David Reich – Bronze Age shock, the Neanderthal puzzle, & the sudden spread of farming

David Reich 0:00 Humans, at least in this part of the world, were wrenched into a way of living that was so different from how the hunter-gatherer ancestors lived that the organism had to adapt very strongly. Maybe the degree of that wrenching process moving into the Bronze Age was qualitatively greater than the degree of the wrenching process that happened from the initial transition to growing plants, which is surprising 'cause our cartoon picture is that the big transition is farming, but the genetic data, the biological readout, is saying our genome is reacting much more strongly to these events that happened five thousand years ago.

Dwarkesh Patel 0:38 I am back with David Reich, who is a professor of ancient DNA at Harvard. How do you describe what it is that you, um, you study?

David Reich 0:47 I'm a geneticist.

Dwarkesh Patel 0:48 All right.

David Reich 0:48 And I work on human history and how people, uh, relate, uh, ancient people relate to each other and people living today.

Dwarkesh Patel 0:56 Great. Um, and so we did an interview, uh, was it two years ago at this point? Which, um, ended up being one of the most popular interviews I've ever done. I think people just found really compelling that there's so much about human history we don't know and are just learning about now as a result of the kinds of techniques that your lab is using. And, um, you have a new preprint, uh, that, um, uh, that's very exciting, and I wanted to talk to you about it. Um, so let's begin. What... Can you, can you t- give me a little bit of context on what we're talking about today?

David Reich 1:24 Well, well, the dream was that when this field started, this ancient DNA field started, uh, more than sixteen or seventeen years ago, that we were gonna learn a lot about biology, learn about how people's biology changed over time by getting DNA out of ancient human remains and tracking changes over time. And that dream has really not been realized, uh, since the beginning of this field. So while the field's been a big success with regard to learning about human history, it's resulted in, um, surprising findings about human migrations, people not being descended from the people who lived in the same place hundreds or thousands or tens of thousands of years before, and mixture being common in human history, sex bias processes being common in human history, and things that were not expected from archeology. And so the field's been a big success from that perspective. But what's not been successful is learning about, uh, biology and biological change. And one big reason for that has been that the sample sizes have been too small. So when you have a single person's DNA, it provides a, a tremendous amount of information about history, and that's because when you look at one person's DNA, it's not a single person, it's many people. It's your two parents, it's your four grandparents, it's your eight great-grandparents and sixteen great-great-great-grandparents, and so on. And going back in time, thousands, tens of thousands, even hundreds of thousands of ancestors going back in time contributing to people today. So when you look at the DNA of a single person's genome or a Neanderthal genome, you have effectively tens of thousands of ancestors all represented in your data, and you can ex- you can position that individual exquisitely with respect to other people from whom you have data. But when you are interested in how a particular genetic variant that affects something like your skin pigmentation or affects your ability to digest cow's milk into adulthood or affects a behavioral trait, when you wanna see how that changes over a time, a single person gives you only one sample or maybe two samples, the one that is in their mother and the one that's in their father. And so to get a high resolution picture of how the frequency changes over time, you need to have very big sample sizes of truly very large numbers of people, and we just didn't have that until the last few years. So what motivates this study that we're, I think, talking about today and the work that hopefully another number of groups will be doing in the coming years, is the fact that we now finally have those numbers, and we can do something with the data to see how frequency changes over time.

Dwarkesh Patel 3:51 And c- can, can I ask a question? Um, I'll be asking a lot of naive questions through the next few hours. But why are frequency changes especially interesting?

David Reich 3:59 So what we're interested in is using the experiment of nature that's occurred, uh, in, in our history over the last tens of thousands of years to understand what's, uh, biologically, uh, significant, uh, in our, in our DNA. And if there has been a change in environment that a, a population has experienced, for example, people have shifted to agriculture or begun living close to domesticated animals or moved to a new environment from a cold place to a warm place or a, a low place to a high place, then there's pressure on the population to adapt to these new stresses, these new, these new needs. And the way you're gonna detect that is you're gonna see that the frequency of a genetic variant that, for example, might allow you to live at higher altitude, for example, or that might sort of nudge you to have a different behavioral pattern that might be advantageous in the new situation. That genetic variant might push systematically in some direction in a way that is enough that you can detect it. Now, it's very hard to detect slight shifts in frequency by a few percent or a ten percent unless you have a very, very big sample size. And so what we're looking for are those changes in frequency that are too extreme to be due to chance, and that will tell us that there have been pushes in the, against the biology as a result of the changes in environment that people have experienced.

Dwarkesh Patel 5:18 Interesting. Okay. So what did you guys find?

David Reich 5:20 So seven years ago, uh, Ali Akbari, uh, who is a, uh, at the time, was a postdoctoral scientist in my laboratory, and a few years later became a permanent staff scientist in my laboratory, set out to use the data that we were producing to learn about biological change over time. And I think the reason he was interested in our laboratory rather than other places was that a focus of our laboratory has been generating truly large amounts of data from ancient humans. We've been really trying to industrialize the process, make it very inexpensive, make it high quality, and generate large numbers of samples, uh, with lots of good data for this purpose. So there's been this large amount of data that we've generated, and it made it possible to conceive again of asking the question about whether there's been frequency changes over time. So the mainstream view in human evolution in the last several decades has been that natural selection has been pretty quiescent over the last several hundred thousands of years of human history.And there's several lines of evidence that have been deployed to document this. One is that if you compare diverse populations from different continents around the world, for example, Europeans and East Asians, and you look at mutations that differ in frequency between these groups, all mutations differ a little bit in frequency, sometimes a lot. You can say, what are the most different mutations in terms of frequency between Europeans and East Asians? And there's almost no genetic changes that are 100% different s- in frequency between Europeans and East Asians. So Europeans and East Asians descend from a common ancestral population 40,000 or 50,000 years ago that came out of Africa and the Middle East. This population had a set of gene frequencies, genetic frequencies, and these variants bopped around, uh, randomly, a process known as genetic drift, or perhaps under selection in one direction or another. And the time that's passed since 40,000 or 50,000 years ago is sufficiently small on an evolutionary timescale that there's just not much genetic differentiation on average between these two groups, Europeans and East Asians. But however, if there's been natural selection, for example, to help people in one place digest, digest alcohol better or, for example, digest milk better or do something else better, what you might expect is that there would be some mutation that would've rocketed up to very high frequency. And 40,000 or 50,000 years is a lot of time. It's maybe 1,500 or 2,000 generations. And so that might be enough time easily to see 100% different in frequency, and yet you don't see any more compared to what you would expect by chance. So this made it seem that just selection has been quiescent. Maybe a few hundred thousand years ago, the ancestral human population got to some kind of optimum, and after that there hasn't been much genetic change in one way or the other, and there's been small amounts of natural selection, or there's been selection to remove bad mutations that are constantly raining down on the genome, but not what we call directional selection, which is newly arising mutations or mutations being pushed in a systematic direction to r- help the population get to a, um, a different adaptive set point that's, that's, that's more favorable for the conditions that population is living in. So we were able to partition how much of the changes in frequencies of, of, of all the mutations that we're seeing in the DNA, we're looking at about 10 m- 10 million positions that vary, is due to directional selection adaptation versus other factors, especially genetic drift. Uh, and 98% of it is other factors, especially genetic drift. So it's overwhelmingly migrations and population structure causing fluctuations in frequency, and as a result, it's super hard to actually detect the signals of natural selection in adaptive natural selection because they're a tiny fraction of the total frequency change. The vast majority of it are these migrations and mixtures. Nevertheless, there's so much natural selection, as our study thinks, has shown, that in fact it's been rampant in the genome.

Dwarkesh Patel 9:15 Can I, can I ask a clarifying question here? So why are we discounting population admixture or replacement as selection? Because if you think about it at a group level, if one population replaces another population, isn't that selection? I f- I, I remember from the last episode you were explaining how there's been huge changes in what kinds of people are in a specific area. One population came in and kind of replaced the previous one, and then a new population came in and replaced the previous one. And to the extent that the genetics are relevant to why that population replaced the other one, um, why, why, why should that not count towards, uh, you know, what we understand to be selection over the last 10,000 years?

David Reich 9:51 It, it could count, uh, and may count, and probably should count in some respects. But it, it could also be that this population replacement is due to some cultural phenomenon, uh, technology held by one of these groups-

Dwarkesh Patel 10:05 Yeah

David Reich 10:05 ... not others, and maybe there's some genetic mutations that are contributing to this. Who knows? It's possible. Uh, but what you're seeing is a whole genome shift. And so what we're looking to see is whether there's one place in the DNA that is driving the change-

Dwarkesh Patel 10:19 Mm

David Reich 10:19 ... in a way that's different from the rest of the genome. And really from a statistical point of view, what happens at these times of migration is there's just huge fluctuations in frequencies, and these are extremely uninformative times for looking and detecting natural selection. The best moments to detect natural selection is when migrations and population admixtures are not happening for a few hundred years. And during these times you can actually see the mutations slowly blowing in one direction as a result.

Dwarkesh Patel 10:46 Yeah.

David Reich 10:47 Really, the way we think about the history of Europe and the Middle East, and the way we think about it for the purpose of this study, is as an archipelago of little populations in space and time, each of which are pretty isolated from each other. So a little population in Britain isolated for a few hundred years, a little population in Hungary isolated for a few hundred years between big events of migration and mixture. And in each of those little experiments of nature, we can ask, does this mutation slightly increase in frequency? Does that same mutation slightly increase in frequency? And if all the arrows point in the same direction, we win.

Dwarkesh Patel 11:19 [laughs]

David Reich 11:19 And they're telling us that natural selection is occurring. So for example, 4,500 years ago in Europe, almost all mutations go through huge frequency changes, and that's not because of natural selection. It's because of the steppe migration from the steppe north of the Black and Caspian Sea. 40%, 50%, 80% of the DNA becomes Yamnaya from steppe pastoralists, and their frequencies of mutations were different, not because of selection necessarily, but just because they had evolved in different places for thousands and tens of thousands of years. And then if you look at the descendant populations, there's huge changes in frequency.

Dwarkesh Patel 11:52 Yeah.

David Reich 11:52 And it's very... What you need to do is see, oh, is natural selection explaining a shift more than you would expect by chance?

Dwarkesh Patel 11:59 Okay, in this next section, David explains the nitty-gritty of the methodology of this paper. It's honestly a bit technical, and I wanted you to get a sense of the results first, so I've moved that section to the end. If you wanna understand the methodology, just stick around for the full episode. Okay, you found these locations that seem to be under selection. Oh, a- a- another clarifying question. So you haveYou say thirty-eight hundred locations which you're fifty percent confident are-- have been under selection in the last ten thousand years.

David Reich 12:29 Seventy-two hundred, which we're, we're, we're fifty percent confident.

Dwarkesh Patel 12:31 Oh, sorry.

David Reich 12:32 So I think we're getting about seventy-two hundred positions in the DNA that have fifty percent confidence of being real.

Dwarkesh Patel 12:38 Yeah.

David Reich 12:39 So only half of those are real.

Dwarkesh Patel 12:41 Uh, I see. Okay.

David Reich 12:42 So thirty-six hund-- which don't know which ones.

Dwarkesh Patel 12:44 Got it, got it, got it, got it, yeah.

David Reich 12:44 So thirty-six hundred of them are real.

Dwarkesh Patel 12:46 Okay. And, um, does that also mean that outside of those seventy-two hundred, you're confident the other locations in the genome are not under selection?

David Reich 12:57 No.

Dwarkesh Patel 12:57 Okay.

David Reich 12:57 So if you look at the twenty-five percent probability cutoff, there will be tens of thousands, uh, and there will be many real ones there too. In fact, multiple analyses we do suggest that the genome is vibrating with natural selection.

Dwarkesh Patel 13:10 Mm.

David Reich 13:10 And, uh, there's all sorts of weaker effects that are there that would be picked up in larger studies even than we've done. Uh, and that, uh, in fact, almost every position in the DNA is, uh, correlated to a position and-

Dwarkesh Patel 13:25 Interesting

David Reich 13:25 ... being dragged in one way or the other, uh, by natural selection. Instead of being quiescent, natural selection is everywhere. Even though it's only two percent of the frequency change, it's tugging the positions in one direction or the other everywhere. So we analyzed these positions that we had identified, these hundreds of positions, the ones we were super confident about.

Dwarkesh Patel 13:45 Yeah.

David Reich 13:45 And we looked to see whether they were randomly distributed in the DNA or whether they had patterns. And what we did is we looked at maybe a hundred or so traits where there had been genome-wide association studies for all sorts of different traits, like ones associated with immunity or autoimmunity or behavior or metabolism and, uh, basically other, o-other things. And for each of these, we could ask, are the genetic variations that are known to affect these traits from genome-wide association studies, do they have an unusual number of genetic selection signals? And what we found is there was a vast enrichment by about a four or five-fold for immune traits. That is, there was a super concentration of selected, uh, signals in immune traits. Whereas also we saw a strong enrichment for metabolic traits, things that might have impact your obesity or fat traits or type two diabetes, and really almost no detectable enrichment as far as we could tell for behavioral traits or for, uh, for, for psychiatric traits.

