WEBVTT 00:00:00.080 --> 00:00:01.280 Oh, we got another comment. 00:00:01.440 --> 00:00:04.960 People hate this is interesting to the theory of humor. 00:00:05.200 --> 00:00:10.160 Some people hate our screwing up the intro. 00:00:11.200 --> 00:00:16.320 Like uh, like there's a comment on X where somebody's like, Well, what it's it's really 00:00:16.320 --> 00:00:17.040 interesting, actually. 00:00:17.120 --> 00:00:17.520 I don't know. 00:00:17.600 --> 00:00:20.000 I wonder why people get so pissed off about that. 00:00:20.640 --> 00:00:21.440 Yeah, I don't know. 00:00:21.600 --> 00:00:25.030 Yeah, I don't know. 00:00:25.190 --> 00:00:25.590 All right. 00:00:25.670 --> 00:00:26.150 Yeah. 00:00:26.470 --> 00:00:28.710 This is Evolutionary Psychology the Podcast. 00:00:28.790 --> 00:00:30.310 I'm David Pietrazuski. 00:00:30.630 --> 00:00:33.750 I'm David Pinsov, and this is actual evolutionary psychology. 00:00:34.070 --> 00:00:35.910 By actual evolutionary psychologists. 00:00:57.340 --> 00:00:59.740 David, I am really excited about this episode. 00:00:59.820 --> 00:01:02.140 Today we have two guests. 00:01:02.300 --> 00:01:07.500 Uh Christina Moya, who's returner, who is a guest co-host, and our 00:01:07.820 --> 00:01:10.780 guest proper is Rob Boyd. 00:01:11.590 --> 00:01:11.910 Yes. 00:01:12.070 --> 00:01:15.030 This was a really fun and interesting episode. 00:01:15.190 --> 00:01:17.350 Uh many tidbits about E. 00:01:17.510 --> 00:01:23.510 coli bacteria and Enola lizards and anecdotes from you know 00:01:23.590 --> 00:01:26.710 evolutionary biology, mathematics. 00:01:26.950 --> 00:01:32.390 What was so interesting about this is um there was some disagreements that we we navigated. 00:01:32.630 --> 00:01:37.960 Uh and we usually don't navigate too many disagreements on this podcast because um Dave and 00:01:37.960 --> 00:01:42.520 I are optimally rational agents who uh who cannot disagree on anything. 00:01:43.560 --> 00:01:48.920 Yes, and to the extent that we do we we we disagree, we we quickly realize largely that 00:01:48.920 --> 00:01:53.720 we're we're just exploring the larger space that we would both agree about from different 00:01:53.720 --> 00:01:54.600 perspectives. 00:01:55.160 --> 00:02:00.990 Yes, but uh Rob Boyd and Pete Richardson uh pioneered the study 00:02:00.990 --> 00:02:06.350 of cultural evolution, the the modeling of culture as its own kind of 00:02:06.350 --> 00:02:11.950 evolutionary process, and the story of how culture uh has been involved in the evolution of 00:02:11.950 --> 00:02:17.790 humanity and what role it has played uh in our preeminence 00:02:17.790 --> 00:02:18.990 on this planet. 00:02:20.020 --> 00:02:25.620 And I think we're still trying to reconcile how this analysis of 00:02:25.620 --> 00:02:31.300 culture can be fit into the Darwinian paradigm or the 00:02:31.380 --> 00:02:32.980 evolutionary behavioral sciences. 00:02:33.220 --> 00:02:38.500 I think Dave and I are of the camp that uh it can be reconciled, that this view of cultural 00:02:38.500 --> 00:02:44.110 evolution is compatible with even the most extreme Santa Barbara uh evolutionary 00:02:44.110 --> 00:02:45.950 psychology model of the mind. 00:02:46.430 --> 00:02:49.710 And we try to explore that, but at the end of the day, there may still be some 00:02:49.710 --> 00:02:55.310 disagreements, and that's part of what makes science fun and awesome is that we get to 00:02:55.310 --> 00:03:00.030 disagree with each other and do some research and get to the bottom of it. 00:03:00.350 --> 00:03:05.470 Yeah, I think I and I think this episode is a lovely example of Rob, is an incredibly 00:03:05.740 --> 00:03:06.540 brilliant. 00:03:06.860 --> 00:03:10.140 I mean, he is a giant whose uh shoulders we're all standing on. 00:03:10.220 --> 00:03:15.020 And a lot of what we take for granted, our our generation, meaning like David and I's uh 00:03:15.020 --> 00:03:16.940 generation, is because of John. 00:03:17.180 --> 00:03:21.980 Um, John and Lita and Rob and Joan and other folks like that. 00:03:22.140 --> 00:03:23.740 And I think Rob talked a lot. 00:03:23.900 --> 00:03:29.370 We talked also about that and just sort of the debates that were had um in their 00:03:29.370 --> 00:03:35.210 generation were sort of necessary for uh for coming to uh what you know uh 00:03:35.370 --> 00:03:41.050 you me and christina's uh view is now and not everybody agrees with us but that's that's 00:03:41.050 --> 00:03:46.490 part of the fun it's also a good example of uh not disagreeing to the point of vilifying 00:03:46.570 --> 00:03:51.770 but do the opposite of like we're all friends we can all be nice uh interpersonally but 00:03:51.770 --> 00:03:57.500 still disagree um uh or have debates we should that's the point of science yep absolutely. 00:03:57.580 --> 00:04:02.860 So it was it was a really fun time uh chatting with Rob and Christina about these big 00:04:02.860 --> 00:04:07.020 issues confronting the evolutionary social sciences and also the history of our field and 00:04:07.020 --> 00:04:08.700 how our field itself has evolved. 00:04:08.780 --> 00:04:11.100 Um I think you'll get a lot out of this conversation. 00:04:11.420 --> 00:04:12.540 Yeah, enjoy. 00:04:16.620 --> 00:04:18.380 Rob, it's really great to see you. 00:04:18.460 --> 00:04:19.980 Um thanks for being on. 00:04:20.140 --> 00:04:26.010 Um I wanted to start out by asking a simple question, which is um when 00:04:26.010 --> 00:04:31.930 I when I think of you and Pete's uh and other people's work, um the 00:04:32.090 --> 00:04:35.690 the sort of not by genes alone expression. 00:04:35.770 --> 00:04:41.450 Um so the idea of sort of uh biological evolution and gene uh gene 00:04:41.450 --> 00:04:47.160 selection um being adequate for an 00:04:47.160 --> 00:04:51.320 organism to be adapted or survive in an environment. 00:04:51.640 --> 00:04:57.080 My understanding is that one of the things that you did was 00:04:57.400 --> 00:05:03.240 to think about these other selective regimes that are on top of genetic 00:05:03.240 --> 00:05:08.600 selection, like cultural selection, as an additional mechanism. 00:05:09.080 --> 00:05:15.030 Is it accurate to say that that's something that you and the people around you really 00:05:15.350 --> 00:05:16.710 initiated and plugged in? 00:05:16.790 --> 00:05:18.310 Where did that idea come from? 00:05:19.110 --> 00:05:24.950 Um we Pete and I got started 00:05:24.950 --> 00:05:27.190 in the mid-1970s. 00:05:27.430 --> 00:05:33.280 And um it's hard to understand now, actually, um, or hard to 00:05:33.840 --> 00:05:39.680 behavioral ecology, um game theory, you know, evolutionary game theory was 00:05:40.720 --> 00:05:42.160 at best nascent. 00:05:42.320 --> 00:05:47.760 I mean, Hamilton had written these landmark papers in the 60s uh about 00:05:47.920 --> 00:05:53.680 kin selection, about senescence, um uh about sexual bunch of 00:05:53.680 --> 00:05:54.320 stuff. 00:05:54.640 --> 00:06:00.400 And and Maynard Smith had written, uh, and Parker and some other people had 00:06:00.400 --> 00:06:06.370 written these um taken basically the very surface ideas of 00:06:06.370 --> 00:06:11.810 game theory and and shown how they could be used to formalize the frequency dependent 00:06:11.810 --> 00:06:16.850 selection that arises when when you have social interactions of various kinds. 00:06:17.170 --> 00:06:23.090 But uh I mean the the textbook I went to graduate school in 1970 and 00:06:23.090 --> 00:06:29.010 the textbook that was the main textbook in ecology 00:06:29.010 --> 00:06:34.540 was a by a guy named Eugene Odom and it set out as its 00:06:34.860 --> 00:06:40.700 central premise that species evolve for the good of the species. 00:06:41.260 --> 00:06:47.260 And um and in the US, people just didn't think the 00:06:47.260 --> 00:06:52.300 same way that we do now about, you know, I mean, if you want to call it individual 00:06:52.300 --> 00:06:55.020 advantage or gene centered, there are various ways to think about it. 00:06:55.180 --> 00:07:01.030 But but and then in 1976 Wilson published sociobiology, which 00:07:01.350 --> 00:07:07.270 had a huge impact, uh, but was only sort of I mean, he 00:07:07.270 --> 00:07:11.910 never really completely understood, in my view, modern evolutionary theory. 00:07:12.150 --> 00:07:17.910 He was he kinda understood it, but you know, it he was 00:07:17.910 --> 00:07:23.300 still rooted, I think, in in to some degree in the older 00:07:23.380 --> 00:07:26.980 ecological, you know, Tinbergen style picture of things. 00:07:27.140 --> 00:07:32.580 Now things were somewhat different in Great Britain, where people were more centered in the 00:07:32.740 --> 00:07:35.540 in the modern way of thinking about things. 00:07:35.860 --> 00:07:41.860 Anyway, and then Dick Alexander, uh sort of, I think of Dick and 00:07:42.230 --> 00:07:47.990 and uh Wilson as kind of the fathers of American anyway, evolutionary 00:07:47.990 --> 00:07:48.550 thinking. 00:07:48.790 --> 00:07:54.470 And Dick wrote this long paper in uh the annual review of ecology 00:07:54.630 --> 00:07:55.670 and systematics. 00:07:55.830 --> 00:08:01.270 And unlike Wilson, it was completely rooted in the new way of thinking. 00:08:01.590 --> 00:08:03.430 And and was also full. 00:08:03.590 --> 00:08:07.910 I mean, Wilson famously had this last chapter where he said this is all going to change the 00:08:07.910 --> 00:08:08.950 social sciences. 00:08:09.110 --> 00:08:10.230 But it was kind of vague. 00:08:10.310 --> 00:08:16.180 And whereas Alexander got down to cases and I don't know if you ever met Dick but 00:08:16.980 --> 00:08:22.900 he was kind of a dark character in some ways but but very insightful 00:08:22.900 --> 00:08:28.740 guy and the the paper is just full of intriguing ideas about human 00:08:28.740 --> 00:08:33.620 evolution so people did the obvious thing they started thinking you know how how can we 00:08:33.620 --> 00:08:39.590 explain human evolution in evolutionary terms And there's a 00:08:39.590 --> 00:08:40.950 lot of enthusiasm. 00:08:41.430 --> 00:08:47.110 And both Pete and I, our initial reaction is yes, but 00:08:48.710 --> 00:08:54.390 it it doesn't, it's it's not enough that people are are as different from other 00:08:54.390 --> 00:08:59.910 vertebrates as you know uh multicellular organisms are from single cell. 00:08:59.990 --> 00:09:04.140 I mean it's and so anyway, that's why we started thinking about this. 00:09:04.300 --> 00:09:09.020 And so from the start, our idea was to try to understand. 00:09:09.100 --> 00:09:12.860 I mean, I mean, the obvious difference is different groups of people behave differently. 00:09:12.940 --> 00:09:16.060 It must have something to do with non-genetic transmission. 00:09:16.300 --> 00:09:21.330 Try to build a theory where that's something that could be favored by natural selection and 00:09:21.330 --> 00:09:24.210 at the same time lead to divergent results. 00:09:24.450 --> 00:09:30.450 And Mark Feldman and Luca Kowali-Sforza had written this book. 00:09:30.610 --> 00:09:36.450 Well, not a book yet, a bunch of papers in the early and mid-70s showing how you 00:09:36.450 --> 00:09:41.650 could use population genetic ideas, ideas from population genetics theories, 00:09:42.140 --> 00:09:43.980 to think about cultural transmission. 00:09:44.140 --> 00:09:47.100 They were not interested in the same questions we were. 00:09:47.740 --> 00:09:53.660 Mark was has been and still is very interested in genes and IQ and trying to make proper 00:09:53.660 --> 00:09:59.020 inferences from phenotypic variation, you know, amongst families and stuff. 00:09:59.340 --> 00:10:04.540 And only much later became interested in what I think of as the as the adaptationist 00:10:04.860 --> 00:10:10.550 questions, really not until the late 80s and 90s, but we were greatly 00:10:10.550 --> 00:10:16.310 benefited by what they taught, basically, in these papers about how you could use 00:10:16.310 --> 00:10:17.990 ideas in population genetics. 00:10:18.070 --> 00:10:24.070 And in our 84 book, I think what we mainly added was, well, 00:10:24.230 --> 00:10:24.950 two things. 00:10:25.430 --> 00:10:31.270 A bunch of ideas about directional processes that would lead to adapt culturally 00:10:31.270 --> 00:10:33.030 mediated adaptation. 00:10:33.270 --> 00:10:38.300 Because what it's got to be, you know, whatever it is, besides making things different, 00:10:38.460 --> 00:10:43.900 it's if it evolved, it's the system has to make has to be adaptive, the psychology has to 00:10:43.900 --> 00:10:44.140 pay. 00:10:44.300 --> 00:10:50.300 And also, uh, I think the thing that that we did that made people take 00:10:50.300 --> 00:10:56.140 notice was we said, okay, but yeah, how how can you make a system like that evolve 00:10:56.140 --> 00:10:58.620 from an organism that doesn't have a system like that? 00:10:58.940 --> 00:11:01.660 How can it produce fitness benefits? 00:11:01.900 --> 00:11:07.890 Um and then of course we're interested and at the same time you know lead to 00:11:07.890 --> 00:11:12.930 all the weird things that people do so that's uh we got started because we were interested 00:11:12.930 --> 00:11:18.610 in that question and uh we just kept plugging away uh what was the 00:11:19.730 --> 00:11:25.570 was the were the tools that these that was in the water that was new was it this 00:11:25.730 --> 00:11:31.650 frequency dependent the game theory or ESS analysis and then then that was 00:11:31.650 --> 00:11:35.880 the that was sort of the idea that was those were the tools. 00:11:36.040 --> 00:11:36.760 Is that correct? 00:11:36.840 --> 00:11:42.760 Or what would you say are were the well I think the the that was you needed those tools 00:11:42.760 --> 00:11:46.440 to do a proper job of asking what natural selection would do. 00:11:46.680 --> 00:11:49.800 You know, I mean you're making lots of simplifications like usual. 00:11:50.040 --> 00:11:55.960 But what Kavali Sforz and Feldman added and we added was seeing 00:11:55.960 --> 00:12:01.310 that uh once you have sufficiently accurate social 00:12:01.550 --> 00:12:07.470 learning, however that works, it creates another system which carries 00:12:07.950 --> 00:12:10.590 information through time, creates history. 00:12:10.750 --> 00:12:14.030 And in most organisms, I mean there are a bunch of things. 00:12:14.190 --> 00:12:19.150 There's succession and and you know all this extended evolutionary synthesis stuff. 00:12:19.230 --> 00:12:24.750 You know, so Pete Pete was raised on a farm and he likes farming examples. 00:12:24.990 --> 00:12:30.920 And uh if you think about transmitting farms, that's a kind of example of 00:12:30.920 --> 00:12:33.400 how you can have a non-genetic transmission. 00:12:33.480 --> 00:12:38.360 If you inherit a farm, your the behaviors that are good for you, everything else, is 00:12:38.360 --> 00:12:40.680 different than if you don't inherit a farm. 00:12:41.080 --> 00:12:46.440 But farms can't spread the way the idea about how to farm can spread. 00:12:46.760 --> 00:12:52.200 Because energetically small things, you know, 00:12:52.440 --> 00:12:58.050 knowing when to plant and knowing how to fertilize and stuff like that, they can spread 00:12:58.050 --> 00:13:03.490 extremely rapidly because they don't the the information itself doesn't count for much. 00:13:03.730 --> 00:13:09.410 Uh so I think that's personally, I think that's what makes culture different than other 00:13:09.410 --> 00:13:10.130 forms of. 00:13:10.290 --> 00:13:15.330 I mean, fins are a good example, but how you get from fins to legs, um 00:13:16.130 --> 00:13:21.410 uh knowing something about development and knowing something about 00:13:21.480 --> 00:13:26.600 homeobox genes and all these things that that encode developmental rules 00:13:27.240 --> 00:13:29.400 gives you a lot of purchase and understanding. 00:13:29.480 --> 00:13:34.920 So you know the story of TikTolic, this I think it's still the oldest fit, uh 00:13:35.240 --> 00:13:37.160 oldest land vertebrate. 00:13:37.320 --> 00:13:41.080 And this this guy whose work I'm uh what's his name? 00:13:41.240 --> 00:13:45.150 Uh your inner fish um I can't remember his name. 00:13:45.230 --> 00:13:48.030 This is a the hazard of old age. 00:13:48.110 --> 00:13:51.230 But anyway, I can't remember anything from the screen. 00:13:52.350 --> 00:13:55.390 My my proper noun module is failing on me. 00:13:55.550 --> 00:14:01.550 But but um so if you look at the you know, invertebrates, the uh uh 00:14:02.110 --> 00:14:07.470 landvertebrates, the you know, you get one bone in the upper arm, two bones in the next 00:14:07.470 --> 00:14:09.310 length, and then all kinds of little bones. 00:14:09.470 --> 00:14:10.910 You don't get any of that in fish. 00:14:10.990 --> 00:14:11.710 You just get this. 00:14:13.160 --> 00:14:18.360 and the question is, how do you get from fish to land 00:14:18.680 --> 00:14:19.320 vertebrates? 00:14:19.400 --> 00:14:25.240 And this guy whose name I will remember eventually, um he was 00:14:25.400 --> 00:14:26.680 he's a paleontologist. 00:14:26.760 --> 00:14:32.280 He worked on yep in North Greenland on these sediments that had um, you know, uh 00:14:32.360 --> 00:14:37.800 500 million year old um no, that's not right, must be more like 300 million year old, 00:14:37.880 --> 00:14:43.370 anyway, early land vertebrates, and um and he and he found these 00:14:43.370 --> 00:14:48.730 forelimbs of these early fishy um land vertebrates. 00:14:48.890 --> 00:14:53.930 And to understand how you got there from fins, you really do need to understand. 00:14:54.090 --> 00:14:58.810 Well, I don't know if you need, but it it's immensely it makes it much easier to understand 00:14:58.810 --> 00:15:04.060 what happens if you understand how limb development works. 00:15:04.380 --> 00:15:10.140 And so, you know, um, you know, the phenotypic 00:15:10.140 --> 00:15:16.140 gambit gets you why these organisms needed rigid forelimbs and and a bunch 00:15:16.140 --> 00:15:19.340 of other stuff, but it doesn't tell you why they're built the way they are. 00:15:19.900 --> 00:15:21.020 Yeah, no, no, no, for sure. 00:15:21.100 --> 00:15:26.630 It's not the whole picture and it's not satisfying for explaining what what which part of 00:15:26.870 --> 00:15:28.790 organism space to to use the talk. 00:15:29.190 --> 00:15:29.430 Exactly. 00:15:29.510 --> 00:15:33.750 It's yeah evolution is depends on where the variation is. 00:15:34.150 --> 00:15:39.270 And the phenotype gamba just essentially says, I don't know about that, so I'm not going to 00:15:39.270 --> 00:15:39.990 worry about it. 00:15:40.230 --> 00:15:40.870 Exactly. 00:15:41.110 --> 00:15:44.470 And I think this is actually something Christina and I have talked a lot about over the 00:15:44.470 --> 00:15:50.470 decades that that also, you know, you simplify what's not relevant for your particular 00:15:50.950 --> 00:15:52.540 um right goals. 00:15:53.020 --> 00:15:53.340 Right. 00:15:53.580 --> 00:15:57.180 Um and I think, you know, and one of the other things too is, you know, I uh obviously I 00:15:57.180 --> 00:15:59.820 was a student of Lita Cosby's and John Tube. 00:15:59.900 --> 00:15:59.980 Yeah. 00:16:00.220 --> 00:16:05.740 And I know there was a history of, you know, it was sort of uh love and conflict in the 00:16:05.740 --> 00:16:10.540 sense of you both had uh there were similar missions of evolutionizing the human behavioral 00:16:10.540 --> 00:16:12.860 sciences, using evolution to understand human behavior. 00:16:13.020 --> 00:16:17.340 But then there was um and yeah I know Rob, you and I have had conversations over the years 00:16:17.420 --> 00:16:17.820 too. 00:16:17.980 --> 00:16:23.510 Um uh yeah I mean maybe the well yeah and Christina no 00:16:23.590 --> 00:16:24.150 exactly. 00:16:24.390 --> 00:16:28.790 Um uh I mean do you I don't even know where to start with that. 00:16:28.870 --> 00:16:34.070 I don't I don't know if I even have a question, but like that might lead into um yeah I 00:16:34.070 --> 00:16:39.700 think it the contrast I think is um uh 00:16:39.940 --> 00:16:40.900 is useful. 00:16:41.060 --> 00:16:46.340 Uh I mean, and I wouldn't have said was, Lita's still around and right, still working, is 00:16:46.340 --> 00:16:46.500 that right? 00:16:46.820 --> 00:16:47.940 Yeah, no, Lita, yes, of course. 00:16:48.020 --> 00:16:53.940 Yeah, no, Lita's and we spent six months together at a 00:16:53.940 --> 00:16:59.940 institute in Germany and um and uh I would say we're 00:16:59.940 --> 00:17:05.370 friends, but um or were with John and but 00:17:05.690 --> 00:17:10.970 definitely pretty deep disagreements about uh how to think about 00:17:11.450 --> 00:17:17.290 both evolution and um and then about human evolution 00:17:17.290 --> 00:17:18.170 in particular. 