:54.190 --> 00:55:56.990 But uh but yeah, it it ended up working out. 00:55:57.150 --> 00:55:58.430 Um all right. 00:55:58.590 --> 00:56:00.750 So you took this uh this leap of faith. 00:56:00.910 --> 00:56:03.070 Well I it's actually it's a more of a leap of logic, I think. 00:56:03.150 --> 00:56:05.390 I think there's really rigorous and solid logic. 00:56:05.470 --> 00:56:07.630 So I don't think it was a leap at all. 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 00:56:14.040 --> 00:56:19.960 walking out onto a new field, another plant metaphor, um, uh, you know, ten years 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 00:56:24.680 --> 00:56:26.040 empirical evidence. 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 00:56:31.640 --> 00:56:33.000 features of this the system? 00:56:33.160 --> 00:56:35.640 What have you learned uh in the past decade or so? 00:56:36.070 --> 00:56:36.710 Yeah, sure. 00:56:36.870 --> 00:56:41.270 So the the overarching thing is the that um 00:56:42.150 --> 00:56:48.070 fundamentally because humans are i uh huh well here 00:56:48.230 --> 00:56:49.270 let me just step back. 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 00:56:55.510 --> 00:57:01.110 a large portion of what is going on in humans is likely to involve social learning, 00:57:01.300 --> 00:57:01.620 right? 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. 00:57:08.020 --> 00:57:13.700 They are edible, um, but they are also dangerous and they can be that in very 00:57:13.700 --> 00:57:14.660 specific ways. 00:57:14.900 --> 00:57:20.660 So most cases plants are um only edible uh or like it's certain 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 00:57:26.820 --> 00:57:31.390 how that's not entirely the case, but that's that's how it works. 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. 00:57:36.430 --> 00:57:42.110 And so that unlocks a lot of plant resources that are otherwise toxic. 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, 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 00:57:52.510 --> 00:57:54.270 of staples of human diets. 00:57:54.350 --> 00:58:00.280 If you look in uh in small scale and small scale indigenous societies you see 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 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 00:58:10.680 --> 00:58:16.600 they're the they are these um staple kind of core basis of and of 00:58:16.600 --> 00:58:22.600 the of the caloric intake um so what that means though is that as a 00:58:22.600 --> 00:58:27.770 human being when you are dropped, when you're born, you're basically dropped into a 00:58:27.770 --> 00:58:29.370 particular environment. 00:58:30.010 --> 00:58:34.810 You can't know in advance what the plant life around you is going to be. 00:58:35.130 --> 00:58:41.050 Um, so because we are omnivores and we don't specialize in like one or 00:58:41.050 --> 00:58:46.820 two particular plants, like some species do, you can't build in something 00:58:46.820 --> 00:58:49.940 that's more like a template for like find this particular plant. 00:58:50.100 --> 00:58:55.140 And if you find this particular plant or this particular features of plants, then you know 00:58:55.220 --> 00:58:56.980 you're fine, go ahead and eat it. 00:58:57.140 --> 00:58:58.420 We're not set up that way. 00:58:58.580 --> 00:59:04.100 We have this large diet breadth, and because we specialize in these higher caloric 00:59:04.100 --> 00:59:09.700 density parts that require processing beforehand, it means 00:59:09.940 --> 00:59:15.590 that any individual human can't construct a human diet on their own, 00:59:15.830 --> 00:59:16.150 right? 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 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 00:59:26.630 --> 00:59:31.990 start eating particular plants and seeing what happens based on what happens to you when 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 00:59:37.920 --> 00:59:39.200 and out of commission. 00:59:39.360 --> 00:59:41.120 At worst, you're going to die. 00:59:41.360 --> 00:59:46.480 And so instead, what you see, and now I've done this with some 00:59:46.480 --> 00:59:52.480 collaborators, is when you run selection dynamic models, when you run the math 00:59:52.480 --> 00:59:58.150 on this, these circumstances select for the evolution of social learning mechanisms 00:59:58.390 --> 01:00:04.390 where instead of trial and error learning the information for yourself, you instead 01:00:04.470 --> 01:00:10.310 the mechanisms are set up to learn the information from the people in your local 01:00:10.310 --> 01:00:12.790 environment who already know it, right? 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 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, 01:00:22.820 --> 01:00:23.140 right? 01:00:23.460 --> 01:00:28.980 Again, this is this is it clearly there is a process there by which the first 01:00:28.980 --> 01:00:33.380 individual figured out that you could eat this, and then the the individuals along the way 01:00:33.460 --> 01:00:37.940 across generations figured out, for example, the processing techniques and things like that 01:00:38.020 --> 01:00:42.900 that you could do, and you have this kind of cumulative cultural evolution of these kinds 01:00:42.900 --> 01:00:45.060 of uh of these aspects of things. 01:00:45.220 --> 01:00:48.930 For right now, for me, that stuff is black boxed, right? 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 01:00:53.810 --> 01:00:54.130 there. 01:00:54.450 --> 01:01:00.370 And then given that babies are dropped into a world where that exists, then the 01:01:00.370 --> 01:01:04.850 argument is that their their psychology, particularly our psychology, human psychology, 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 01:01:10.930 --> 01:01:15.720 really geared towards getting that information from watching what other people do, Right. 01:01:16.040 --> 01:01:21.960 So what we have found is at a broad level 01:01:22.280 --> 01:01:28.120 is that infants show evidence of a psychology that is designed 01:01:28.120 --> 01:01:34.040 for balancing the costs and benefits of plants, such that when infants are first 01:01:34.040 --> 01:01:40.030 confronted with unfamiliar plants, they show a reluctance to 01:01:40.030 --> 01:01:43.710 reach out and touch plants compared to other things. 01:01:43.950 --> 01:01:49.230 So we do this by uh we test babies with a series of different objects. 01:01:49.390 --> 01:01:54.830 We have real plants, we have artificial plants that look very realistic, but we 01:01:54.830 --> 01:01:56.750 include them for two reasons. 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 01:02:02.540 --> 01:02:04.380 testing, and the real plants do. 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. 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 01:02:13.500 --> 01:02:18.540 weren't just getting babies responding to stuff that smelled one way versus things that 01:02:18.540 --> 01:02:19.580 don't smell at all. 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 01:02:25.530 --> 01:02:31.290 examine whether babies are responding to plants per se, or are they responding to 01:02:31.290 --> 01:02:32.090 particular features? 01:02:32.170 --> 01:02:38.170 Like is it a broader class of anything that's green or anything that has 01:02:38.170 --> 01:02:41.770 some a particular kind, particular kinds of shapes? 01:02:42.250 --> 01:02:44.250 So we build these artifacts. 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 01:02:50.120 --> 01:02:54.440 artifacts that share features of the plants, but they when you see them especially up 01:02:54.440 --> 01:02:56.680 close, they are definitely not plants. 01:02:56.920 --> 01:03:02.440 Um we also include familiar objects, objects that are both things that 01:03:02.440 --> 01:03:07.320 babies would uh would use all the time themselves, like little board books, and then 01:03:07.320 --> 01:03:12.280 objects that would also be things that parents would caution babies about using. 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 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. 01:03:23.630 --> 01:03:29.550 And then we have another category of stimuli that are other inanimate natural kinds that 01:03:29.550 --> 01:03:30.350 are not plants. 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 01:03:36.110 --> 01:03:41.920 examine whether it's a broader category potentially of natural versus human-made, right? 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 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 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. 01:03:58.800 --> 01:04:01.440 So we see this plant specific response. 01:04:01.680 --> 01:04:07.410 They treat the real and the artificial plants similarly And show this 01:04:07.410 --> 01:04:08.450 reluctance to touch. 01:04:08.690 --> 01:04:13.810 And we've replicated that now, I think, seven times in different 01:04:13.810 --> 01:04:19.810 contexts, including some work with collaborators looking at indigenous 01:04:19.890 --> 01:04:25.170 small scale societies, where we see aspects of this also in those societies as well. 