Dwarkesh Patel 14:47 And, and just to make sure I understand, this is not to say the behavioral traits or psychiatric traits or cognitive traits are not under selection. It's just that the individual sites where such traits are controlled are not especially likely to be among the locations that you've identified as under selection.

David Reich 15:05 Yeah, that's exactly right. So, so it might seem from the, uh, results of that analysis that in fact immune traits are highly selected and that there's been no selection for behavior in the last eighteen thousand years in this part of the world. But in fact, that's a wrong conclusion, and in fact, we have evidence that that's a wrong conclusion. And in fact, there's clear evidence of selection also on behavioral traits. And the, uh, reason we think we see, and we have evidence that this is so, uh, much weaker signals for behavioral traits is that behavioral traits we know from other studies, medical studies, are underpinned by much larger numbers of genes than immune traits, which are underpinned by relatively small numbers of genes of strong effect. Behavioral traiks-- traits are shaped genetically by very large number of genes of weak effect, and we just don't have the statistical power to detect these very weak signals there. So when we do an analysis where we look at our very strong signals of selection, that collection of very strong results is very effectively querying the immune traits, but is not very effectively-

Dwarkesh Patel 16:11 Interesting

David Reich 16:11 ... querying the behavioral traits. It may still be the case, and I guess it is, that immune traits are the most selected category, but it is not at all the case, and in fact, we can prove it's not the case, that behavioral traits are not selected.

Dwarkesh Patel 16:23 Interesting.

David Reich 16:23 So

David Reich 16:24 we think there's two reasons why natural selection has, uh... We've been able to prove really that there's two reasons why, uh, w- how to reconcile the previous observations with our new observations. Remember, the previous observation is that, is that natural selection seems to have been quiescent over a timescale of hundreds of thousands or many tens of thousands of years. Reason? That you don't see a hundred percent different in frequency variance across Europeans and East Asians.

Dwarkesh Patel 16:49 Yeah.

David Reich 16:49 So now we're seeing hundreds of positions that are rocketing up in frequency with s-selection rates one percent or more in a lot of cases. So one percent or more selection rates will mean that there'll be a rapid doubling over periods of dozens of generations, and so over fifteen hundred, two thousand generations like you see separating Europeans and East Asians, shouldn't you see many f- genetic variants that are a hundred percent differently-- different in frequency across populations. So we were able to show that this is explained by at least two factors. So one of them is that we actually, in this part of the world, Europe and the Middle East, are in a period of accelerated natural selection. And one way to see this is to look at this enrichment pattern that we're observing, where immune traits are unusually associated with these selection signals. And we could compare the last five thousand years of our, of our time period, with what's called the Bronze Age and further onward, uh, to the previous five thousand years. And what we see is that this intensification of selection around immune traits, similarly the intensification around metabolic traits, has accelerated over this time period. So it's not like natural selection has been at the same rate over all s- places and times. In fact, it's increasing over the time period we're analyzing, and so plausibly, the whole time period has increased compared to previous periods. So we're in a period of intensified selection. That's not implausible, because this is a t-- a population that went through a huge shock in terms of the way people live and the culture. So this is aPopulation that almost everybody we're analyzing are farmers or food producers in one way or another. Farming was invented for the first time anywhere in the world in the Middle East 11,000 or 12,000 years ago. The people who invented farming, uh, exploded into Europe after 8,500 years ago and spread across Europe and expanded rapidly. In the Bronze Age, there was an intensification of how people lived with much higher pop-population densities, people living more and more next to their animals and getting their diseases and exchanging their diseases with them and with each other. And so this is a period of rapid, rapid change in terms of how people are living, resulting in different biological, uh, needs of this population. So it's not surprising, perhaps, that in the context of these dramatic changes, the biology of the population might be not in the i-ideally adapted, uh, position. That is that there might be what some people call an evolutionary mismatch, where you take a, a genetic, uh, variation that's evolved in hunter-gatherers and put it into farmers or pastoralists, and it's not exactly right. And so what you're seeing is the DNA of this population, which is descended from hunter-gatherers only 10,000 years ago, reacting to the shock of having been moved into an agricultural and Bronze Age and high population density and urban environment. And a hypothesis is that what we're seeing is the adaptation that occurs as a result of that.

Dwarkesh Patel 19:40 Interesting. Okay, so it might be helpful to... You, you, uh, in the paper, you have, you, you have many examples of, um, this intensification of selection around the Bronze Age, and so, um, feel free to navigate it yourself. But it might be helpful to go through some of these-

David Reich 19:54 Sure

Dwarkesh Patel 19:55 ... specific examples.

David Reich 19:56 So we look-- One of the things we do in this work is we look carefully at many, many of these positions in the, in, in the DNA. We've-- actually have an internet browser that you could look at called the Ages Browser that Ali and a colleague of his, who's a co-author of our paper, built, uh, that allows you to query these, each of these ten million positions and see the trajectories at each, at each position and the evidence for selection. And one of the things that we see is that while for the most part, uh, the, the signals of natural selection we detect are consistent with being constant natural selection over time, in a handful of them, we're able to see that there's been a reversal-

Dwarkesh Patel 20:31 Mm

David Reich 20:31 ... or a radical change in natural selection. And very often that occurs in the period between 5,000 to 2,000 years ago, which is the Bronze Age and the, uh, Iron Age, a period of rapid population growth and rapid movement to, uh, intensive use of, of, of, um, of many technologies that were not used that way before. So an example of this is the TIC2, uh, genetic variant that is a major risk factor for severe tuberculosis, which is the major infectious disease, the most important infectious disease killer in the world today. And if you look at the, this major risk factor for tuberculosis, this variant rockets up in frequency from eight or six thousand years ago to maybe nine or ten percent in this part of the world. And then it rockets down in frequency in the last three thousand years. In both cases, there's very clear evidence of natural selection, in the first case to increase in frequency, and then in the next case to decrease in frequency. And a possible reason for this is maybe the spread of tuberculosis, uh, maybe becomes endemic in the population two or three thousand years ago. That's potentially consistent with, uh, pathogen, uh, sequence data and other lines of evidence. And maybe this variant was protecting against something before then, but then tuberculosis became, uh, significant after that point, and it was so bad that it pushed in the op-opposite direction. That's speculative.

Dwarkesh Patel 21:52 Oh, interesting. And, uh, the thing it was protecting against was probably another disease?

David Reich 21:56 Maybe.

Dwarkesh Patel 21:58 Prepping for this episode required a full lit review. I needed to understand why other methods had failed to find evidence of natural selection over the last ten thousand years. What exactly did Reich and Akbari do differently? Honestly, this was quite subtle because the most important points were distributed across a bunch of different papers. And it was frustrating to talk to LLMs about it because they kept getting confused. One of them would fail to understand an important crux, and so I'd switch over to a different model, and that one would get tripped up on the very next point. I ended up using Cursor to kick off a handful of models at the same time and compare their results after. I could have one model critique the response of another. This was super useful because while I'm not a geneticist, I do have enough taste to be able to say, "Hey, this answer makes sense. These ones don't." I also had Cursor turn this work into a flashcard so I could retain what I learned. Cursor started as a programming tool, but I found it really great for this kind of research. There's no other interface where I can get answers from a bunch of independent LLMs all while reading the relevant paper on the same screen. Go to cursor.com/dwarkesh to try it out. One of the big takeaways for me, uh, from the paper was just that something weird happened in the Bronze Age, um, and that, as you said, we're not-- like, across trait after trait, uh, the selection intensifies during the Bronze Age. And this makes sense for some things. For example, why do we see lactase persistence, uh, where adults can process milk? Why is that intensified during this period? Oh, well, it makes sense. This is the time when we don't-- we start using cattle not just for the meat, but then also for milk and wool and other secondary products. Um, so it makes sense this is why l-lactose would matter, lactase persistence would matter more. But then there's other things which seem like they should have been relevant since the dawn of agriculture. I forget the exact name of the allele, but w-was it, uh, FADS1?

David Reich 23:50 Yeah.

Dwarkesh Patel 23:50 Um, which, uh, helps convert plant fatty acids into long-chain fatty acids that your body needs. Uh, and that's obviously relevant when you move from a diet of meat as a hunter-gatherer to a diet of cereals.But why, why, y- that is also one I think you found was under a special selection, or e- especially high selection during the Br- uh, you know, f- 5,000, 3,000 years ago. Um, yeah, so w- w- what's going on? W- why is the Bronze Age so special across all these different traits that you're observing?

David Reich 24:19 Right. So FADS, FADS1:2, this variant is sort of a vegetarian/meateating ad- ad- adaptation.

Dwarkesh Patel 24:27 Yeah.

David Reich 24:27 And already in work prior to this, actually Ian Mathieson, who, uh, w- was a former, uh, colleague, uh, w- worked with me in 2015, identified this as a very strongly selected variant, and it's actually been ancient. You see, uh, copies in archaic humans too.

Dwarkesh Patel 24:42 Mm-hmm.

David Reich 24:42 Um, one of the findings of our paper is the ABO blood system. You know, you get your blood typed as A, B, and O. The B variant has increased up to 10% at the expense of A, but previous work has shown that A and B were both already present in the ancestor of humans and gibbons.

Dwarkesh Patel 24:57 Mm-hmm.

David Reich 24:58 You know, other, other, other apes. Uh, and so these mutations, some of them have been going back and forth and fluctuating over time, uh, in different time periods, but we're talking about changes in the Bronze Age. So this TIC2 variant for, uh, tuberculosis risk, uh, multiple sclerosis risk variant inflected and increased in frequency before the Bronze Age, and then 2,000 or 3,000 years ago reversed at that period, and there's differences in Northern Europe where this process is super strong, very strong positive selection, very strong negative selection. And then in Southern Europe, only a little bit, and not even very strong negative selection. For hemochromatosis, which is iron, pathogenic iron buildup that causes problems, uh, in Europe, that too has reversed around this period. Um, in some of the complex traits that maybe we'll talk about later, these traits too have periods of intensification of natural selection. For example, depigmentation-

Dwarkesh Patel 25:54 Mm

David Reich 25:54 ... which is the, uh, Europeans have depigmented, gotten lighter skin over the last 10,000 years. You can see it in our data. The period of strongest depigmentation is between about 4,000 to 2,000 years ago, and then after that it's much less. And so this seems to be a very impactful, eventful, important period where a lot of the processes that we are s- seeing become very powerful. And it's surprising on first principles. You might think before you walked into this genetic data that the big change is gonna be starting to grow plants-

Dwarkesh Patel 26:24 Yeah

David Reich 26:24 ... and maybe farm animals. That happens in the Neolithic, you know, beginning 10 or 11 or 12,000 years ago. It spreads into Europe after 8,500 years ago. But actually the intensification happens like 5,000 years ago, 4,000 years ago. And so it's really interesting, this, this observation of that being a key point, that being an inflection point, tells us something about when humans, at least in this part of the world, were wrenched into a way of living that was so different from how the hunter-gatherer ancestors lived that the organism had to adapt very strongly. And that may be the degree of that wrenching process moving into the Bronze Age was qualitatively greater than the degree of the wrenching process that happened from the initial transition to growing plants. So which is surprising, 'cause our cartoon picture is that the big transition is farming, but the genetic data, the biological readout, is saying our genome is reacting much more strongly to this, these events that happened 5,000 years ago.

Dwarkesh Patel 27:24 So you did some work with, uh, Batya and many other colleagues in 2014. You were looking at 20,000 or 30,000 African American genomes today, and you were saying, look, there's some percentage, 80% West African DNA and then 20% European DNA, and can we look at their, uh, genomes today, and do we see that their, uh, allele frequencies are much different than what you'd, you'd just expect from this admixture? Um, and you find, uh, correct me if I'm wrong, but you found that they weren't. That is to say that over 200, 300 years of extremely intense environment change, you know, going from, uh, you know, y- yeah, chattel slavery and, uh, c- yeah, completely new environment, uh, there's no effect of natural selection. And so we see episodes like this where we don't see natural selection and then, but then the Bronze Age apparently must have had an even stronger effect, or the change in environment is even stronger than what we see from Africans in Africa then being trans- migrated to the, uh, uh, to the New World and then living under slavery.

David Reich 28:30 That, that may be the case. It also may be the case that that period is just too s- short to see much effect.

Dwarkesh Patel 28:35 Mm-hmm.

David Reich 28:36 So what you're looking in for in the Batya et al paper, uh, where we looked at about 30,000 African Americans and looked to see whether there is, instead of the average percentage of maybe around 80% West African ancestry, in some places in the DNA more than 80%, in some places in the DNA less than 80%, significantly, as you would expect if there was natural selection from some r- genetic variant for Eur- from Europeans or from Africans. We didn't see any place in the DNA that was significantly different from what you would expect by chance.

Dwarkesh Patel 29:05 Hmm.