00:17:18.410 --> 00:17:24.170 Um I was my evolution training came uh 00:17:24.730 --> 00:17:30.220 at UC Davis, which in those days was the 00:17:30.220 --> 00:17:33.180 heartland of selectionist biology. 00:17:33.740 --> 00:17:39.100 And then I did a postdoc at the University of Chicago, um, where 00:17:39.580 --> 00:17:42.700 the there was a renaissance. 00:17:42.940 --> 00:17:48.620 Uh it didn't last that long, but uh in uh monitative 00:17:48.620 --> 00:17:54.190 genetics and genetics of characters that are affected by genes at many loci. 00:17:54.750 --> 00:18:00.110 And and I would say that John and I had real disagreements about, 00:18:00.590 --> 00:18:03.790 forget about culture, about how evolution worked. 00:18:04.030 --> 00:18:09.710 And um, I mean, I still think I'm right or was right, but but I'm sure he thought the 00:18:09.710 --> 00:18:10.110 same. 00:18:10.350 --> 00:18:16.260 Uh he had a very fisherian view of of i and i don't really know i never talked to lead 00:18:16.420 --> 00:18:21.940 about this very much but s selection being acting on dragging 00:18:21.940 --> 00:18:27.940 genes slowly and he put a lot of emphasis on species as a real thing and i think 00:18:27.940 --> 00:18:33.620 they're at best an abstraction uh and the picture of evolution that that i think is 00:18:34.310 --> 00:18:39.830 is correct is that m most evolution now 00:18:39.990 --> 00:18:41.030 isn't always true. 00:18:41.190 --> 00:18:47.190 Sometimes it does work in a fisheron way, but but it's working on standing variation. 00:18:47.750 --> 00:18:53.510 So I don't know if you take uh so I mean there's been a lot of 00:18:53.510 --> 00:18:59.460 water under the bridge since, but um so this guy, John Losos, I don't know if you 00:18:59.460 --> 00:19:00.260 know his work at all. 00:19:00.420 --> 00:19:05.460 He works on anoles in in um the Caribbean. 00:19:05.700 --> 00:19:11.140 And um so it turns out that on each of the Caribbean islands there are 00:19:11.460 --> 00:19:15.700 a whole community of these lizards, anoless lizards. 00:19:15.860 --> 00:19:19.780 And there's big ones that live in the top of the trees and the little skinny ones that run 00:19:19.780 --> 00:19:25.230 along branches, and other ones that hold, you know, and And they've got typical 00:19:25.230 --> 00:19:29.710 phenotypic, these are mainly morphological color differences. 00:19:29.950 --> 00:19:33.710 And none of the of these guys on the different islands are related. 00:19:33.950 --> 00:19:39.630 On each island, these um morphs evolved from some 00:19:39.630 --> 00:19:44.430 generalist that made it to the island and then differentiated into all these things. 00:19:44.750 --> 00:19:48.120 Okay, not so radical already. 00:19:48.280 --> 00:19:53.400 They've done experiments where they in Loso says, and this is there's lots of work like 00:19:53.400 --> 00:19:58.600 this now, where they introduce lizards to islands with no lizards. 00:19:59.000 --> 00:20:04.520 And within five years, you begin to see 00:20:04.840 --> 00:20:10.760 these species first track the ones that run the little branches end up being having shorter 00:20:10.760 --> 00:20:14.440 legs, and the ones that live higher up in the trees have longer legs. 00:20:15.350 --> 00:20:16.470 but five years. 00:20:16.630 --> 00:20:22.470 This isn't gene new mutations happening and being dragged slowly across to fixation. 00:20:22.710 --> 00:20:28.630 This is taking standing variation that affects morphology and rapidly 00:20:28.630 --> 00:20:29.110 shifting. 00:20:29.190 --> 00:20:35.110 And there's lots and lots of examples like this coloration in deer mice, um 00:20:35.750 --> 00:20:41.500 uh coloration in guppies, life history variables in guppies. 00:20:41.660 --> 00:20:47.420 So you can so in Guppies, there are these 00:20:47.420 --> 00:20:49.900 rivers in Trinidad where all this work has been done. 00:20:50.060 --> 00:20:54.540 And as you go up the river, eventually you get to a pond above a waterfall where there are 00:20:54.540 --> 00:20:55.820 no predators. 00:20:56.060 --> 00:21:02.060 And the guppies up there are have slow life histories, and the guppies just below the 00:21:02.060 --> 00:21:04.140 waterfall have fast life histories, right? 00:21:04.220 --> 00:21:06.380 Because they got to get going before they get eaten. 00:21:06.700 --> 00:21:12.370 And so this guy Dave Resnick, who's at at Riverside, 00:21:12.530 --> 00:21:17.730 um put various predators, two different kinds of predators in these things above the 00:21:17.730 --> 00:21:18.130 things. 00:21:18.210 --> 00:21:23.250 And within three or four years, you've got faster life histories. 00:21:23.570 --> 00:21:29.250 And um so can I ask if if the implication of this difference 00:21:29.960 --> 00:21:35.880 in thinking is that evolution can happen much quicker if it's acting on standing 00:21:35.880 --> 00:21:36.520 variation. 00:21:36.840 --> 00:21:42.040 But is it also something about the nature of the variation, like that these are something 00:21:42.040 --> 00:21:46.680 like packages of traits, something going back a little bit to the phenotypic problems of 00:21:46.680 --> 00:21:48.040 the phenotypic gambit? 00:21:48.360 --> 00:21:48.600 Yeah. 00:21:49.470 --> 00:21:50.590 don't yeah. 00:21:50.750 --> 00:21:54.110 Are there constraints that you think are important to consider or no? 00:21:55.470 --> 00:21:58.670 There are, I'm certain, but I don't think we know what they are. 00:21:58.990 --> 00:22:04.750 I think um so resnik also, I mean, so these are all pretty simple 00:22:04.750 --> 00:22:09.230 changes, although life history, I don't think we really understand exactly what's going on 00:22:09.230 --> 00:22:09.550 there. 00:22:09.790 --> 00:22:15.560 Um but uh he he did uh in the same genus as guppies, but not 00:22:15.560 --> 00:22:16.200 guppies. 00:22:16.520 --> 00:22:21.480 Um he worked on um the evolution of live birth. 00:22:21.880 --> 00:22:26.360 So um uh a lot of fish have live birth. 00:22:26.440 --> 00:22:29.000 They retain the eggs inside their bodies. 00:22:29.320 --> 00:22:35.270 The the little developing embryos feed on the yolk, and then they have 00:22:35.270 --> 00:22:35.910 live birth. 00:22:35.990 --> 00:22:37.430 That's not such a big deal. 00:22:37.670 --> 00:22:43.030 But there are three species in this genus that have 00:22:43.030 --> 00:22:46.390 evolved placentas, basically. 00:22:46.550 --> 00:22:50.710 So they they lay eggs with hardly any yolk. 00:22:50.950 --> 00:22:56.710 And then they have uh an organ that uh it's not like our placenta 00:22:56.790 --> 00:23:02.390 particularly, it's designed differently, but still it's a complex organ whose job it is 00:23:02.710 --> 00:23:08.480 to provide nutrients to these little developing embryos 00:23:08.480 --> 00:23:10.640 that don't have any yolk to eat. 00:23:11.040 --> 00:23:16.080 And uh at a minimum, they've evolved that those have evolved in 00:23:16.080 --> 00:23:21.760 250,000 years in one of the species, maybe a million in the other two. 00:23:21.920 --> 00:23:22.800 And that's a minimum. 00:23:22.880 --> 00:23:27.760 That's from the last common ancestor that doesn't that doesn't have this tray. 00:23:28.160 --> 00:23:33.970 Um, So I don't think we really know about the evolution of I mean 00:23:34.130 --> 00:23:37.810 simple things like morphology, we know for sure that can evolve fast. 00:23:38.450 --> 00:23:44.130 And it it evolves fast, not because it's one gene, it evolves fast because it's many 00:23:44.130 --> 00:23:46.290 genes, each with small effect. 00:23:50.050 --> 00:23:54.610 You make a wolf into a Pekinese and you know, in hardly any time at all. 00:23:54.860 --> 00:24:00.860 And and I don't think we know about um but I do think it makes you think 00:24:00.860 --> 00:24:06.460 twice about the EEA and and th that our mind 00:24:06.780 --> 00:24:12.780 is a or our brain is a series of modules that were designed to deal 00:24:12.780 --> 00:24:16.460 with things ten thousand years ago and haven't changed since. 00:24:16.620 --> 00:24:22.470 Uh I actually think this is a problem that so my colleague here, um uh 00:24:22.630 --> 00:24:27.510 Kevin Langergraber has has argued that chimps have menopause. 00:24:27.590 --> 00:24:32.470 Uh and that's hugely controversial right this second, and people argue back and forth. 00:24:32.630 --> 00:24:34.710 I don't want to get in the middle of that one. 00:24:35.110 --> 00:24:40.550 But menopause, uh, people have measured the heritability of menopause. 00:24:40.820 --> 00:24:43.380 I had a student a long time ago, Jocelyn Pichet. 00:24:43.540 --> 00:24:44.820 You knew Jocelyn, didn't you? 00:24:45.060 --> 00:24:46.100 No, it was before my time. 00:24:46.420 --> 00:24:46.900 Before your time. 00:24:48.500 --> 00:24:51.620 She measured the heritability of menopause about 0.3. 00:24:52.180 --> 00:24:57.700 And her there were some problems with her work, but it's been done twice since, 00:24:58.020 --> 00:25:00.660 and estimates are about the same. 00:25:00.980 --> 00:25:06.340 So what that tells you is if there were a selected, so now you have peasant populations, 00:25:06.500 --> 00:25:11.370 agricultural populations, where, you know, women could keep having kids. 00:25:11.530 --> 00:25:13.450 Why aren't they keep having kids? 00:25:13.690 --> 00:25:18.330 Um and if you I mean the selective advantage ought to be pretty big. 00:25:18.570 --> 00:25:24.090 You could move menopause, this is the age of menopause, which in most populations is around 00:25:24.090 --> 00:25:27.290 50, pretty easily in a few thousand years. 00:25:27.450 --> 00:25:28.090 Not even that. 00:25:28.170 --> 00:25:33.480 I mean, and we know a thousand years, well, we know historical evidence, let's say, that 00:25:33.480 --> 00:25:37.800 suggests it hasn't changed much in the age of menopause in 2000 years. 00:25:37.960 --> 00:25:43.320 Now that's not very good data, but so anyway, I think there are I I don't have an answer to 00:25:43.320 --> 00:25:43.720 this question. 00:25:43.960 --> 00:25:49.720 I mean, in the end, uh I'm more of a agnostic about these things than than Lita and John 00:25:49.960 --> 00:25:50.200 were. 00:25:50.360 --> 00:25:52.250 And uh yeah, go ahead. 00:25:52.570 --> 00:25:55.450 Maybe like one of their arguments would be, or maybe not them. 00:25:55.530 --> 00:25:55.770 I don't know. 00:25:55.850 --> 00:26:00.810 I've seen Ed Hagen recently, like Yeah, it's a good good foil because he's so smart. 00:26:02.330 --> 00:26:03.530 Be so careful, right? 00:26:03.850 --> 00:26:03.930 Yeah. 00:26:04.090 --> 00:26:09.930 And I my understanding of some of their argument is that um complex adaptations, which is 00:26:10.170 --> 00:26:13.210 I mean, it is a complex adaptation because like now we're talking about, you know, 00:26:13.290 --> 00:26:19.050 quantitative traits that have multiple those sides, multiple phenotypes, but that um you 00:26:19.080 --> 00:26:24.440 know, I guess it's not arguable to say that the human brain is a complex adaptation, but 00:26:24.440 --> 00:26:25.800 there might be diff, you know, differences. 00:26:25.960 --> 00:26:31.480 Obviously, there's genetic variation in various cognitive, but I'm sure memory is I'm sure 00:26:31.560 --> 00:26:32.120 so so many things. 00:26:32.360 --> 00:26:32.760 Yeah, yeah, yeah. 00:26:33.320 --> 00:26:34.120 What isn't? 00:26:34.360 --> 00:26:40.120 Um, but that like the fundamental kind of um questions about human cognition that are like 00:26:40.360 --> 00:26:46.290 more species typical are unlikely to have changed as much in the last, 00:26:46.370 --> 00:26:48.610 I don't know, 10,000 years or something like that. 00:26:48.770 --> 00:26:49.730 Um, what do you make? 00:26:50.050 --> 00:26:56.050 I guess obviously it can't be any kind of um categorical 00:26:56.050 --> 00:27:02.050 break um in terms of what has and hasn't changed, but I guess there is, 00:27:02.210 --> 00:27:08.050 you know, there there's the equivalent of um biological anthropologists who look at kind 00:27:08.050 --> 00:27:14.000 of lumbar morphology and bipedalism and how it kind of works generally in humans. 00:27:14.320 --> 00:27:18.960 And I guess maybe their argument, but you guys might represent it better, would be 00:27:18.960 --> 00:27:22.560 something like there's the the equivalent attempt at doing something like that for the 00:27:22.560 --> 00:27:23.440 human mind. 00:27:23.760 --> 00:27:29.520 Um and and I think, you know, yeah, I there are things like lumbar morphology that are 00:27:29.600 --> 00:27:34.870 species typical in humans, but there's a lot of other stuff that's, you know, family 00:27:34.870 --> 00:27:40.630 typical and and uh you know so uh and and I don't think 00:27:40.870 --> 00:27:46.870 uh you know how much of I No what's exactly species also but 00:27:47.190 --> 00:27:52.230 yeah we are very, very you know uh living as I am living amongst 00:27:52.230 --> 00:27:56.160 paleoanthropologists these days, um uh No mess. 00:27:56.800 --> 00:28:02.640 Well, you know, I mean my my the director of the Institute of Human Origins, uh 00:28:02.720 --> 00:28:08.400 Johannes Heile Selassie, has just published in Nature a few weeks 00:28:08.400 --> 00:28:13.280 ago this species of Australopithecus uh 00:28:13.440 --> 00:28:14.560 Deridimata. 00:28:14.880 --> 00:28:16.080 Derridimata. 00:28:16.240 --> 00:28:18.480 When he first published it, I thought, ah, come on. 00:28:18.560 --> 00:28:19.840 You know, is that really that different? 00:28:20.000 --> 00:28:20.720 Is that as well? 00:28:21.120 --> 00:28:22.130 How the heck do we know? 00:28:22.290 --> 00:28:24.930 Living at exactly the same time as Aphorensis? 00:28:25.090 --> 00:28:29.010 And now he's got pretty good evidence that it had a significantly different mode of 00:28:29.010 --> 00:28:35.010 locomotion, that it had a opposable, semi-opposable toe and and um much 00:28:35.010 --> 00:28:36.290 longer arms. 00:28:36.530 --> 00:28:38.770 And you know, is that a species? 00:28:38.930 --> 00:28:43.490 Uh you know, I mean, all dogs are the same species, right? 00:28:43.570 --> 00:28:49.380 But if but if people found those fossils in the fossil record, Actually, 00:28:49.460 --> 00:28:54.500 this goes back to a story when Lyle visited Darwin in the 00:28:54.500 --> 00:28:55.940 mid-1850s. 00:28:56.020 --> 00:28:58.340 And you know, Darwin was a pigeon. 00:28:58.420 --> 00:29:04.020 He he kept pigeons of and and people had bred all these and you know, just as 00:29:04.020 --> 00:29:06.180 diverse as dogs, basically. 00:29:06.500 --> 00:29:12.070 And Lyle said, you know, shuddered that this 00:29:12.150 --> 00:29:17.030 basically wrecked everything because if we found these pigeons in the fossil record, they'd 00:29:17.030 --> 00:29:18.150 be different families. 00:29:18.310 --> 00:29:21.030 Yeah, more from based on their morphology. 00:29:21.270 --> 00:29:25.110 So you know, so I don't know how I got there exactly. 00:29:25.670 --> 00:29:29.910 As a very short person, oftentimes, like with towering people around me, I think how 00:29:29.860 --> 00:29:35.060 paleontologic would have surely classified as a but I'm not enough of a paleontologist to 00:29:35.060 --> 00:29:35.140 know. 00:29:35.460 --> 00:29:38.020 I mean maybe if they only got like my humorous or something like that. 00:29:38.260 --> 00:29:39.060 Yeah, exactly. 00:29:39.300 --> 00:29:45.060 Joan says that uh uh if you don't know David, Joan's about the same height 00:29:45.140 --> 00:29:47.860 as Christina, roughly, don't you think, Christina? 00:29:48.020 --> 00:29:49.380 I think maybe she has an inch on me. 00:29:49.460 --> 00:29:50.340 So I'm 4'11. 00:29:50.580 --> 00:29:51.460 Oh, she's five feet. 00:29:51.540 --> 00:29:51.700 Yeah. 00:29:51.940 --> 00:29:53.540 Those inches really make yeah, yeah. 00:29:54.100 --> 00:29:55.860 So she claims five feet. 00:29:55.940 --> 00:30:00.130 Uh and um she says all people are tall. 00:30:00.210 --> 00:30:05.970 You know, I can't tell a difference between okay. 00:30:06.050 --> 00:30:08.130 So I I don't know about John and Lita. 00:30:08.290 --> 00:30:14.290 I mean, I uh their method required them 00:30:14.450 --> 00:30:20.440 that there were these modules and by looking at contemporary behaviors, because they 00:30:20.440 --> 00:30:24.680 were the result of modules or some kind of enclosed I know you've written about modules. 00:30:24.920 --> 00:30:28.760 Yeah, but I mean but I mean it doesn't I don't mean modules in that technical psychological 00:30:28.920 --> 00:30:29.080 sense. 00:30:29.400 --> 00:30:35.400 Yeah yeah uh but that you could map particular input output relations back 00:30:35.560 --> 00:30:37.320 to some problem in the police. 00:30:38.120 --> 00:30:42.200 If you can't do that you've got problems, right? 00:30:42.360 --> 00:30:48.050 And I'm skeptical about that and uh you know uh and I'll I'll rat 00:30:48.610 --> 00:30:49.570 Pete out here. 00:30:49.650 --> 00:30:54.450 Uh Pete and I have ferocious arguments about this, 00:30:55.170 --> 00:30:56.130 basically. 00:30:56.290 --> 00:30:59.890 Um, he thinks there are none, no modules. 00:31:00.050 --> 00:31:04.450 And he bases this on, he's read a lot more than I have, of 00:31:05.250 --> 00:31:06.530 neurobiology. 00:31:06.770 --> 00:31:12.080 And um, there was a paper in Nature um some nature 00:31:12.080 --> 00:31:17.840 reviews a few a year or two ago uh which argued basically human brains 00:31:17.840 --> 00:31:23.760 just have more of the same they're just chimp brains with more of everything and no special 00:31:23.760 --> 00:31:29.760 f features i i can't i have no idea how to evaluate those kind of arguments 00:31:30.150 --> 00:31:32.870 And so I say, Pete, what about birds' nests? 00:31:33.030 --> 00:31:35.270 What about you know, beaver dams? 00:31:35.430 --> 00:31:37.270 Those look like modules to me. 00:31:37.510 --> 00:31:43.350 And you know, beavers, I've read quite a bit about beavers and uh little beavers. 00:31:43.510 --> 00:31:49.510 So beavers live in ponds where the everybody behind the dam is fairly closely 00:31:49.510 --> 00:31:49.990 related. 00:31:50.150 --> 00:31:56.070 The ecologists have studied them, you know, the averages are like 0.3 or 0.4 or 00:31:56.070 --> 00:31:56.630 something like that. 00:31:56.790 --> 00:32:00.680 So, and you know, pretty impressive, actually. 00:32:01.000 --> 00:32:06.760 But when the little beavers leave, they disperse, and they beavers build different 00:32:06.760 --> 00:32:12.040 kinds of structures and different kinds of aquatic environments. 00:32:12.280 --> 00:32:18.200 Sometimes they build little canals back to a pond they make for themselves. 00:32:18.280 --> 00:32:21.190 Sometimes they just build lodges on the side of streams. 00:32:21.270 --> 00:32:22.630 Sometimes they build dams. 00:32:22.790 --> 00:32:26.790 They build dams in different ways depending on how much water pressure there is. 00:32:26.950 --> 00:32:32.070 And those little beavers seem to know how to do that without ever having seen a dam being 00:32:32.070 --> 00:32:32.390 built. 00:32:32.550 --> 00:32:34.550 There's no social learning involved. 00:32:34.710 --> 00:32:36.790 And the same thing is true of birds' nest. 00:32:36.950 --> 00:32:42.630 Uh there uh so weaver birds, people have done raised weaver birds uh without 00:32:42.820 --> 00:32:46.900 any um exposure to nest building. 00:32:47.060 --> 00:32:50.100 And they build now, they don't do there is learning involved. 00:32:50.180 --> 00:32:55.620 So the first nest a weaver bird built is not as good as the second nest that he builds. 00:32:55.780 --> 00:33:00.260 And they are all the men or the males are building the nest, so he is okay. 00:33:00.420 --> 00:33:06.180 But um so there's some kind of information encoded in weaver 00:33:06.180 --> 00:33:09.940 bird brains and in beaver brains that tells them how to build a nest. 00:33:10.350 --> 00:33:16.350 Uh and so that makes me skeptical of the neurobiological arguments. 00:33:16.590 --> 00:33:20.350 Uh and I can't convince Pete. 00:33:20.430 --> 00:33:25.790 He's he's really really gone over to the everything is is um 00:33:26.030 --> 00:33:27.870 plastic kind of picture. 00:33:28.030 --> 00:33:30.190 And it's based on, you know, he's not stupid. 00:33:30.270 --> 00:33:34.430 He doesn't think it's a blank slate, but but he thinks it's there are these general 00:33:34.820 --> 00:33:38.660 motivational and embodied principles. 00:33:38.820 --> 00:33:41.060 And then that's where all the details come from. 00:33:41.220 --> 00:33:42.500 And I don't know. 00:33:42.740 --> 00:33:48.740 So I I just know that I'm I can't, I'm not convinced that anybody knows the answer 00:33:48.740 --> 00:33:49.140 to that. 00:33:49.300 --> 00:33:53.380 So do you think it's like an ontogenetic phylogenetic distinction? 