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 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 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 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 01:04:49.000 --> 01:04:50.760 to see what they're doing, right? 01:04:51.000 --> 01:04:56.680 So in these studies, the adult experimenters across the table from the baby, they put these 01:04:56.680 --> 01:04:58.440 uh stimulus objects down. 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 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 01:05:10.050 --> 01:05:12.450 and then I will go ahead and try and touch it. 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 01:05:16.690 --> 01:05:17.890 you to see what to do. 01:05:18.130 --> 01:05:23.740 So we see this kind of like social information gathering thing, and then we also have 01:05:23.740 --> 01:05:29.180 evidence that in addition to looking for social information prior to making contact with 01:05:29.180 --> 01:05:35.100 plants, we we see that babies appear to be geared to learn that particular 01:05:35.100 --> 01:05:36.140 plants are edible. 01:05:36.220 --> 01:05:39.420 So we see kind of selective learning of plant edibility. 01:05:39.900 --> 01:05:44.220 We see that that information that babies learn about plants is 01:05:45.930 --> 01:05:51.610 when it's generalized to new things, they're really careful about how they generalize 01:05:51.610 --> 01:05:55.050 information about plants, especially edibility information. 01:05:55.130 --> 01:06:00.330 They seem to generalize that more tightly than they do, say, toxicity information. 01:06:00.490 --> 01:06:05.130 And when they're generalizing just information like name information about plants, they use 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 01:06:09.530 --> 01:06:14.410 little fine grain features more than when it's a human made artifact. 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 01:06:20.060 --> 01:06:25.180 of the problems is after you learn about a particular plant in your environment, you have 01:06:25.180 --> 01:06:27.820 to be able to apply that information in new settings. 01:06:28.060 --> 01:06:33.980 And the because many plants look very similar and they have 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, 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 01:06:44.850 --> 01:06:48.290 available features to make these kind of fine-grained distinctions. 01:06:48.450 --> 01:06:54.050 And we're seeing some evidence about that in babies and some in 01:06:54.050 --> 01:06:55.010 adults too. 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 01:06:59.490 --> 01:07:01.490 large, the big picture at this point. 01:07:01.650 --> 01:07:06.880 Initial reluctance, look uh evidence of looking for social information, and then 01:07:07.520 --> 01:07:12.080 gathering social information in specific ways, and then generalizing that information in 01:07:12.080 --> 01:07:13.600 specific ways as well. 01:07:14.480 --> 01:07:15.200 Fascinating. 01:07:15.520 --> 01:07:21.520 I mean it it it makes uh good logical sense um what you're talking about, 01:07:21.600 --> 01:07:27.290 because with with a physical artifact, like say a chair, chairs vary uh quite substantially 01:07:27.290 --> 01:07:29.050 in terms of how big they are, their shape. 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 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. 01:07:39.130 --> 01:07:40.010 Like what is the purpose? 01:07:40.170 --> 01:07:43.770 You know, chairs are for sitting and um hammers are for hammering nails. 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 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 01:07:53.680 --> 01:07:53.920 is. 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 01:07:59.520 --> 01:08:03.600 great deal in terms of differentiating um one plant from another plant. 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 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 01:08:12.960 --> 01:08:14.480 eating something that is edible. 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 01:08:19.530 --> 01:08:20.890 psychology is. 01:08:21.770 --> 01:08:27.770 Um I also think it's fascinating how laser specific uh these mechanisms are. 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 01:08:32.490 --> 01:08:33.130 sharp things. 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 01:08:39.130 --> 01:08:44.580 triggering this psychology and this reluctance to touch this curiosity about what other 01:08:44.580 --> 01:08:47.540 adults think of this thing and whether they think it's safe? 01:08:48.500 --> 01:08:49.860 It's truly fascinating. 01:08:50.980 --> 01:08:55.940 Given that you've uh uh gathered all this evidence about this, you know, seemingly 01:08:55.940 --> 01:09:01.700 laser-focused psychology uh on plants, how would you refer to this 01:09:01.940 --> 01:09:04.970 uh uh This system, this collection of mechanisms. 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. 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. 01:09:14.410 --> 01:09:15.930 If it's not a module, what is it? 01:09:16.090 --> 01:09:17.930 How do you talk about this system? 01:09:18.330 --> 01:09:24.250 Yeah, I mean, though so the way that I think about it is that what 01:09:24.250 --> 01:09:29.780 I'm looking at is a collection of sort of 01:09:29.780 --> 01:09:33.940 related but uh overlapping systems, right? 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 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 01:09:45.940 --> 01:09:51.060 systems for plant learning and avoiding natural toxins or plant systems. 01:09:51.220 --> 01:09:56.910 Um, but I don't think about this as there is a single module for 01:09:56.910 --> 01:09:57.950 plants, right? 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 01:10:04.270 --> 01:10:10.110 use the the use of module and modularity gets tied up in implications 01:10:10.110 --> 01:10:14.190 of Fodorian modularity, and I certainly do not mean that. 01:10:14.430 --> 01:10:15.310 Um I understand. 01:10:16.880 --> 01:10:22.800 Yeah, to Jerry Fodor, who was funny, uh scathing um and pretty controversial philosopher of 01:10:22.800 --> 01:10:25.760 mine at Rutgers, who was actually a colleague of Alan Leslie's, right? 01:10:25.840 --> 01:10:27.040 If I'm is that right, Andy? 01:10:27.840 --> 01:10:29.680 But but he basically the idea is like a module. 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 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. 01:10:38.320 --> 01:10:40.880 You know, like seeing an illusion is a classic example. 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 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 01:10:49.350 --> 01:10:50.790 other parts of the scene. 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, 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 01:10:59.030 --> 01:10:59.670 theory mind. 01:10:59.910 --> 01:11:03.590 Like that theory of mind parts of you can't control something. 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, 01:11:08.070 --> 01:11:09.430 there's a whole paper on it you can read. 01:11:09.510 --> 01:11:14.140 But basically, the idea is like Fodor had a reason for differentiating like the stuff you 01:11:14.220 --> 01:11:17.820 quote unquote the little person can control versus those other things. 01:11:18.060 --> 01:11:23.660 Evolutionary psychology really never meant that evolved stuff are those things that you 01:11:23.660 --> 01:11:26.860 can't control, but it kind of got tied together. 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 01:11:31.340 --> 01:11:34.220 often want to compartmentalize it to some things. 01:11:34.380 --> 01:11:36.620 And it is often the things you can't control. 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 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 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. 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 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 01:11:59.510 --> 01:12:00.390 talking about here. 01:12:00.710 --> 01:12:01.110 That's right. 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 01:12:06.150 --> 01:12:11.920 like a list of of criteria that a system has if you're claiming that 01:12:11.920 --> 01:12:15.040 it's modular and it's things like fast, automatic, encapsulated. 01:12:16.880 --> 01:12:22.880 And uh when when it when as Dave said, when evolutionary psychologists talk about 01:12:22.880 --> 01:12:26.640 modularity, they're talking about a functionally specif specialized system, right? 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 01:12:32.240 --> 01:12:33.680 encapsulated, maybe it's not. 01:12:33.760 --> 01:12:39.230 It's the the it's the George Williams adaptationism, the form follows the function, right? 