David Reich 29:05 And so, uh, one possible explanation for that is just that there's only a handful of generations, maybe five, over which the natural selection would operate. And so maybe if the selection was 2% a generation, you would still only see maybe a 10% compounded effect, and there's just not enough time to detect it. But the Bronze Age is not 300 years. It's 3,000 years. It's the power of compound interest, and you have enough time to begin to see a strong effect. But this really, really, really does seem to be a very impactful time in terms of human history, and you can see it in our complex traits. So for example, if you look at pigmentation, for example, uh, which is the, uh, strongest signal of selection for a complex trait in-Uh, our data set. So you look at genetic mutations that are known to affect pigmentations. You add up their effect across all of the DNA, so there's dozens or hundreds of them. And you look to see in what time are s- the natural selection strongest, and the time period is really, uh, 2,000 to 4,000 years ago. Uh, and for some of these other traits as well, you see again the time period over which the selection is strongest, uh, is 2,000, 4,000 years ago. So for example, if you look at, uh, genetic variants that affect, uh, measures of cognitive performance, for example, uh, such as performance on, uh, intelligence tests, uh, in, uh, people in White British people today. Uh, so this is, of course, a very strange trait to measure in the past because there were no intelligence tests and there was no school. But it is a predictor today, and you could look at how it's changed in the past. And we see very strong natural selection for this combination of genetic variants that predicts people's performance on IQ tests and also is highly correlated to the predictor that predicts the number of years of school or the household wealth of people. All crazy traits in the past because there was no wealth in the past. There was no school in the past. But if you look at the predictors today, there is a strong, uh, there is a strong movement in a systematic direction, a, a large effect about a standard deviation on the scale of modern variation. And then we can do this trick of looking to see whether there's periods of time when this natural selection has occurred more intensely or less intensely. What we do is we drag a 2,000-year window through our data, and we repeat our whole analysis, not on 18,000 years, but just on a short 2,000-year window. And we can measure the strength of selection in each of these 2,000-year windows. And what you see when you look at intelligence is you see that this maxes out in the Bronze Age between 5,000, 4,000, 3,000, 2,000 years ago. And the impact in the last 2,000 years is almost nothing. There's no evidence of natural selection at all. You might think your bias coming into this, my bias perhaps, if there's any signal of natural selection on this trait at all, might be that it would be unusually strong in the last 2,000 years. Maybe this is a time of industrialization. Maybe this is a time of greater need for this particular trait. But in fact, there's no evidence of natural selection at all in the last 2,000 years, but there's very strong evidence in between 2,000 and 4,000 years ago, where instead of a one standard deviation strength of selection, it's a two standard deviation strength, uh, sort of averaged over this time period.

Dwarkesh Patel 32:16 A- a- and the, the standard deviation here is how, how much the polygenic score for the trait itself moves or?

David Reich 32:23 How much the polygenic score trait moves, uh, over a 10,000-year period-

Dwarkesh Patel 32:28 Got it

David Reich 32:29 ... uh, within a population that is held constant in terms of its ancestry.

Dwarkesh Patel 32:34 Got it.

David Reich 32:34 Because what's actually we're doing is we're looking in our data set at a kind of heterogeneous group of people. There's, you know, Southern Europeans and Northern Europeans and hunter-gatherers and farmers, and at different times in the past, those groups are more or less represented.

Dwarkesh Patel 32:48 Yeah.

David Reich 32:48 So the whole strength of the methodology Ali Akbari developed is it corrects for that, uh, changing ancestry over time. And as I mentioned before, really what's being asked here is we've divided up our whole data set into an archipelago of little populations in different places in space and time. And we're asking in each place in space and time a little pocket of people in Britain from 4,000 years ago to 3,500 years ago. A little p- pocket of people in Hungary, a little pocket of people in, in Italy from 2,000 years ago to 1,500 years ago. In each of these places, uh, where the ancestry is relatively similar without being too disrupted in that short period by, uh, migrations, we watch to see if the genetic changes blow in the same direction.

Dwarkesh Patel 33:33 Yeah.

David Reich 33:34 And what we're doing here is we're measuring the strength of selection at each point in time after correcting for the big population changes that have occurred.

Dwarkesh Patel 33:43 Okay, so the, the effect here is huge then. 'Cause, like, if you're, if you're saying one standard deviation, um, a standard deviation above the median would be somebody in the 85th percentile. So you're saying that the effect of selection has been so strong that compared to 10,000 years ago versus now, um, uh, you know, the, the, the median has gone to the 85th percentile. Um, and that- that's just, like, a huge effect over the last 10,000 years on something like intelligence or, um, this, the, the thing that predicts household income or whatever. Um, so these seem like the, the... Especially given that this is only 2% of the change in allele frequencies, and then, like, the 98% is coming from migration. So that, then it's sort of stupendous to think about, like, well, what is the impact of migration then? [laughs]

David Reich 34:28 Yeah.

Dwarkesh Patel 34:29 If this alone can explain, um, or is driving a standard deviation change in these kinds of qualities, at least among the kind of variation we see in the world today.

David Reich 34:37 Well, one, one thing you can see in the data is the migration impact is huge. So for example, if you look at the trajectory for, you know, measures of cognitive performance like, uh, scores on intelligence tests-

Dwarkesh Patel 34:47 Yeah

David Reich 34:47 ... in White British people today, but you look at the predictor of that in people in ancient times, the estimate for the hunter-gatherers of Europe is, like, three standard deviations below the modern mean.

Dwarkesh Patel 34:58 Right.

David Reich 34:59 So that's hugely different.

Dwarkesh Patel 35:00 Yeah.

David Reich 35:00 Uh, and then you see a huge jump from them to the hunter, to the farmers, who are, like, uh, at the mean, at zero, and that's migration.

Dwarkesh Patel 35:09 Yeah.

David Reich 35:09 Uh, so what you're seeing is those two groups had different set points for those traits.

Dwarkesh Patel 35:14 Yeah.

David Reich 35:14 And then the Steppe pastoralists have a lower set value of this.

Dwarkesh Patel 35:17 Mm.

David Reich 35:17 And so you see huge fluctuations in the predictor of this trait over time. That doesn't prove selection. What that is just telling you is migration. But what our test is telling you is, in addition to those fluctuations due to selec- uh, due to migration, is there a consistent effect of natural selection blowing the trait in the same direction over all, over all places and times?

Dwarkesh Patel 35:39 Right.

David Reich 35:39 And that's what we're detecting.

Dwarkesh Patel 35:40 Yeah. So there's this, uh, a person who has this theory of collective intelligence hypothesis, which is this idea that, um, the selection forIntelligence has actually been in the opposite direction, that as society has developed, there's been more specialization. If there's more specialization, each person only needs to understand a smaller and smaller part of the world. And, um, therefore, actually the ancients were much smarter than us, and we've sort of evolved out in intelligence. And your results seem to point in the opposite direction, that although there's not been elect- a selection in the last 2,000 years as so- you know, society's gotten more complicated, at least when society began, there was more need for the kind of thing that predicts intelligence today. And the reason that's surprising is if you think about hunter-gatherers, um, yeah, reading your colleague Joseph Henrich's book, the amount of information that they needed to ha- ha- hold onto and assess everything from, um, how to process food, to how to build shelters, fire, et cetera, compared to my world where I gotta, like, know how to set up mics and ask questions.

David Reich 36:48 [laughs]

Dwarkesh Patel 36:48 It's just like, it seems like the demands on intelligence should've been, like, way higher in the ancestral environment. And so it's very surprising that the beginnings of civilization increase the, um, the selection on intelligence.

David Reich 37:02 Right. So, you know, this is the power of data, right? Like, you know, the... I think Joe, if you asked him, uh, prior to this work, uh, what the hunter-gatherer selection would be and where their set point for, uh, you know, this particular trait would've been, you know, I think he probably wouldn't have made a very strong prediction. But he would've said, "Well, maybe you would've expected it to have a high predicted value of this trait because these people were really having to do a lot of things and figure st- a lot of stuff out maybe. Uh, and that maybe once you have more complex societies, there'd be more of a collective brain, and maybe there'll be selection against this trait." And in st- in fact, it's sort of the opposite in some ways. So it's the power of data. It's not what you expect. And, you know, after looking at this data, it's actually the value of data to try to make sense of all these things. You know, it's very interesting. Like, uh, the genetic predictor of intelligence, there's lots of kind of things that are confusing about it, so it's actually worth talking about it.

Dwarkesh Patel 37:56 Yeah.

David Reich 37:56 Uh, or the genetic predictor of years of schooling, which is highly correlated to it and is measured even better. So if you look at the pre- genetic predictor of years of schooling, there's another amazing study from 2017 from a group in Iceland, uh, that looked at this measure over the last 100 years in Iceland, and it looked at older people, and it looked at younger people, people born more recently in Iceland. And there's a estimated 0.1 standard deviation decrease in genetic predictor of intelligence in Iceland just within one century. Uh, it's an absolutely huge effect-

Dwarkesh Patel 38:27 Yeah

David Reich 38:27 ... over a short period. Uh, and this is selection against years of schooling. If, if I said intelligence, I didn't mean to. It's selection against, uh, the num- uh, genetic predictors of numbers of years of school. And so one possible interpretation of this, uh, sort of hand-wavy, uh, is that actually what's being measured here is not selection for years of schooling or for actually real intelligence but for another trait altogether that's correlated to both of them. So for example, the predictor of numbers of years of schooling is very, very strongly correlated to the age at which women have their first kid. Uh, and if you control for that, for number of c- years of schooling, all of the signal of, uh, years of schooling goes away. So maybe what you're measuring is women's decision about when to have children.

Dwarkesh Patel 39:12 Mm.

David Reich 39:12 And, you know, if you have children earlier, you don't go to school as much. If you have children later, you go to school more. Maybe it's some kind of measurement of delaying gratification or putting things off or planning. The same trait is correlated to body mass index, to obesity, or to, uh, walking pace. So is this really like, uh, intelligence as we think about it, or is it something else that manifests itself differently in different times, uh, in the past?

Dwarkesh Patel 39:39 Yeah. Um, okay, so obviously a trait like years of schooling was not itself a meaningful thing in the past. Um, and the underlying things for it seem to have been under strong selection. So whatever in the genome predicts years of schooling seems to have been under strong selection. Um, and how, how should we think about this? What, like, what is the actual thing that's changing in the genome?

David Reich 40:00 Yeah. Well, I think that there's two things going on that you need to think about. So one of them is that, uh, is that years of schooling is connected to so many other things genetically. So if you look at the genetic predictor of years of schooling, th- this trait has been measured in millions of people now. It's actually correlated to really, really surprising things. It's correlated to the age at which women have their first kid.

Dwarkesh Patel 40:23 Mm.

David Reich 40:23 It's correlated to people's obesity. It's correlated to people's walking pace. It's correlated to people's household wealth. Uh, it's correlated to, uh, a variety of other traits that seem quite different from it. So if you think you're actually measuring years of sc- uh, genetic prediction of, uh, intelligence or years of, or, or actual, you know, studiousness or something like that, you should think again because there's many things that it's correlated to. There seems to be some kind of general trait that maybe you could think of as executive function or maybe propensity to defer gratification or something, or I may just waving my hands, that is under selection, and it pushes all these traits in the same direction, uh, one way or the other. And in different times in the past, it's, it's, it's advantageous or disadvantageous. But when we found this signal of, uh, years of schooling, uh, being increased, the, the g- genetic propensity to go to school for more years, uh, as it manifests itself to, in people, in white British people today, uh, when we found the signal, we were sort of incredulous, like, "How could this be? Maybe this is a problem." So we did a few tests to try to figure out whether this was real, and one of the tests we did is we looked at, for a study where this measurement of the numbers of years of school was done not in Europeans.But was done in Chinese people in China. And we looked at variants that had the effect size of many variants as they affected the number of years of school in China. And we saw whether they had a relationship, a correlation to the trajectory of those same genetic variants in Europeans over the last ten thousand years. So these are two parts of the world where the populations have been essentially completely disconnected, and there's no way by chance that the trajectory in Europeans over the last ten thousand years will have anything to do with the number of years, uh, the effect on the years of schooling in China today. But there's actually a huge statistical correlation of five or six standard deviation correlation between the effect size of variance, a number of years of school in China today, and the trajectory in Europe just as strong actually-

Dwarkesh Patel 42:28 Mm

David Reich 42:28 ... as the effect size of variance in Europeans to years of school-- to, to the trajectory in Europeans. So we just could not see a way this could happen by chance. And once we saw that, we really felt quite convinced that this was a real signal, and that really somehow there has been natural selection to increase the genetic changes that today manifest themselves as more years of school-- at predicting more years of schooling.

Dwarkesh Patel 42:52 Okay, just to make sure I understood, you're saying you're, um, you know, you're, you're looking at this ancient DNA in Europe, and you're saying, well, it seems to predict years of schooling for modern people in Europe, um, or at least a selection on those, uh, ancient DNA... That ancient DNA seems to predict more years of schooling in modern Europe. And then you also find, well, it also predicts how the same, um, variants predict more years of schooling for Chinese people in China.

David Reich 43:22 Yeah.

Dwarkesh Patel 43:23 And so this is not just some weird artifact from the way these GWAS were done in Europe. This seems to have rebu-- These parts of the genome seem to robustly predict the kind of thing that actually leads to more years of schooling, at least in people today.

David Reich 43:37 Correct.