00:33:53.460 --> 00:33:57.630 Like, I mean, do you think the people are saying it's just more of they're looking at the 00:33:57.630 --> 00:34:03.390 ontogeny and then the sort of to to to be really glossy about it, like John 00:34:03.630 --> 00:34:08.590 and Lita are thinking about sort of the the phylogenetic design on the developmental system 00:34:08.750 --> 00:34:10.830 to kind of bring it back to what we talked about before. 00:34:10.990 --> 00:34:15.150 But they weren't emphasizing that because they weren't studying the developmental system. 00:34:15.470 --> 00:34:16.430 Yeah, I don't know. 00:34:16.590 --> 00:34:22.380 I mean, uh uh every time I read neurobiology, I think, you know, they don't know what 00:34:22.380 --> 00:34:25.500 they're talking about, but at the same time they know a huge amount of stuff. 00:34:25.660 --> 00:34:27.660 And uh so I don't know. 00:34:27.820 --> 00:34:33.420 I just don't, you know, I I I never have had the enough background or 00:34:33.420 --> 00:34:39.340 ambition to um really and I don't think my own guess is I mean I bet 00:34:39.660 --> 00:34:43.180 my career on this kind of that it's not there yet. 00:34:43.260 --> 00:34:48.220 They don't know enough to know how it all works and um and uh 00:34:49.150 --> 00:34:54.590 and firm conclusions one way or the other, yeah, uh are dubious. 00:34:54.670 --> 00:35:00.350 But yeah, I I remember uh Randy Gallstell gave his talk because he's got that Gallastel um 00:35:00.590 --> 00:35:04.350 uh and I can't think of the other person's name because I can't think of nouns either. 00:35:04.510 --> 00:35:09.310 Um, but uh but they've got this book about you know memory requires addressable read write 00:35:09.470 --> 00:35:09.870 format. 00:35:10.030 --> 00:35:10.350 Yeah. 00:35:10.510 --> 00:35:15.550 And uh, you know, neural conductance changes don't doesn't buy you that. 00:35:15.820 --> 00:35:19.580 And I remember he gave a talk at Yale when I was a postdoc and he gave the talk in front of 00:35:19.580 --> 00:35:23.180 the neuroscientists at Yale and he gave this like hour long talk and they went crazy. 00:35:23.500 --> 00:35:25.980 And actually he was like the nobody had a good answer. 00:35:26.060 --> 00:35:31.100 And really when it came down to literally one of the people said, Yeah, but it's hard. 00:35:32.220 --> 00:35:34.380 So yeah, so I think your career is fine, Rob. 00:35:34.460 --> 00:35:35.260 I think they don't know. 00:35:35.900 --> 00:35:36.300 We don't know. 00:35:36.380 --> 00:35:37.260 No, we don't know anything. 00:35:37.340 --> 00:35:38.860 None of us know how this stuff works. 00:35:39.420 --> 00:35:43.610 I will tell you a Randy Gallstall anecdote, which is on the same theme. 00:35:43.770 --> 00:35:49.370 So I was at a conference in Paris, and and uh I was sitting next to Randy, who is a has a 00:35:49.370 --> 00:35:50.970 wicked sense of humor. 00:35:51.210 --> 00:35:54.890 And um uh and it's kind of a contrary, you know. 00:35:55.130 --> 00:36:00.730 And uh so this guy was giving this, you know, it was kind of a typical um 00:36:01.050 --> 00:36:02.410 neurobiology talk. 00:36:02.570 --> 00:36:07.160 He was an anatomist, and he was, you know, this is kind of like the old song, you know, the 00:36:07.160 --> 00:36:08.840 thigh bones connected to the neck bones. 00:36:09.000 --> 00:36:14.040 They have all these circuits in the brain and and different pieces are connected. 00:36:14.200 --> 00:36:19.240 And he had done a whole bunch of fancy work to to learn how, you know, 00:36:19.720 --> 00:36:24.680 information, we presume, is being transmitted between these uh 00:36:25.880 --> 00:36:28.520 uh anatomically different parts of the brain. 00:36:28.760 --> 00:36:34.450 And so somebody, and I don't know who raised their hand and said, Uh can you 00:36:34.450 --> 00:36:40.210 explain uh how the information that's transmitted all along these circuits is encoded? 00:36:40.770 --> 00:36:46.770 And Randy leaned over to me and he said, Now a glimpse into the abyss. 00:36:47.010 --> 00:36:52.880 And and and uh so uh 00:36:53.040 --> 00:36:54.160 and the guy had no answer. 00:36:54.240 --> 00:36:55.520 I said, We have no idea. 00:36:55.680 --> 00:36:58.640 And uh no, this is 20 years ago, but yeah. 00:36:59.280 --> 00:37:00.640 Well, at least it was an honest answer. 00:37:00.720 --> 00:37:04.480 Yeah, no, I mean, and that's yeah, I think that's I mean, I I appreciate that about all of 00:37:04.480 --> 00:37:09.920 us here is you know, I don't know, it's a good thing to Didn't you say I Rob, I feel like 00:37:09.920 --> 00:37:13.120 this is a story you told about John Maynard Smith where something somebody said something, 00:37:13.280 --> 00:37:14.400 Oh, you changed your mind once. 00:37:14.480 --> 00:37:15.600 And he said, Of course I did. 00:37:15.680 --> 00:37:16.560 I I knew the data. 00:37:16.640 --> 00:37:18.480 Like, is that no, I don't know that story. 00:37:18.720 --> 00:37:19.360 Okay, yeah, yeah. 00:37:19.440 --> 00:37:24.050 But I think that yeah, thinking that feeling like you have to know something is is a curse 00:37:24.050 --> 00:37:25.170 of the ac the account. 00:37:25.410 --> 00:37:25.730 Yeah, yeah. 00:37:25.810 --> 00:37:31.650 No, he was uh John is my intellectual hero and um and uh 00:37:32.610 --> 00:37:35.090 he was an honest guy that way. 00:37:35.330 --> 00:37:35.570 Yeah. 00:37:35.810 --> 00:37:36.850 Did you know him? 00:37:37.170 --> 00:37:38.690 Um kind of. 00:37:38.930 --> 00:37:44.780 Uh I uh I met him at various conferences and then we we got 00:37:44.780 --> 00:37:47.580 invited to this, both got invited to this. 00:37:47.980 --> 00:37:53.820 Uh that it's in Steyr, um, Austria, every year they 00:37:53.820 --> 00:37:59.820 have a kind of a school on on um some topic. 00:38:00.140 --> 00:38:06.140 And uh uh the I got invited to give a bunch of lectures on, and and they invite a 00:38:06.140 --> 00:38:09.810 bunch of students for a week, and then the last day a bunch of big shots show up. 00:38:10.050 --> 00:38:15.890 And uh so I wasn't a very big shot, but I they talked me into giving lectures 00:38:15.890 --> 00:38:21.810 about game theory and kin selection to all these students, you know, four 00:38:21.810 --> 00:38:24.850 days, hour and a half lecture every day. 00:38:25.170 --> 00:38:30.210 And uh so I get there, and who's in the audience but John Maynard Smith? 00:38:30.290 --> 00:38:31.490 Holy crap! 00:38:31.730 --> 00:38:37.540 And uh and um so unlike the other big shots, he showed up the 00:38:37.540 --> 00:38:41.780 first day, listened to the whole thing, talked to the students. 00:38:42.100 --> 00:38:43.540 Uh, he was great. 00:38:43.700 --> 00:38:47.460 And it turned out that like me, he's an early riser. 00:38:47.620 --> 00:38:53.460 So, you know, at 6 30 every morning, he and I were there at the beginning of the line to 00:38:53.460 --> 00:38:53.940 get breakfast. 00:38:54.020 --> 00:38:56.180 And so I had breakfast with him every morning for the week. 00:38:56.260 --> 00:38:57.300 And I hung out with them. 00:38:57.380 --> 00:39:00.950 We got to be, you know, we were hanging out together a lot. 00:39:01.110 --> 00:39:01.270 Yeah. 00:39:01.430 --> 00:39:03.510 And then I met him some other times. 00:39:03.670 --> 00:39:09.510 And I I mean, he was a prickly guy, but I thought great. 00:39:09.750 --> 00:39:15.510 And um and um you know, not a modest fellow, 00:39:15.590 --> 00:39:18.950 but but uh I don't think he probably had good reason not to be honest. 00:39:19.430 --> 00:39:20.470 That's that that is true. 00:39:20.710 --> 00:39:26.000 Um I I wanna see if I could so uh it'll probably be um of interest to our listeners to see 00:39:26.000 --> 00:39:31.360 if we could really nail down on what the disagreements are between uh you and Lita and 00:39:31.360 --> 00:39:31.520 John. 00:39:31.680 --> 00:39:35.120 So in discussing these differences about how evolution works, it's gonna really make me 00:39:35.120 --> 00:39:35.840 fess up here now. 00:39:35.920 --> 00:39:36.720 But okay sorry. 00:39:38.000 --> 00:39:42.000 No I think it's important for us to get a handle on precisely what the disagreements are 00:39:42.000 --> 00:39:43.040 and whether they even exist. 00:39:43.120 --> 00:39:45.790 Because I think there are some people who think that we can all just get along and these 00:39:45.790 --> 00:39:49.710 disagreements are just kind of narcissism of petty differences. 00:39:49.950 --> 00:39:55.710 Um but uh so in 00:39:55.710 --> 00:40:00.430 talking about your your differences between Lita and John, you mentioned rapid evolutionary 00:40:00.430 --> 00:40:02.110 change and guppies and lizards. 00:40:02.190 --> 00:40:05.950 You talked about uh the evolution of menopause, how it has surprisingly low heritability 00:40:06.030 --> 00:40:08.750 and how there may have been surprisingly high heritability. 00:40:08.990 --> 00:40:09.470 Oh, you think? 00:40:09.630 --> 00:40:09.710 Okay. 00:40:09.960 --> 00:40:10.520 Regardless of the thing. 00:40:10.760 --> 00:40:16.760 0.3 means that if you get a one standard deviation change due to selection, you get 00:40:16.760 --> 00:40:20.600 a three tenths of a standard deviation change per generation. 00:40:20.840 --> 00:40:21.720 Do the math. 00:40:21.880 --> 00:40:23.640 You get Yeah, that's true. 00:40:24.760 --> 00:40:29.640 Um but nevertheless, uh I I believe the suggestion was that um, you know, there could have 00:40:29.640 --> 00:40:33.800 been selection for uh increased menopause in recent human evolutionary history, but the 00:40:33.800 --> 00:40:37.750 fact that we didn't see that suggests that there's some kind of constraint to um to 00:40:37.990 --> 00:40:38.630 adaptiveness. 00:40:38.790 --> 00:40:39.430 Is that the same thing? 00:40:39.590 --> 00:40:44.870 No, or that, or that for some reason a 50-year-old menopause is is fitness 00:40:44.870 --> 00:40:45.830 maximized. 00:40:45.990 --> 00:40:47.110 Uh okay. 00:40:47.430 --> 00:40:47.750 All right. 00:40:47.910 --> 00:40:51.190 Um well so the I I'm still trying to nail down what the disagreement is then. 00:40:51.270 --> 00:40:56.710 Is it just that um uh there's been more recent uh evolution than perhaps Tubian 00:40:56.790 --> 00:40:57.590 Cosmodies think? 00:40:57.750 --> 00:41:02.070 That uh maybe the EEA is more recent than they they might have thought, or is it is the 00:41:02.070 --> 00:41:06.960 point that there are constraints on optimality that limit the utility of adaptationist 00:41:06.960 --> 00:41:07.360 analysis. 00:41:07.520 --> 00:41:13.120 What what what is Yeah, no, I uh all this is secondary. 00:41:13.280 --> 00:41:18.800 Uh um uh the real disagreement between John, 00:41:19.360 --> 00:41:25.200 Lita, Pete and I uh is I think about 00:41:25.920 --> 00:41:31.360 um cultural evolution and its role in explaining 00:41:31.600 --> 00:41:32.480 behavior. 00:41:33.040 --> 00:41:38.830 Um Pete and I think that uh, well, to put it 00:41:38.830 --> 00:41:44.270 as bluntly as possible, that in humans, selection has favored a 00:41:44.270 --> 00:41:50.190 psychology that does stuff that causes people to do stuff that they 00:41:50.190 --> 00:41:55.000 see people around them doing, even though they have no uh 00:41:55.480 --> 00:41:59.080 adaptive reason to think that's the correct thing to do. 00:41:59.800 --> 00:42:03.480 And uh I've got models, of course, that show that's possible. 00:42:03.720 --> 00:42:09.560 Now that's you know, why maybe as as Pete's kid used to say. 00:42:09.800 --> 00:42:13.400 Um and uh uh uh 00:42:14.920 --> 00:42:20.680 philosophers use talk about why possibly, that's what models but I like why maybe better. 00:42:20.840 --> 00:42:26.770 Um and uh I mean I think, I mean, I've talked to 00:42:26.770 --> 00:42:27.890 John about this. 00:42:28.050 --> 00:42:33.810 Uh he just I had never talked to Lita about this, but uh uh 00:42:34.050 --> 00:42:39.810 he thought that was impossible, that our psychology couldn't be 00:42:39.810 --> 00:42:45.560 built in a way that uh you would learn to be 00:42:45.560 --> 00:42:51.560 celibate, or you would learn to risk your life climbing mountains, or you would learn all 00:42:51.560 --> 00:42:57.080 those things would have to arise from motivations and information 00:42:57.080 --> 00:43:02.360 processing that would have been favored by selection in a 00:43:02.360 --> 00:43:04.360 hunter-gatherer existence. 00:43:04.680 --> 00:43:08.040 Um small bubble bands, et cetera, et cetera. 00:43:08.200 --> 00:43:13.630 And I just think that's wrong that that selection has created a 00:43:13.630 --> 00:43:18.270 psychology that causes us to be susceptible to 00:43:19.630 --> 00:43:24.350 the social environment, informational environment in which we live. 00:43:24.830 --> 00:43:30.510 And because it it it's so social 00:43:30.670 --> 00:43:32.670 learning is a two-edged sword. 00:43:33.340 --> 00:43:39.100 It gives us immense adaptive power, much greater adaptive power 00:43:39.100 --> 00:43:41.020 than any other vertebrate. 00:43:43.580 --> 00:43:48.140 Since now I'm giving a speech, but I'll give the speech anyway. 00:43:53.500 --> 00:43:57.260 It depends who you listen to, emerged from Africa. 00:43:57.580 --> 00:44:02.390 And they spread across the world in a few thousand years. 00:44:02.790 --> 00:44:07.190 So this is a a um a 00:44:08.310 --> 00:44:14.070 vertebrate uh a tropical forager living 00:44:14.390 --> 00:44:19.910 in warm environments with a particular mix of of adaptations that are 00:44:19.910 --> 00:44:20.470 necessary. 00:44:20.710 --> 00:44:26.320 And it looks like within a few thousand years they're living north of the Arctic 00:44:26.320 --> 00:44:32.000 Circle, and in which the suite of adaptations 00:44:32.240 --> 00:44:36.800 necessary to make a living is immensely different. 00:44:37.680 --> 00:44:42.720 And you need clothing, you need housing, you need all kinds of stuff. 00:44:43.040 --> 00:44:48.970 And uh this people were able to acquire all these adaptations for 00:44:48.970 --> 00:44:54.810 all the different parts of the world they lived in because they could evolve 00:44:54.810 --> 00:45:00.250 culturally and acquire inf so it's not 00:45:00.250 --> 00:45:03.290 individual humans that adapt. 00:45:03.690 --> 00:45:09.120 Human populations adapt because they can share information 00:45:09.680 --> 00:45:13.520 and they can it only works if you 00:45:15.120 --> 00:45:21.040 adopt adaptations that you don't understand why they're 00:45:21.040 --> 00:45:22.240 the way they are. 00:45:23.680 --> 00:45:25.360 Credulity, yeah, like the kayakism. 00:45:26.080 --> 00:45:27.600 Yeah, so you have to be credulous. 00:45:28.320 --> 00:45:32.170 And what you get for that is this 00:45:33.770 --> 00:45:39.690 huge adaptive machine that gives you things that individual 00:45:39.690 --> 00:45:44.250 cognition, as smart as we are, is grotesquely 00:45:45.210 --> 00:45:47.370 underpowered to acquire. 00:45:47.690 --> 00:45:53.620 And uh but that means that you're prone to picking up ideas that 00:45:53.700 --> 00:45:55.860 you know aren't that sensible sometimes. 00:45:56.020 --> 00:46:01.060 And so I think it's a it's like lots of stuff in evolution, there's a trade-off. 00:46:01.140 --> 00:46:06.500 There's a trade-off between having cultural adaptation, and I'll say just as an aside, 00:46:06.740 --> 00:46:12.340 David, uh I think selection's important, but so are non-selective processes. 00:46:12.580 --> 00:46:16.580 So it it it it it cultural selection is only part of the story. 00:46:16.820 --> 00:46:22.690 Um I mean transformative processes like spurber and all those guys 00:46:22.850 --> 00:46:24.610 are are for sure important. 00:46:25.410 --> 00:46:31.250 And um uh uh and we can talk about that if you want. 00:46:31.410 --> 00:46:36.690 But but so uh and I think I mean maybe I'm 00:46:36.690 --> 00:46:42.530 caricaturizing caricaturing um uh John and Lita, but 00:46:42.530 --> 00:46:47.540 I I think and I've talked more to John about this than Lita. 00:46:47.860 --> 00:46:49.540 He just thought that was nonsense. 00:46:49.780 --> 00:46:55.380 That uh that um um people were smart. 00:46:55.460 --> 00:46:59.700 They had all these domain-specific adaptations and 00:47:01.220 --> 00:47:07.220 um it it seems like though that there's a compatibility between the two 00:47:07.220 --> 00:47:07.620 views. 00:47:07.700 --> 00:47:12.990 I the only disagreement that I can pick up on is on the extent of of credulity about this 00:47:12.990 --> 00:47:14.110 cultural information. 00:47:14.270 --> 00:47:19.230 But it seems like you could get that kind of cultural adaptation with a fair amount of 00:47:19.230 --> 00:47:23.550 credulity and a fair amount of scrutiny of the different cultural variants and a fair 00:47:23.550 --> 00:47:28.110 amount of sensitivity to, say, the success of a particular hunting practice or a particular 00:47:28.110 --> 00:47:31.550 person who's adopting that practice or the particular social benefits. 00:47:31.710 --> 00:47:35.870 You know, all of these, the psychology could be sensitive to all of these variables, and 00:47:35.870 --> 00:47:37.630 you could still get this cultural adaptation. 00:47:37.710 --> 00:47:41.300 And in fact, it could even facilitate this cultural adaptation if you have these 00:47:41.300 --> 00:47:42.580 psychological sensitivities. 00:47:42.900 --> 00:47:43.300 Of course. 00:47:43.460 --> 00:47:43.780 Yeah. 00:47:43.860 --> 00:47:48.500 I mean, this is um, you know, what people say about scientific theories. 00:47:48.580 --> 00:47:52.580 Um uh the first the first reaction is well, that's complete nonsense. 00:47:52.660 --> 00:47:54.020 How could that possibly be? 00:47:54.180 --> 00:47:58.980 The second reaction is, well, maybe under particular circumstances, and the third reaction 00:47:58.980 --> 00:48:00.660 is that's what we thought all along. 00:48:01.140 --> 00:48:07.110 And um, and uh, you know, uh I maybe I think maybe 00:48:07.110 --> 00:48:11.990 there's a sociological pr point here to make which is that like I think for the point of 00:48:12.230 --> 00:48:16.630 showing the novelty and the of of being able to make new predictions. 00:48:16.790 --> 00:48:22.070 Um I think you know culturalists have often pointed to really amazing things that are weird 00:48:22.070 --> 00:48:27.680 in humans, like you mentioned celibacy, like sacrificing for and Kind of the 00:48:27.680 --> 00:48:28.400 in-group. 00:48:28.640 --> 00:48:32.080 And I do bet that like some people don't think that that's, you know, there are different 00:48:32.080 --> 00:48:35.680 explanation people propose different explanations for those extreme examples. 00:48:35.840 --> 00:48:41.440 Um, but I think that that has maybe sometimes lended to be characterized as like uh people 00:48:41.440 --> 00:48:47.360 are dumb perspective, or that like the the credit like that's the extreme 00:48:47.360 --> 00:48:48.560 level of credulity, right? 00:48:48.720 --> 00:48:51.200 Like that is credulous, yeah. 00:48:51.520 --> 00:48:51.760 Right. 00:48:51.840 --> 00:48:57.590 I I I mean, um so if you think people are endowed with a 00:48:57.910 --> 00:49:03.510 so the thing is well, I mean, celibacy is an interesting one 00:49:03.670 --> 00:49:06.070 because people obviously like sex, right? 00:49:06.310 --> 00:49:10.630 And um and so the question is, how could it be? 00:49:10.790 --> 00:49:16.580 I mean, I've not just from John Alita, I mean Dick Alexander and all 00:49:16.580 --> 00:49:17.060 those people. 00:49:17.140 --> 00:49:21.700 Come on, you know, I mean try to find an adaptation like people know what they're doing 00:49:21.860 --> 00:49:27.380 right now that it's worth and the thing is uh the 00:49:28.020 --> 00:49:33.460 selection can't I mean in my view, selection can't endow us with you know have sex no 00:49:33.460 --> 00:49:37.700 matter what, because uh there are always trade-offs. 00:49:38.020 --> 00:49:43.730 So um it I mean uh to take an example, 00:49:43.890 --> 00:49:49.730 uh in in uh the Maasai, um young 00:49:50.050 --> 00:49:55.650 men, Maran E, uh are the warriors were supposed to be 00:49:55.650 --> 00:49:56.530 celibate. 00:49:57.010 --> 00:50:02.900 And um when they graduated from that age set, then they could get married 00:50:02.900 --> 00:50:03.700 and have sex. 00:50:03.860 --> 00:50:09.300 And of course, big surprise, sometimes they had sex, but you know, as Murani, 00:50:09.700 --> 00:50:11.860 not as as as seniors. 00:50:12.180 --> 00:50:14.180 But it was costly, right? 00:50:14.260 --> 00:50:17.940 There were norms in place that people imposed costs. 00:50:18.100 --> 00:50:23.780 And so people, sure, they like sex, but they're also sensitive to, you know. 00:50:23.940 --> 00:50:26.100 And so where do the norms come from? 00:50:26.580 --> 00:50:32.450 The norms on John Alita's account, I would say, have to come from some module 00:50:32.530 --> 00:50:33.010 somewhere. 