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 01:12:44.030 --> 01:12:45.630 to solve, the function that it has. 01:12:45.790 --> 01:12:47.390 Those are the design criteria it has. 01:12:47.470 --> 01:12:50.350 It's Clark Barrett's thing of it depends, right? 01:12:50.830 --> 01:12:56.270 And uh and uh so um that's why I would not say 01:12:56.270 --> 01:12:58.280 it's a module. 01:12:58.680 --> 01:13:01.480 Well, that's why I would say it's not a module, right? 01:13:01.560 --> 01:13:06.520 I would say that I'm looking at systems that are functionally uh 01:13:07.000 --> 01:13:11.960 functionally specialized around the problems that people face with respect to plants. 01:13:12.120 --> 01:13:15.240 And I'm you may also hear I'm also saying there's multiple, right? 01:13:15.400 --> 01:13:19.400 So I don't think that there is just one problem with respect to plants. 01:13:19.480 --> 01:13:24.750 And I also find just in thinking through doing the task analysis and what and making 01:13:24.750 --> 01:13:30.750 predictions about the design that, and again, this is maybe where my approach to 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, 01:13:35.950 --> 01:13:41.550 you know, this that there's at best there's sort of 01:13:41.550 --> 01:13:47.150 subcomponents to the problem of plants, but more likely I think there are 01:13:47.550 --> 01:13:53.240 these the that the problems, the adaptive problems, uh are to some degree 01:13:53.400 --> 01:13:55.000 distinct within plants. 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 01:14:00.840 --> 01:14:05.160 of being interested in plants is actually larger than just plants, right? 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, 01:14:10.760 --> 01:14:15.960 that there's probably actually a larger category of stationary resource foraging, which 01:14:15.960 --> 01:14:21.330 would include things like honey, and it would include things like probably marine life, 01:14:21.410 --> 01:14:22.930 aspects of marine life. 01:14:23.490 --> 01:14:29.170 And so then a psychology designed for that is not really plant specific, but 01:14:29.170 --> 01:14:31.330 plants, there would be a lot of overlap. 01:14:31.650 --> 01:14:36.210 You could get to thinking about that psychology from starting with plants and then seeing 01:14:36.210 --> 01:14:37.730 commonalities with other things. 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 01:14:43.090 --> 01:14:49.040 set of cognitive mechanisms that have overlap with 01:14:49.040 --> 01:14:54.960 these other systems and other problems that are functionally 01:14:54.960 --> 01:14:56.960 specialized for those problems. 01:14:57.120 --> 01:15:00.880 And so in a way, it's an unsatisfying answer because it's complicated, right? 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 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 01:15:10.470 --> 01:15:15.830 interested in thinking about plants is I think kind of the plant problems first, right? 01:15:16.070 --> 01:15:21.190 And then seeing that there is often overlap with other things. 01:15:21.910 --> 01:15:22.070 Yeah. 01:15:22.390 --> 01:15:28.310 Yeah, it's actually a beautiful example of how you wouldn't uh necessarily expect a 01:15:28.310 --> 01:15:33.510 well-designed system for solving the problem of finding edible plants and avoiding toxic 01:15:33.510 --> 01:15:33.750 plants. 01:15:33.910 --> 01:15:38.980 You wouldn't expect that system to be fast automatic and encapsulated from the rest of 01:15:38.980 --> 01:15:39.460 cognition. 01:15:39.540 --> 01:15:42.820 In fact, if it was, it would serve its function extremely poorly. 01:15:43.300 --> 01:15:46.020 You want to be open to other kinds of social information. 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 01:15:50.340 --> 01:15:52.820 other adults around you are having with regard to the plant. 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 01:15:56.580 --> 01:15:58.660 information that should feed into the system. 01:15:58.980 --> 01:16:03.470 So there's a rich variety of information that should that this learning system should be 01:16:03.470 --> 01:16:04.350 connected to. 01:16:04.750 --> 01:16:07.630 And it doesn't necessarily need to be fast or automatic. 01:16:08.590 --> 01:16:14.430 And what the the modularity, the Fodorian modularity 01:16:14.430 --> 01:16:19.310 approach, I think, misleads us into doing is to thinking that 01:16:19.630 --> 01:16:25.630 adaptations have one shape, or that they that uh instead of looking at what 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. 01:16:29.300 --> 01:16:34.340 And then just abandoning all your preconceptions about what a good solution would be and 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 01:16:39.460 --> 01:16:40.980 that would be fitness promoting. 01:16:42.420 --> 01:16:43.540 Yeah, that's exactly right. 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 01:16:46.580 --> 01:16:47.860 we used to call that binning. 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 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 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 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 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 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 01:17:17.300 --> 01:17:20.900 wrong way to go about it because the form follows the functions. 01:17:20.980 --> 01:17:26.740 So it's really thinking about what is the problem, what what are the design 01:17:26.740 --> 01:17:32.180 features that could solve the problem, and then test for the presence of those design 01:17:32.180 --> 01:17:32.580 features. 01:17:32.660 --> 01:17:35.700 And if if there if there's evidence for them, great. 01:17:35.860 --> 01:17:38.500 If there's not, then you've made an error somewhere along the way. 01:17:38.580 --> 01:17:42.980 You can falsify your predictions and you can go back and really think about the structure 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 01:17:47.190 --> 01:17:48.470 particular bin, right? 01:17:48.630 --> 01:17:48.790 Yeah. 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 01:17:55.670 --> 01:17:59.670 silly and pointless debate about whether something counts as a module. 01:17:59.830 --> 01:17:59.990 Yes. 01:18:00.230 --> 01:18:04.550 Like that is the absolutely the wrong question that we should be asking and the wrong 01:18:04.550 --> 01:18:05.910 debate to be having. 01:18:06.070 --> 01:18:06.230 Yeah. 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 01:18:11.620 --> 01:18:16.420 that we know that our ancestors would have needed to solve to survive and reproduce, and 01:18:16.420 --> 01:18:19.460 just going about and figuring out how those systems work. 01:18:20.180 --> 01:18:25.300 Whether something you know fits some definition of a module is just the wrong question to 01:18:25.300 --> 01:18:25.940 be asking. 01:18:26.180 --> 01:18:27.380 And it's a distraction. 01:18:27.700 --> 01:18:28.180 Exactly. 01:18:28.340 --> 01:18:29.380 That's exactly right. 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 01:18:35.270 --> 01:18:41.030 evolved learning system is something that I hope is a 01:18:41.030 --> 01:18:42.310 contribution of this work. 01:18:42.390 --> 01:18:48.390 Because you have uh in in many areas of psychology, you have a misconception 01:18:48.390 --> 01:18:51.270 that evolved things are somehow opposite. 01:18:52.150 --> 01:18:54.070 Evolution is the opposite of learning, right? 01:18:54.150 --> 01:18:56.070 That either it's evolved or it's learned. 01:18:56.150 --> 01:19:01.750 And I think it does come in part from this Fodorian from a from 01:19:01.750 --> 01:19:05.160 thinking that things follow Fodorian modularity, right? 01:19:05.240 --> 01:19:09.400 So that there can't be learning if you have a Fodorian module. 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 01:19:15.320 --> 01:19:15.800 learning. 01:19:15.960 --> 01:19:18.280 And in fact, there should be learning here. 01:19:18.440 --> 01:19:21.080 And then of course there's the whole you talk to Christina Moya. 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 01:19:25.800 --> 01:19:31.370 evolutionary social sciences about this, but it's not clear that um 01:19:31.930 --> 01:19:37.610 that information makes it out into the wider world, the it or at least to 01:19:37.850 --> 01:19:43.850 the the the the other scientific communities that I care very much about 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. 01:19:49.370 --> 01:19:51.450 Evolution can design a learning system. 01:19:51.900 --> 01:19:52.220 Right. 01:19:52.460 --> 01:19:54.060 And and even needs to, right? 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 01:19:59.260 --> 01:20:00.060 plants, right? 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 01:20:06.140 --> 01:20:07.980 like what you're saying because there's like kind of two things. 01:20:08.060 --> 01:20:09.820 One is like in its affordance base. 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. 