Dwarkesh Patel 43:38 Jane Street is pretty secretive, but I did learn about one internal mechanism which illustrates how high trust and weird their culture is. Researchers aren't given compute allocations. Instead, Jane Streeters use an internal currency called hive bucks to bid for compute in real-time auctions. Everybody can spend as many hive bucks as they want, but your hive buck bid is meant to represent the real dollar value of the experiment that you wanna run. Now, notably during the auction, anybody can change anybody else's bid, and after the auction, people can even kill each other's jobs. People just trust each other to do this in a way that benefits the whole firm. As a result, Jane Street's allocations reflect a near real-time consensus on the highest priority uses of compute. As Axel, one of their ML engineers put it.

Speaker 44:19 I think Jane Street is, like, pretty bottom-up in terms of we have lots of different researchers who are all training their own models, sequence models, uh, all sorts of other weird and wonderful things.

Dwarkesh Patel 44:28 By the way, with their new compute deal, they've just added a six billion dollar hive buck stimulus to their internal economy. Jane Street is hiring researchers, engineers, and interns. Go to janestreet.com/dwarkesh to learn more. Okay, so stepping back, I wanna understand-- I think there's this question about, uh, what, what does this tell us about what actually changed in our environments, um, over the last eighteen thousand years? And I-- We talked a little about what happened after the Bronze Age. I wanna understand. It's surprising to me we're talking about this during the collective intelligence part of the conversation, but it's surprising to me that things like intelligence or lack of schizophrenia or so forth, things just seem kinda robustly good, were not maxed out, um, before the Bronze Age. And in fact, there was so much-- The diversity among different populations was so big that you have, uh, the European hunter-gatherers, um, having three standard deviations less predicted, uh, value for, uh, you know, what they would score on an intelligence test if, a test if it existed. Uh, but, you know, they were existing in the real world in a place where intelligence matters. And so how can it be that, um, the, this was not a tr-- You just look at the human body or any animal and just like, there's-- Evolution has been acting on it so strongly to make it functional, the things it needs to do. And this one thing which seems, like, so relevant, especially to what human hunter-gatherers needed to do, is not under, s-s-- Doesn't seem to have been under that strong selection, uh, in the Mesolithic or Paleolithic or those eras.

David Reich 46:09 I think that that's a great question, and like, as we talked about before, uh, th-th-th-the human adap- selection is very effective. You-- It can move the mean value of traits within hundreds or thousands-

Dwarkesh Patel 46:22 Yeah

David Reich 46:22 ... of years in one direction or the other, if that's adaptive in a particular environment. And so you might wonder, isn't intelligence good-

Dwarkesh Patel 46:30 Yeah. [laughs]

David Reich 46:30 ... you know, in all contexts and places in time? And I think that there's a number of ways to think about that. First of all, I think we are speaking from the point of view of a society which intensely values this particular trait, you know, ability to score well on, uh, IQ tests or things like them, or to go to school for a long time or whatever it is. And I think this is unprecedented in human history that we live in a time like this. Like, if you look at the, you know, Hebrew and Christian Bible and you look at how much intelligence is valued, it's basically not at all.

Dwarkesh Patel 47:00 Well, but that-- When, when the Bible is being written, esp-especially the Old Testament, is exactly when selection for intelligence is the highest point-

David Reich 47:07 Yeah

Dwarkesh Patel 47:07 ... it's apparently ever been.

David Reich 47:08 Yeah, exactly.

Dwarkesh Patel 47:09 [laughs]

David Reich 47:09 But, like, there it's, it's about strength or courage or religiosity or... Right. Those are the values, right? Or if you read Homer, uh, or the other texts of other religions, it's not intelligence. It's, it's beauty. It's, like, other, other things. And so this value system, which has a hyperfocus on, you know, um, you know, smarts, is not obviously a trait, trait value that's been common in the past. You might think that in certain communities, like, you know, some communities or not, there might be valuation of things that are more proximate to, you know, years of schooling. But really broadly, it's not been a high value in the population.

Dwarkesh Patel 47:47 Um, but obviously the, the thing we're referring to is not-Or the thing we care about is not direct performance on an IQ test, especially in the past. The, I think the thing I'm trying to understand better is this, is intelligence more broadly, and maybe just that IQ test intelligence is not that correlated with, here is a new, uh, world environment, and go figure out how to process food there and make shelter and everything else. All the things which, you know, your colleagues like Joseph Henrich talked about, like the, how modern people underestimate the difficulty of, um, doing this kind of thing with a small band of people. Anyways, this is a, like, m- maybe that's not IQ test intelligence, and that's why we don't see that strong a selection effect on this thing. But I just intuitively it seems like regardless of the value system, it just seems very valuable to, uh, ha- have this trait maxed out, um.

David Reich 48:36 So, so I'm being very speculative.

Dwarkesh Patel 48:37 Yeah.

David Reich 48:37 And let me give you two examples about how, about what this is, about i- in my head, how I'm thinking about this, and not that I'm a particularly good authority on these things.

Dwarkesh Patel 48:46 Mm-hmm.

David Reich 48:46 But as I mentioned, a lot of these traits, which are quite disparate, are highly correlated to each other.

Dwarkesh Patel 48:50 Yeah.

David Reich 48:50 Uh, obesity, years of schooling-

Dwarkesh Patel 48:53 Right

David Reich 48:53 ... walking pace, you know, performance on IQ tests, household wealth, all these crazy traits all seem to be governed to a substantial extent by a shared combination of genetic variance. And let's just think about what this might mean. So in Iceland in the last hundred years, there's been selection against this combination of variance. Uh, and one possible interpretation is it's basically selection for two ways of investing in your children, uh, having many kids and not investing a lot in them or having few kids and investing more in them, right? So if you invest in deferring, deferring having kids, but becoming, you know, having more wealth, having more resources, and putting more into each kid, you're gonna have a lower fertility, and you're gonna have fewer kids. And that's gonna result in r- lower fertility, but those kids might survive more and do better in society. Alternatively, you can just have as many kids as you can and invest less in them. They might have individually less good outcomes, but in a time of plenty, which is potentially Iceland in the 20th century, it might make sense to have more kids and invest less in them. And so there's a toggle between having more kids and investing less in them and having more kids and investing in less in one's life, uh, and having fewer kids and investing more in excelling in various ways or something like this. And so you can imagine that actually at different times and in different places, in, in ecology, there's resource, there's different ways, like mammals often invest a lot in, with a pregnancy in a small number of children, whereas fish will spawn huge numbers of offspring into, you know, the, the, the river, the great majority of whom will be eaten. Uh, but that is an effective way to produce offspring in certain conditions. So there'll be a toggle depending on the environmental conditions back and forth between investing in large numbers of offspring with fewer and less investment or smaller numbers of offspring with more investment, and maybe we're just seeing that move back and forth over different places and times. Similarly for schizophrenia and bipolar disease, how could this ever be advantageous? But maybe what we're seeing with these diseases is a kind of readout of some kind of spectrum of traits that actually o- in some contexts might be advantageous. Maybe being anxious or being i- imaginative or being neurotic might be helpful in a shamanistic tradition, you know, in a religious tradition which values people who can have visions, uh, or values people who can be creative. And maybe these are subclinical versions of schizophrenia or bipolar disease that in certain times may be advantageous and in other times may be disadvantageous. Maybe you're just seeing selection from different types of creativity or other thinking that can be valuable in different contexts.

Dwarkesh Patel 51:30 Mm.

David Reich 51:30 I'm waving my hands here, but my sense is that these complex traits have not pushed in one direction because there's advantage, there are spectrums where there's advantages to both ends of the spectrum, and there's multidimensional, uh, uh, uh, you know, impacts of these different traits.

Dwarkesh Patel 51:47 Mm. Uh, Julian Jaynes has this famous theory in The Origins of Consciousness in the Bicameral Mind that, I'm butchering this, but f- fundamentally, the way I understand it is that up until Homer, basically everybody was schizophrenic. [laughs] Um, in the sense that people had, people genuinely thought that gods or whatever were real people that you were communicating with. And h- his claim is that ancient texts seem to show people behaving in this way or, um-

David Reich 52:15 You're being asked to believe in visions.

Dwarkesh Patel 52:16 Yeah, exactly.

David Reich 52:17 You know, and even today, I think, you know, there's valuation in some religious communities and, you know, communicating with God and having visions-

Dwarkesh Patel 52:23 Right

David Reich 52:23 ... and having supernatural communions.

Dwarkesh Patel 52:25 Yeah.

David Reich 52:26 And so, uh, I, I just don't know.

Dwarkesh Patel 52:29 Yeah.

David Reich 52:30 But I think it's super interesting to imagine, to, to, to ask the question why certain traits are not always advantageous. For schizophrenia and bipolar disease, there is a sense in which most of the mutations are disadvantageous.

Dwarkesh Patel 52:40 Right.

David Reich 52:41 We can see that from the patterns of variation where the variants that are risk factors tend to be low frequency-

Dwarkesh Patel 52:46 Yeah

David Reich 52:47 ... and they tend to be small effects.

Dwarkesh Patel 52:48 So another trait you find under selection is, um, the trend away from body fat-

David Reich 52:53 Yes

Dwarkesh Patel 52:53 ... since the agricultural revolution. Wh- why is that?

David Reich 52:56 So this is, uh, what you see is a reduction in the combination of genetic mutations that make you at risk for obesity, body mass index, and similarly, and very correlated to it, higher fat mass, higher waist-to-hip ratio, higher type 2 diabetes risk. And so there is clear selection by about a standard deviation on the scale of modern variation for these traits, reducing about ten thous- over the last ten thousand years, uh, in this part of the world. So what can be going on there? Why was there not selection f- for this combination of traits before? There's a long-standing idea known as the thrifty genes hypothesis.

Dwarkesh Patel 53:31 Mm-hmm.

David Reich 53:31 The idea is that, uh, that once you have hunter-gatherer populations that move into a farming environment where there's plentiful food, there is no longer a need, uh, to the same extent to be able to build up body fat to sort of survive in times of stress because there's more constant stores of food. And so as a result, there will be no, there will be natural selection against body fat, which can be, uh, once you move into an agricultural environment and to periods of food plenty. And so maybe what you're seeing is that thisGroup of people in Europe and the Middle East over the last 10,000 years has moved into a, a period of relatively more stable food where building up stores of fat are not as advantageous, and there's been selection against this combination of traits. Europeans actually are relatively better protected genetically against type 2 diabetes than some other populations around the world, like African Americans and Native Americans that have perhaps not been as exposed to ag- agriculture for as much time. So you may be seeing the effect of more exposure to more stable food accessibility.

Dwarkesh Patel 54:35 Hmm. This is also another way in which the data goes against a common story. And the common story is that hunter-gatherers actually had much more stable diets because they were more varied, and so they weren't reliant on a single cereal or a single crop for their calories. And if, you know, if one game went away, they had other things that they could scout for. They could move locations more easily 'cause they weren't tied down to the land. Um, and so they were more food stable. But in fact, if there's been selection against storage of body fat, that suggests that as, um, as unstable and as common as famines might have been in agricultural societies, it's at least more stable than what the hunter-gatherers had.

David Reich 55:17 I think there's a timescale issue.

Dwarkesh Patel 55:18 Hmm.

David Reich 55:19 Uh, you're absolutely right. So I think, as I understand it, I'm no anthropologist and no, uh, uh... But my understanding is that when there's a hunt in some of these, uh, in, uh, in, in traditional or societies or communities that hunt, people will often gorge themselves and eat-

Dwarkesh Patel 55:34 Mm-hmm

David Reich 55:34 ... a huge amount and build up a sort of temporary store of fat, and then go with multiple days without eating meat sometimes until the next hunt. And so there is this sort of boom-bust, uh, access to high-value nutrition-

Dwarkesh Patel 55:46 Mm

David Reich 55:46 ... uh, that is not true to the same extent in farming communities. Uh, on the flip side of this, uh, these long, these famines are, I think, something that occurs more commonly in agricultural societies, but the timescale and the tempo of them is very different from the hunting tempo. So maybe there's a famine every three years. And indeed, if you look at the bones of farmers, uh, at least in some communities, there's more stress in them, maybe due to a famine every three years or a famine every five years.

Dwarkesh Patel 56:14 Mm-hmm.

David Reich 56:14 But selection might not be a- acting on that three-year time period. Your fat store, uh, it, from, you know, the latest hunt is not gonna carry you through to the famine-

Dwarkesh Patel 56:22 Right

David Reich 56:22 ... three years later. And so survival of famines is a different thing than building up body fat, uh, for, uh, being able to, uh, survive two weeks later.

Dwarkesh Patel 56:33 Hmm. A kind of random question I have is if w- you were mentioning, look, as compared to these other things which matter much more for fitness in the ancestral environment, the immune system, especially after the Bronze Age, um, all these other things have mattered more than intelligence. And so they've been under much more selective pressure than intelligence.

David Reich 56:51 Right.

Dwarkesh Patel 56:51 That makes you wonder whether there's much more room at the top for intelligence. As in, if humans had been selected, especially for intelligence, they could have been much smarter. And the reason that's relevant is we're currently building AI systems which we're trying to make as smart as possible. And in fact, the only goal of the training process is intelligence. We don't have to worry about also at the same time making their immune systems powerful and at the same-

David Reich 57:12 We have lots of energy to spend on it, right? [laughs]

Dwarkesh Patel 57:14 Yeah. And at the same time, making sure they're not schizophrenic. I guess we kind of don't worry about that. Um, but, um, if intelligence has not been the dominant trait under selection for humans over the last 10, 20, 100 thousand years, does that mean that there's more room at the top for this trait?