00:50:33.570 --> 00:50:39.570 And um on my account, they can evolve all over the place because we don't know. 00:50:40.050 --> 00:50:44.450 It we're not very good at figuring out how society should be organized. 00:50:44.770 --> 00:50:47.810 That's another thing we don't understand very well. 00:50:48.290 --> 00:50:52.520 I mean, I I've argued sort of endlessly that 00:50:53.800 --> 00:50:59.000 selection of cultural differences between groups is one force that shapes norms. 00:50:59.160 --> 00:51:02.680 I am surely that can't be the only thing. 00:51:02.840 --> 00:51:04.520 It doesn't explain a lot of change. 00:51:04.680 --> 00:51:05.480 It's too slow. 00:51:05.640 --> 00:51:10.120 There are a lot of reasons why it can't be the main, the only main process, and I don't 00:51:10.120 --> 00:51:15.810 think we're very good at at there's some papers by Lehman and Powers and some other people 00:51:15.810 --> 00:51:17.410 about bargaining. 00:51:17.970 --> 00:51:22.850 I I think there are problems with that way of looking at it, but I think within group 00:51:22.850 --> 00:51:25.170 processes uh must be important. 00:51:25.490 --> 00:51:28.210 And um and so we got to figure that out. 00:51:28.370 --> 00:51:34.370 But it's I I think that the fact that these things are heritable at the group level, 00:51:34.530 --> 00:51:40.240 that they meaning that groups persist, you ship shift environments 00:51:40.400 --> 00:51:44.240 and and they'll shift eventually, but there it often is quite slow. 00:51:44.400 --> 00:51:49.680 And you can predict a lot about what people's norms are from what language they speak. 00:51:50.000 --> 00:51:55.680 And all these things are not the signatures of a 00:51:55.680 --> 00:52:01.520 universal psychology mapping environment, meaning the ecological 00:52:01.680 --> 00:52:05.770 physical environment, onto social behavior. 00:52:05.930 --> 00:52:10.650 It's there's some history and and um if 00:52:11.290 --> 00:52:15.050 evolutionary psychologists want to th say that's what we believe, fine. 00:52:15.930 --> 00:52:16.810 I've won. 00:52:18.490 --> 00:52:21.050 But uh and I think that's right. 00:52:21.130 --> 00:52:24.170 I mean to just put it like you know like I think Christina and I have these conversations. 00:52:24.330 --> 00:52:27.930 I think I like you know I wonder when you and John were talking, I think we're we're 00:52:28.090 --> 00:52:32.330 hindsight is 2020 and I think we wouldn't have the understanding we have if you and John 00:52:32.490 --> 00:52:36.660 hadn't had that debate, but I mean one thing I appreciate as a John Lita student was you 00:52:36.660 --> 00:52:42.580 know the kayak example where you don't just to to caricature the the 00:52:42.660 --> 00:52:48.420 the the the the john and leita uh my training would be sort of there's no account of 00:52:48.420 --> 00:52:53.460 kayak design right in the mind right that that there's you can have to explain that 00:52:53.460 --> 00:52:59.110 complexity and that adaptation and why that kayak does so well what I like about this. 00:52:59.510 --> 00:53:00.230 Or bicycle. 00:53:00.390 --> 00:53:01.510 Yeah, or bicycle or anything. 00:53:01.590 --> 00:53:01.910 Exactly. 00:53:01.990 --> 00:53:02.150 Yes. 00:53:02.230 --> 00:53:03.270 I prefer bikes as we know. 00:53:03.350 --> 00:53:03.430 Yeah. 00:53:03.590 --> 00:53:03.990 Yeah, exactly. 00:53:05.990 --> 00:53:11.750 But um, yeah, no, I I mean I like that there's an extra thing to explain, which is 00:53:11.750 --> 00:53:15.830 this uh shorter time span, the trial and error. 00:53:15.990 --> 00:53:19.110 Everything is trial and error, you just don't see the error all the time, but it's you 00:53:19.110 --> 00:53:24.870 know, just variance in the world, and there's selective retention of variation in the 00:53:24.870 --> 00:53:25.350 design. 00:53:25.510 --> 00:53:30.920 And I think, you know, Christina and I, my feeling is that now evolutionary 00:53:30.920 --> 00:53:36.760 psychologists are often thinking about like, what's the EEA of the class of things 00:53:36.760 --> 00:53:41.800 that are like kayak design, exactly in the day way that David's talking about it, where 00:53:41.800 --> 00:53:47.640 there's sort of there are entries for I'm gonna accept something with credulity, 00:53:47.880 --> 00:53:48.200 right? 00:53:48.600 --> 00:53:54.310 Um because this has been an aspect that has recurrently been so I actually think 00:53:54.310 --> 00:54:00.070 we've come, I believe we've come to completely both both being 00:54:00.070 --> 00:54:04.070 integrated, but I think we didn't we couldn't have gotten there if you guys hadn't had that 00:54:04.390 --> 00:54:06.630 argument because I do think it was missing. 00:54:06.710 --> 00:54:10.920 You know, I will say that as a student of John Leader, like I do think that the extra um I 00:54:10.920 --> 00:54:12.360 mean, I think the the idea was there. 00:54:12.440 --> 00:54:17.080 I mean the true to be DeVore paper had that idea, but I don't I do think it was under 00:54:17.480 --> 00:54:18.120 emphasized. 00:54:18.200 --> 00:54:20.520 And I do think you we needed to have that argument. 00:54:20.680 --> 00:54:25.320 Maybe that's maybe that's my buffalo everybody can get along upbringing, but I but that's 00:54:25.320 --> 00:54:25.800 my opinion. 00:54:25.880 --> 00:54:26.920 That's my two cents about it. 00:54:27.080 --> 00:54:29.480 I don't know what Christina uh thinks about it. 00:54:29.640 --> 00:54:35.110 Um I think that there's a method I'm not we've been skirting around like the methodological 00:54:35.110 --> 00:54:35.830 difficulty of it. 00:54:35.990 --> 00:54:39.190 I mean I I generally agree that they're compatible, Rob, for what it's doing with. 00:54:39.590 --> 00:54:42.310 And I don't, and maybe historically they weren't. 00:54:42.470 --> 00:54:48.470 Um but there's a methodological difficulty as well in like parsing out, you 00:54:48.470 --> 00:54:53.800 know, no, if we all agree that the kayak isn't the EEA, but there's like a kayak-like 00:54:54.760 --> 00:54:54.920 things. 00:54:55.320 --> 00:54:59.720 There's no kayak module, but there's maybe is like, you know, a cock, there has to be a 00:54:59.720 --> 00:55:03.240 cognition that's capable of accepting and processing kayak-like things. 00:55:04.120 --> 00:55:06.280 And what is the category of kayak-like things? 00:55:06.520 --> 00:55:11.720 The difficulty is that, like, I'm not sure that we the kayak is a is a good or bicycle is a 00:55:11.720 --> 00:55:15.080 good example of that because we know it's like technological evolutionary history. 00:55:15.320 --> 00:55:19.160 But things like kinship structures or social systems, we have no idea. 00:55:19.320 --> 00:55:24.930 And then it becomes, I think, a much harder process of like disentangling of like, 00:55:25.090 --> 00:55:29.890 well, you know, is the reason that we have these kinds of like intuitions about kinship or 00:55:29.890 --> 00:55:34.050 about um, I don't know, maybe reciprocity or maybe about fatherhood? 00:55:34.210 --> 00:55:35.810 Like, is that like a kayak? 00:55:36.050 --> 00:55:36.370 I see. 00:55:36.450 --> 00:55:36.610 Yeah. 00:55:36.690 --> 00:55:42.210 So you're just don't have like the the historical knowledge of when this kind of fatherhood 00:55:42.210 --> 00:55:45.010 institution or this social system evolved? 00:55:45.250 --> 00:55:49.860 Or is that really a deep seated part of human cognition? 00:55:50.420 --> 00:55:51.860 Well, I mean, kinship. 00:55:52.020 --> 00:55:55.300 We know that there's a lot of cultural variation in kinship, yeah. 00:55:55.460 --> 00:56:00.580 And and we've got some idea of the timescales on which um 00:56:01.460 --> 00:56:02.340 those systems are. 00:56:02.820 --> 00:56:06.660 I guess with like phylogenetic kind of from Ruth Mace kind of stuff. 00:56:06.900 --> 00:56:07.060 Yeah. 00:56:07.220 --> 00:56:07.540 Yeah. 00:56:07.780 --> 00:56:12.990 And so I mean, throughout Western 00:56:13.710 --> 00:56:18.830 central Australia, all the dry bits basically, people had these 00:56:18.910 --> 00:56:23.230 incredibly complicated eight-section kinship systems. 00:56:23.310 --> 00:56:24.350 Do you guys know about those? 00:56:24.830 --> 00:56:26.030 Yeah, Christina knows. 00:56:26.110 --> 00:56:26.590 She's around. 00:56:27.710 --> 00:56:28.670 Yeah, exactly. 00:56:28.910 --> 00:56:33.230 And uh there's I tried to learn that it's really complicated. 00:56:34.190 --> 00:56:39.960 And and you know, that's evolved on something like 10,000 year timescales, 00:56:40.120 --> 00:56:40.280 right? 00:56:40.440 --> 00:56:46.040 Um and well we know from the geographical extent, I think, that 00:56:46.360 --> 00:56:48.920 and linguistic correlation that we don't really know. 00:56:49.080 --> 00:56:54.920 But but I mean it's not like bicycles, 00:56:55.000 --> 00:56:56.440 it's not the last hundred years. 00:56:56.520 --> 00:57:01.110 It's it's uh and kayaks we don't really know. 00:57:01.350 --> 00:57:07.190 I mean, I wish we did, but we the history of kayaks, there's some toy kayaks from about 00:57:07.190 --> 00:57:08.150 4,000 years ago. 00:57:08.230 --> 00:57:11.910 They look like the modern ones, but and that's about all we have. 00:57:11.990 --> 00:57:14.550 Uh, and then some that are a few hundred years old. 00:57:14.790 --> 00:57:18.230 Um, so we don't really know very much about the time scale. 00:57:18.550 --> 00:57:24.320 Um and surprisingly, people on the north coast of Asia 00:57:24.880 --> 00:57:30.720 and Kamcheka and places like that, which you'd think present pretty similar 00:57:30.720 --> 00:57:32.080 ecological problems. 00:57:32.240 --> 00:57:36.880 They do build skin boats, but they're really crude compared to the skin boats of people in 00:57:36.880 --> 00:57:37.680 North America. 00:57:37.840 --> 00:57:40.400 So I wish we knew more about that. 00:57:40.560 --> 00:57:46.550 And um the only good examples I think we really have are 00:57:46.710 --> 00:57:49.670 uh pretty recent um things. 00:57:49.830 --> 00:57:55.670 Uh there's a gor there's this guy whose name I forget again, sorry, who English guy who 00:57:55.670 --> 00:57:59.510 um studies the evolution of looms in East Asia. 00:57:59.750 --> 00:58:01.510 Uh they're fantastic. 00:58:01.750 --> 00:58:07.190 He really understands the history and the phylogenetic patterns, and there's a bunch of 00:58:07.190 --> 00:58:12.780 horizontal transmission, which makes, I mean, horizontal not in the between group 00:58:12.780 --> 00:58:14.060 transmission of ideas. 00:58:14.140 --> 00:58:15.180 And anyway. 00:58:15.740 --> 00:58:17.580 So I don't think we know. 00:58:17.980 --> 00:58:22.940 But I guess what I was trying to argue, Rob, is that like we know that we we we have good 00:58:22.940 --> 00:58:26.860 reason to believe that like 50,000 years ago we didn't have kayaks everywhere. 00:58:27.020 --> 00:58:28.540 Uh I don't buy that. 00:58:29.580 --> 00:58:29.740 Okay. 00:58:29.820 --> 00:58:29.900 Okay. 00:58:30.220 --> 00:58:31.100 No, I don't buy that at all. 00:58:31.260 --> 00:58:33.980 So so there could have been like we could have, I mean, I know there's debate about like 00:58:33.980 --> 00:58:39.180 Neanderthals also doing some level of like seafaring or Oh, I think the evidence evidence 00:58:39.180 --> 00:58:45.010 for seafaring uh and the first people who got to actually of all people, Kristen Hawks 00:58:45.090 --> 00:58:48.370 has a paper, uh, Kristen and Jim O'Connell. 00:58:48.690 --> 00:58:54.130 Um, quite good, I think, for my taste, quite good evidence that the earliest 00:58:54.130 --> 00:58:57.650 settlers of Australia had ocean-going boats. 00:58:57.810 --> 00:58:58.610 Oh, wow, okay. 00:58:58.850 --> 00:59:04.660 Um they get this from the settlement of offshore islands, which are which 00:59:04.980 --> 00:59:08.500 would have been you know 50 or 100 kilometers. 00:59:08.900 --> 00:59:11.140 Or maybe there is a kayak module. 00:59:11.700 --> 00:59:13.780 No, but they weren't the same boats. 00:59:13.860 --> 00:59:17.780 You know, the uh all the details about how to make the kayak. 00:59:18.100 --> 00:59:18.820 No, I agree. 00:59:19.140 --> 00:59:25.060 You know, it it's there may be some boat module, possibly. 00:59:25.140 --> 00:59:30.990 I I'm skeptical actually, but but um uh But more more plausibly there 00:59:30.990 --> 00:59:32.990 are folk physics modules. 00:59:33.150 --> 00:59:36.670 I mean, I don't like the term module, but there are systems that have intuitions or 00:59:36.750 --> 00:59:40.830 expectations about the physical world and how objects interact. 00:59:41.150 --> 00:59:46.030 Surely there are there are probably uh you know folk engineering or tool use modules where 00:59:46.030 --> 00:59:49.070 we have a concept of what a tool is and that it has a specific function. 00:59:49.630 --> 00:59:53.390 That's what this guy uh o Suriak, this French guy. 00:59:53.550 --> 00:59:55.060 Uh Anyway, sorry to interrupt. 00:59:55.300 --> 01:00:00.580 Yeah, no, and and Clark Barrett has argued this in his book Um Uh The Shape of Thought. 01:00:00.820 --> 01:00:06.660 So it seems to me that even the extreme uh Santa Barbara 01:00:06.660 --> 01:00:11.700 school picture of the mind, which is filled with these context sensitive, specialized 01:00:11.700 --> 01:00:12.740 modules, right? 01:00:12.980 --> 01:00:17.060 Is totally compatible with cultural evolution and cultural adaptation. 01:00:17.620 --> 01:00:19.460 Do you see any kind of incompatibility there? 01:00:19.540 --> 01:00:22.710 Because it seems like those those two pictures of the mind could both be true. 01:00:22.870 --> 01:00:27.990 We could both have really sophisticated minds with complex specialized adaptations, and we 01:00:27.990 --> 01:00:32.070 could have cultural evolution and culturally adaptive processes at the same time. 01:00:32.150 --> 01:00:36.230 And it may be even be the case that the two complement each other, that you're more likely 01:00:36.230 --> 01:00:40.390 to get cultural evolution in a more adaptive direction if you have the the the 01:00:40.550 --> 01:00:43.910 sophisticated mind to evaluate the different outputs of culture. 01:00:44.310 --> 01:00:48.800 But then you can't Yes, I agree with everything you just said. 01:00:49.040 --> 01:00:49.360 Okay. 01:00:49.520 --> 01:00:53.200 Um, but that's not what John Alita said. 01:00:53.440 --> 01:00:53.760 Okay. 01:00:54.000 --> 01:00:59.680 Uh they wanted to go from stories about I 01:01:00.000 --> 01:01:01.760 that's pejorative, I shouldn't say that. 01:01:02.640 --> 01:01:08.480 They wanted to go from hypotheses about uh life 01:01:08.480 --> 01:01:13.840 in mobile foraging bands in um the late Pleistocene, 01:01:14.400 --> 01:01:20.270 and make inferences about how people should behave now. 01:01:21.070 --> 01:01:26.670 And that means that there's a direct correspondence between some 01:01:26.750 --> 01:01:32.270 adaptive, I mean, I'm quoting them now almost, some adaptive problem that people 01:01:32.590 --> 01:01:38.030 faced in these Pleistocene societies and how 01:01:38.190 --> 01:01:41.870 behavior is expressed now in response to cues that people get. 01:01:42.430 --> 01:01:45.940 And uh I'm sure that's true to some extent. 01:01:46.100 --> 01:01:51.620 I mean, but um I also think there's a huge range of 01:01:51.620 --> 01:01:55.220 behavior, which that doesn't help you with. 01:01:55.380 --> 01:01:59.140 But John John, I think, thought that got you the whole package. 01:01:59.620 --> 01:02:03.940 I mean it well, it could it could well get you the whole like what if some of those modules 01:02:03.940 --> 01:02:09.810 involve evaluating potential uh tools or uh uh potential uh foraging strategies 01:02:09.970 --> 01:02:13.810 or potential social norms in terms of whether they advocate for one's interests or through 01:02:13.970 --> 01:02:19.570 the norm or the tool should be like correct they don't but they could nevertheless 01:02:20.130 --> 01:02:21.570 right I think that's that's true. 01:02:21.730 --> 01:02:23.090 That that's the key difference, right. 01:02:23.330 --> 01:02:27.730 But it seems like i if if we're assuming that they don't tell you the content of the norms 01:02:27.810 --> 01:02:32.100 or the content of the tool, then it seems like they're entirely compatible perspectives 01:02:32.100 --> 01:02:36.740 that you could yeah yeah but we got to fill in the details and you know uh 01:02:39.060 --> 01:02:42.740 yeah I don't think we're very close to that actually and I think Christina's point I mean 01:02:42.900 --> 01:02:47.780 just want to echo Christina's point it also then means that there is this issue of at what 01:02:47.780 --> 01:02:53.380 level of abstraction and the the concern would be that you're looking at um something 01:02:53.700 --> 01:02:58.410 that so just to be clear, like we were talking about like where does the evolved psychology 01:02:58.410 --> 01:03:02.170 end and where does the information stored in the environment begin? 01:03:02.970 --> 01:03:08.970 And Christina's point, if I understood it, was that you it's hard to know, and there may 01:03:08.970 --> 01:03:14.490 be cases where we think something is so well designed that uh 01:03:14.650 --> 01:03:19.770 we're really looking at it as like this is something that's in the phenotype, that's you 01:03:19.770 --> 01:03:25.440 know, reliably developing, and that's why it has the problem-solving and form 01:03:25.680 --> 01:03:27.600 fit relationship we do. 01:03:28.080 --> 01:03:33.840 But then there's this other thing of once we once we accept that cultural 01:03:33.840 --> 01:03:39.280 selection can create form-fit relationships, then we might be 01:03:39.280 --> 01:03:45.280 inferring, for just for lack of a better way of putting it, like genetic selection 01:03:45.600 --> 01:03:50.250 systems, where in fact it's more cultural selection systems. 01:03:50.410 --> 01:03:53.930 It's oh when we know the clear distinction, like Christina always talks about like reading, 01:03:54.010 --> 01:03:57.530 I think is a good example where you know if we didn't know about the history of reading, we 01:03:57.530 --> 01:03:59.450 might think it's just it's a module. 01:03:59.770 --> 01:04:00.330 It's a module. 01:04:00.410 --> 01:04:01.450 I mean maybe not. 01:04:01.530 --> 01:04:02.170 I don't I don't know. 01:04:02.250 --> 01:04:04.010 Like 'cause the fact that not everybody learns to read. 01:04:04.090 --> 01:04:07.210 Like I I I you know like any example has its issues. 01:04:07.370 --> 01:04:09.050 But I think that's a fair point, Christine. 01:04:09.130 --> 01:04:11.720 I want to make sure like that like is that fair, Christina? 01:04:11.960 --> 01:04:16.360 Yeah, and I think that so I was trying to also I not to be like material versus social is 01:04:16.360 --> 01:04:21.160 like a clear distinction, but I think that the social world is fuller of that ambiguity. 01:04:21.320 --> 01:04:24.200 Like we don't know very much about about Paleolithic social life. 01:04:24.280 --> 01:04:25.880 It probably was super diverse. 01:04:26.040 --> 01:04:31.080 Um we don't know what it was like two million years ago, three million years ago, like 01:04:31.330 --> 01:04:32.610 forget it, right? 01:04:32.850 --> 01:04:38.690 Um, and like to to do a parallel to the reading example, like almost every society has 01:04:38.690 --> 01:04:39.410 marriage today. 01:04:39.570 --> 01:04:41.010 I know there are exceptions. 01:04:41.410 --> 01:04:46.610 Um, and so we might infer that there's like a marriage-like modular world cognition that 01:04:46.610 --> 01:04:50.210 really favors marriage when you know we have good theoretical reasons to believe that 01:04:50.210 --> 01:04:51.890 that's probably a cultural institution. 01:04:52.050 --> 01:04:56.450 Like, yes, you know, partly driven by like psychological motivations that are patent human 01:04:56.530 --> 01:05:02.260 and so forth, but I think it's a real challenge to disentangle those, and more so when we 01:05:02.260 --> 01:05:07.700 don't have like a good paleontology or archaeology to kind of help with our intuition about 01:05:07.860 --> 01:05:07.940 it. 01:05:08.100 --> 01:05:08.660 Yeah, yeah, yeah. 01:05:08.900 --> 01:05:13.700 The idea that our brain is just uh you know a shapeless mass with no 01:05:13.700 --> 01:05:17.860 predispositions, that's just obviously stupid. 01:05:18.180 --> 01:05:24.100 And um I you know, Steve Pinker's book, The Blank Slate. 01:05:24.790 --> 01:05:29.750 I mean, I know there are lots of social scientists who believe in the blank slate, but 01:05:30.630 --> 01:05:33.110 they're just not thinking hard about things. 01:05:33.270 --> 01:05:33.910 It can't be. 01:05:34.070 --> 01:05:38.790 It just it just no matter what, they can't be, you know, 01:05:39.910 --> 01:05:43.830 and so it's always about how does it work exactly. 