01:20:14.530 --> 01:20:20.130 And so you're privileging all the ways to categorize a research program into what are 01:20:20.130 --> 01:20:22.530 likely the evolutionarily relevant affordances. 01:20:22.770 --> 01:20:27.010 And people just weren't looking at these things psychologically or developmentally. 01:20:27.490 --> 01:20:31.090 But then it's also respecting the entity itself. 01:20:31.330 --> 01:20:34.210 And plants have just have specific properties, right? 01:20:34.450 --> 01:20:39.880 And so that combination of like respecting the entity and its properties and the 01:20:39.880 --> 01:20:41.880 affordances that are evolutionary. 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 01:20:46.920 --> 01:20:48.520 north star of the work you're doing. 01:20:48.600 --> 01:20:50.120 And it's really interesting. 01:20:50.360 --> 01:20:53.480 You alluded to some of the affordances or like the different systems. 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 01:20:57.800 --> 01:21:03.650 use plants for other than food and occasionally failing to misidentify 01:21:03.650 --> 01:21:05.730 a toxic plant and sources of death. 01:21:06.130 --> 01:21:10.290 Like so, other than like having a full stomach or dying, what else do plants provide 01:21:10.290 --> 01:21:10.530 people? 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 01:21:14.370 --> 01:21:18.530 not talking to like human behavioral ecologists who are out in the out in the world. 01:21:18.690 --> 01:21:19.170 Um yeah. 01:21:19.650 --> 01:21:19.810 Yeah. 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 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, 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 01:21:35.800 --> 01:21:36.440 life. 01:21:36.920 --> 01:21:38.920 Plants are a huge part of that as well. 01:21:39.160 --> 01:21:44.120 So plants are a huge part of human material culture. 01:21:44.680 --> 01:21:50.600 Plants don't fossilize, which is, or they don't fossilize, they don't fossilize the 01:21:50.600 --> 01:21:51.240 same way. 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 01:21:56.050 --> 01:22:01.810 so things like um things like ropes and baskets and 01:22:01.810 --> 01:22:07.650 clothing and uh and um like shelters and the 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 01:22:14.210 --> 01:22:19.940 the wooden spear right that's uh that that the the the point 01:22:20.020 --> 01:22:21.700 made it, but the spirit didn't. 01:22:22.020 --> 01:22:27.140 And when you read, when you read the literature, the people who are looking and the 01:22:27.140 --> 01:22:30.660 archaeological record for plants, this is something that comes up a lot. 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. 01:22:36.660 --> 01:22:42.580 But if you look at modern populations and people living in societies 01:22:42.580 --> 01:22:48.550 today that still use subsistence practices that include hunting and gathering and 01:22:48.550 --> 01:22:51.270 small scale, small-scale horticulture. 01:22:51.510 --> 01:22:55.270 You see, plants are used to build all kinds of different things. 01:22:55.350 --> 01:22:58.390 They're also used for their underlying chemical properties. 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 01:23:04.230 --> 01:23:10.180 ritual things and making dyes and making face paints and making uh like 01:23:10.500 --> 01:23:13.060 making making the things you make pretty. 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 01:23:18.580 --> 01:23:24.580 exactly functional uses versus versus more kind of decorative uses, but 01:23:24.580 --> 01:23:26.420 there is that as well. 01:23:26.580 --> 01:23:30.100 Um so yeah, plants get used for pretty much everything. 01:23:30.260 --> 01:23:35.710 Um yeah, interesting folk uh chemistry, or maybe not even folk chemistry, just sort of 01:23:35.710 --> 01:23:36.430 different cultural. 01:23:36.750 --> 01:23:38.510 I mean, that's a really interesting thing. 01:23:38.990 --> 01:23:39.150 Yeah. 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 01:23:43.950 --> 01:23:48.430 they um use uh uh they do barbosco fishing. 01:23:48.590 --> 01:23:54.220 So it's you there's a plant that you use that you poison the river 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. 01:24:00.300 --> 01:24:04.940 So uh you're there are um and you can eat them meat, right? 01:24:05.020 --> 01:24:06.460 Like that's important too, right? 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 01:24:12.140 --> 01:24:14.430 suffocate Yes, they suffocate it. 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. 01:24:19.470 --> 01:24:21.790 But I mean it's just such an a a lovely example, right? 01:24:21.870 --> 01:24:24.910 Of like, you know, it's so improbable. 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 01:24:29.630 --> 01:24:30.750 learning as you're putting it. 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. 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 01:24:38.760 --> 01:24:39.000 okay. 01:24:39.080 --> 01:24:39.320 Yeah. 01:24:39.560 --> 01:24:40.200 Yeah. 01:24:41.560 --> 01:24:47.320 But yeah, so and and people use uh uh plant toxins to poison 01:24:47.320 --> 01:24:49.160 arrows for hunting. 01:24:49.400 --> 01:24:55.160 Um, so I mean it we are an ingenious bunch, us humans, and people 01:24:55.160 --> 01:24:56.590 exploit plants. 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 01:25:02.670 --> 01:25:04.990 eaten, the toxic part is used for something else. 01:25:05.550 --> 01:25:05.790 Interesting. 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 01:25:10.350 --> 01:25:10.830 eaten. 01:25:11.070 --> 01:25:16.830 There uh this um this literature, maybe Ed Hagen might know, probably knows 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 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 01:25:28.120 --> 01:25:30.920 plants that people in that particular environment eat. 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 01:25:38.120 --> 01:25:41.800 these social learning systems like shunting people in particular ways. 01:25:42.360 --> 01:25:48.070 There's probably also the uh the the kind of cultural learning, cultural 01:25:48.070 --> 01:25:53.910 evolution part of specializing in the plants that end up having the highest nutritional 01:25:53.910 --> 01:25:55.990 yield over time. 01:25:56.070 --> 01:26:02.070 And so there's, I think there's something very interesting there to be 01:26:02.070 --> 01:26:03.030 dug into. 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 01:26:09.350 --> 01:26:11.750 interested in looking into what's going on with that. 01:26:12.200 --> 01:26:12.440 Yeah. 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, 01:26:16.360 --> 01:26:19.240 the other materials could be used for like material construction. 01:26:19.320 --> 01:26:22.920 That would be another reason for it to not be modular in this quote unquote encapsulated 01:26:22.920 --> 01:26:26.760 way, which is that as you're interfacing with this object, what are all the other 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 01:26:32.680 --> 01:26:38.650 thing to to get the food, well, what are the other things that could this thing 01:26:38.650 --> 01:26:39.530 could afford, right? 01:26:39.610 --> 01:26:43.210 Like I mean, evolved organisms are really non-entropic. 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, 01:26:49.530 --> 01:26:50.650 you know, essentially, right? 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 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 01:26:59.160 --> 01:26:59.720 tall, right? 01:26:59.800 --> 01:27:01.160 And that's what makes wood strong. 01:27:01.320 --> 01:27:04.760 So like there's there's all these I don't think this is wood. 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 01:27:12.680 --> 01:27:14.360 I mean we we have similar offices. 01:27:14.600 --> 01:27:15.080 I don't know. 01:27:15.160 --> 01:27:16.200 Maybe the door is wooden. 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 01:27:22.360 --> 01:27:28.210 the so because I was starting with infants, and because I wanted to start with the 01:27:28.210 --> 01:27:32.930 very, very basic questions of looking at uh 01:27:33.250 --> 01:27:37.330 avoiding danger, learning that it could be eaten. 01:27:37.570 --> 01:27:43.170 There's this whole category of thing of uh how do plants intersect with artifact psychology 01:27:43.250 --> 01:27:47.170 and actually the building and making of artifacts, because artifact psychology is very 01:27:47.170 --> 01:27:48.130 interesting. 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 01:27:54.700 --> 01:28:00.140 90s early 2000s is a really fascinating um topic it's kind of 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 01:28:06.060 --> 01:28:11.530 literature but it's really interesting to think about how plants factor into 01:28:11.530 --> 01:28:16.570 artifact psychology and how using materials from plants, and also this is an area where 01:28:16.570 --> 01:28:18.010 this is wider than plants, right? 