David Reich 57:29 I think there's more room at the top for a lot of these traits.

Dwarkesh Patel 57:31 Yeah.

David Reich 57:32 Uh, I think that you can move height very extremely in one direction-

Dwarkesh Patel 57:36 Yeah

David Reich 57:36 ... much more than it is today. You can move any of these traits very much more extreme in the other direction. There's probably very strong negatives to doing that. You're probably sacrificing other things. Uh, and I think that there's trade-offs probably. Uh, but, uh, I think it's highly likely that if natural selection was pushed, pushed any of these traits, uh, in, uh, more in one direction than it is, the, the mean would move.

Dwarkesh Patel 58:00 Hmm. So a- all of this, um, evolution since out of Africa is acting on alleles that already exist in the pool of human variance from that first group, which we were talking about last time, on the order of 10,000 people that, um, you know, exploded out of, uh, out of Africa. And it's a, it... Is it surprising that across all these different traits, from cognitive profiles to, uh, resistance to different kinds of diseases, to, um, height, to whatever, that that one pool of people contained so much latent v- uh, variation that they could supply the, you know, enough s- you know, stretchiness to accommodate all these different traits that you're s- studying now?

David Reich 58:49 Um, that's a rich question, and I think that the human population has within it, for complex traits, a tremendous amount of variation.

Dwarkesh Patel 58:58 Hmm.

David Reich 58:58 So, uh, within the human population, there's a huge amount of variation that affects height. Uh, there's a huge amount of variation that affects body mass index. If you take all these mutations and all set them to the high height variant, a person will be extremely tall, like as tall as a tall building.

Dwarkesh Patel 59:14 Yeah.

David Reich 59:14 You know, if you... Of course, which will never happen. But if you take all these variants that affect schizophrenia risk, they will, and you point them all in the same direction, uh, there will be extreme risk or extreme protection, uh, for schizophrenia. So for complex traits, one's underpinned by many mutations. All the variation already exists to move the population to a different adaptive set point that's optimal in the environment which it's in. So if you push the inv- uh, population into a new environment within hundreds or thousands of years, the population can rapidly move to a new adaptive set point. There are some unusual traits, like ability to digest cow's milk or protection against sickle cell anemia, that require a single very important mutation that may not yet exist in the population, and then you have to wait for the mutation to occur in some, some people. And when the populations are relatively small, only 10,000 people, you might have to wait dozens or hundreds of generations for that mutation to arise. But when the populations are large, uh, there's not mutation limiting anymore.

Dwarkesh Patel 1:00:14 Hmm.

David Reich 1:00:14 Every mutation that can occur does occur. There's eight billion people in the world.There are maybe 30 new mutations every generation, so that's like, what is it? It's like 240 billion new point mutations every generation. There's only three billion DNA bases in the genome, so every mutation that can occur does occur about 100 times every generation, and we're not mutation limited anymore. And so it's not like you have to... That the mutations can arise again. They do arise again, but when the population's only 10,000, you have to wait dozens or hundreds of generations sometimes-

Dwarkesh Patel 1:00:48 Mm-hmm

David Reich 1:00:48 ... for the new mutation to occur.

Dwarkesh Patel 1:00:49 And so how, how likely is it that the thing that changes the Bronze Age is just that the human population was big enough? So you, you, 3000 BC, you go to, I think, a population of 50 million-ish people. Um, the population is big enough that, and the gene flow between different areas is high enough such that things whi- which don't have an overwhelming selection coefficient, which aren't overwhelmingly favored by evolution, are finally visible, uh, visible to selection.

David Reich 1:01:13 I think that's not likely to be true, but it's extremely interesting thing to think about. So I think already when population sizes are on the order of a million so or so, every mutation that can occur does occur within a few generations. And so that's well before the Bronze Age, if you take the population even of a place like Europe, but also, also of, of, of, of other places, or maybe it's at the, uh, dawn of the Bronze Age or the farming period. So the, the question you ask is maybe when the population is small, natural selection doesn't work effectively.

Dwarkesh Patel 1:01:43 Yeah.

David Reich 1:01:43 So a common thing that people think about with natural selection, and that is true, is that in small populations, selection doesn't work effectively. Um, and that's because mutations bop around in frequency from generation to generation-

Dwarkesh Patel 1:01:56 Yeah

David Reich 1:01:56 ... a lot in a small population just randomly. So if you have a population of size of 1,000, populations var- mutations will bop around o- by a frequency of one over 1,000 every generation. And if the selection coefficient is less than that, it will be drowned in the random bopping around of frequencies due to genetic drift. But that is already for a population of 1,000. 0.1% selection coefficient is very weak. We're talking about 1% effects, and that's much very strong. It will work very well even in a population of a size 1,000 or 10,000.

Dwarkesh Patel 1:02:27 Mm.

David Reich 1:02:28 If you are talking about mutations of the type that will start rising in some, only in large populations, but not small populations, those are selection coefficients that are on the scale of one over 10,000 or one over 100,000, and those ones will take 10,000 or 100,000 generations to rise in frequency, which is hundreds of thousands or millions of years. So that's not gonna do anything over the timescale we're talking about.

Dwarkesh Patel 1:02:50 Mm.

David Reich 1:02:50 There's just a timescale issue.

Dwarkesh Patel 1:02:52 Understand.

David Reich 1:02:52 So we're talking about strong measurable selection coefficients on the order of half a percent or more in this study, and all of those are gonna work in small populations or large populations. It's not gonna be affected by the population size.

Dwarkesh Patel 1:03:05 Interesting. But you're saying more generally, once you hit a given threshold of population, the dominant factor is time span-

David Reich 1:03:10 Correct

Dwarkesh Patel 1:03:10 ... not population size.

David Reich 1:03:11 Correct.

Dwarkesh Patel 1:03:12 Okay. Interesting.

David Reich 1:03:13 It's very interesting, and it's actually not widely understood. Yeah.

Dwarkesh Patel 1:03:16 Mm-hmm. Okay. So speaking of data contradicting what you might have otherwise assumed, uh, one of the papers you sent me beforehand, Malik 2016, found that there are not fixed differences between modern and archaic humans 50,000 years ago. Um, and of course, we know this is the period in which the so-called cognitive revolution happened and modernity started and people are making art or whatever. Um, does this suggest that nothing biological changed to make modern humans modern and some... The thing that happened was some cultural change? How, how do we understand what this data tells us?

David Reich 1:03:58 Right. 50,000 years ago or so, or maybe 100,000 to 50,000 years ago, there's a quickening of the pace of change in culture. So people, you see the first extensive rep- uh, uh, representational art and, like, bead necklaces and drawings on the wall and so on and so forth, and also a rapid increasing pace of innovation, the types of tools that people use. And so the thought might be that there was gonna be, have been some kind of genetic switch, a kind of, uh, important genetic change that, uh, was occurred in the population and that swept to high frequency that everybody suddenly had, soon had, and that made it possible for do these thi- to do these things, maybe s- some genes that, uh, allowed people to have repre- uh, li- complex language, representational language, for example. And so one thing that we did in 2016 in this paper by Shaat Malik and colleagues, uh, is we looked across the DNA for places that might be expected to look like this, that where all people living today or nearly all people living today share a common ancestor, uh, maybe 100,000 or 200,000 years ago. And we looked really hard, and right across all the DNA we could look at, we couldn't find anything more than four or five hundred, more recent than four or five hundred thousand years ago. This is like a crazy result because, uh, it looks like there's no key selective sweeps that have occurred in this period that is ancestral to everyone living today. We talked before about no selective sweeps between Europeans and East Asians, but there don't even seem to be any selective sweeps between, like, shared between all humans in this really important period when a lot of, uh, um, uh, evidence in the material culture record appears. And so it could be that there's biological adaptation in this period, but it's polygenic. There's lots of mutations that all shift in the same direction to help the population to move to a new set point, but there's no key biological change that rises to high frequency-

Dwarkesh Patel 1:05:54 Mm

David Reich 1:05:54 ... in this time.

Dwarkesh Patel 1:05:55 And this group, uh, 50,000 years ago, they are the ancestors of everybody out of Africa or also some Africans?

David Reich 1:06:03 So this is 100 to 50,000 years ago.

Dwarkesh Patel 1:06:06 Right.

David Reich 1:06:06 And, uh, this is the population that's ancestral to West Africans, to most East Africans, to all non-Africans.

Dwarkesh Patel 1:06:13 Mm.

David Reich 1:06:13 And there's a couple of populations in Africa that have substantial ancestry that comes from more divergent groups. Uh, for example, Khoisan, uh, from Southern Africa or Central African rainforest hunter-gatherers have substantial fractions of their ancestry from groups that diverged maybe 200,000 years ago from the other lineages. But all of these groups today are able to do, go to college, do everything everybody else does.

Dwarkesh Patel 1:06:38 Yeah.

David Reich 1:06:38 And so there is, like, no evidence that there is any key mutation lacking in some groups that are n- not present in the others.

Dwarkesh Patel 1:06:46 Mm. So, um,The, the differences we see between different groups of people, um, especially if this group of people, fifty to a hundred thousand people, uh, years ago, had a very small population size. I think last time we were discussing on the order of ten thousand people?

David Reich 1:06:59 Yeah.

Dwarkesh Patel 1:07:00 So basically, everybody in the world or almost everybody in the world, um, or the variance we see between different humans today was latent in this group, and which, which sort of seems... And I get your point that, well, um, if you just stack up different, um, uh, different, uh, different things across the genome, then stacking them up really has a big effect. But that, um, it's interesting that, like, we have so many different groups in the world today and th- that all that diversity c- comes from a very small population size.

David Reich 1:07:33 I think a lot of us in human genetics think that the, uh, our population contains within it the clay that's needed to make almost, uh, any trait.

Dwarkesh Patel 1:07:41 Mm.

David Reich 1:07:42 Uh, and that depending on environmental conditions or selection conditions, the mean value of these traits will move in different directions. There's an empirical question, a real question about how much selection there's been, uh, in different human populations over time. One of the things this new work that we're involved in is doing is showing that at least in the last eighteen thousand years, ten thousand years, five thousand years in this part of the world, there actually has been significant movement, at least for a handful of important traits.

Dwarkesh Patel 1:08:10 Interesting.

David Reich 1:08:11 We looked at more than five hundred traits. About a hundred of them, uh, complex traits showed significant movement in, uh, systematic direction, uh, over this time period. So it really does seem that there is a response, uh, to the environments people are living in that has occurred over this period and is potentially stronger than in previous periods.

Dwarkesh Patel 1:08:30 Crusoe has an amazing ML infra team that keeps finding clever ways to squeeze more performance out of their hardware. For example, tokenization has become a real bottleneck for agentic workloads. Agentic prompts are often extremely long. They tend to have high KV cache hit rates, which shrinks the GPU's prefill work. This means that the tokenization step, which is traditionally sequential, is a much larger fraction of time to first token. To solve this, Crusoe built fasttokens, an open source Rust-based tokenizer which parallelizes things in order to take advantage of all the cores on modern CPUs. Crusoe had to get creative here because a naive approach doesn't work. For example, for pre-tokenization, you can't just split your text into chunks and run regex because you'd end up with issues whenever a word straddled the split. Crusoe solved this by giving each thread an authority zone plus the ability to read one kilobyte past its own edges. This one-kilobyte buffer guarantees that you won't misprocess a token, and the authority zone guarantees that you won't end up with duplicates. No cross-thread coordination required. Crusoe combined this optimization with a handful of other smart tweaks in order to get up to forty percent faster time to first token on real production workloads. To learn more, go to crusoe.ai/dwarkesh.

Dwarkesh Patel 1:09:41 We were talking earlier how there's no fixed differences between, um, humans fifty thousand years ago and humans today.

David Reich 1:09:47 Mm-hmm.

Dwarkesh Patel 1:09:47 So if there's no genetic basis for, uh, the kind of thing that allowed humans to have more symbolic representation, have farming, et cetera, I think I asked you this question last time we talked, but especially with this context, why no farming before the Ice Age? Genetically, we were there.

David Reich 1:10:05 That is such an interesting question. Right. Genetically, we're there.

Dwarkesh Patel 1:10:08 Yeah.