01:05:44.150 --> 01:05:50.140 And um or I completely agree with you Christina maybe exact we're never 01:05:50.140 --> 01:05:55.260 going to get to exactly but maybe a little bit of structure uh and um 01:05:56.140 --> 01:06:02.140 and uh I so what I would say is questions 01:06:02.140 --> 01:06:07.870 are not about whether there's evolved stuff in the human 01:06:07.870 --> 01:06:12.270 brain that shapes the way we respond to cues in the environment. 01:06:12.350 --> 01:06:13.790 That's gotta be, right? 01:06:14.110 --> 01:06:19.550 But there are questions about, you know, quantitative questions about where we sit on 01:06:20.030 --> 01:06:21.150 a kind of continuum. 01:06:21.230 --> 01:06:27.150 And my picture is um, because we're predisposed strongly to 01:06:27.150 --> 01:06:32.960 think what people around us do must be sensible, um uh uh we 01:06:32.960 --> 01:06:38.800 get a lot of stuff from that and um and i i 01:06:38.800 --> 01:06:44.160 if that's the way that evps psych is going i'm pleased i mean that's um 01:06:44.720 --> 01:06:49.600 uh uh you know you know when there's gonna be disagreements you know we're scientists right 01:06:49.680 --> 01:06:55.650 that's the business we're in but but uh but on the other side of things coming from like 01:06:55.810 --> 01:07:01.650 what um what questions might have influenced cultural evolutionary theorists 01:07:01.730 --> 01:07:06.930 um coming from like the more cynical like economists or of psych side, do you think that 01:07:06.930 --> 01:07:12.450 there's been any shift in like thinking about what that credulity has to look like? 01:07:12.770 --> 01:07:15.090 Or like what the limits of that credulity are? 01:07:15.410 --> 01:07:16.850 Yeah, it's a good question. 01:07:17.090 --> 01:07:22.580 Um I mean I think of it more uh I 01:07:22.580 --> 01:07:28.180 mean so so I talk to Sarah Matthew quite a bit, and 01:07:28.740 --> 01:07:34.580 she and I differ about um how likely it 01:07:34.580 --> 01:07:40.370 is that evolved motivations, I would call them about kinship and 01:07:40.370 --> 01:07:44.850 stuff, structure, cultural evolution. 01:07:45.890 --> 01:07:48.290 And, you know, she could be right. 01:07:48.450 --> 01:07:50.770 I mean, um, I could be right. 01:07:50.850 --> 01:07:53.090 Uh these are things that we're gonna learn. 01:07:53.170 --> 01:07:59.010 But I wouldn't say uh I I think of it as a bunch of specific stuff, not 01:07:59.010 --> 01:08:04.610 some general limitation about how credulous we are, but how 01:08:04.610 --> 01:08:10.480 strongly we're motivated in by different kinds of things we experience in 01:08:10.480 --> 01:08:15.760 the environment to to um to think well no yeah 01:08:16.960 --> 01:08:22.720 uh there's this xkcd cartoon that that um the 01:08:22.720 --> 01:08:28.530 mother is asking the kid you know um Are you, you know, the 01:08:28.530 --> 01:08:32.290 kid says, I I'm, you know, you you're doing this just because all your friends are doing 01:08:32.290 --> 01:08:32.370 it. 01:08:32.450 --> 01:08:37.970 And the kid says, is, yeah, that would what would I I I always succumb to kin pressure. 01:08:38.130 --> 01:08:40.130 And the mother says, why would you do that? 01:08:40.210 --> 01:08:43.250 You know, suppose you were on a on a burning bridge. 01:08:43.410 --> 01:08:49.170 And uh, and the kid says, Well, if 50 of my friends, well informed, 01:08:49.330 --> 01:08:51.640 jump off the bridge, who am I? 01:08:51.800 --> 01:08:56.120 You know, what's the newspaper the next day gonna say about the people who stayed on the 01:08:56.120 --> 01:08:56.680 bridge? 01:08:56.920 --> 01:08:59.320 And but that depends on the cue. 01:08:59.480 --> 01:09:02.280 It depends on what inferences you can make from the environment. 01:09:02.440 --> 01:09:04.120 You know, maybe all those people were stupid. 01:09:04.280 --> 01:09:08.840 They jumped off the bridge, and you're the smart person who who made the calculation to do 01:09:08.840 --> 01:09:09.880 it correctly. 01:09:10.120 --> 01:09:15.790 Um something that makes me super anxious about our enterprise here 01:09:15.950 --> 01:09:20.190 is that I think I think we can largely agree that there about like certain basic 01:09:20.190 --> 01:09:21.310 motivations that we have, right? 01:09:21.390 --> 01:09:25.390 Like motivations like hunger is motivating, um, sex is motivating, so forth. 01:09:25.870 --> 01:09:29.550 And you know, you might think on a good day, like, okay, we just need to find like the 01:09:29.550 --> 01:09:33.950 order in which the prior like the algorithm that prioritizes some motivations or the other, 01:09:34.030 --> 01:09:37.230 including the motivation to conform to others, might be like, I think there might be a 01:09:37.230 --> 01:09:42.940 little bit of a debate about how much that's in an uh bit of motivation to conform to what 01:09:42.940 --> 01:09:43.500 others do. 01:09:43.740 --> 01:09:44.060 Yeah. 01:09:44.220 --> 01:09:49.820 Um but on my nihilistic days, I think what's crazy is that those motivations themselves 01:09:49.820 --> 01:09:50.940 culturally evolve. 01:09:51.260 --> 01:09:51.740 For sure. 01:09:52.060 --> 01:09:57.900 So that makes kind of coming up with like a well, but look, I 01:09:57.900 --> 01:10:00.220 mean motivations to conform, culturally. 01:10:00.460 --> 01:10:04.620 You're prone to these kinds of motivated by hunger, right? 01:10:04.780 --> 01:10:10.350 Or like how much you should be motivated by yeah but you're prone to these depressive uh 01:10:10.670 --> 01:10:16.510 uh uh feelings Christine I've known you this long uh think of where we've come in the last 01:10:16.830 --> 01:10:22.110 75 years even 50 years you know I wouldn't we're much less confused now. 01:10:22.270 --> 01:10:22.830 I'm sorry. 01:10:22.990 --> 01:10:28.750 Yeah yeah I I wouldn't frame that as the motivation to conform evolving itself. 01:10:28.910 --> 01:10:30.430 That doesn't really make a lot of sense to me. 01:10:30.510 --> 01:10:35.560 What might make sense is that the costs of not conforming might vary from place to place. 01:10:35.720 --> 01:10:39.560 Well, I think the power imbalances and the alliance structure might be such that there are 01:10:39.560 --> 01:10:42.840 really powerful people who are really going to do bad things to you if you violate the 01:10:42.840 --> 01:10:43.080 norms. 01:10:43.240 --> 01:10:47.400 And in some environments the power structure is different and those costs aren't as high. 01:10:47.640 --> 01:10:50.680 But I wouldn't explain that as culture shaping the motivation to conform. 01:10:50.840 --> 01:10:55.080 I would just explain that in terms of, you know, the mind making cost benefit calculations 01:10:55.080 --> 01:10:58.600 about what what is going to be the likely course of action in this particular social 01:10:58.600 --> 01:10:58.920 context. 01:10:59.160 --> 01:10:59.320 Yeah. 01:10:59.400 --> 01:11:01.560 You're a real evolutionary psychologist. 01:11:01.960 --> 01:11:06.990 Uh uh there's quite a bit of evidence that in other 01:11:07.150 --> 01:11:12.030 creatures that uh there's an innate conformist propensity. 01:11:12.110 --> 01:11:16.270 It's got nothing to do with norms or other people's punishments. 01:11:16.430 --> 01:11:21.710 Uh some evidence in people, it's somewhat conflictual, conflicting, um, 01:11:22.190 --> 01:11:27.440 but models show that in the right kind of environment, having an 01:11:27.440 --> 01:11:32.880 intrinsic motive to conform can make you better off. 01:11:32.960 --> 01:11:33.280 Yeah. 01:11:33.520 --> 01:11:35.760 And uh in the fitness sense. 01:11:36.000 --> 01:11:40.080 And uh now it hangs on being hard to figure out what the right answer is. 01:11:40.320 --> 01:11:46.080 And um and uh so and I think I mean 01:11:46.160 --> 01:11:52.030 now this is I won't live long enough to find out what 01:11:52.030 --> 01:11:57.710 the answer to this question is, but uh I think we are innately 01:11:58.030 --> 01:12:03.470 predisposed, or innately, we have, you know, reliably developing whatever you want to call 01:12:03.470 --> 01:12:08.590 it, uh um propensity to obey social norms. 01:12:09.230 --> 01:12:15.150 Um we don't do a cal well, we do do calculations, but we don't need to. 01:12:15.470 --> 01:12:21.340 We're we uh all other things being equal 01:12:21.740 --> 01:12:27.340 if if the norm is to um you know 01:12:27.580 --> 01:12:33.580 play the game a particular way lime in the corn sure yeah so you know these these 01:12:33.580 --> 01:12:39.500 experiments that Mike Tomasalo has done i watch the videos he te they teach 01:12:39.500 --> 01:12:45.340 some little German kid a new game Daxing and um and then the 01:12:45.430 --> 01:12:51.190 kid learns how to play the game, and then they have a f a Schill who then 01:12:51.190 --> 01:12:52.950 plays the game wrong. 01:12:53.190 --> 01:12:58.710 And the kids, Nick, not not not Daxing, he says in German, you know, he gets gets really 01:12:58.710 --> 01:12:59.190 agitated. 01:12:59.430 --> 01:13:00.310 That's his verboten. 01:13:00.470 --> 01:13:00.550 Yeah. 01:13:02.310 --> 01:13:07.750 And uh you know, I don't think uh evolutionary 01:13:07.750 --> 01:13:13.180 psychology um i i think our 01:13:13.660 --> 01:13:19.340 our sense that some things are right and some things are wrong there's morality and uh 01:13:19.580 --> 01:13:24.860 and we feel intrinsically motivated about uh moral 01:13:24.860 --> 01:13:30.780 violations that's not in my view now this is a hypothesis not a fact 01:13:31.020 --> 01:13:36.350 uh uh a calculation based on the cost and benefits of powerful people. 01:13:36.590 --> 01:13:42.590 It's something we feel and I can make models that show how such a thing 01:13:42.590 --> 01:13:43.230 could evolve. 01:13:43.390 --> 01:13:44.990 Doesn't mean evolve that way. 01:13:46.430 --> 01:13:52.190 And it again depends on uh on the difficulty 01:13:52.190 --> 01:13:54.270 of doing the calculations. 01:13:54.350 --> 01:14:00.180 Uh and um um so uh I think uh 01:14:00.420 --> 01:14:03.620 that one is one which we're gonna make progress on, actually. 01:14:03.780 --> 01:14:06.500 That uh uh yeah, totally. 01:14:06.580 --> 01:14:07.780 You you you may be right there, Rob. 01:14:08.020 --> 01:14:12.740 There may be a real disagreement here, but I want to push you and and uh to acknowledge 01:14:12.740 --> 01:14:14.180 that maybe there is no disagreement. 01:14:14.260 --> 01:14:18.980 We're just talking past each other because even your model of norms is built on the 01:14:18.980 --> 01:14:20.020 foundations of punishment. 01:14:20.180 --> 01:14:24.710 What a norm is is something that people are punished for doing and the non-punishers are 01:14:24.710 --> 01:14:25.750 punished, right? 01:14:26.070 --> 01:14:29.910 And so the the punish the idea of punishment, the infliction of costs, is built into the 01:14:29.910 --> 01:14:30.150 model. 01:14:30.390 --> 01:14:35.590 That's it's built into the evolutionary model, not the contemporary why people do it model. 01:14:36.150 --> 01:14:40.230 So that explains why we have a norm psychology. 01:14:40.390 --> 01:14:46.230 Once you've got a norm psychology, you know, the reason that you're outraged that oh, what 01:14:46.390 --> 01:14:49.910 it was some outrage at the Olympics recently about uh some rule. 01:14:49.990 --> 01:14:53.900 But anyway, um uh or I mean seriously. 01:14:54.380 --> 01:14:58.460 But doesn't it presuppose that you have to know what's being punished and what's not being 01:14:58.460 --> 01:14:58.700 punished? 01:14:59.020 --> 01:14:59.580 No, no, no. 01:14:59.660 --> 01:15:01.180 You just need to know what the norm is. 01:15:01.500 --> 01:15:05.420 But then how but how do you know what what the norm is if unless you're observing because 01:15:05.660 --> 01:15:07.660 people teach you, because you see what everybody does. 01:15:07.980 --> 01:15:08.860 How are they teaching you though? 01:15:08.940 --> 01:15:13.100 Presumably they have to, you know, threaten you with punishment or actually punish you, 01:15:13.180 --> 01:15:13.260 right? 01:15:13.580 --> 01:15:14.300 No, no. 01:15:14.540 --> 01:15:17.820 Uh so I I don't even think you believe this. 01:15:17.980 --> 01:15:23.150 Um uh uh so uh is it okay to beat your wife? 01:15:23.550 --> 01:15:24.670 I mean, obviously not. 01:15:24.750 --> 01:15:26.350 And well, some I call it. 01:15:26.430 --> 01:15:27.310 I think it's fine. 01:15:27.550 --> 01:15:31.470 Uh yeah, when we did this fieldwork in Fiji, um 01:15:33.310 --> 01:15:39.230 uh Fijian norms uh uh have it that if you don't beat your wife when she's 01:15:39.550 --> 01:15:45.460 talks back or does some uppity thing, uh you're a not just that 01:15:45.460 --> 01:15:47.700 you don't get what you want, you're a bad person. 01:15:48.100 --> 01:15:53.860 And uh okay, so one of our field assistants was a 01:15:53.860 --> 01:15:55.940 couple, a married couple. 01:15:56.260 --> 01:16:01.780 And um uh the guy, you know, 01:16:02.100 --> 01:16:05.140 beat his wife pretty severely one night. 01:16:05.460 --> 01:16:07.060 So what do you do about that? 01:16:07.220 --> 01:16:12.610 Uh you're living in a culture where um that's the right thing to do. 01:16:12.850 --> 01:16:15.410 Uh we told him he couldn't do it. 01:16:15.490 --> 01:16:20.930 And so these moral beliefs, by the time you get to be mine, sure are strongly held. 01:16:21.010 --> 01:16:26.770 And they've got nothing to do with the calculation of of my long-term 01:16:26.770 --> 01:16:27.410 benefit. 01:16:27.570 --> 01:16:29.330 Uh I I might disagree there. 01:16:29.490 --> 01:16:34.960 I mean, like uh it I think if you ask anyone, you know, uh what will happen if you are seen 01:16:34.960 --> 01:16:39.200 as a domestic abuser, they will say that you will you will suffer horrible reputational 01:16:39.200 --> 01:16:39.760 consequences. 01:16:40.240 --> 01:16:45.840 But we pay we took this guy who was our field assistant and we paid a 01:16:45.840 --> 01:16:51.840 substantial cost to yell at him and tell him he couldn't do that in a culture where 01:16:51.840 --> 01:16:54.320 everybody thought what he was doing was fine. 01:16:54.930 --> 01:16:59.330 I think there may be presumably people understand that there are reputational costs for 01:16:59.330 --> 01:17:00.770 engaging in certain behaviors. 01:17:00.850 --> 01:17:04.210 And that was where was the reputational cost to me? 01:17:04.610 --> 01:17:10.450 Uh I I don't uh I mean maybe to be super cynical, maybe you know it was 01:17:10.450 --> 01:17:13.570 gonna get back to your colleagues that you had a wife beater already. 01:17:13.890 --> 01:17:15.890 Yeah I mean that's the argument you'd have to make. 01:17:16.690 --> 01:17:18.690 But can I subject I don't believe that argument. 01:17:18.850 --> 01:17:23.170 I I I I mean to give you another example from my 01:17:24.760 --> 01:17:30.760 failed field work um uh uh in Fiji there's a very strong norm 01:17:30.920 --> 01:17:36.600 that women must be covered from head to toe in the village and uh 01:17:36.680 --> 01:17:42.600 and Fijian guys gossip endlessly about shoulders and ankles uh and uh 01:17:42.760 --> 01:17:48.360 uh you know they never see anything else young guys that is and uh so 01:17:48.600 --> 01:17:54.010 we spent three months in this village and we went to the um to um 01:17:54.810 --> 01:18:00.730 uh we got at the village boat, took us you know several hours down 01:18:00.730 --> 01:18:06.570 the archipelago and dropped us at this beach where a tourist boat would come and pick us 01:18:06.570 --> 01:18:06.890 up. 01:18:07.210 --> 01:18:12.250 And so we're sitting on the beach having lunch, and a tourist walks by, a woman, and she's 01:18:12.250 --> 01:18:13.290 in a bikini. 01:18:13.370 --> 01:18:19.220 And I had this overwhelming that woman needs to put 01:18:19.220 --> 01:18:20.340 some clothes on. 01:18:20.660 --> 01:18:23.780 She is not dressed properly. 01:18:24.180 --> 01:18:29.700 And um there you did adapt to the local circumstances. 01:18:30.260 --> 01:18:31.460 I did, absolutely. 01:18:31.540 --> 01:18:34.340 Uh but it was, I didn't realize that adapted. 01:18:34.820 --> 01:18:40.420 You know, it was um this is not science, this is you know, it's my I'm giving 01:18:41.540 --> 01:18:46.330 anecdot that living in a place where 01:18:47.610 --> 01:18:52.170 people thought it was wrong for women, and this is all brand new in Fiji. 01:18:52.410 --> 01:18:54.170 This is only 150 years old. 01:18:54.330 --> 01:19:00.090 Uh um, and she was dressed completely fine by 01:19:00.250 --> 01:19:05.050 you know, we got on this boat and it's covered with college age tourists, all of them 01:19:05.290 --> 01:19:09.530 bikinis, and in 45 minutes I didn't feel that way anymore. 01:19:09.770 --> 01:19:15.740 But uh uh um but I speak to like three different timescales at least at 01:19:15.740 --> 01:19:19.820 which like things like punishment and I mean we could there's a whole debate about what 01:19:19.820 --> 01:19:22.380 kinds of social costs these are might be acting. 01:19:22.540 --> 01:19:24.300 So mainly not punishment, I think. 01:19:24.460 --> 01:19:26.620 Mainly loss of social standing. 01:19:26.700 --> 01:19:26.940 Yeah. 01:19:29.420 --> 01:19:31.420 That's a kind a kind of p a kind of cost, yeah. 01:19:31.740 --> 01:19:34.790 Well, but it doesn't it's not costly punishment, it doesn't cost right. 01:19:34.950 --> 01:19:39.670 If if you deprive people of costly services, you'd have to give them with because they were 01:19:39.670 --> 01:19:42.550 good people, then it actually pays you to punish them. 01:19:42.630 --> 01:19:47.190 But so there are models that are like this is about intergenerational evolutionary 01:19:47.190 --> 01:19:48.390 timescales that we're talking about. 01:19:48.470 --> 01:19:54.310 And this endowed us with some sort of like genetically evolved intuition for conforming to 01:19:54.310 --> 01:19:59.110 whatever we see other people around us to do in order to avoid those social costs. 01:19:59.270 --> 01:20:02.540 Then there's a possibility and these are not mutually exclusive because it seems like even 01:20:02.540 --> 01:20:04.540 your experiences are at different timescales, right? 01:20:05.100 --> 01:20:05.820 Two different timescales. 01:20:06.140 --> 01:20:06.940 Two different timescales. 01:20:07.180 --> 01:20:11.980 Another one is that like you in you like currently there are institutions that ostracize 01:20:11.980 --> 01:20:14.860 you, punish you, whatever, for not conforming. 01:20:14.940 --> 01:20:20.220 And so you learn about that early in childhood, let's say, and you kind of develop these in 01:20:20.220 --> 01:20:23.650 internalized ideas about what is morally right and wrong. 01:20:23.810 --> 01:20:27.490 And then like if the social environment changes for you like in adulthood, it's not going 01:20:27.490 --> 01:20:30.130 to change very quick like those intuitions aren't going to change very quickly. 01:20:30.530 --> 01:20:33.010 They're shallow, the diff the the things yeah. 01:20:33.170 --> 01:20:36.850 I I think the only thing there is a third there is a third though, just to be complete. 01:20:37.010 --> 01:20:40.050 Like there is a third possibility, I don't know if anybody believes this, but that it's 01:20:40.130 --> 01:20:42.050 like very much in the moment, right? 01:20:42.130 --> 01:20:47.250 That like the current incentive structures shape in the moment throughout your life. 01:20:47.410 --> 01:20:48.770 Like what is right and what is wrong. 01:20:48.930 --> 01:20:50.640 And I don't know how credible that is. 01:20:51.280 --> 01:20:53.280 I mean this is these are questions, right? 01:20:53.360 --> 01:20:54.080 Good questions. 01:20:54.320 --> 01:20:59.840 Uh um I mean the only thing I would add to to the to the 01:21:00.800 --> 01:21:06.720 is that once you've internalized that beating your wife is wrong, then when 01:21:06.720 --> 01:21:11.280 you do the calculation about should I beat my wife? 01:21:11.520 --> 01:21:17.190 Um uh I mean on David's account, and I I certainly think 01:21:17.190 --> 01:21:22.230 that's part of it, is I'm thinking about what'll happen to me if I get caught beating my 01:21:22.230 --> 01:21:22.710 wife. 01:21:23.030 --> 01:21:29.030 But I'm also have feelings that affect my trade-off that that 01:21:29.030 --> 01:21:30.390 this is not the right thing to do. 01:21:30.470 --> 01:21:36.470 I I I I get negative, you know, displeasure, whatever it is, um 01:21:37.720 --> 01:21:43.720 Because I grew up in a society and and so that tips, that changes the 01:21:43.720 --> 01:21:46.280 way I do the the the calculation. 01:21:46.600 --> 01:21:51.400 And um you know, I so anyway. 