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 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 01:28:28.410 --> 01:28:29.210 different things. 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 01:28:34.650 --> 01:28:40.480 thinking about how to build artifacts and the psychology for building material culture in 01:28:40.480 --> 01:28:45.920 a hunter-gatherer world, there's probably a huge overlap in that between plants and animals 01:28:46.000 --> 01:28:48.160 and in how that psychology is set up. 01:28:48.240 --> 01:28:49.920 Um it'd be very interesting to look at. 01:28:50.160 --> 01:28:50.240 Yeah. 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 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, 01:28:58.400 --> 01:29:01.680 like there's people who specialize in like carpentry or there's like chemists or 01:29:01.680 --> 01:29:05.610 physicists, you know, and like there's just these different things, but like, you know, we 01:29:05.610 --> 01:29:09.930 have software for doing chemistry and physical construction and like thinking about 01:29:09.930 --> 01:29:10.490 artifacts. 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 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 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 01:29:21.450 --> 01:29:22.810 just peel the bark off randomly. 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 01:29:27.690 --> 01:29:32.010 the repertoire behavioral motor repertoires of what we do, even to the point where I'll 01:29:32.010 --> 01:29:34.640 just do it even when it's for no purpose. 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 01:29:40.080 --> 01:29:46.000 discrepancy between sort of this job has been taken care of for us by the division 01:29:46.000 --> 01:29:50.560 of labor in a modern environment, but yet the software still exists in us. 01:29:50.720 --> 01:29:56.490 And maybe to the extent we don't understand it, we're actually possibly not 01:29:56.490 --> 01:29:58.330 doing as well as we could be. 01:29:58.410 --> 01:30:00.490 Um, you know, like that's that's another thing. 01:30:00.650 --> 01:30:03.850 I know you're starting to think about also like food and nutrition. 01:30:04.090 --> 01:30:04.330 Yes. 01:30:04.490 --> 01:30:09.690 And just also like there there are consequences of this mismatch that are both health and 01:30:09.690 --> 01:30:11.290 physical and also maybe mental. 01:30:11.530 --> 01:30:13.770 Can you maybe talk a little bit about that? 01:30:14.330 --> 01:30:14.570 Yeah. 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 01:30:20.570 --> 01:30:26.200 and actually engaging with plants and with the with with the natural world 01:30:26.200 --> 01:30:27.160 around you. 01:30:27.400 --> 01:30:33.160 That's kind of the being immersed in the natural world and growing up, having 01:30:33.160 --> 01:30:39.160 this rich first-person experience, not only with the natural world, but with watching 01:30:39.160 --> 01:30:44.840 other people who have this rich knowledge, manufacturing the kinds of things you need to 01:30:44.840 --> 01:30:49.960 survive, getting the food you need to survive, processing the food you need to survive. 01:30:50.190 --> 01:30:53.230 All of those things are things we're just really missing. 01:30:54.110 --> 01:30:59.870 And it it with respect to food, the way that I have looked at 01:30:59.950 --> 01:31:05.950 um uh plant edibility so far with babies is largely with showing 01:31:05.950 --> 01:31:07.150 them an adult. 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 01:31:13.310 --> 01:31:14.030 in Berlin. 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, 01:31:20.020 --> 01:31:20.260 right? 01:31:20.340 --> 01:31:22.820 And that is a cue of edibility. 01:31:22.980 --> 01:31:28.900 Um, and it seems to be something that uh plants are selectively seen as edible, even 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 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 01:31:38.420 --> 01:31:40.980 edible, um, even though the action is the same. 01:31:41.140 --> 01:31:46.630 So the social information is uh is is uh is processed 01:31:46.630 --> 01:31:50.710 differently when depending on what is being acted upon. 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 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 01:31:59.030 --> 01:32:03.580 can't eat it until you do a lot of other things to it first. 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, 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 01:32:14.860 --> 01:32:18.380 yourself and your family and the other people in your community. 01:32:18.620 --> 01:32:24.380 And so oftentimes babies are just like along for the ride for foraging, 01:32:24.540 --> 01:32:24.700 right? 01:32:25.100 --> 01:32:28.220 They're when they're really little, they're carried along for foraging. 01:32:28.540 --> 01:32:33.890 When uh children get a little bit older, they are tend to be kind of 01:32:33.890 --> 01:32:39.810 together in these um uh multi-age groups of kids running around, 01:32:39.970 --> 01:32:44.850 but there's still those little groups of kids go out and do their own foraging. 01:32:45.010 --> 01:32:50.690 Um uh Karen Kramer gave a great talk at uh CWES recently at the at a 01:32:50.690 --> 01:32:56.530 conference we we had here recently detailing all the ways that kids do this kind 01:32:56.530 --> 01:32:57.490 of foraging. 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. 01:33:02.240 --> 01:33:08.160 And also people like uh Sheena Lou Levy is working on 01:33:08.160 --> 01:33:08.320 this. 01:33:08.480 --> 01:33:10.320 There's really, there's really great work. 01:33:10.400 --> 01:33:15.200 And Barry Hewlett, of course, has all of this work on hunter-gatherer, children and 01:33:15.200 --> 01:33:15.760 childhoods. 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. 01:33:22.320 --> 01:33:28.150 But it there now is starting to be some very, very interesting great 01:33:28.150 --> 01:33:30.390 work looking at what kids actually do. 01:33:30.790 --> 01:33:36.230 And this also includes that they're doing it themselves with their multi-age peers, but 01:33:36.230 --> 01:33:41.830 they're also around while their parents are processing these various food items. 01:33:42.070 --> 01:33:47.990 And so what my work suggests is the littlest babies, their initial response to 01:33:47.990 --> 01:33:50.390 unknown plants is to kind of avoid them, right? 01:33:50.870 --> 01:33:56.740 As a way of avoiding exposure to these potentially dangerous toxins until 01:33:56.740 --> 01:33:59.780 they have some information about how to proceed. 01:34:00.420 --> 01:34:06.260 But if you have this psychology that's basically like, just don't engage 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 01:34:10.500 --> 01:34:12.100 social information that it's edible. 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 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 01:34:21.330 --> 01:34:25.090 where you have a lot of very young kids who will not touch vegetables. 01:34:25.250 --> 01:34:25.730 Right. 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 01:34:32.690 --> 01:34:36.770 as they are developing their own motor skills and their own independence. 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 01:34:41.170 --> 01:34:46.050 this neophobia, this food neophobia for these potentially dangerous things in the 01:34:46.050 --> 01:34:47.010 environment. 01:34:47.520 --> 01:34:53.120 but in hunter-gatherer kinds of situations, in these small-scale societies in which our 01:34:53.120 --> 01:34:58.800 brains evolved, you would see the information that would show you, no, no, this is the 01:34:58.800 --> 01:34:58.960 thing. 01:34:59.120 --> 01:35:00.720 Like this, this is the thing we're processing. 01:35:00.800 --> 01:35:02.240 This is the thing that everybody's eating. 01:35:02.320 --> 01:35:03.920 This is the thing that's being gathered. 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 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 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 01:35:19.050 --> 01:35:21.130 food as opposed to the adult food. 01:35:21.210 --> 01:35:25.130 Um and you know they haven't seen how it gets there. 01:35:25.210 --> 01:35:27.770 And you're like, no no trust me, it's food, just eat it. 01:35:27.850 --> 01:35:33.450 And you end up fighting this battle of getting a small child to accept something where 01:35:33.840 --> 01:35:38.640 potentially from their mechanisms perspectives, they're like, why are you feeding me 01:35:38.640 --> 01:35:39.200 poison? 01:35:39.440 --> 01:35:40.000 Right. 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 01:35:46.480 --> 01:35:49.440 my lab built here in uh Santa Barbara. 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 01:35:53.440 --> 01:35:59.230 unpacking what are the what is the entirety of the set of cues of 01:35:59.230 --> 01:36:02.270 food learning, of how something becomes food. 