David Reich 1:10:08 The common ancestral population has all of the ingredients for-

Dwarkesh Patel 1:10:11 Right

David Reich 1:10:11 ... farming fifty thousand years ago. Uh, and you know, these people are distributed into different parts of the world, the Americas, you know, fifteen thousand years ago or whatever it is. Uh, you know, New Guinea forty thousand years ago, East Asia, you know, Europe, you know, West Africa. No farming develops, uh, before, you know, twelve or eleven thousand years ago. It only f- develops in the last, you know, twelve thousand years, the period known as the Holocene, which is sort of the end of the Ice Age. And if you talk to climate scientists, uh, and archaeologists, you know, I keep asking people this question every time I meet someone who's an expert in this, it's like, "How can this be that farming develops in all these places? Are we really living in such an unusual time?" And people tell me, indeed, we're living in an un- very unusual time on a scale of two million years. That is, twelve thousand years ago, we switched into this period of not just warmth, but climate stability, and that, uh, and that actually this is true, and sort of hard to believe that we're living in special, such a special time. But if you look at, for example, uh, data from s- bottoms of ponds where you can measure the fluctuations of temperatures using isotopic signatures, apparently we're in a period where it's just fluctuating a lot less year to year and sea- and ten years to ten years and a hundred years to a hundred years, and it's just a period of relative stability that we are miraculously living in, and that when this period of relative l- stability happens, you somehow the, it follows that multiple groups independently turn to agriculture, even though the genetic complement, uh, you know, w- all of whom have the same genetic complement that arises fifty thousand, a hundred thousand, two hundred thousand, three hundred thousand years ago. It's kind of a crazy observation that people just accept, uh, but it's, like, unbelievable.

Dwarkesh Patel 1:11:53 Oh, so y- you, you, you increased the range there. So you said a hundred thousand, two hundred thousand, three hundred thousand years ago, and we, based on the genetic differences between modern, uh, modern people and people from even three hundred thousand years ago, you think basically there's, they're modern three hundred thousand years ago?

David Reich 1:12:10 I don't know. Like, I'm thinking about this all the time right now.

Dwarkesh Patel 1:12:13 Yeah. [laughs]

David Reich 1:12:13 Uh, this is actually, like, actively what I'm thinking about-

Dwarkesh Patel 1:12:15 Yeah

David Reich 1:12:15 ... right now. And, like, you know, there's a big transformation in terms of the culture of humans three hundred, four hundred thousand years ago, this invention of Levallois technology, the ability to make stone tools out of cores.

Dwarkesh Patel 1:12:28 Yeah.

David Reich 1:12:28 The Middle Stone Age revolution or the Middle Paleolithic revolution, depending on whether y- what you call it in Africa or Eurasia. And this is aRevolution, a new way of making stone tools that's shared by Neanderthals and by modern humans, but is not shared in East or South Asia.

Dwarkesh Patel 1:12:44 Hmm.

David Reich 1:12:44 Um, and it's a big change, and it, it involves a cognitive change presumably in order to make this sort of technology. And then there's a further change to the Upper Paleolithic later Stone Age, uh, maybe, uh, 100 to 50,000 years ago, uh, when there's this second transition with a new type of tool making, but not as revolutionary as the earlier one. So when the cognitive leap happens is unclear. The diversification of the lineages leading to people living today, like Khoisan southern Africas and rainforest hunter-gatherers, and, uh, that all occurs more on the timescale of 300,000 or 200,000 years. Uh, and all of these people are capable of, you know, going to college-

Dwarkesh Patel 1:13:23 Right

David Reich 1:13:23 ... and doing everything. And so, you know, it's not obvious that all the toolkit, the cognitive toolkit, the behavioral toolkit, the genetic abilities were not all in place 200 or 300,000 years ago, and that even Neanderthals had them, right? So it's not obvious that this was not the case.

Dwarkesh Patel 1:13:39 Yeah.

David Reich 1:13:39 And so like, I just don't know. You sort of distribute these people descended from this diversification that happens 200, 300,000 years ago to different parts of the world, and then bing, you know, after 12,000 years ago you start having agriculture popping up in different places. It's kind of an outstanding mystery-

Dwarkesh Patel 1:13:58 Right

David Reich 1:13:58 ... of human history. And, you know, I, I find it unbelievable that we live in a pla- in a time period that climatologically is so unique on the scale of two million years. But my colleagues tell me it's true.

Dwarkesh Patel 1:14:10 The climate thing seems surprising given there were so many different environments in which agriculture was independently developed. N- I, now I understand that across environments the variance could have gone down. But it just like, if, if it only had happened in one place at one time, I, I could have bought that explanation. But the fact that they're making maize in the New World, and they've got, um, uh, you know, cereals in the Old World and so forth, and just in, in very different environments makes it surprising that it would-

David Reich 1:14:39 It's very, very surprising.

Dwarkesh Patel 1:14:41 Yeah.

David Reich 1:14:41 And I think we accept it, but it's just like a crazy observation-

Dwarkesh Patel 1:14:44 Right

David Reich 1:14:44 ... that most normal people don't realize.

Dwarkesh Patel 1:14:46 Yeah.

David Reich 1:14:47 You know, th- the thing that basically everybody accepts is that the common ancestral population of almost everybody in the world except for rainforest hunter-gatherers and Khoisan is, like, around 70,000 years ago.

Dwarkesh Patel 1:14:59 Yeah.

David Reich 1:14:59 And everybody accepts that these people all have in place the cognitive, behavioral, intellectual ingredients that are necessary for the farming revolution and state, building state societies. Because when these descendants of these people get distributed to West Africa, to East Africa, to the Americas, to Europe, to South Asia, to East Asia, to New Guinea, and so on, their descendants all do this.

Dwarkesh Patel 1:15:19 Yeah.

David Reich 1:15:19 Like, independently or semi-independently or completely independently.

Dwarkesh Patel 1:15:23 Yeah.

David Reich 1:15:23 Or demonstrably completely independently in all these different parts of the world. So the cognitive resources for doing this must have all been in place, but it's a very long fuse. Like, it delays for 40,000 years, for 70, s- you know, 60,000 years in all these different places after the common ancestral population splits up. And then, you know, ignites into, like, agriculture and all these other things after that point. It's kind of a crazy claim. You know, and then you could argue about whether the actual fuse is 300,000 years, [laughs] you know, from when Neanderthals separated and from when different lineages of extant modern humans separate, and that's also plausible. So it's kind of a crazy sort of set of things that we're being asked to believe.

Dwarkesh Patel 1:16:04 Is it possible that agriculture existed, but you didn't have modern metallurgy or whatever it was that allowed populations to explode starting in 5000 BC with the Bronze Age? 'Cause, like, population-wise, it doesn't seem like, you know, 10,000 BC to 5000 BC, the early Neolithic, much is happening. Is it, is it possible that they had farming, but they didn't have copper, they didn't have tin, uh, which you needed to go to, I guess, the Middle East for to develop a civilization that could make use of bronze at a large scale, and so they just disappeared from the historical record?

David Reich 1:16:38 I, I think we would see their archeology.

Dwarkesh Patel 1:16:39 Hmm.

David Reich 1:16:40 And, like, you know, the, um, extraordinary developments in the Americas, uh, which are entirely Stone Age, uh, you know-

Dwarkesh Patel 1:16:47 You would, you would see them today if, if they had gone, completely vanished.

David Reich 1:16:50 Oh, yeah. I mean, there's like, you know, you, you, you know, we, we should go for a, a trip to Teotihuacan-

Dwarkesh Patel 1:16:55 [laughs] Oh, yeah

David Reich 1:16:55 ... in Mexico.

Dwarkesh Patel 1:16:56 Of course, of course. [laughs]

David Reich 1:16:56 And it's, like, like, so impressive.

Dwarkesh Patel 1:16:59 Oh, yeah.

David Reich 1:16:59 Like, you know, when I went there when I was 20, you know, it's just like, it's totally as impressive as-

Dwarkesh Patel 1:17:04 Yeah

David Reich 1:17:04 ... as ancient Egypt.

Dwarkesh Patel 1:17:05 Yeah.

David Reich 1:17:05 You know, it's, like, huge. It's massive. It's without metal.

Dwarkesh Patel 1:17:09 And it's, um, it's even more impressive because it's not only without metal, but it's without animals and without wheels, which is crazy, like-

David Reich 1:17:15 Right

Dwarkesh Patel 1:17:15 ... [laughs] the, the, the marble is just, like-

David Reich 1:17:17 Right

Dwarkesh Patel 1:17:17 ... hauled without wheels.

David Reich 1:17:18 Right. Like, take any person who has, like, an old world superiority, and, like, take them to these places, and they will not have it anymore.

Dwarkesh Patel 1:17:26 Yeah.

David Reich 1:17:26 It's just extraordinary what's in these places. And these are people who separated 20,000 years ago at least from the ancestors of East Asians, and 40,000 years ago from the ancestors of West Eurasians.

Dwarkesh Patel 1:17:36 Hmm.

David Reich 1:17:37 And, you know, just had the same biological, you know, uh, cultural shared toolkit from then, but there's just a, a fuse, a ti- a long fuse delay until all this stuff happens.

Dwarkesh Patel 1:17:49 Interesting.

David Reich 1:17:49 It's kind of, like, an amazing thing, and we don't question

David Reich 1:17:52 it.

Dwarkesh Patel 1:17:52 What are other questions you have that, um, pe- uh, yeah, you're, you're either ha- are investigating right now or want to investigate these kinds of big picture questions of human history?

David Reich 1:18:04 I think that I'm ... I mean, I'm, I'm perplexed. I don't know if we talked about it before, but, like, I remain very, very confused about the relationships between archaic and modern humans.

Dwarkesh Patel 1:18:15 Hmm.

David Reich 1:18:15 We have genome sequences now from archaic humans who lived in Europe and the West Eurasia and Central Eurasia and the Neanderthals. We have archaic sequences from these ena- enigmatic Denisovans, who we now have, uh, a skeleton for, um, since we last talked. There's now a s- a f- a skull from a Denisovan-

Dwarkesh Patel 1:18:32 Hmm

David Reich 1:18:32 ... that's been shown to be a Denisovan. Uh, and we have data from lots of modern humans. Uh, and there's really big mysteries about the relationships amongst these groups. So genetically-The Denisovans and the, uh, Neanderthals are sisters. They descend from a common ancestral population 5 or 600,000 years ago, and that group descends a couple hundred thousand years before, uh, 7 or 800,000 years ago from the common ancestors of modern humans. And so genetically, the whole genome data says that Neanderthals and Denisovans are archaic humans from a common ancestral archaic population. But there are so many things shared between Neanderthals and modern humans that don't seem to be shared between, with East Asians. Uh, they both share, uh, Middle Stone Age tone, stone tools, level of technology, this cognitively unique type of way of making stone tools that wasn't used in East Asia. They both have the same mitochondrial DNA and Y chromosome sequence. So the Y chromosome sequence of Neanderthals, the mitochondrial DNA of Neanderthals is actually modern human that came through interbreeding-

Dwarkesh Patel 1:19:37 Hmm

David Reich 1:19:37 ... two or 300,000 years ago and then shot up to 100% frequency. And then Neanderthals and modern humans are both the product of mixture events that happened between archaic and modern humans 300 or 200,000 years ago, uh, demonstrably through patterns of variation in ancient and modern DNA. And so it feels that there's something shared between Neanderthals and modern humans that's not shared with Denisovans, even though the vote of the whole genome says that Denisovans and Neanderthals are related. So one wonders whether there's something connecting kind of, uh, Neanderthals and modern humans that's different from Denisovans, even though genome-wide Denisovans and Neanderthals cluster. So I'm thinking about that all the time now.

Dwarkesh Patel 1:20:17 And then connecting them would be interbreeding events or being in the same place at the same time that we missed?

David Reich 1:20:24 There's a known interbreeding event-

Dwarkesh Patel 1:20:25 Yeah

David Reich 1:20:25 ... from the lineage leading to, uh, modern humans into Neanderthals, but it's supposed to be only 5%.

Dwarkesh Patel 1:20:31 Yeah.

David Reich 1:20:32 So I'm interested in that, that, that 5% is actually a sign of something much more impactful, that is that somehow Neanderthals are in some sense deeply modern in some ways. And even though they get swamped by archaic genes, that somehow-

Dwarkesh Patel 1:20:45 Hmm

David Reich 1:20:45 ... they actually have more of a modern impact than one would think, and that the Middle Stone Age and, you know, Middle Paleolithic revolution that they share with modern humans is actually more fundamentally a part of who they are in some sense than we think.

Dwarkesh Patel 1:20:59 Interesting. I- sorry, w- wh- uh, when was this interbreeding event?

David Reich 1:21:02 300,000 to 200,000 years ago.

Dwarkesh Patel 1:21:04 And so the common ancestor between Neanderthals and most humans alive today is potentially more recent than the common ancestor between all humans alive today.

David Reich 1:21:14 Oh, for sure.

Dwarkesh Patel 1:21:15 Yeah.

David Reich 1:21:15 Yeah.

Dwarkesh Patel 1:21:16 Which is crazy.

David Reich 1:21:16 Yeah. Well, you- not, not... The divergence to all the archaic humans, including Denisovans, is within human variation.

Dwarkesh Patel 1:21:23 Okay.

David Reich 1:21:23 So, but, uh-

Dwarkesh Patel 1:21:24 Wait, what?

David Reich 1:21:25 Yes. So the average time to the common ancestor of any two human genes is one or two million years ago. So, like if you look at any, the, a bit of your DNA that you get from your mother, and a bit of your D, that same bit of your DNA on the same chromosome. The copy of chromosome three you get from your mother, and the copy of chromosome three you get from your father, typical time they share a common ancestor is one or two million years ago. That's before the split from Neanderthals and Denisovans. So there's many places in your DNA where you're more closely related to a Neanderthal on your mother's side than you are to your father.