01:21:51.560 --> 01:21:55.720 So yeah, I think some of the issue too is I think with all of these conversations, one of 01:21:55.720 --> 01:22:01.650 the problems is uh the entire conversation we've had, natural selection or 01:22:01.650 --> 01:22:05.570 selective selection based thinking of cultural things. 01:22:05.890 --> 01:22:11.410 We we lack a good nat, we don't have a natural vocabulary of what are the entities, right? 01:22:11.490 --> 01:22:17.010 Like, is it a piece of um culture design, uh 01:22:17.330 --> 01:22:18.290 a module? 01:22:18.610 --> 01:22:22.690 And now we're talking about sort of emotions, and you know, there's sort of well, like cost 01:22:22.770 --> 01:22:23.330 benefit. 01:22:23.410 --> 01:22:26.120 There's a sense in which I can calculate the cost benefit. 01:22:26.200 --> 01:22:30.200 Like Rob, I think the other thing I do is I get really angry when people cross uh 01:22:30.360 --> 01:22:33.560 pedestrian no walks now after living in Germany. 01:22:33.880 --> 01:22:34.280 Exactly. 01:22:34.520 --> 01:22:38.120 And that's like a very that's like how many times do you get yelled at in Germany from 01:22:38.600 --> 01:22:40.040 violating some rule you didn't know? 01:22:40.680 --> 01:22:42.600 Which I yeah, I I I loved it actually. 01:22:42.760 --> 01:22:44.840 I was dispositionally German. 01:22:44.920 --> 01:22:49.930 Uh but anyway, um but uh uh but but then like there, but there's another sense of which 01:22:50.010 --> 01:22:51.770 David, you know, even the emotions, right? 01:22:51.850 --> 01:22:55.290 Like maybe the emotions baked into the emotions are cost benefit. 01:22:55.450 --> 01:23:00.170 But of course, there's a difference between the kind of rational cost benefit that sort of 01:23:00.170 --> 01:23:05.450 like goal or planning systems are considering in this very short time scale versus maybe 01:23:05.450 --> 01:23:07.770 these longer timescale emotional systems. 01:23:08.010 --> 01:23:13.820 So I think in a lot of ways, um what typically is failing us is that there's 01:23:13.820 --> 01:23:19.580 just distinctions that are not made in the natural language that we all sort of have as 01:23:19.580 --> 01:23:23.500 organisms or just as cultural beings in the 21st century now. 01:23:24.220 --> 01:23:25.500 English speakers in the 21st century. 01:23:25.820 --> 01:23:26.780 Exactly, yeah, precisely. 01:23:26.860 --> 01:23:27.500 Yeah, exactly. 01:23:27.580 --> 01:23:31.830 And that's uh yeah, we had Clark on recently and he was making a point that um, you know, 01:23:31.990 --> 01:23:35.670 it that's is also useful to talk to other people from different cultural backgrounds 01:23:35.750 --> 01:23:39.990 because they'll make different distinctions that we might be able to use, you know, or or 01:23:39.990 --> 01:23:41.590 at least see like our cultural bias. 01:23:41.750 --> 01:23:47.350 But I think, like for me at least, uh there there's a sense in which all of these 01:23:47.670 --> 01:23:53.670 debates can be resolved, but they really hang on making more distinctions, and 01:23:53.670 --> 01:23:57.430 you can't start to make those more distinctions till you maybe you have the debates to 01:23:57.430 --> 01:23:57.910 begin with. 01:23:58.150 --> 01:23:59.110 Yeah, I agree with that. 01:23:59.190 --> 01:24:04.880 Yeah, I think um uh you know we've made 01:24:04.880 --> 01:24:05.280 progress. 01:24:05.600 --> 01:24:06.240 That's good. 01:24:06.400 --> 01:24:11.520 Uh and science is the you know series of 01:24:11.520 --> 01:24:13.680 hypotheses now refuted. 01:24:13.840 --> 01:24:18.560 And also, you know, Mox Planck said science progresses one funeral at a time. 01:24:18.800 --> 01:24:21.680 Um, and I think there's some truth to that too. 01:24:21.920 --> 01:24:27.710 Um Rob just to push on like I mean for Pete's argument that it's sort of 01:24:27.710 --> 01:24:33.630 all very general he'll allow motivations yeah but no 01:24:33.790 --> 01:24:39.390 that can be quite specific motivations but there aren't any um 01:24:40.430 --> 01:24:46.270 I'm not actually sure how he parses this out but but uh uh there's 01:24:46.270 --> 01:24:52.220 nothing in there that tells you um what would be good examples I mean, obviously 01:24:52.380 --> 01:24:53.500 technological examples. 01:24:53.580 --> 01:24:56.620 There's nothing we're you know, like birds' nests. 01:24:56.860 --> 01:25:02.780 Uh and um maybe like no propensities 01:25:02.780 --> 01:25:05.980 to think about taxonomic categories in a yeah, yeah, exactly. 01:25:06.060 --> 01:25:07.580 That'd be a good thing. 01:25:07.740 --> 01:25:13.490 Uh uh that we don't we aren't innately Linnaean in our taxonomic 01:25:13.570 --> 01:25:16.050 um right way of thinking. 01:25:16.130 --> 01:25:19.170 Uh and I think the evidence is pretty good we aren't. 01:25:19.410 --> 01:25:25.170 Uh uh the Fijians put dolphins and and fish in the 01:25:25.170 --> 01:25:31.010 same category, but um uh yeah, and 01:25:31.010 --> 01:25:35.420 they don't and you know so they don't have any animals they care about. 01:25:35.500 --> 01:25:40.860 They're pigs and chickens and and you know and they just don't think about 01:25:40.860 --> 01:25:44.380 vertebrates very much, but I mean land vertebrates, but anyway. 01:25:44.620 --> 01:25:44.780 Yeah. 01:25:44.940 --> 01:25:49.420 But do you think I mean I do the I mean like we all I think we all do this, and I think 01:25:49.420 --> 01:25:54.940 this is something I learned from Christina, which is this notion of you make the 01:25:54.940 --> 01:26:00.550 tentative Almost like a gambit or like a assumption that's 01:26:00.550 --> 01:26:03.270 helpful for your own carving up the world, right? 01:26:03.350 --> 01:26:08.710 So, like I, as a as a John and Lita adaptationist, I don't want to study the 01:26:08.710 --> 01:26:13.590 complexities of like developmental programs or like genetic pleotropy. 01:26:13.830 --> 01:26:15.510 Like, I want to I want to assume that away. 01:26:15.590 --> 01:26:16.550 And so I do. 01:26:16.790 --> 01:26:21.190 And there's an argument in sense which like that's fair of me because of what I'm studying. 01:26:21.350 --> 01:26:26.880 Somebody else later, even though I'm wrong about saying it doesn't matter if I say that, it 01:26:26.880 --> 01:26:31.680 does matter, I can assume it away because for what the slice of the world is that I'm 01:26:31.680 --> 01:26:35.120 studying, I have to assume it away at least for now. 01:26:35.360 --> 01:26:39.360 Does is Pete what is is Pete assuming he's a hundred percent with that? 01:26:39.520 --> 01:26:44.950 I mean I I mean I we think of ourselves as com full adaptationists. 01:26:45.030 --> 01:26:45.350 Yeah. 01:26:45.510 --> 01:26:51.430 And and uh but we just see the adaptive problem as different 01:26:51.510 --> 01:26:56.630 than I see it differently than than maybe John and Lita did. 01:26:57.430 --> 01:27:03.350 And uh you know in our in Nobajin Salon we have this example of the 01:27:03.350 --> 01:27:09.340 avocado slicer that uh I was, you know, 01:27:09.580 --> 01:27:15.340 the the adaptationist paradigm is uh it's not a paradigm, 01:27:15.420 --> 01:27:16.540 it's a heuristic. 01:27:16.780 --> 01:27:22.460 And uh it is an extremely powerful heuristic, which sometimes leads you 01:27:22.460 --> 01:27:23.260 astray. 01:27:23.580 --> 01:27:29.100 And um uh and depends on a bunch of ancillary 01:27:29.410 --> 01:27:34.290 hypotheses about trade-offs and costs and benefits and a bunch of other stuff. 01:27:34.450 --> 01:27:39.970 And um uh and I, you know, I have no time whatsoever 01:27:40.290 --> 01:27:46.130 for Goodian or or um uh the guy 01:27:46.130 --> 01:27:52.050 that studied Tiktalic, this fish, he's a big believer in, you 01:27:52.420 --> 01:27:53.620 developmental constraints. 01:27:53.780 --> 01:27:55.860 I I don't think they're constraints. 01:27:56.020 --> 01:28:01.860 I think there are developmental pathways that affect the 01:28:01.860 --> 01:28:07.780 patterns of variation that can that do exist now and that will exist 01:28:07.940 --> 01:28:11.460 in the future if we make if we make some changes. 01:28:11.700 --> 01:28:13.380 And they're obviously important. 01:28:13.460 --> 01:28:17.860 And the extent that they're important, they make the adaptation as paradigm. 01:28:22.570 --> 01:28:26.170 Because if you don't know what those developmental um 01:28:29.850 --> 01:28:34.090 couldn't is this a I'm thinking something about why you wouldn't call this a constraint. 01:28:34.570 --> 01:28:37.610 Um like a pathway versus a constraint. 01:28:38.330 --> 01:28:44.220 Um maybe it comes from my background is doing I did for three years did 01:28:45.180 --> 01:28:51.100 optimization mathematics as a you know to design things like power plant systems and stuff. 01:28:51.260 --> 01:28:57.260 And a constraint is something is a relationship between variables that you're trying to 01:28:57.260 --> 01:28:58.860 adjust that is fixed. 01:28:59.660 --> 01:29:05.490 So either, you know, temperature is related to volume and there's a curve and 01:29:05.490 --> 01:29:11.090 then you have to travel along that curve or um or 01:29:11.330 --> 01:29:17.250 uh there's a constraint the you know something can't be greater than uh less than zero, 01:29:17.410 --> 01:29:18.210 say or something like that. 01:29:18.450 --> 01:29:18.610 Right. 01:29:18.690 --> 01:29:23.250 If you make the the smokestack higher with less concrete, it would be better, but it's not 01:29:23.250 --> 01:29:24.130 gonna stay up to the state. 01:29:24.370 --> 01:29:25.250 There is no smokestack. 01:29:25.520 --> 01:29:25.840 Yeah. 01:29:25.920 --> 01:29:26.560 It's a constraint. 01:29:26.720 --> 01:29:26.880 Yeah. 01:29:27.040 --> 01:29:32.080 And I think most of the things we ha we see in biology are 01:29:32.640 --> 01:29:38.480 things that shape the patterns of variation that selection can work 01:29:38.480 --> 01:29:38.800 on. 01:29:38.960 --> 01:29:44.160 They don't say it can't go there, but they affect the 01:29:44.320 --> 01:29:49.650 likelihood that new variants um are produced. 01:29:50.050 --> 01:29:53.570 And so sometimes it can be absolutely crucial, you know. 01:29:53.730 --> 01:29:58.370 So do you guys know the Lensky experiments with with um E. 01:29:58.530 --> 01:29:58.850 coli? 01:29:59.650 --> 01:30:02.050 Yeah, like lots of different evolutionary trajectories, right? 01:30:02.210 --> 01:30:02.450 Yeah. 01:30:02.610 --> 01:30:04.450 So Lensky did experiments. 01:30:04.530 --> 01:30:10.130 I think he's got 14 replicants now 65,000 plus 01:30:10.370 --> 01:30:11.010 generations. 01:30:11.410 --> 01:30:17.090 Uh in the same it puts them in a new environment 65,000 generations ago and 01:30:17.880 --> 01:30:19.240 watches what happens. 01:30:19.560 --> 01:30:22.680 At first, um, they diverge. 01:30:22.840 --> 01:30:28.440 Some of them uh they go in the same average direction, they get bigger, the individual E. 01:30:28.600 --> 01:30:34.360 coli get bigger, uh, they do a bunch of other things, but some lines are 01:30:34.360 --> 01:30:35.960 doing better than other lines. 01:30:36.040 --> 01:30:39.770 So, and he can prove this because he he's got them in the freezer. 01:30:39.930 --> 01:30:41.050 He's got fossil E. 01:30:41.210 --> 01:30:42.490 coli in the freezer. 01:30:42.650 --> 01:30:47.610 And he creates competition experiments between a thousand generations ago and now. 01:30:47.930 --> 01:30:51.370 And sure enough, the new ones always beat the old ones. 01:30:51.610 --> 01:30:52.970 Okay, so this is all great. 01:30:53.050 --> 01:30:58.730 And then after 20 or 30,000 generations, a lot of that variation disappears. 01:30:59.130 --> 01:31:04.730 And they are all pretty much on the same, not quite, but almost on the same trajectory. 01:31:05.050 --> 01:31:08.280 And now these are not eukaryotes, right? 01:31:08.360 --> 01:31:11.640 So they don't have full-blown recombination. 01:31:11.800 --> 01:31:13.080 They have some recombination. 01:31:13.240 --> 01:31:15.160 But so it takes a while. 01:31:15.320 --> 01:31:20.520 My picture of this and his picture is that it takes a while for you know the order in which 01:31:20.520 --> 01:31:22.760 mutations occur matters, right? 01:31:22.920 --> 01:31:28.040 Both because mutations potentiate other mutations and all this kind of stuff. 01:31:28.440 --> 01:31:33.720 But then at like 50,000, I don't know the exact number, but in about 50,000 generations, 01:31:34.200 --> 01:31:37.210 all of a sudden, one of the lines 01:31:40.090 --> 01:31:42.970 just beats the crap out of everybody else. 01:31:43.690 --> 01:31:46.010 So the typical, you know, how this experiment works? 01:31:46.170 --> 01:31:51.210 He puts he puts in some glucose in the morning. 01:31:51.530 --> 01:31:55.290 The population expands to carrying capacity, then they shut down. 01:31:55.450 --> 01:31:57.530 The next morning gives them more glucose. 01:31:57.610 --> 01:31:59.770 And that goes on for 40,000 generations. 01:31:59.850 --> 01:32:01.770 And they get better at that environment. 01:32:01.900 --> 01:32:07.660 Now there's citrate in the medium, and it's very well known in E. 01:32:07.820 --> 01:32:09.820 coli biology that E. 01:32:09.980 --> 01:32:14.060 coli cannot digest citrate in the presence of oxygen. 01:32:14.300 --> 01:32:19.580 The enzyme that's necessary to do the job is inactivated in the presence of oxygen. 01:32:19.740 --> 01:32:24.930 This is something that people who do, It was thought to be true of all E. 01:32:25.170 --> 01:32:27.810 coli, but not at 50,000 generations. 01:32:29.250 --> 01:32:35.090 A series of neutral mutations had occurred, and then eventually, and those are 01:32:35.090 --> 01:32:40.610 all improbable that they drift to high enough frequency, and then a new 01:32:40.610 --> 01:32:45.740 mutation that Coupled with those neutral ones, 01:32:46.380 --> 01:32:47.180 allowed the E. 01:32:47.260 --> 01:32:50.540 coli to digest citrate in the presence of oxygen. 01:32:50.940 --> 01:32:54.140 And all of a sudden, all bets are off. 01:32:54.220 --> 01:32:58.940 It completely annihilated the the previous um 01:32:59.900 --> 01:33:01.740 50,000 generations. 01:33:01.820 --> 01:33:07.630 You know, in humans, that goes back, you know, to the Mesozoic practically, 01:33:07.710 --> 01:33:07.950 right? 01:33:08.030 --> 01:33:13.630 I don't know exactly how far, but but 60,000 times 10 is 01:33:13.630 --> 01:33:18.110 600,000 gen uh uh no 600,000 years. 01:33:18.590 --> 01:33:23.710 Yeah, so it doesn't go back to the Mesozoic, but it goes back well before people, and um, 01:33:24.030 --> 01:33:29.320 so there is this kind of stuff you would never have predicted that on an 01:33:29.320 --> 01:33:34.520 adaptationist program if you took this 01:33:34.840 --> 01:33:36.840 species-specific property of E. 01:33:37.000 --> 01:33:43.000 coli, namely they can't digest citrate in the presence of oxygen as a fix as a 01:33:43.000 --> 01:33:44.040 constraint, right? 01:33:44.200 --> 01:33:49.800 And um, and it wasn't a constraint, there just wasn't any variation in the necessary 01:33:51.530 --> 01:33:56.490 genes which gave rise to the necessary phenotypic variation for that to happen. 01:33:56.650 --> 01:34:02.490 And the series of mutations and events, namely drift, that had to occur for that to 01:34:02.490 --> 01:34:06.090 happen, um are very improbable. 01:34:06.570 --> 01:34:12.320 So I you know I think you know the 01:34:12.320 --> 01:34:18.000 adaptation is it hypothesis extremely powerful, but sometimes it gets you the wrong 01:34:18.000 --> 01:34:18.400 answer. 01:34:18.560 --> 01:34:19.040 Yeah. 01:34:19.360 --> 01:34:24.960 So what do you make of some people are really um kind of concerned about making equilibrium 01:34:25.200 --> 01:34:29.280 type arguments, which is kind of maybe another version of the phenotypic gambit? 01:34:29.520 --> 01:34:29.920 I don't know. 01:34:30.080 --> 01:34:36.000 Just that um even if we're adaptations, like the world is constantly changing and no time 01:34:36.160 --> 01:34:37.360 more than today. 01:34:37.600 --> 01:34:42.670 Um, does this I think Pete has actually made some arguments to this effect and some of his 01:34:42.670 --> 01:34:47.310 students that like equilibrium thinking is just at odds with what we know about the human 01:34:47.310 --> 01:34:47.950 experience. 01:34:50.110 --> 01:34:54.910 Does this give us pause for making adaptationist kinds of we should think about the 01:34:54.910 --> 01:34:57.310 timescale on which variation takes place? 01:34:57.470 --> 01:35:01.710 And and I know Pete knows all about this, but he likes to argue. 01:35:02.030 --> 01:35:04.830 I have not argued with Pete about this particular item. 01:35:05.070 --> 01:35:09.240 Uh I mean there's variation on all kinds of timescales, right? 01:35:09.400 --> 01:35:15.160 And um and uh on some time scales, I 01:35:15.160 --> 01:35:19.800 think you know that technically, so if we have variation on 01:35:20.920 --> 01:35:26.440 um say we have an organism that has a one-year generation time and and we have 01:35:27.110 --> 01:35:29.910 temporal variation on 100-year timescales. 01:35:30.230 --> 01:35:36.070 Um, it's never going to reach an equilibrium, but uh, but there'll be a 01:35:36.070 --> 01:35:38.950 stationary distribution of types, right? 01:35:39.190 --> 01:35:45.190 And um it'll respond to some temporal average or in spatial, you know, 01:35:45.270 --> 01:35:48.150 it's all these averages in population genetics. 01:35:49.360 --> 01:35:55.280 I think that's clearly of great importance to get the right timescale on which you 01:35:55.280 --> 01:35:58.240 think adaptation is responding. 01:35:58.560 --> 01:36:00.320 But it's not an imprinciple thing. 01:36:00.400 --> 01:36:05.040 It's just one of the things you have to take into account when it's, you know, it's there 01:36:05.040 --> 01:36:06.160 are trade-offs, right? 01:36:06.240 --> 01:36:09.840 And and um if only we knew. 01:36:10.400 --> 01:36:15.680 Well, I think, yeah, uh I I'm more of an optimist than you are, Christina. 01:36:18.590 --> 01:36:18.910 Yeah. 01:36:19.950 --> 01:36:25.790 I think so Pete and I have argued that agriculture didn't evolve uh during 01:36:25.790 --> 01:36:31.790 the Pleistocene because not because you couldn't grow plants, because you know, wheat was 01:36:31.790 --> 01:36:32.830 growing somewhere for sure. 01:36:32.910 --> 01:36:35.870 It didn't just appear magically 10,000 years ago. 01:36:36.110 --> 01:36:41.700 Um uh but because the timescale of fluctuations during the last 01:36:41.700 --> 01:36:47.380 glacial was too short for the and I, you know, we would 01:36:47.380 --> 01:36:52.580 support that with so if you look at the spread of agriculture across the world, 01:36:53.140 --> 01:36:56.260 agriculture didn't spread, agriculturalists spread. 01:36:56.500 --> 01:37:02.100 So, um, and so populations which already had the norms, you know, 01:37:02.340 --> 01:37:07.950 women's roles, you have to be willing when you're an agriculturalist, you've got to be able 01:37:07.950 --> 01:37:08.910 to save stuff. 01:37:09.070 --> 01:37:11.230 And so sharing norms have to change. 01:37:11.390 --> 01:37:14.670 There's a whole bunch of stuff that has to change. 01:37:15.470 --> 01:37:20.030 And our argument would be that that doesn't change on 500-year timescales. 01:37:20.270 --> 01:37:25.230 And um, you know, um, now that might be wrong. 01:37:25.390 --> 01:37:29.870 Um I have to say, archaeologists haven't taken it very seriously. 01:37:30.030 --> 01:37:35.720 Um, but uh but um that's a case where 01:37:35.720 --> 01:37:41.240 our picture of the temporal scale on which norms evolve is 01:37:41.480 --> 01:37:46.680 related to the temporal scale on which the environment's evolving. 01:37:46.760 --> 01:37:51.320 And if you you know, I mean I could go on and on, but but the the the environmental 01:37:51.320 --> 01:37:56.680 variation in the Pleistocene was staggering compared to the to the Holocene. 01:37:56.920 --> 01:38:02.910 I mean, um, you know, you could be a hunter-gatherer living in what would 01:38:02.910 --> 01:38:08.590 be now the south coast of France, and 500 years later you're living in northern Norway 01:38:08.670 --> 01:38:10.990 someplace without having moved at all. 01:38:11.150 --> 01:38:17.070 That was this that was the scale and and the amplitude and timescale of and now 01:38:17.070 --> 01:38:21.390 the place, the Holocene is this happy, warm, stable world. 01:38:21.550 --> 01:38:26.060 Uh, and um, I really think we really ought to think about that. 01:38:26.140 --> 01:38:30.060 And and uh uh Eric Smith thinks. 01:38:30.380 --> 01:38:35.340 So I Pete and I published this paper, this shows you, you know, how you get hoisted on your 01:38:35.340 --> 01:38:36.220 own petard. 01:38:36.620 --> 01:38:42.140 Um uh we published this paper a couple years ago about large-scale cooperation in 01:38:42.140 --> 01:38:43.740 Holocene Hunter-gatherers. 