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 01:36:07.070 --> 01:36:12.830 collaborator Camille Rioux, who uh is uh who is in a 01:36:12.830 --> 01:36:15.310 research center in Dijon in France. 01:36:15.550 --> 01:36:20.960 Um She and I have started looking, doing some initial work looking at food 01:36:20.960 --> 01:36:26.880 processing and how infants respond to signals that somebody 01:36:26.880 --> 01:36:29.520 has uh it previously interacted with the food. 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 01:36:34.160 --> 01:36:39.600 student, Karula Schlegelmilch, and former postdoc as well, um, looking at what babies do 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 01:36:45.010 --> 01:36:50.690 versus a control action of just touching it, but not in a way that processes it. 01:36:51.090 --> 01:36:51.410 Interesting. 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 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 01:37:01.330 --> 01:37:02.130 prepare the food? 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 01:37:06.380 --> 01:37:07.020 want Mama to do it. 01:37:07.180 --> 01:37:08.540 I want Mama to put me the milk. 01:37:11.100 --> 01:37:11.980 Is it though, David? 01:37:12.060 --> 01:37:14.460 Are you is it is she saying you're bad cook? 01:37:14.620 --> 01:37:15.980 Or are you just cutting out carrots? 01:37:16.060 --> 01:37:17.260 Maybe you're bad cutting a sun. 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 01:37:22.060 --> 01:37:24.220 that like she didn't die when she ate that food. 01:37:24.300 --> 01:37:26.140 So she's not gonna take a risk on me, I guess. 01:37:26.220 --> 01:37:26.780 I don't know. 01:37:27.980 --> 01:37:28.540 I don't know. 01:37:28.700 --> 01:37:31.710 She she might have things to say about the your cooking house. 01:37:34.190 --> 01:37:35.870 No, but it is it is really interesting. 01:37:35.950 --> 01:37:40.430 I mean, and this is um my colleague here, Zoe Liberman, has been looking at social 01:37:40.510 --> 01:37:42.670 inferences based on food, right? 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 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 01:37:53.790 --> 01:37:57.220 what people are eating and food sharing and things like this. 01:37:57.540 --> 01:38:02.980 And Ashley Thomas has some work touching on this as well of people who are like 01:38:03.300 --> 01:38:07.380 uh uh well, people who are getting like their saliva and food and things like that. 01:38:07.540 --> 01:38:12.980 But um but uh but it would be fascinating to actually look at 01:38:13.620 --> 01:38:18.660 what happens when you have different kinds of people giving different kinds of information 01:38:18.660 --> 01:38:19.300 about food. 01:38:19.460 --> 01:38:25.310 And you might you could expect, for example, that something about information about whether 01:38:25.310 --> 01:38:30.350 something is toxic or not, it might not matter who's telling you that, right? 01:38:30.830 --> 01:38:36.190 So like if somebody who's, you know, somebody who is in some kind of 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 01:38:42.110 --> 01:38:45.340 this thing, you might just accept that information no matter what. 01:38:45.500 --> 01:38:51.500 But if it's something more something more nuanced about how a food is prepared or 01:38:51.740 --> 01:38:56.540 um or something about how you build a particular artifact, something something like that, 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. 01:39:00.460 --> 01:39:03.500 So yeah, it would be that's something that would be fascinating to look at. 01:39:03.820 --> 01:39:05.170 We'll eat your cooking, David. 01:39:06.290 --> 01:39:06.530 Okay, good. 01:39:06.690 --> 01:39:07.490 That'll make me feel better. 01:39:07.650 --> 01:39:10.450 Because uh yeah, my daughter has insulted me uh one too many times. 01:39:10.610 --> 01:39:12.450 So I could use an ego boost. 01:39:12.770 --> 01:39:17.810 Um another thing that occurred to me um, have you thought about how emotions might 01:39:17.810 --> 01:39:19.010 interface with this system? 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 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 01:39:28.130 --> 01:39:30.530 involve toxins and poisons and make you sick. 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 01:39:34.680 --> 01:39:38.840 really the emotion I feel when I think about a toxic plant. 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 01:39:44.040 --> 01:39:45.480 or something or rotting meat. 01:39:46.600 --> 01:39:48.280 Which is really interesting to me. 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 01:39:53.480 --> 01:39:57.720 use plants for, you know, for making tools, for preparing food, even for hunting in some 01:39:57.720 --> 01:39:58.360 cases. 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 01:40:04.110 --> 01:40:08.270 functional sense that we wouldn't feel disgust necessarily toward a plant. 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 01:40:12.830 --> 01:40:14.910 engaging with the plant in a way that might make you sick. 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 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 01:40:24.910 --> 01:40:26.510 distance from it in every way possible. 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, 01:40:31.080 --> 01:40:33.160 say, but you might want to use it for these other purposes. 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 01:40:38.920 --> 01:40:42.360 comes to plants and it's more of just a kind of caution or fear. 01:40:42.520 --> 01:40:44.680 Uh have have you thought about that in any way? 01:40:45.080 --> 01:40:45.640 Yeah, I have. 01:40:45.720 --> 01:40:46.440 And I think you're right. 01:40:46.600 --> 01:40:52.050 I think I think it's I mean, so to preface this by we have not 01:40:52.050 --> 01:40:53.570 tested this yet. 01:40:53.810 --> 01:40:57.010 So to try to distinguish between these things empirically. 01:40:57.410 --> 01:41:03.330 Um, but what what my the way that I think about it is that 01:41:03.490 --> 01:41:08.930 what makes sense for plants is basically just an avoidance, right? 01:41:09.090 --> 01:41:13.260 It's not it's i I mean, watching the kids, it looks like boredom. 01:41:13.500 --> 01:41:17.340 It looks like they kind of want to do anything else other than be there. 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 01:41:22.940 --> 01:41:28.460 don't see any evidence of them exhibiting a disgust reaction to plants. 01:41:28.700 --> 01:41:34.540 I also don't think that fear per se is necessarily involved 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 01:41:40.570 --> 01:41:44.490 spider, something that you need to like get up and move away from. 01:41:44.730 --> 01:41:48.410 It's not clear that being afraid of a plant per se is necessary. 01:41:48.570 --> 01:41:52.570 It really, I think, is this is why I talk about it as an avoidance mechanism. 01:41:52.650 --> 01:41:58.100 It really is just as far as I am aware, um it's an avoidance, right? 01:41:58.260 --> 01:42:00.180 It's like an and a caution, right? 01:42:00.260 --> 01:42:03.220 And it particularly as you say, there's different parts of a plant. 01:42:03.300 --> 01:42:09.140 So there's lots of plants that you have like raspberries or 01:42:09.140 --> 01:42:12.100 blackberries or any of those kind of brambly plants. 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 01:42:17.460 --> 01:42:19.380 themselves you don't have to be cautious of. 01:42:19.460 --> 01:42:22.420 But the broader plant you have to exhibit caution around. 01:42:22.660 --> 01:42:25.250 Yeah, I mean it's almost a a a a distinct emotion. 01:42:25.410 --> 01:42:27.250 Like it's not disgust, it's not fear. 01:42:27.410 --> 01:42:29.730 It really is this this caution state. 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 01:42:33.970 --> 01:42:35.810 could be differentiated from fear and disgust. 01:42:36.210 --> 01:42:36.450 Yeah. 01:42:37.010 --> 01:42:37.730 I totally agree. 01:42:37.890 --> 01:42:38.530 I totally agree. 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 01:42:42.850 --> 01:42:48.610 plant learning, the way I think about that is that it's gonna likely be a 01:42:48.610 --> 01:42:50.850 largely observational system. 01:42:51.200 --> 01:42:51.520 right? 01:42:51.760 --> 01:42:57.360 So especially with what we what the literature says about the way that social 01:42:57.760 --> 01:43:03.680 or the way that um kind of teaching unfolds in small-scale societies is 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 01:43:09.600 --> 01:43:11.440 necessarily explicit teaching. 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 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 01:43:22.630 --> 01:43:25.910 westernized cultures for lack of a better term. 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 01:43:33.030 --> 01:43:36.790 when they know they have a naive learner who's there observing them. 