Dwarkesh Patel 1:21:56 And, um, I'm sure that there's a simple explanation, but how?

David Reich 1:22:00 This is, it's the same reason that, like, if you have, like a sister, uh, you know, you're s, in some places in your DNA more closely related to her than you are to me 'cause you share a parent.

Dwarkesh Patel 1:22:08 Yeah.

David Reich 1:22:08 But in other places you're more closely related to me than you are to your sister because you happen not to share the same DNA from your parents.

Dwarkesh Patel 1:22:15 Right.

David Reich 1:22:15 It's a proc- i- it, it's just that the DNA that we get from our common ancestral population was already quite variable-

Dwarkesh Patel 1:22:23 I see

David Reich 1:22:23 ... 500,000 years ago, 700,000 years ago, a million years ago, and some of us descend from some of those ancestors, and others of us descend from other of those ancestors. And Neanderthals split from our lineage really close in time-

Dwarkesh Patel 1:22:35 Yeah

David Reich 1:22:35 ... on human evolutionary timescale, such that in some places in our DNA we're more closely related to Neanderthals than to each other.

Dwarkesh Patel 1:22:41 Interesting. Um, what are the other big questions?

David Reich 1:22:44 I think that's the main thing that I'm thinking about a lot these days.

Dwarkesh Patel 1:22:47 Yeah.

David Reich 1:22:48 Uh, you know, I think that I'm really continue to be very obsessed with, uh, questions about, uh, the spread of human populations around the world, and trying to reconstruct that with ancient DNA.

Dwarkesh Patel 1:22:59 After the recording ended, David started spontaneously explaining a new theory he's working on about Neanderthal genetics on a whiteboard in the room, which I ended up capturing on my iPhone.

David Reich 1:23:08 The thing I'm thinking about a lot recently is the possibility that it's maybe we're not thinking of ri- in the right way about the relationship between archaic and modern humans. Uh, so the standard model is one like this, where, uh, uh, uh, Denisovans, these archaic humans that were found from ancient DNA, and Neanderthals descend from a common ancestral populations 5 or 600,000 years ago. And that these two separate earlier, maybe 700 to 800,000 years ago from the ancestors of modern humans, people like us. So that's the big result of a lot of studies since 2010. Uh, but there's also evidence of a interbreeding event, uh, that happened maybe 200 to 300,000 years ago. Uh, and that actually tur- resulted in, uh, modern humans, uh, contributing DNA to the ancestors of Neanderthals. So this is maybe 5% of the DNA of Neanderthals comes from this interbreeding event, and a lot of studies have shown this. And so, uh, I'm f- very interested in this because, uh, actually from the archeological record, Neanderthals and modern humans sort of look actually quite similar to each other, much more similar to each other than in s- a lot of them do to Denisovans.

Dwarkesh Patel 1:24:42 Hmm.

David Reich 1:24:42 These archaic humans in East Asia. Uh, so a lot of the history people have thought that Neanderthals are our sister, but in-Two-- But in 2010, the sequencing of the Denisovan genome made it very clear that on average, Denisovans are closer to Neanderthals than to modern humans. So this was, like, a very confusing result. Um, and most people now think that Neanderthals and Denisovans are, like, descend from a common ancestral population separated earlier from the ancestors of modern humans. Hmm. So, uh, I'm interested in the possibility that actually the right way to think about Neanderthals is actually as somehow culturally modern humans, uh, and, uh, even though that genetically they're mostly Denisovans. And the model I'm thinking about is motivated by this archa- archaeological phenomenon known as the Middle Stone Age revolution. So if this is Africa and this is, I don't know, Europe, uh, we know that the, uh, new way of making stone tools, uh, with, uh, these cores that were, uh, very carefully, uh, mined far away from the locations they were used, made out of high-quality stone like flint, start being used three or four hundred thousand years ago, first in the Caucasus, places like Georgia today or East Africa. And that this way of making stone tools, which is quite revolutionary and is known in Europe as the middle Paleolithic, in Africa as the Middle Stone Age, and is associated with much more widespread use of fire, uh, and also moving stone and around at much further distances than before. I'm interested in the idea that this is something that's shared between Africa, uh, between modern humans and Neanderthals. There's somehow some shared cultural feature that's absent in East Asia, and that might have a relationship in the genetic data and is somehow related to this five percent DNA. Hmm. So the idea I'm interested in is the possibility that there is a population here that invents the Middle Stone Age and the middle Paleolithic, sometimes called Levallois technology, and that people from this population expand into Europe, and they mix with the local archaic humans who are there. And that is what this five percent interbreeding event is. It happens two to three hundred thousand years ago, and it produces a group that, as it expands across this landscape in Europe, uh, mostly picks up the local DNA and becomes mostly archaic genetically, but retains its modern human culture, the way of making stone tools and some of its traditions. And so one of the things that's super interesting about this is that if you actually look at the genetics, uh, the whole genome, the Neanderthals and Denisovans cluster. But if you look at the mitochondrial DNA, which people get from their moms, and they get from their moms, Neanderthals and modern humans cluster. So if you look at the mitochondrial DNA, Denisovans and modern humans share an ancestor well more than seven hundred or eight hundred thousand years, as you expect for the history. And if you look at the Y chromosome that you get from your dad, Denisovans and modern humans share an ancestor more than seven or eight hundred thousand years ago, which is, uh, consistent with this history. But if you look at the Neanderthal mitochondrial DNA, it's only three to four hundred fifty thousand years. If you look at the Y chromosome, it's only three to four hundred fifty thousand years. So what the current genetic work is asking us to believe is that even though this is only five percent of the whole genome, it re- introduces mitochondrial DNA and Y chromosomes, and they jump up to a hundred percent frequency. It's kind of a crazy claim because the probability of this occurring by chance is low, maybe five percent times five percent, so a very small number. And so it's sort of what we actually all believe. Uh, but it's sort of a very sort of surprising event, and somehow it's accreted all the findings in the whole literature so that we make ourselves believe this. But it seems sort of unlikely on first principles that somehow only five percent will introduce both the Y chromosome and mitochondrial DNA. And it really looks like this. So there's this amazing data from this site in Spain that's like two to four hundred thousand years old. It's three to four hundred thousand years old at a site called Sima de los Huesos. And they have a nuclear genome that looks Neanderthal-like, most of the genome, but their mitochondrial DNA and Y chromosome is Denisovan-like. So it really looks like there was a population related to modern humans that pushed into this Sima de los Huesos-like population, displaced its mitochondrial DNA and Y chromosome, but kept the rest of its genome. So it really looked like something like this happened. So the idea that I'm sort of playing with, and you know, probably it's wrong, who knows, but is that there's a landscape, this is maybe Europe, and you can break it up into a hundred or so demes, little areas. And modern humans get introduced at the bottom right corner in the Middle East or something, and they spread into Europe. And as this population spreads, there's a wave front of expansion, and they're interacting with the local archaic humans. And even if there's a small amount of interbreeding, the theory, uh, from lots of studies of simulations and lots of studies of all these different species, like, uh, mammals and birds and so on, shows that there is, uh, when there's even a little amount of interbreeding as there's an invasion or a movement of expansion of one group into the territory occupied by the other, there's massive introgression of local genes. There's, uh, th- th- that, that these pioneers at the wave front, they'll sometimes interbreed with the local population. There are so many of them around that their DNA will get swamped by the local group, so by the time they make it to the other side, they're largely local. Hmm. And so maybe what we're seeing is that this is what's happened. You have, like, a modern human population that's matrilineal, for example, where transmission of making t- stone tools this way is happening from your mother to the kid, and that's why they're retaining their mitochondrial DNA. But by the time they get to the other end of Europe, they're mostly archaic. They're mostly local archaic. So you end up with a ninety-five percent population replacement. So this would explain why the mitochondrial DNA is shared between Neanderthals and modern humans, and it would ex- also explain why the mixture proportion is only five percent. But, like, the really interesting thing is that actually there's other evidence from studies of modern humans that actually modern humans are too also admixed, and that the right way to think about thisIs that modern humans are a mixture of two groups, maybe like 1.5 million years ago, and that they come together 2 to 300,000 years ago with like 20%, 200 to 300,000 years ago, with maybe 20% ancestry from this archaic African group and 80% ancestry from this early modern lineage, and that the same group then mixes with, with Neanderthals, and it's 5% modern here and 95% local here. And so you actually have this key population that makes the Middle Stone Age or Levallois technology, this one that appears here, and it expands in all directions into Europe here, into Africa here 2 to 300,000 years ago, bringing this technology, bringing these new ideas, bringing perhaps some genetic adaptations. It expands into archaic humans in Europe. It mixes with the local population. It gets 95% replaced, but still retains its cultural features and maybe some genetic features. And it expands in Africa too, and here it's not 95% replaced, it's only 20% replaced, and probably the reason that happens is that this group is much, much more diverged. It's archa- much more archaic. It's 1.5 million years diverged rather than 7 to 800,000 years diverged. And as a result, there's many more incompatibilities genetically, and there's much more barriers to gene flow. But there's still a lot, maybe 20%, and we have evidence that this is a big mixture that happens. And so what you're actually seeing is a modern human expansion both into Europe and into Africa. In one places it forms Neanderthals, in one places it forms the ancestors of everybody living today. But all of these groups are descended from this key sort of revolutionary event that happens here.

Dwarkesh Patel 1:32:52 Interesting.

David Reich 1:32:53 So we often talk about the revolutionary events 50 to 100,000 years ago, the more symbolic behavior and so on and so forth, uh, that sort of first appear in Africa and the Middle East and spread beyond. But there's also this earlier event, and this event is sort of contemporaneous with the breakup of all the different groups also in Africa today, uh, you know, the Khoisan southern Africans and the Central African rainforest hunter-gatherers. So one wonders whether this is an equally important formative event. And it also, if that's true, makes you think of Neanderthals as actually somehow our cousins, that they actually share our Y chromosome, they share our mitochondrial DNA, they share formation of this 2 or 300,000-year-old event, their shared toolkit. So even though the genome is telling us that they're cousins of Neanderthal, uh, Denisovans, the, the, the actual correct way to think about them may be in an important sense somehow the, uh, you know, relations or the close cousins of modern humans.

Dwarkesh Patel 1:33:55 I, I have so many questions. Do you have 15 more minutes?

David Reich 1:33:57 Yeah, yeah.

Dwarkesh Patel 1:33:57 Okay. Um, first of all, what is going on with this group of archaic Africans 1.5 million years ago? Where in Africa are they, and what happens to the portion of them that don't form modern humans? Do they survive?

David Reich 1:34:14 So they, uh, the genetic data suggests, uh, uh, this is analysis not of any ancient DNA-

Dwarkesh Patel 1:34:22 Yeah

David Reich 1:34:22 ... but only an analysis of modern DNA from different people, mostly in Africa, but also non-Africans. In multiple studies, there's at least three, maybe four or five studies that I've, I know about, have looked at the patterns of variation in people today and say the data in modern people today, including in Africans, is not consistent with a homogeneous population. It looks like a population that split well more than a million years ago into multiple, at least two, but maybe many groups, and then came together with an important coming together a few hundred thousand years ago. The papers have different models that they fit, but they all have this feature of, of more than a million years ago there's a split up, and then on the order of a few hundred thousand years ago, there's a coming together and a remixter event forming the ancestors of anatomically modern humans.

Dwarkesh Patel 1:35:05 And th- this includes the Khoisan and whatever other groups.

David Reich 1:35:08 Yes.

Dwarkesh Patel 1:35:08 Okay, great.

David Reich 1:35:08 All of these groups have this. Maybe it's in slightly different proportions. So you ask, where are these people living? Who knows, right?

Dwarkesh Patel 1:35:14 [laughs]

David Reich 1:35:14 Like, you know, in this scenario, the 80% is coming from the Caucasus or Northeast Africa, where this Middle Stone Age form, it's from this population that forms-

Dwarkesh Patel 1:35:23 Yeah

David Reich 1:35:23 ... the Mil- Middle Stone Age. And they mix with, like, local groups. And who knows where they are? Southern Africa, Western Africa, Central Africa, Eastern Africa. We don't have any ancient DNA, but, like, you know, this is a very rich environment. People have been living there for, like, 7 million years at least, and, like, there would have been different groups of people everywhere. Probably it's not just two groups, it's probably more groups. I think the important theme here is there's evidence of substructure that's well more than a million years ago, and this place would have been a landscape full of archaic humans that would have been differently, you know, related to these expanding people and would, and would have admixed with them when they came through.

Dwarkesh Patel 1:35:59 Okay, so the Neanderthals, first time around 300,000 years ago, our ancestors share culture with them. They share the Middle Stone Age technology, but they don't replace the population. The technology spreads through culture basically, um-

David Reich 1:36:15 Well, it spreads through genes too. If you look at Yamnaya in India, there's almost no Yamnaya ancestry in India.

Dwarkesh Patel 1:36:22 Huh?

David Reich 1:36:23 I mean, it's just diluted, diluted, diluted down.

Dwarkesh Patel 1:36:25 Mm.