01:38:43.820 --> 01:38:49.420 That I would argue shows there's plenty of large-scale cooperation in, 01:38:49.580 --> 01:38:55.030 and we argue, see, These ethnographic studies of the Kung and the 01:38:55.030 --> 01:38:58.870 Hadza and so on are not good models for the Pleistocene. 01:38:58.950 --> 01:39:04.790 That um that uh if you think about Pleistocene cooperation, you could you should think 01:39:04.790 --> 01:39:08.070 about large-scale cooperation amongst non-relatives. 01:39:08.230 --> 01:39:12.150 And Eric said, Oh yeah, but uh 01:39:13.500 --> 01:39:18.940 Pleistocene climate variation was so great that the social institutions necessary to 01:39:18.940 --> 01:39:24.460 support large-scale cooperation couldn't have evolved, so they were just like the Hodsa. 01:39:26.860 --> 01:39:28.380 I thought that was mean. 01:39:29.900 --> 01:39:30.940 Full circle, yeah. 01:39:31.420 --> 01:39:33.100 At least he cited you, right? 01:39:33.740 --> 01:39:35.180 He was one of the reviewers. 01:39:35.260 --> 01:39:36.060 That's how I know. 01:39:36.140 --> 01:39:37.900 It wasn't that he wrote a paper about this. 01:39:37.980 --> 01:39:43.710 It's that so we we quoted him in the paper and and uh 01:39:44.110 --> 01:39:49.950 and we got permission to use his name because Eric is a very smart guy and thoughtful. 01:39:50.030 --> 01:39:50.430 But yeah. 01:39:50.910 --> 01:39:54.670 Rob, this is a slight change of or topic, just methodological for a second. 01:39:54.750 --> 01:39:58.030 I know uh like do you what is your opinion about sort of computer technology? 01:39:58.110 --> 01:40:01.550 Because a lot of the stuff we're talking about is also like there's you can do if you 01:40:01.550 --> 01:40:06.160 understand the concepts, you can do the math, but then there's also a lot of computational 01:40:06.160 --> 01:40:07.360 modeling of things. 01:40:07.680 --> 01:40:13.040 Do you view the sort of analytic or you know math um thinking about 01:40:13.040 --> 01:40:16.240 ESSs versus modeling and simulations? 01:40:16.800 --> 01:40:20.480 Do you view that as still separate? 01:40:20.720 --> 01:40:26.720 And is there a cost of losing the first to the second with all the technology? 01:40:26.800 --> 01:40:28.640 Or what's your st what's your take on that? 01:40:28.960 --> 01:40:29.280 You know? 01:40:29.680 --> 01:40:32.400 I I I think they've always been complementary. 01:40:32.720 --> 01:40:38.390 Um I think they're the the you know the cheapness and 01:40:38.390 --> 01:40:44.230 speed of of computing has made agent based simulations better and more 01:40:44.230 --> 01:40:45.110 practical. 01:40:45.350 --> 01:40:51.030 Um I think that agent based simulations uh there's a temptation to over 01:40:51.430 --> 01:40:57.040 specify uh that people because it's easy, people have a 01:40:57.040 --> 01:41:02.160 tendency to to build what they think of as realism into the models. 01:41:02.400 --> 01:41:05.600 And you know, all models are wrong, some are useful. 01:41:05.680 --> 01:41:07.600 That's a famous aphorism. 01:41:10.640 --> 01:41:16.400 And I think that done right, um analytic 01:41:16.400 --> 01:41:22.290 models and um Computer simulations should be used 01:41:22.290 --> 01:41:27.570 together to understand things, especially things where random 01:41:27.570 --> 01:41:33.410 factors are important, like climate change or small population effects, or any of 01:41:33.410 --> 01:41:34.210 those things. 01:41:36.290 --> 01:41:42.050 I will say that for kind of sociological reasons, I think, or 01:41:42.050 --> 01:41:47.600 maybe cultural evolutionary reasons, when I publish an 01:41:47.600 --> 01:41:53.440 analytical result, the the uh I put nowadays, I didn't used to, but all the math 01:41:53.440 --> 01:41:57.440 is in the, you know, the the uh what do they call that? 01:41:57.520 --> 01:42:01.680 The supplementary the supplementary material, but somebody can follow it. 01:42:01.840 --> 01:42:02.000 Yeah. 01:42:02.240 --> 01:42:02.880 That's not true. 01:42:03.200 --> 01:42:08.400 There's no, you know, people always say I put my code in the in you know the supplementary, 01:42:08.480 --> 01:42:14.160 but it might as well be on the moon because we don't have any conventions about how to 01:42:14.400 --> 01:42:17.910 to to and I will tell you a story. 01:42:18.150 --> 01:42:24.070 Um uh I like stories, but um uh Herb Gintis and I, this 01:42:24.070 --> 01:42:29.910 2001 paper that's been cited more than any other paper I've ever written, and I actually 01:42:29.910 --> 01:42:35.190 think is maybe not such a great paper, um where we looked at uh 01:42:35.430 --> 01:42:37.270 cultural group selection. 01:42:37.590 --> 01:42:42.880 Um uh Well, the details are important. 01:42:43.200 --> 01:42:48.800 But for reasons I don't really remember, Herb and I decided to do um 01:42:49.680 --> 01:42:52.560 uh uh clean room simulations. 01:42:52.880 --> 01:42:58.800 So we both wrote simulations, we clearly specified what the model should be 01:42:58.800 --> 01:43:04.570 like, and then we wrote the simulations and they did completely different things 01:43:05.130 --> 01:43:10.570 and um uh it took us a month of hard work to 01:43:10.810 --> 01:43:16.250 find out where they diverged and why they diverged and it was all 01:43:16.250 --> 01:43:20.890 stupid reasons none of it had was conceptual and 01:43:21.900 --> 01:43:23.340 nobody does that, right? 01:43:23.420 --> 01:43:27.500 The only people who do that are people writing programs to fly airplanes and stuff like 01:43:27.500 --> 01:43:27.740 that. 01:43:28.060 --> 01:43:33.980 And um uh I think this is a big problem actually, that that the 01:43:34.060 --> 01:43:39.020 the reliability of analytical stuff is better than the 01:43:39.020 --> 01:43:44.780 reliability of simulations because you know I write 01:43:44.780 --> 01:43:47.180 simulations and I, you know, I've never done that since. 01:43:47.340 --> 01:43:53.030 It took and uh so I don't know how we're gonna solve that, uh, 01:43:53.190 --> 01:43:54.150 but we will, I think. 01:43:54.230 --> 01:43:59.750 We'll we'll come up with and it's gonna make simulations a lot harder, uh, I think uh to to 01:43:59.750 --> 01:44:01.030 to make sure they're right. 01:44:01.190 --> 01:44:06.870 And um you might be able to ask AI today what's the difference between those and herbs. 01:44:07.510 --> 01:44:12.950 Maybe maybe I I I ask AI to look at I I've been doing some simulation so 01:44:13.510 --> 01:44:16.550 Moshi and I, you remember those conversations we had. 01:44:16.710 --> 01:44:22.620 Moshi and I got in this argument about um uh the the 01:44:22.620 --> 01:44:28.300 paper that minwa and i and christin and uh about continuous 01:44:28.300 --> 01:44:33.660 norms and uh so mo she said well blah blah blah blah and 01:44:34.060 --> 01:44:40.060 uh i couldn't the um the uh programming that minwa 01:44:40.220 --> 01:44:45.420 had written couldn't be modified very easily to to address most these questions so i 01:44:45.420 --> 01:44:51.150 rewrote an agent based model which fortunately produced the same results that 01:44:51.150 --> 01:44:56.990 Benoit's produced, um, and was way faster, and so I'd forced Benoit to do all 01:44:56.990 --> 01:44:59.870 this work because I thought the other way it'd be faster. 01:45:00.110 --> 01:45:05.870 Anyway, uh and so then I I thought, well, I should ask 01:45:05.870 --> 01:45:11.820 Chat GPT to look at this code, and and and and it had 01:45:11.820 --> 01:45:13.740 all kinds of stupid suggestions. 01:45:13.980 --> 01:45:19.980 Uh uh, so I I this was now t how long ago was it that we were arguing 01:45:19.980 --> 01:45:20.540 with Moshi? 01:45:20.780 --> 01:45:22.060 Two or three years ago, something like that. 01:45:22.380 --> 01:45:23.020 Two years ago. 01:45:23.180 --> 01:45:23.740 Yeah. 01:45:23.980 --> 01:45:26.140 Uh and it may be that it's a lot better. 01:45:26.220 --> 01:45:31.340 I mean, they're making and I know that from my daughter that that it is getting better. 01:45:31.420 --> 01:45:32.860 So maybe it would work now. 01:45:33.020 --> 01:45:38.730 But then it just had uh I thought it it it 01:45:38.970 --> 01:45:44.890 it made a bunch of suggestions that would have made the code five percent faster and 01:45:46.410 --> 01:45:49.130 a thousand percent harder to understand what it did. 01:45:49.850 --> 01:45:55.130 And uh um so anyway, that's my anecdote about 01:45:55.130 --> 01:45:56.410 ChatGPT. 01:45:57.050 --> 01:45:58.810 It has no conceptual understanding. 01:45:58.890 --> 01:46:04.060 Yeah, just do you think that's Yeah, it doesn't it at least then it didn't care about how 01:46:04.060 --> 01:46:05.100 expressive the code was. 01:46:05.420 --> 01:46:05.660 Right. 01:46:05.740 --> 01:46:05.980 Yeah. 01:46:06.540 --> 01:46:12.380 Do do you think we ought to be using more just basic analytic models, basic 01:46:12.380 --> 01:46:15.740 algebra relative to agent based simulations? 01:46:16.380 --> 01:46:18.380 Is that part of the the argument you're making? 01:46:18.460 --> 01:46:21.420 That that that way of thinking is kind of underplayed? 01:46:22.060 --> 01:46:27.970 It's harder and um uh I think, yeah, I do think it's not 01:46:27.970 --> 01:46:29.090 enough of it being done. 01:46:29.250 --> 01:46:35.170 And I think part of the problem is, I mean, this is another cultural evolutionary thing. 01:46:37.250 --> 01:46:42.290 The people who do it, analytical work, are mainly 01:46:42.930 --> 01:46:47.570 physicists and mathematicians that are looking for another job. 01:46:47.890 --> 01:46:53.540 And they place a big store on the you know my 01:46:53.540 --> 01:46:56.980 equations are longer than your equations kind of competition. 01:46:57.220 --> 01:47:01.860 And uh and so this is really clear in reciprocity theory. 01:47:02.020 --> 01:47:07.620 So um Rus I I just Sarah and I have just written a review of 01:47:07.620 --> 01:47:12.100 reciprocity theory for um for um ticks. 01:47:12.660 --> 01:47:18.310 And um I would say since 2005, maybe 01:47:18.470 --> 01:47:24.470 somewhere in there, 95% of modeling and reciprocity 01:47:25.030 --> 01:47:28.790 is responding to previous models of reciprocity. 01:47:29.190 --> 01:47:34.550 And almost none of it is in 01:47:34.550 --> 01:47:39.720 response to questions about observed behavior. 01:47:39.960 --> 01:47:45.720 And that's because I work with a mathematician, Bertha Schoenmann, who was a 01:47:45.720 --> 01:47:50.360 wonderful person and a good colleague, but too sensitive to work in the evolutionary 01:47:50.360 --> 01:47:51.080 biology world. 01:47:51.160 --> 01:47:53.080 He quit because we were so mean. 01:47:53.800 --> 01:47:55.320 Reviewers were so mean. 01:47:55.560 --> 01:48:01.550 Anyway, uh, he said mathematicians, to be a successful mathematician, you have to find 01:48:01.550 --> 01:48:07.390 a problem that is not too easy, so anybody 01:48:07.390 --> 01:48:10.670 could do it, and not so hard, so you can't do it. 01:48:10.910 --> 01:48:14.670 But this sweet spot in between is something you can make progress on. 01:48:14.830 --> 01:48:18.990 There's a lot of interesting developments, and that's what reciprocity theory is. 01:48:19.150 --> 01:48:24.780 It's a really nice problem, a lot of possibilities, and I think mainly a waste of time. 01:48:25.180 --> 01:48:31.100 Uh um uh and this is uh oh what few friends I have left in that field 01:48:31.180 --> 01:48:33.580 I'm not gonna have any more after we publish this paper. 01:48:33.740 --> 01:48:39.580 But um that's why John Minor Smith is my my intellectual hero. 01:48:40.060 --> 01:48:42.700 Um he never did anything complicated. 01:48:43.020 --> 01:48:43.260 Yeah. 01:48:43.580 --> 01:48:47.100 Look at the f the classic, you know, Hamilton's rule, the classic Trevor's paper. 01:48:47.180 --> 01:48:49.980 This is all this is just basically has no math in it. 01:48:50.060 --> 01:48:52.150 But but there's a little bit of a little bit of it. 01:48:52.230 --> 01:48:57.990 But yeah, I I well he he says Bill Hamilton told me that that you could represent this as 01:48:57.990 --> 01:48:59.270 a prisoner's dilemma. 01:48:59.510 --> 01:49:00.790 Here's what Hamilton said. 01:49:01.030 --> 01:49:07.030 I just you know I've read that paper recently so I'm it's easy for me to be an expert here. 01:49:07.110 --> 01:49:13.000 But but um uh uh and that paper is full of bad 01:49:13.000 --> 01:49:15.080 confusions, the Tververs paper. 01:49:15.240 --> 01:49:21.240 But uh you know, he he well, I won't go into that, but but you know we should have a 01:49:21.240 --> 01:49:22.360 two hour episode about Trivers. 01:49:22.840 --> 01:49:27.400 He's one of our you know powerful ancestors, but he's not a clear thinker. 01:49:27.560 --> 01:49:33.400 He he's uh he's uh extremely brilliant, intuitive thinker, but you 01:49:33.800 --> 01:49:35.240 you gotta check, right? 01:49:35.400 --> 01:49:41.210 I mean um you know the key is to find simple 01:49:41.210 --> 01:49:46.410 enough representations of some problem that you can make analytical progress. 01:49:46.570 --> 01:49:49.050 And there are some problems you just can't do that way. 01:49:49.210 --> 01:49:54.810 I mean, you know, uh anything involving random drift-like features. 01:49:54.970 --> 01:49:59.210 I mean, there is analytical stuff, but it's hopelessly complicated and it can't do 01:49:59.210 --> 01:49:59.690 anything. 01:49:59.850 --> 01:50:03.370 Well, there's lots of interesting stuff it can't do very easily. 01:50:03.530 --> 01:50:09.240 Uh Anything, any model in which selection varies in 01:50:09.240 --> 01:50:12.280 time or space, and it isn't white. 01:50:12.440 --> 01:50:18.280 So if there's any correlations in time and space, there's no analytical method to deal with 01:50:18.280 --> 01:50:18.440 that. 01:50:18.520 --> 01:50:22.760 That's completely opaque to analytical approaches. 01:50:22.840 --> 01:50:24.280 And it's quite easy to deal with. 01:50:24.360 --> 01:50:26.440 John Gillespie did a lot of work on that. 01:50:27.000 --> 01:50:29.400 And so, and that's obviously a question of importance. 01:50:29.480 --> 01:50:31.240 So we ought to do a lot of simulations. 01:50:33.090 --> 01:50:35.810 but if we can do the analytical stuff, it's very powerful. 01:50:35.890 --> 01:50:39.730 It gives you intuitions that are hard to get out of the simulations. 01:50:39.890 --> 01:50:45.650 You can get them, but it's harder because the equations talk to you. 01:50:45.730 --> 01:50:50.290 You know, they when you look at the equations, they tell you things without actually having 01:50:50.290 --> 01:50:51.410 to solve them. 01:50:51.810 --> 01:50:57.540 And um And as yet, I think we'll fix this, but as 01:50:57.540 --> 01:51:03.380 yet, our simulation tools don't do this. 01:51:03.540 --> 01:51:09.380 Um I've been working with a couple of Spaniards uh uh uh economists 01:51:09.620 --> 01:51:15.620 who do simulations of repeated prisoners' dilemma of all things, but I just 01:51:15.620 --> 01:51:17.060 got done criticizing. 01:51:17.300 --> 01:51:22.950 And um they use this thing that's often thought of as kind of a 01:51:22.950 --> 01:51:25.910 child's play programming language, net logo. 01:51:26.550 --> 01:51:32.310 And um I'm really impressed to the extent to which they're able to get 01:51:32.950 --> 01:51:38.470 intuitions out of the way how easy it is. 01:51:38.920 --> 01:51:44.280 It's very slow and a kind of stupid language and as a computer science kind of project. 01:51:44.520 --> 01:51:49.080 But in terms of teaching stuff, I'm very impressed. 01:51:49.160 --> 01:51:50.280 I'm gonna try to learn it. 01:51:50.360 --> 01:51:53.560 And anyway, so I think this is technological, a lot of it. 01:51:53.640 --> 01:51:56.840 We just haven't we haven't been doing it long enough to to be good at it. 01:51:57.000 --> 01:52:02.970 And um the the Asian-based simulation says, But 01:52:02.970 --> 01:52:08.810 the idea is that uh the anal the analysis so far or the formulas are 01:52:09.050 --> 01:52:15.050 you're forced to know what your the concepts and the relationships in a way that you could 01:52:15.050 --> 01:52:18.810 sort of be agnostic um about in a simulation. 01:52:18.890 --> 01:52:23.130 Like you might run a simulation where like, well, yeah, I don't know what that I don't know 01:52:23.130 --> 01:52:25.080 why, I don't know what the relationship is. 01:52:25.240 --> 01:52:26.680 I just know I got an outcome. 01:52:26.920 --> 01:52:30.360 And I don't really know what all the things that I fit into what mattered or didn't. 01:52:30.440 --> 01:52:36.440 It's just in in compared to the analysis or the formula where or the analytic math, you 01:52:36.440 --> 01:52:42.360 have to know what the entity is and what the relationships are, 01:52:42.440 --> 01:52:44.200 or otherwise you're not able to do that. 01:52:44.360 --> 01:52:45.560 Oh, I I I disagree with that. 01:52:45.720 --> 01:52:46.040 Okay, yeah. 01:52:50.650 --> 01:52:52.410 Asian-based simulation. 01:52:52.810 --> 01:52:56.490 So, in an analytical model, typically you've got a bunch of state variables, you know, 01:52:56.570 --> 01:52:58.970 frequencies of genes or whatever it is. 01:52:59.210 --> 01:53:05.210 And you write down a dynamical system in which you posit relationships based on some in my 01:53:05.210 --> 01:53:08.250 way of thinking, and Christina was forced to go through all this. 01:53:08.410 --> 01:53:13.370 In my class, you write down a life cycle and you ask what happens to individuals, and you 01:53:13.530 --> 01:53:19.100 and then you use the law of large numbers to then ask to create 01:53:19.100 --> 01:53:21.420 relationships for the state variables. 01:53:21.740 --> 01:53:27.580 Um I think agent-based simulations are exactly the same in the sense you have to 01:53:27.580 --> 01:53:31.740 write down a life cycle, you have to write down state variables, but now the state 01:53:31.740 --> 01:53:36.780 variables aren't these aggregate ones, they're ones at the individual level, you know, what 01:53:36.780 --> 01:53:39.020 it knows, how big it is, whatever it is. 01:53:39.340 --> 01:53:44.870 And so your space of possibilities is much bigger. 01:53:45.510 --> 01:53:51.510 But I think in at least the way I think about things, 01:53:51.750 --> 01:53:56.950 uh there's a quantitative difference between them, but 01:53:56.950 --> 01:53:59.430 conceptually they're exactly the same. 01:54:00.150 --> 01:54:06.080 There's nothing uh you have to specify ahead of time 01:54:06.640 --> 01:54:08.800 what the possibilities are. 01:54:09.280 --> 01:54:10.560 Uh you can't have unknown. 01:54:10.800 --> 01:54:16.080 And I there was a physicist at S of I when I was there who went on and on about what was 01:54:16.080 --> 01:54:21.120 wrong with evolutionary theory, is that it specified the possibilities in advance, and 01:54:21.120 --> 01:54:23.360 evolution really didn't do that. 01:54:23.520 --> 01:54:28.450 It could go, and I think this is really an argument about how big the space is. 01:54:28.610 --> 01:54:32.290 And if the space gets big enough, then um 01:54:34.850 --> 01:54:39.810 yeah, that lends itself to I think I have seen agent-based models that don't give a good 01:54:39.810 --> 01:54:44.930 intuition at the end, even in the article of or have I I have seen articles where they 01:54:44.930 --> 01:54:47.890 don't give a good intuition of why it resulted the work that they did. 01:54:48.050 --> 01:54:53.250 And I do think that's rare in analytical models because I mean I think it could still 01:54:53.250 --> 01:54:53.490 happen. 01:54:53.890 --> 01:54:56.770 It happens, but it's much I agree, it's much rarer. 01:54:56.900 --> 01:55:02.660 It it it um there's like a they because part of the process of publishing the analytical 01:55:02.660 --> 01:55:08.100 model is like walking you through why the next thing right and and and also the analytical 01:55:08.100 --> 01:55:14.100 model because the intern internal works of the um of 01:55:14.100 --> 01:55:19.860 the simulation model aren't visible to you in the same way, uh it's much harder to 01:55:19.860 --> 01:55:21.780 figure out what's happening. 01:55:22.100 --> 01:55:27.730 And um and I think we need to do I mean 01:55:29.010 --> 01:55:34.770 we we need to do a lot more exp of experimentation with with agent 01:55:34.850 --> 01:55:40.050 based models you know go in and do experiments look at intermediate values uh 01:55:41.490 --> 01:55:47.410 and I you know my bet is that over time referees and 01:55:47.410 --> 01:55:50.850 the scientific process will force people to do that. 01:55:51.010 --> 01:55:54.720 Uh Now I teach a version of that class, Rob T. 01:55:54.960 --> 01:55:55.360 Oh, do you? 01:55:56.960 --> 01:55:59.440 But I think that most of them don't want to be modelers. 