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 01:43:42.230 --> 01:43:48.020 preparation or around artifact building, you would have kids just observing what the 01:43:48.020 --> 01:43:51.700 adults or the older kids are doing when they're making these things. 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 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. 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 01:44:06.100 --> 01:44:08.740 bothering to do anything differently, but the baby's still there. 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 01:44:14.530 --> 01:44:16.690 the relevant information, right? 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 01:44:22.530 --> 01:44:24.690 for pick something off of a plant and eat it? 01:44:24.770 --> 01:44:29.090 Like, because I think these are probably largely observational systems, and it's not 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 01:44:33.090 --> 01:44:33.410 with this. 01:44:33.490 --> 01:44:35.090 First you do this, first you do that. 01:44:35.250 --> 01:44:39.660 Instead, there's people living their lives and doing these things, And it's a young 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 01:44:45.660 --> 01:44:49.020 practice it and in in safe ways. 01:44:50.380 --> 01:44:51.020 Yeah. 01:44:52.380 --> 01:44:52.940 Interesting. 01:44:53.100 --> 01:44:53.340 Yeah. 01:44:53.420 --> 01:44:55.820 There's a whole I mean, oh, and that's what I was sorry. 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. 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 01:45:06.550 --> 01:45:12.310 like uh disgust sleep maybe it happens and certainly I bet plants are bitter right the 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 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 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 01:45:28.520 --> 01:45:32.200 that you need disgust as the input. 01:45:32.360 --> 01:45:35.080 I mean, certainly our our our work suggests that you don't. 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 01:45:39.560 --> 01:45:41.240 before there's social information. 01:45:41.720 --> 01:45:41.960 Right. 01:45:42.200 --> 01:45:42.440 Yeah. 01:45:42.600 --> 01:45:43.800 Fear is sort of like you're far. 01:45:44.040 --> 01:45:45.880 Oh, sorry, David, you're like kind of far into it. 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 01:45:50.280 --> 01:45:53.320 sudden you realize you use the poisonous plant, you might get afraid, right? 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 01:45:57.270 --> 01:46:00.230 forest and you realize there's no way out, and you become afraid. 01:46:00.390 --> 01:46:03.590 Like that, that's engaging that, but that's sort of incidental that it's plants. 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 01:46:08.070 --> 01:46:09.590 get out of this situation. 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 01:46:15.910 --> 01:46:19.270 everything is going right, and you don't need those emotions exactly. 01:46:19.350 --> 01:46:25.350 And I David, I love the idea of sort of this cautionary, um, distinct category. 01:46:25.510 --> 01:46:26.230 Um, yeah. 01:46:26.630 --> 01:46:31.060 I think yeah it could very well be its own distinct emotion with its distinct design 01:46:31.060 --> 01:46:35.940 features and that it prompts attention to parts rather than holes and procedures and and 01:46:35.940 --> 01:46:39.700 where you know uh uh prompts a greater attention toward you know how other people are 01:46:39.700 --> 01:46:41.540 reacting to it and and social learning. 01:46:41.700 --> 01:46:44.260 So yeah, it's an interesting underexplored topic. 01:46:44.420 --> 01:46:45.220 But yeah, yeah. 01:46:45.460 --> 01:46:50.410 And again, because you know, since long before we were humans, this was a problem, right? 01:46:50.570 --> 01:46:55.930 So having something, having a motivational system that kind of shifts everything, all the 01:46:55.930 --> 01:47:00.570 necessary uh different other systems into the right setting when you're engaging with it 01:47:00.730 --> 01:47:02.090 makes a lot of sense, right? 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 01:47:06.890 --> 01:47:07.530 for plants. 01:47:07.610 --> 01:47:12.250 I think convincing them that there might be a separate emotional component for plants would 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. 01:47:16.000 --> 01:47:16.320 Right. 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 01:47:20.000 --> 01:47:25.040 lot about too, about not sort of like overselling results from studies or telling people 01:47:25.040 --> 01:47:25.520 what to do. 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. 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 01:47:33.280 --> 01:47:36.160 preparation and the fact that they're not getting that. 01:47:36.400 --> 01:47:41.710 Um, and there's like this whole category of like, you know, like plant uh 01:47:42.030 --> 01:47:44.750 interactions of like cooking, like on YouTube. 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 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 01:47:53.390 --> 01:47:55.390 love watching like people make stuff. 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 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 01:48:05.950 --> 01:48:08.590 people are sort of physically interacting with the environment as much. 01:48:08.830 --> 01:48:09.070 Yeah. 01:48:09.280 --> 01:48:09.600 Yeah. 01:48:09.760 --> 01:48:10.800 I mean, I think so. 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. 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 01:48:20.160 --> 01:48:26.080 on this food learning thing is because I in an ideal world, I'd be able 01:48:26.080 --> 01:48:29.840 to identify kind of what are these relevant cues. 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 01:48:36.090 --> 01:48:40.970 sitting, you know, we're not going back to a small-scale world in all likelihood. 01:48:41.130 --> 01:48:46.970 Um, and but how could we provide aspects of those cues to toddlers, 01:48:47.130 --> 01:48:52.890 to infants, to young kids in ways that could help to get them over some of 01:48:52.890 --> 01:48:58.740 this very um reasonable reluctance towards the what what turn out to 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 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. 01:49:09.540 --> 01:49:11.460 Um and yeah we'll see. 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 01:49:17.460 --> 01:49:22.980 a a a big task um but but fun to do um and I think 01:49:23.210 --> 01:49:29.050 there is a world where you could imagine like ways of designing things that you 01:49:29.050 --> 01:49:33.850 could potentially target the design of these systems to get you kind of the biggest bang 01:49:33.850 --> 01:49:36.330 for your buck in these kinds of systems. 01:49:36.730 --> 01:49:39.210 Let let the kids plan the dirt and plant some things. 01:49:39.610 --> 01:49:39.930 Exactly. 01:49:40.090 --> 01:49:42.250 And and let them see where their food is coming from. 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 01:49:47.920 --> 01:49:53.200 from her PhD actually showing that some of this food neophobia stuff seems maybe uh the 01:49:53.200 --> 01:49:59.120 result of um having less or more immature categorization abilities. 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 01:50:05.440 --> 01:50:10.160 the same kind of thing you've encountered before, you are more likely to show neophobia. 01:50:10.240 --> 01:50:13.170 So if you're into categorization abilities, yeah, right. 01:50:13.250 --> 01:50:17.410 If you're if your categorization abilities, if you score more high, uh highly on 01:50:17.410 --> 01:50:21.890 categorization abilities, you're less likely to exhibit neophobia in some of her studies. 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 01:50:26.210 --> 01:50:26.530 daughter. 01:50:27.170 --> 01:50:28.690 Honestly, I think that might be it. 01:50:28.770 --> 01:50:30.610 Yeah, I'm cutting them in the wrong shape or something. 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 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 01:50:42.100 --> 01:50:44.740 the the specific tortilla chip that she wanted. 01:50:45.220 --> 01:50:45.540 Right. 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 01:50:50.100 --> 01:50:54.420 were all they were distinct tortilla chips and she had her eye on that particular tortilla 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 01:50:58.510 --> 01:51:00.830 of the same type of thing, and that and that could be driving this. 01:51:00.990 --> 01:51:01.150 Yeah. 01:51:01.390 --> 01:51:01.630 Yeah. 01:51:01.710 --> 01:51:03.230 And I mean, food is one of those things. 01:51:03.310 --> 01:51:05.950 Like, we look at it, this is a big instinct blindness thing, right? 01:51:06.030 --> 01:51:08.110 Like we look at it and it's very clearly food. 01:51:08.190 --> 01:51:09.870 And why can't you see that it's food? 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. 