01:55:59.520 --> 01:56:05.520 And so mo a lot of the time is spent just like so their final project is reading a model 01:56:05.680 --> 01:56:10.480 and making sure that they can understand why the results are the way that they are. 01:56:10.960 --> 01:56:13.600 It could be a simulation, it could be a mathematical one. 01:56:13.760 --> 01:56:18.030 Um, because that's what I think a lot of us well, a lot of the evolutionary social 01:56:18.030 --> 01:56:21.070 scientists who are not going to be modelers themselves still need that practice to be able 01:56:21.070 --> 01:56:25.550 to read that literature and understand why the results turn out that way, as opposed to 01:56:25.550 --> 01:56:27.950 take it for granted that there's going to be this relationship. 01:56:28.270 --> 01:56:34.030 I think that's actually led to a lot of confusion or taking at face value um kind of 01:56:34.030 --> 01:56:34.590 conclusions. 01:56:34.750 --> 01:56:35.150 Yeah. 01:56:35.470 --> 01:56:39.790 Without thinking about the conditions under which or the assumptions that allow those 01:56:39.790 --> 01:56:40.990 patterns to arise. 01:56:41.310 --> 01:56:41.470 Yeah. 01:56:41.710 --> 01:56:46.380 I think the I mean this is a problem with not just evolutionary social science but 01:56:46.380 --> 01:56:52.380 evolutionary biology more generally is that it's not a norm 01:56:53.020 --> 01:56:58.780 that practitioners understand the mathematical 01:56:58.780 --> 01:56:59.420 theory. 01:56:59.820 --> 01:57:05.820 Um and um it's not a norm that mathematical theorists are 01:57:05.820 --> 01:57:09.420 well versed in the empirical facts. 01:57:09.820 --> 01:57:15.170 And I mean, so if you interact with physicists or to a lesser extent with 01:57:15.170 --> 01:57:16.290 economists. 01:57:18.050 --> 01:57:22.610 Every empiricist knows the theory, at least at some level. 01:57:22.690 --> 01:57:27.010 I mean, really knows it in a in a substantial way. 01:57:27.570 --> 01:57:33.570 And um in economics, now economics has become very empirical. 01:57:33.730 --> 01:57:36.370 I mean, much more than it used to be. 01:57:37.330 --> 01:57:41.160 And you know, and it's deeply rooted in game theory. 01:57:41.320 --> 01:57:47.320 Now, my my own personal opinion is most of it is kind of crazy that it it's not 01:57:47.640 --> 01:57:53.000 very well coupled to anything about real humans, the game theory that, but anyway, be that 01:57:53.000 --> 01:57:58.890 as it may, when you talk to economists and you they're talking about econom uh I 01:57:58.890 --> 01:58:04.010 go three times a year to this group of listen, I'm part of this network, which has got, you 01:58:04.010 --> 01:58:09.770 know, Samoglu and Robinson and Myerson and all these Nobel Prize winning economists and 01:58:09.770 --> 01:58:15.370 various students and stuff, and they really understand exactly what 01:58:15.690 --> 01:58:21.080 how the models work, what they say, and they're not doing modeling themselves at all, the 01:58:21.080 --> 01:58:22.440 people that I'm listening to. 01:58:22.520 --> 01:58:26.920 They're doing, you know, mainly these big regression kinds of studies. 01:58:27.160 --> 01:58:30.520 And um, so that's their version of empiricism. 01:58:30.760 --> 01:58:36.760 Um, and it is, and then if you listen to biologists, let's forget about 01:58:36.760 --> 01:58:41.880 evolution or self-c, but they kind of pick and choose theory the way they want. 01:58:42.040 --> 01:58:44.200 They don't really understand the models that well. 01:58:44.490 --> 01:58:50.170 you know there this obviously varies from person to person but um um 01:58:51.130 --> 01:58:56.970 I think you know it's because when you teach this course you 01:58:56.970 --> 01:59:01.930 don't you can be a nobody's requiring this course whereas if if you're in physics or con 01:59:02.170 --> 01:59:07.210 economics you take a year in graduate school where they teach you all the same stuff you 01:59:07.210 --> 01:59:13.180 learned in undergraduate school all over again you know, theory of the firm, game theory, 01:59:13.260 --> 01:59:14.300 all this stuff. 01:59:14.860 --> 01:59:17.340 So they really got it deep. 01:59:17.980 --> 01:59:22.940 And um, you know, I think what a biologist would say, that's all a waste of time. 01:59:23.020 --> 01:59:26.620 We don't have enough theory to make that worthwhile. 01:59:26.780 --> 01:59:31.660 And I think there's some truth to that because the system hasn't developed, so that the 01:59:31.660 --> 01:59:36.300 theory and the empiricism is inextricably linked together. 01:59:36.540 --> 01:59:42.230 And um you know it's better integrated in economics the 01:59:42.470 --> 01:59:43.190 Oh yeah, much better. 01:59:43.430 --> 01:59:48.470 But like so, but is it inherent to the body of theory that they've developed that it's no, 01:59:48.550 --> 01:59:51.030 it comes it's it's just cultural evolutionary. 01:59:51.590 --> 01:59:51.990 Yeah, right. 01:59:52.230 --> 01:59:54.870 It's it has to do with the way the institution evolved. 01:59:55.430 --> 02:00:00.260 Um the it was so theoretical when I took graduate economics in 02:00:00.260 --> 02:00:02.580 1971, there was hardly any. 02:00:02.820 --> 02:00:06.420 I mean, empiricism was kind of like biology, this casual empiricism. 02:00:07.060 --> 02:00:12.660 And um then in the 90s uh and knots, 02:00:13.220 --> 02:00:18.340 uh, economics did this big shift to um 02:00:19.060 --> 02:00:24.820 so now hardly anybody gets a PhD um doing 02:00:24.820 --> 02:00:25.380 theory. 02:00:25.590 --> 02:00:29.910 The way you get a PhD is is, you know, it's like a biologist. 02:00:29.990 --> 02:00:35.830 You find some system that allows you to to test something, but you do that having 02:00:35.990 --> 02:00:41.910 you're absolutely deeply knowledgeable about game theory, but not game theory the way 02:00:41.910 --> 02:00:46.550 we do it, game theory the way economists do it, which I think is, well, you don't care what 02:00:46.550 --> 02:00:52.220 I think about it, but it it's kind of yeah it's you know 02:00:52.540 --> 02:00:53.420 wacky basic. 02:00:53.660 --> 02:00:55.660 I shouldn't say that on a podcast. 02:00:55.980 --> 02:00:56.940 It's a technical term. 02:00:57.020 --> 02:00:57.660 Yeah. 02:00:58.540 --> 02:01:03.260 You know, I mean their equilibrium concepts are not evolutionary. 02:01:03.340 --> 02:01:08.540 They're about you think that I think that you think that I think uh and um 02:01:09.490 --> 02:01:12.690 uh and they're deeply committed to those. 02:01:12.850 --> 02:01:18.610 And if you uh you know, I go to these meetings and I voice mild skepticism in people 02:01:19.010 --> 02:01:22.370 and they're very very ethnocentric about economics. 02:01:22.450 --> 02:01:26.850 They don't think the rest of the social sciences is worth listening to, except history, 02:01:26.930 --> 02:01:28.370 maybe hardly at all. 02:01:28.610 --> 02:01:33.980 And um, but you know I I figure I'm doing missionary work on yeah and uh 02:01:34.380 --> 02:01:35.900 fighting the good fight, yeah. 02:01:36.940 --> 02:01:40.380 You know, missionaries end up in the stewpot sometimes. 02:01:42.540 --> 02:01:47.100 Uh yeah, but I think I think the connection, I mean theory, I think theory to sort because 02:01:47.100 --> 02:01:52.220 we're wrapping up here, theory and empirics, I think, is a theme of sort of Rob, your 02:01:52.220 --> 02:01:57.470 contribution, and I think all the evolutionary sciences is that we've sort of, you know, 02:01:57.710 --> 02:02:00.670 for a while there was a lot of theory, not a lot of empirical work. 02:02:00.830 --> 02:02:04.750 Maybe we've swung to there's lots of empirical work, but not enough theory. 02:02:04.990 --> 02:02:10.830 But I think, I don't know, I mean, I think uh um I'm I'm at least heartened that 02:02:10.830 --> 02:02:16.830 we're we compared to a lot of human psychology, for example, and and uh I'm 02:02:16.990 --> 02:02:18.990 I'm speaking as a psychologist, yeah, yeah. 02:02:19.230 --> 02:02:24.580 Um, you know, there's a lot more theory we have at our disposal as a fish and and a lot of 02:02:24.580 --> 02:02:25.620 psychologists per se. 02:02:25.860 --> 02:02:31.620 Yeah, I think I mean Joe and Michael have written this paper about that and yeah and uh 02:02:31.780 --> 02:02:37.540 when I interact with the social psychologists here, Doug Kenrick and and uh 02:02:37.780 --> 02:02:40.020 um oh gosh. 02:02:40.180 --> 02:02:43.220 Anyway, um and Steve Newberg. 02:02:43.300 --> 02:02:46.660 Uh yeah, really smart, accomplished people. 02:02:46.820 --> 02:02:46.980 Yeah. 02:02:47.140 --> 02:02:49.930 But they they would do better if they had more theory. 02:02:50.010 --> 02:02:50.650 Yeah, I think. 02:02:51.050 --> 02:02:51.290 Yeah. 02:02:51.370 --> 02:02:51.530 Yeah. 02:02:51.770 --> 02:02:52.410 Different histories. 02:02:52.490 --> 02:02:52.650 Yeah. 02:02:52.730 --> 02:02:55.530 Different so as you said, different, different different institutions. 02:02:55.850 --> 02:02:58.170 Different institutional selection, different histories. 02:02:58.410 --> 02:02:58.890 Absolutely. 02:02:58.970 --> 02:02:59.450 Yeah. 02:02:59.690 --> 02:03:03.690 Um uh Christina, do you have any uh final questions? 02:03:03.930 --> 02:03:07.690 Uh oh, that's a really tough spot to put. 02:03:08.170 --> 02:03:08.730 Yeah. 02:03:09.050 --> 02:03:11.850 I mean we can always ask Rob if we should have asked him anything. 02:03:11.930 --> 02:03:12.970 That also is a tough before. 02:03:13.930 --> 02:03:19.620 I wanted to ask if there's anything that you've changed your mind about like over the last 02:03:19.620 --> 02:03:20.900 several decades. 02:03:21.620 --> 02:03:24.340 Um maybe based on the empirics or maybe better theories. 02:03:24.660 --> 02:03:29.460 Yeah, uh I used to be more gung-ho about cultural group selection than I am now. 02:03:29.700 --> 02:03:35.220 Um I'm more aware of the empirical um 02:03:36.230 --> 02:03:41.030 I mean a lot of the criticism of cultural group selection has kind of been in principle 02:03:41.190 --> 02:03:44.710 group selection can't work and that's wrong, right, for sure. 02:03:45.030 --> 02:03:50.950 But the problem is there are well, first of all, I worry a 02:03:50.950 --> 02:03:51.110 lot. 02:03:51.270 --> 02:03:57.190 I have been worried ever since 1985 about how fast it is and can 02:03:57.190 --> 02:03:58.550 it explain enough? 02:03:58.710 --> 02:04:02.630 Uh you know, it's a lot of norms we've got evolved, and is there enough cultural group 02:04:02.630 --> 02:04:03.030 selection? 02:04:03.190 --> 02:04:06.640 And um, And I worry about that actually. 02:04:06.880 --> 02:04:12.080 And I have come to think that within group processes 02:04:13.200 --> 02:04:18.960 have got to be more important, both based on that and based on lots of empirical 02:04:18.960 --> 02:04:22.960 examples, which just there's no there's no group selection involved, and yet there's lots 02:04:22.960 --> 02:04:23.920 of change. 02:04:27.330 --> 02:04:31.650 I am bothered by the fact that I can't think of a good theory. 02:04:31.890 --> 02:04:37.650 I I think the bargaining theories don't make sense because, or at least they can't 02:04:37.650 --> 02:04:43.490 explain the variation we see, because um the scale on which 02:04:44.370 --> 02:04:50.130 I mean small scale people can bargain on the scale of a few thousand people, maybe, 02:04:50.340 --> 02:04:56.100 and we see norms on the scale of continents and and so there has to be something else that 02:04:56.100 --> 02:04:58.980 causes successful norms to spread from one group to another. 02:04:59.140 --> 02:05:01.220 It can't all be within group bargaining. 02:05:01.300 --> 02:05:03.220 And I've got some ideas about that. 02:05:03.300 --> 02:05:06.020 But and Sarah has got some ideas about that. 02:05:06.180 --> 02:05:10.820 And I'm less convinced about conformism than I used to be 02:05:13.210 --> 02:05:14.970 as a learning strategy. 02:05:15.210 --> 02:05:19.850 Um is that because there are better ones out like basically we're gonna be able to do that. 02:05:20.010 --> 02:05:25.930 No, just because uh because the the the the data are ambiguous is what I 02:05:25.930 --> 02:05:27.210 would say mixed. 02:05:27.450 --> 02:05:33.210 Um uh the data for other animals surprisingly stronger are much stronger 02:05:33.290 --> 02:05:38.170 yeah so these wonderful experiments that Lucy Applin has done uh on 02:05:38.730 --> 02:05:43.360 bird learning, or you know, they're they they are conformists for sure. 02:05:43.600 --> 02:05:49.120 Um and interestingly, so the the the so a kind of 02:05:49.120 --> 02:05:54.320 psychology you might think, well, the number of instances is what people would respond to. 02:05:54.480 --> 02:05:58.800 But the theory tells you it's the number of individuals, not the number of instances, 02:05:58.960 --> 02:06:04.230 because that's well because that's what generates adaptive information and sure enough 02:06:04.310 --> 02:06:09.510 those birds don't care about instances they care about the number of individuals and can I 02:06:09.510 --> 02:06:13.590 can I put a pause and just say something that is like common knowledge according to like 02:06:13.590 --> 02:06:17.910 the rest of the social sciences if you repeat something more people will believe it. 02:06:18.070 --> 02:06:23.350 Yeah and that is that doesn't make sense to me like why but what are the what is the 02:06:23.510 --> 02:06:27.880 radical side but is the empirical side true As far as I'm aware, at least in humans, the 02:06:27.880 --> 02:06:29.640 empirical side hasn't been holding up on that. 02:06:30.200 --> 02:06:31.560 This is what they call it. 02:06:32.120 --> 02:06:32.360 Yeah. 02:06:32.600 --> 02:06:32.920 Yeah. 02:06:33.080 --> 02:06:38.600 And uh I think they need a theory to tell them what 02:06:39.080 --> 02:06:41.880 you know what kinds of repeats are important. 02:06:42.840 --> 02:06:46.600 And repeats across individuals are important. 02:06:47.000 --> 02:06:51.800 Repeats within individuals will matter in an environment which is changing on time scales 02:06:52.040 --> 02:06:53.240 that are fast enough. 02:06:53.480 --> 02:06:57.010 But anyway, um, so what else have I changed my mind about? 02:06:57.170 --> 02:07:02.930 Um and just to be clear, the the um slight increased skepticism about 02:07:02.930 --> 02:07:07.090 cultural group selection is just that it doesn't account for as many norm changes as you 02:07:07.090 --> 02:07:11.570 might have thought that they did because that um change is happening too quickly, culture 02:07:11.730 --> 02:07:12.530 change is happening too quickly. 02:07:13.090 --> 02:07:13.970 Too quickly. 02:07:14.210 --> 02:07:19.560 And you know, so the shift in norms about tobacco smoking in the US. 02:07:19.800 --> 02:07:19.960 Right. 02:07:20.120 --> 02:07:21.080 No group selection there. 02:07:21.160 --> 02:07:22.280 There, you know, it's, you know. 02:07:22.680 --> 02:07:25.320 They're running migrants to like the no smoking zone. 02:07:25.640 --> 02:07:25.800 Right. 02:07:25.880 --> 02:07:26.120 Right. 02:07:26.280 --> 02:07:28.760 It's it's it's it it's not that. 02:07:29.160 --> 02:07:35.160 Um and um uh now, well, I don't want to go in 02:07:35.160 --> 02:07:40.040 all the details, but this is an area which I thought when I first started, I thought I had 02:07:40.040 --> 02:07:41.000 the answer. 02:07:41.320 --> 02:07:43.640 Now I think it's part of the answer. 02:07:43.800 --> 02:07:45.400 Uh how big a part? 02:07:45.670 --> 02:07:46.390 I don't know. 02:07:46.630 --> 02:07:50.950 Um uh uh Joe gets really mad when I say that. 02:07:51.190 --> 02:07:55.430 But um uh at least I think he does. 02:07:55.590 --> 02:07:57.270 Um I mean it could be faster. 02:07:58.150 --> 02:07:59.030 You don't want to hear all this. 02:07:59.350 --> 02:08:02.710 It might have mattered more historically than it does now, like when there was so much lots 02:08:02.710 --> 02:08:04.230 of sort of variation. 02:08:04.470 --> 02:08:04.710 Yeah. 02:08:04.870 --> 02:08:08.310 Well, I think the main form is gonna be differential spread. 02:08:08.550 --> 02:08:08.790 Yeah. 02:08:09.040 --> 02:08:14.880 So I groups imitating successful other groups, individuals in imitating people and 02:08:15.040 --> 02:08:16.400 successful neighbors. 02:08:17.040 --> 02:08:19.600 But I still don't think that explains a lot of stuff. 02:08:19.760 --> 02:08:24.320 And um I don't know. 02:08:24.400 --> 02:08:26.160 I can't think of anything else off the top of my head. 02:08:26.240 --> 02:08:27.840 I've been right about so many things. 02:08:31.120 --> 02:08:34.160 You can't show that you're a good scientist if you're just right all the way. 02:08:34.560 --> 02:08:36.480 I have to I have to think of something. 02:08:37.910 --> 02:08:41.590 But I do think I mean Rob, just to say like as we're closing up too, like I do appreciate 02:08:41.590 --> 02:08:45.670 that, you know, as a student of John Alitas, like you've been very gracious over the years. 02:08:45.830 --> 02:08:51.750 And and I think talking about the evolved psychology explicitly, and I do think that you 02:08:51.750 --> 02:08:57.590 are part of the reason why for people like Christina and David, 02:08:57.830 --> 02:09:03.510 that the the the gap between sort of cultural evolution and evpsych, uh at least in 02:09:03.510 --> 02:09:08.940 principle, and maybe a lot of times in practice is very narrow and and and and nowadays 02:09:09.020 --> 02:09:11.980 this I don't even think most people I don't even I don't know. 02:09:12.140 --> 02:09:17.820 I mean I'm in my experience it's it's more in Christina language sort of people's uh 02:09:17.980 --> 02:09:23.660 um emphasis in terms of their methods, less thus than their sort of deep 02:09:23.660 --> 02:09:28.550 commitments um you know where I think somebody who's an evolutionary psychologist like yeah 02:09:28.630 --> 02:09:31.590 there's cultural evolution and somebody who's cultural evolutionist like oh yeah there's 02:09:31.590 --> 02:09:36.470 evolved psychology I may not use it in my model but you know that yeah yeah I unfortunately 02:09:36.470 --> 02:09:41.110 have another thing that I need to get to yeah so um but yeah it was this was great thank 02:09:41.110 --> 02:09:46.550 you Rob thank you for my pleasure yeah this was a lot of fun yeah thank you 02:09:48.070 --> 02:09:52.220 you never know what to say for the outro Thanks for listening. 02:09:52.460 --> 02:09:53.420 Yeah, this was great. 02:09:53.580 --> 02:09:55.180 Uh everybody have a good week. 02:09:55.260 --> 02:09:57.900 You know, do the usual Patreon um show. 02:09:58.380 --> 02:10:00.940 Patreon, social media, kind review, you know the drill. 02:10:01.100 --> 02:10:01.340 Yep. 02:10:01.420 --> 02:10:02.780 We should get t shirts, David. 02:10:03.100 --> 02:10:04.380 T shirts, fanny packs. 02:10:04.860 --> 02:10:06.220 Can I say our logo? 02:10:06.380 --> 02:10:07.580 I don't love our logo. 02:10:07.740 --> 02:10:12.060 In terms of like I I like our logo for the purposes of a podcast, but I don't know if I 02:10:12.060 --> 02:10:14.220 would want the brain on a shirt for me. 02:10:14.300 --> 02:10:15.340 What do you think? 02:10:15.630 --> 02:10:16.190 Hmm. 02:10:16.910 --> 02:10:18.350 Yeah, I don't know. 02:10:18.430 --> 02:10:23.390 I don't really have any aesthetic taste or fashion sensibility. 02:10:23.870 --> 02:10:25.710 Here's my vision of a t-shirt. 02:10:25.870 --> 02:10:30.510 A black t-shirt that says nothing except the podcast in parentheses. 02:10:30.910 --> 02:10:33.070 Oh, that like kind of a minimalist direction. 02:10:33.470 --> 02:10:34.670 It's like you gotta be on the end. 02:10:34.910 --> 02:10:36.270 It's sort of like you know, bank. 02:10:36.670 --> 02:10:39.790 Ah, sort of small small dino in covert signal. 02:10:40.030 --> 02:10:40.590 Exactly. 02:10:40.830 --> 02:10:41.470 Oh, okay. 02:10:41.550 --> 02:10:42.110 I like that. 02:10:42.350 --> 02:10:42.670 Yeah. 02:10:42.830 --> 02:10:43.230 All right. 02:10:43.390 --> 02:10:44.830 Well, maybe that's what we'll do. 02:10:45.160 --> 02:10:45.560 All right. 02:10:45.640 --> 02:10:45.960 Yeah. 02:10:46.120 --> 02:10:46.440 Cool. 02:10:46.600 --> 02:10:49.960 Well, we can't do it w unless you um support us. 02:10:50.040 --> 02:10:50.280 Yeah. 02:10:50.440 --> 02:10:53.880 And, you know, maybe give us some some money on Patreon for the t shirts. 02:10:54.120 --> 02:11:00.040 If you if you run a a t shirt concern and have the ability to silk screen 02:11:00.200 --> 02:11:03.560 um, you know, however many of those, let us know. 02:11:03.960 --> 02:11:04.600 Yeah. 02:11:04.910 --> 02:11:05.470 Totally. 02:11:05.710 --> 02:11:05.790 Okay. 02:11:06.110 --> 02:11:06.430 All right. 02:11:06.750 --> 02:11:07.390 See you next week. 02:11:07.950 --> 02:11:08.110 Bye. 02:11:08.190 --> 02:11:09.630 Have a good week, everybody.