01:51:15.870 --> 01:51:18.350 And why should that be food and not something else? 01:51:18.510 --> 01:51:18.590 Right. 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 01:51:22.720 --> 01:51:26.080 was a different shape, you know, like she was paying attention to details that I completely 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 01:51:29.120 --> 01:51:32.160 works, like it's not obvious what details are worth paying attention to. 01:51:32.640 --> 01:51:33.120 Exactly. 01:51:33.600 --> 01:51:36.000 Yeah, build a robot that can identify food. 01:51:36.160 --> 01:51:41.760 That's the uh but uh one of the questions we always 01:51:41.760 --> 01:51:45.520 ask people is is there any question we should have asked you? 01:51:46.850 --> 01:51:49.650 Oh, uh, I don't know. 01:51:49.730 --> 01:51:51.890 I feel like you got them all. 01:51:52.370 --> 01:51:54.610 Um, yeah. 01:51:55.010 --> 01:51:59.250 Well, I mean, David sort of alluded to did I slip on a plant? 01:51:59.330 --> 01:52:05.170 And there was, there is one like big plant experience that I did have uh 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 01:52:10.690 --> 01:52:16.460 climbed up a poison oak vine, not knowing that it was poison oak uh and 01:52:16.780 --> 01:52:22.700 got huge poison oak rash on my face it was like summer so it was along 01:52:22.700 --> 01:52:28.300 my my legs my whole body and got a really really really terrible rash so I 01:52:28.300 --> 01:52:33.420 learned firsthand that plants can be really dangerous and really 01:52:33.420 --> 01:52:37.100 unpleasant uh and that you might not want to touch them. 01:52:38.110 --> 01:52:39.630 That's a great origin story. 01:52:40.190 --> 01:52:43.950 Poison Oak would be a great supervillain name for you where you use your technology. 01:52:44.510 --> 01:52:45.150 That's great. 01:52:48.270 --> 01:52:49.470 Poison Oak strikes again. 01:52:50.190 --> 01:52:53.630 It's also a good like folk fusion band name, Poison Oak, sort of. 01:52:53.950 --> 01:52:54.350 Oh yeah. 01:52:54.430 --> 01:52:54.670 Totally. 01:52:54.990 --> 01:52:56.670 Maybe a little bit of rocking it too. 01:52:56.750 --> 01:52:56.910 Yeah. 01:52:56.990 --> 01:53:00.910 Um I want to see the movie where you seek revenge on Reviewer 2 by us. 01:53:01.550 --> 01:53:02.510 As Poison Oak. 01:53:02.990 --> 01:53:04.190 Yeah, Poison Oak. 01:53:07.880 --> 01:53:09.480 The really good superpower, yeah. 01:53:09.720 --> 01:53:11.560 Like harnessing the power of plants. 01:53:11.640 --> 01:53:12.360 I mean that's yeah. 01:53:12.760 --> 01:53:14.360 Um who was saying, David, do you remember? 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. 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 01:53:23.240 --> 01:53:25.960 like really just you know, no, they are not your friends. 01:53:27.670 --> 01:53:29.750 They're building weapons factories. 01:53:29.990 --> 01:53:31.030 I mean, really, they are. 01:53:31.190 --> 01:53:32.550 That's how they defend themselves. 01:53:32.710 --> 01:53:33.750 This is what they've come up with. 01:53:33.830 --> 01:53:36.150 And they've come up with some very clever ways to do it. 01:53:36.390 --> 01:53:37.270 Um yeah. 01:53:37.510 --> 01:53:37.670 Yeah. 01:53:37.830 --> 01:53:37.910 Yeah. 01:53:38.150 --> 01:53:39.990 You gotta respect the plants. 01:53:40.790 --> 01:53:41.030 Yeah. 01:53:41.350 --> 01:53:42.310 Respect plants. 01:53:42.550 --> 01:53:43.030 Yeah, yeah. 01:53:43.110 --> 01:53:45.750 So respect the adaptations and respect plants. 01:53:45.830 --> 01:53:47.270 And yeah. 01:53:47.430 --> 01:53:50.470 So um yeah, but uh David, anything else? 01:53:50.980 --> 01:53:53.940 No, I I think, you know, we we covered a lot of ground. 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 01:54:00.100 --> 01:54:01.140 just keep rattling off. 01:54:01.620 --> 01:54:02.580 Keep going, keep going. 01:54:03.300 --> 01:54:05.220 And now we're out of time. 01:54:05.780 --> 01:54:07.700 Oh T H Y M E. 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 01:54:14.430 --> 01:54:14.830 modality. 01:54:15.150 --> 01:54:16.190 Yeah, but you know. 01:54:16.670 --> 01:54:17.790 But yeah, no, thank you so much. 01:54:17.870 --> 01:54:23.310 And you know, genuinely, like, you know, personal bias aside, like the work that you're 01:54:23.310 --> 01:54:28.990 doing, it's extremely important, not only because you're uncovering a new area of 01:54:28.990 --> 01:54:33.950 adaptations people hadn't looked before, but because it's also an example of exactly what 01:54:33.950 --> 01:54:39.200 you said, like learning is not opposed to evolutionary and the connection to development. 01:54:39.280 --> 01:54:41.440 I mean, we had Deb Lieberman Deb Lieberman on. 01:54:41.600 --> 01:54:46.320 She was really excited about the special issue with development, um, on development. 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 01:54:51.040 --> 01:54:55.840 doing, which is that as a developmental psychologist, you were already asking like a good 01:54:55.840 --> 01:54:58.560 question, and evolutionary psychology answered it. 01:54:58.850 --> 01:55:04.690 And I do think that the connection between developmental and evolutionary approaches are 01:55:04.690 --> 01:55:09.810 very much kindred because in many cases developmentalists are asking, and you can you're 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 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 01:55:17.810 --> 01:55:19.810 really think about what's the Q structure. 01:55:20.290 --> 01:55:26.120 I think there's a lot of connections to integrating development evolutionary. 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 01:55:31.640 --> 01:55:37.320 both development and evolutionary psychology sort of invigorated and um thriving 01:55:37.480 --> 01:55:41.560 and flourishing uh to tiptoe towards a plant pun. 01:55:42.840 --> 01:55:43.720 Well thank you. 01:55:43.880 --> 01:55:44.760 Thank you for saying that. 01:55:44.920 --> 01:55:46.310 That that that means a lot. 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. 01:55:50.390 --> 01:55:53.430 And I I uh I appreciate that. 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 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 01:56:04.390 --> 01:56:04.950 assistance. 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 01:56:09.920 --> 01:56:10.880 me and my work. 01:56:10.960 --> 01:56:16.480 Um, and hopefully we can bring development and uh evolution, evolutionary 01:56:16.480 --> 01:56:17.920 approaches closer together. 01:56:18.160 --> 01:56:20.960 Yeah, the lab name, it's a relatively new lab name. 01:56:21.040 --> 01:56:21.840 What is the lab? 01:56:22.240 --> 01:56:26.000 Uh the lab for infant learning and cognition or lilac. 01:56:27.920 --> 01:56:28.560 Yeah, nice. 01:56:28.800 --> 01:56:29.920 Plant puns. 01:56:30.160 --> 01:56:30.880 All right, yeah. 01:56:31.120 --> 01:56:32.800 Top, top that, yeah. 01:56:33.950 --> 01:56:36.830 Uh but yeah, thank you so much both of you for having me on. 01:56:36.910 --> 01:56:37.710 This is a real pleasure. 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 01:56:42.510 --> 01:56:43.790 this is a different format. 01:56:44.510 --> 01:56:44.750 Exactly. 01:56:44.830 --> 01:56:46.110 But we don't often get to talk to you. 01:56:46.510 --> 01:56:47.070 So thank you. 01:56:47.230 --> 01:56:47.710 Yeah. 01:56:48.510 --> 01:56:49.310 Oh yeah. 01:56:49.470 --> 01:56:50.110 All right. 01:56:50.350 --> 01:56:50.750 All right. 01:56:50.990 --> 01:56:56.750 David, we have ended another episode, this one full of the weird combination of 01:56:56.750 --> 01:56:58.190 babies and plants. 01:56:58.670 --> 01:56:59.230 Yes. 01:56:59.470 --> 01:57:02.140 It was a uh wild ride. 01:57:02.300 --> 01:57:07.820 Um a lot of seeds were planted, um, a lot of flowers of insight 01:57:07.820 --> 01:57:08.380 bloomed. 01:57:08.940 --> 01:57:12.380 And it was in but now it's time to end the episode. 01:57:12.780 --> 01:57:14.540 O T H Y M E okay. 01:57:15.500 --> 01:57:17.660 There's a lot of the homonyms really don't come across on podcasts. 01:57:17.820 --> 01:57:18.460 I really don't know. 01:57:18.540 --> 01:57:18.860 Yeah, exactly. 01:57:19.260 --> 01:57:20.220 Not the ideal format. 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 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 01:57:30.170 --> 01:57:31.450 topics you want us to cover. 01:57:31.610 --> 01:57:35.450 Uh if you're so inclined, you can uh support us on Patreon. 01:57:35.610 --> 01:57:37.930 Uh anything else people can do, Dave? 01:57:38.170 --> 01:57:43.930 Um, you know, just you know, look up uh interesting, important work in 01:57:43.930 --> 01:57:45.930 evolutionary social sciences. 01:57:46.090 --> 01:57:49.530 And if you come across stuff that we should cover, let us know. 01:57:49.820 --> 01:57:50.700 Yeah, please do. 01:57:50.940 --> 01:57:51.340 All right. 01:57:51.500 --> 01:57:53.020 We'll see you guys next week. 01:57:53.340 --> 01:57:53.660 See ya. 01:57:54.060 --> 01:57:54.700 Bye.