David Reich 1:36:25 As modern, as Yamnaya expanded into Central Asia, you know, like expands into Europe, it makes the Corded Ware. There's a 25% dilution. It expands back across Central Asia. It goes through the Hindu Kush.You know, it gets into Northern/South Asia, it admixes more with local people. By the ti- you know, today, the most Yamnaya ancestry you see in India is 20% or 10. You know, most people have less than 10% or 5%.

Dwarkesh Patel 1:36:49 I see.

David Reich 1:36:49 It's, you know, there's just been a lot of mixture on the way, but it is the tracer dye, right? Like-

Dwarkesh Patel 1:36:53 Yeah

David Reich 1:36:54 ... it tracks Indo-European languages, and important aspects of Indo-European culture are coming through Yamnaya. So if you know where to look, that tracer dye is only 10%, it's only 5%, it's only 2% in some groups, but it's the languages people speak, and it's important cultural shared elements that connect them to people on the other side of the Indo-European-speaking world. So this 5%, you s- you shouldn't sneeze at it, right? Like, that's tracing something important.

Dwarkesh Patel 1:37:17 And-

David Reich 1:37:18 In this model

Dwarkesh Patel 1:37:18 ... and then, um, I understand that if things are transmitted more through women that... Actually, yeah, sorry, let me back up. I don't understand why the maternal DNA and, uh, m- mitochondrial DNA and the Y chromosome would be especially privileged as the spreading is happening. Can you explain that?

David Reich 1:37:36 Um, so the reason I'm talking about these matrilineal or patrilineal-

Dwarkesh Patel 1:37:40 Yeah

David Reich 1:37:40 ... expansions is I'm really troubled, and have been troubled for, like, many years, uh, actually 15 years, but, like, especially in the last three or four years, by the fact that the mitochondrial DNA and Y chromosome cluster Neanderthals and modern humans.

Dwarkesh Patel 1:37:52 Yeah.

David Reich 1:37:52 But the rest of the genome clusters Neanderthals and Denisovans.

Dwarkesh Patel 1:37:55 Right.

David Reich 1:37:55 This is like a crazy result that-

Dwarkesh Patel 1:37:57 Yeah

David Reich 1:37:57 ... is not seen in any other species-

Dwarkesh Patel 1:37:58 Yeah

David Reich 1:37:58 ... where you see this pattern. So I'm very interested in patterns that would explain this. If you invoke and assume that there was, like, a matrilineal or a patrilineal expansion, um, it could be either, uh, where it, modern humans, when they were expanded a- across the landscape of Europe, uh, retained their identity along one of the lines. Like, if you incorporate a local, if it's, if it's matrilineal, w- when they incorporate a male from the local community, they're brought into the community, and the kids are raised by, based on the culture of the mothers or something. Or, or if it's a patrilineal expansion, they incorporate a female from the community. It's incorporated, sort of raised with the culture of the fathers. Um, so if that happens, it guarantees one of these two parts of the genome to look like it does. Because it's a modern human expansion, if it's patrilineal, it will retain the Y chromosome. If it's matrilineal, it will retain the mitochondrial DNA. So it will solve one of your two problems.

Dwarkesh Patel 1:38:52 But not both. [laughs]

David Reich 1:38:53 It won't solve the other one, so you need to solve the other one. Uh, so the other one you can solve either by natural selection, or you can solve it by social selection.

Dwarkesh Patel 1:39:01 Hm.

David Reich 1:39:01 So, uh, it's c-... So, so by the way, patrilineality and matrilineality are the rule, not the exception, in human communities. Usually communities sort of follow cont- have continuity along the male or the female line. Um, and u- usually it's patrilineality, sometimes it's matrilineality. Um, so you can also have phenomena like social selection. So, uh, so it could be that once you have kids of someone who is from, uh, the, uh, whose father, for example, is from the outside community, that those, the male c-... Uh, usually in most communities, uh, females all reproduce. Like, that's typical today. Like, usually women have kids if they can. But men in traditional societies are actually very variable in their reproductive success. A large fraction of men never have kids. Uh, and then there's a relatively smaller number of, there's a, a subset of men have many kids-

Dwarkesh Patel 1:39:52 Yeah

David Reich 1:39:52 ... with many women. Um, and so there's competition among men for kids. So in this context where males are competing for access to females, then female mate choice begins to be an important process. And, uh, you have a phenomenon where, uh, it could be the case that, like, the, if you are, your dad is an archaic male, then you're not gonna be as successful in the competition for local females as if your dad is a non-archaic male.

Dwarkesh Patel 1:40:19 I see.

David Reich 1:40:20 So a, some simple social phenomenon like that could explain the data. And we actually see this in human society. So for example, if I remember right, like, in Central African rainforest hunter-gatherers, there's different treatment of boys and girls depending on whether their dad or mom is one group or the other.

Dwarkesh Patel 1:40:35 I, I guess I don't understand how the maternal... Like, okay, um, y- you know, uh, the group spreads, and it gets to the next front.

David Reich 1:40:45 Yeah.

Dwarkesh Patel 1:40:45 And, uh, they have kids, and some of those kids are, um, I, uh, okay, I, I, the, the, from the group, from the humans that have just entered, the kids will have the maternal DNA or the mitochondrial DNA from the humans.

David Reich 1:41:00 Yeah.

Dwarkesh Patel 1:41:01 But from the existing people, they will have the mitochondrial DNA of the archaic humans.

David Reich 1:41:05 Yeah.

Dwarkesh Patel 1:41:06 And why are the people with the archaic mitochondrial DNA not surviving?

David Reich 1:41:11 Um, so, uh, it's a question. Uh, so there's multiple possible explanations. Uh, but it's much easier to explain that than both the mitochondrial DNA and the Y chromosome.

Dwarkesh Patel 1:41:21 Hm.

David Reich 1:41:21 One possibility is that the mitochondrial DNA was less biologically fit. Another possibility is that there's social discrimination on, against, uh, uh, people based on whether their parents are archaic or not.

Dwarkesh Patel 1:41:31 Interesting. Um-

David Reich 1:41:32 Which is, I think, not at all surprising in a human context.

Dwarkesh Patel 1:41:35 Yeah. What, okay, so then the Neanderthals-

David Reich 1:41:36 It's the weakest link in this, this argument.

Dwarkesh Patel 1:41:38 Hm.

David Reich 1:41:38 This argument's probably wrong, but I'm just telling you what I'm thinking about.

Dwarkesh Patel 1:41:41 Um, okay, then Neanderthal. So 300,000 years ago, we, um, our lineage interacts with them, but mostly their lineage survives, and there's cultural diffusion, et cetera, um, and genetic diffusion. And then is it 70,000 years ago that we interact again?

David Reich 1:42:00 Yes.

Dwarkesh Patel 1:42:01 And they don't survive.

David Reich 1:42:03 The, the genetic ancestry doesn't survive.

Dwarkesh Patel 1:42:05 The genetic ancestry doesn't survive. So, um, uh, presumably there was also other contact in between 300,000 years ago and 70,000 years ago.

David Reich 1:42:11 Probably, yeah.

Dwarkesh Patel 1:42:12 But what is-

David Reich 1:42:12 But these are the bi- these are the ones we are detecting currently.

Dwarkesh Patel 1:42:15 Is it, is it just sort of like there's not really an answer, just contingent why one time there's this kind of diffusion where most of the archaic, uh, genome survives and the other time it's total replacement?

David Reich 1:42:28 I think that this is not at all surprising given the context. So, like, if, if you look at, if you think about this model, this is 7 or 800,000 years ago. This is 300,000 years ago, right?

Dwarkesh Patel 1:42:37 Yeah.

David Reich 1:42:37 So this is, like, 400,000 years separated. You talked about the Bhatia paper with me earlier.

Dwarkesh Patel 1:42:42 Yeah.

David Reich 1:42:43 That's two populations 70,000 years separated. There's no biological incompatibilities-

Dwarkesh Patel 1:42:46 Yeah

David Reich 1:42:46 ... between West Africans and Europeans. There's no natural selection against biological incompatibilities. So we know with, when Neanderthals and modern humans met and mixed-Uh, there were. There were biological incompatibilities. That was at 700,000 years ago. Um, and so there's, as populations become more apart, there begins to be biological incompatibilities rapidly developing, probably as the square of the distance-

Dwarkesh Patel 1:43:08 Yeah

David Reich 1:43:08 ... separation because you need pairs of interacting genes, and therefore it's the square of the separation. Uh, so here it would've been maybe only 400,000 years separated between this lineage and this lineage.

Dwarkesh Patel 1:43:19 Interesting.

David Reich 1:43:19 Here, it's like 1.2 million years. It's a lot. So these are at the b- edge of not being able to produce children. So this is quite different humans. These are actually three times closer than these.

Dwarkesh Patel 1:43:32 Yeah.

David Reich 1:43:33 You know, and like if you look at mixtures of humans today, there are mixtures in Southern Africa today are people who are half this distance.

Dwarkesh Patel 1:43:39 Yeah.

David Reich 1:43:39 Right? Like K- you know, if you look at Khoisan and Bantu people mixing in Southern Africa, like the Xhosa, which is the an- you know, the population of, for example, Nelson Mandela.

Dwarkesh Patel 1:43:47 Yeah.

David Reich 1:43:47 This is groups that are separated by almost 200,000 years.

Dwarkesh Patel 1:43:49 Yeah.

David Reich 1:43:49 Which is half of this. Totally compatible, compatible. And so like what you're seeing is this is a group that's actually completely permeable genetically or nearly completely permeable. This, this one is almost certainly has substantial biological incompatibilities because 300,000 years later, two or 300,000 years later, we see the interbreeding between Neanderthals and modern humans, or between Denisovans and modern humans. There's clear evidence of incompatibility at that point.

Dwarkesh Patel 1:44:14 Interesting.

David Reich 1:44:14 But this would be even bigger. So what you would expect to see is that as this group spread, they would be moving into a territory full of archaic humans, and there would be some interbreeding, but the kids would be not very fit.

Dwarkesh Patel 1:44:25 Yeah.

David Reich 1:44:25 They would die off. There would be a lot of infer- infertility. And so the barriers to gene flow or the of, of, and to interbreeding would be greater. So to me, it's not at all surprising that as this group moves into Eurasia, here's Eurasian archaics, you know, the ancestors of D- Denisovans, you know, and these are only 400,000 years diverged from these people over here. And here's African archaics, and these are like 1.2 million [laughs] years diverged.

Dwarkesh Patel 1:44:54 Yeah.

David Reich 1:44:54 So, you know, they just don't interbreed as much, and so you don't get as much, uh, much, much, much gene flow. But the key thing is at the same time. It's the same time. So like it really feels like the signature of an explosion of people from one place interacting with people here, interacting with people here. It's the same sort of, sort of cultural revolution or technological revolution-

Dwarkesh Patel 1:45:15 Yeah

David Reich 1:45:15 ... impacting this place, impacting this place, and creating populations that are kind of both impacted by this cultural revolution, which we know is the case because it's, they share the same toolkit.

Dwarkesh Patel 1:45:25 Yeah.

David Reich 1:45:26 Um, and so, you know, some people argue that Levallois technology is independently invented, but this would be a sort of ... But you know, it's very similar, and, uh, this would be a way that it would have the same origin.

Dwarkesh Patel 1:45:37 Interesting.

David Reich 1:45:38 Um, and sort of so there's a cultural shared thread, this shared tool- toolkit. There's a mitochondrial DNA and Y chromosome th- thread which is, and then there is a, a timing sort of shared thread, which is they're both formed by mixture.

Dwarkesh Patel 1:45:51 Because otherwise you'd have to believe that Neanderthals independently developed Stone Age tools.

David Reich 1:45:56 Yes, which is not i- inconceivable, but like-

Dwarkesh Patel 1:45:58 Yeah

David Reich 1:45:58 ... it's a little bit like believing that farming independently developed in multiple parts of the world.

Dwarkesh Patel 1:46:02 Right. But when it did.

David Reich 1:46:03 It did.

Dwarkesh Patel 1:46:04 Yeah. Um [laughs] .

David Reich 1:46:05 So as I said, this is probably wrong.

Dwarkesh Patel 1:46:07 Um-

David Reich 1:46:07 I'm trying to tell you that like we don't really know the world we live in.

Dwarkesh Patel 1:46:10 Yeah.

David Reich 1:46:11 And like, you know, like this is not obviously wrong. In fact, to me, this is much more plausible-

Dwarkesh Patel 1:46:16 Yeah

David Reich 1:46:16 ... than the model we currently like sort of write down. Like, you know, it's probably wrong, but like it's just much, mu- m- more plausible.

Dwarkesh Patel 1:46:24 Right.

David Reich 1:46:24 It explains many more things. It's no more complicated.

Dwarkesh Patel 1:46:26 Interesting. Um, do, do you want to recapitulate the thing you were saying about the, I thought the analogy to the, uh, Ptolemy and the epicycles was quite interesting.

David Reich 1:46:34 [laughs]

Dwarkesh Patel 1:46:34 Um.

David Reich 1:46:34 Yeah. I mean, you know, like I think that, you know, the model that we've put together collectively about the relationships between archaic and modern humans is sort of accreted over time. There was this, you know, idea that modern humans are distinct and that Neanderthals and Denisovans are like sisters of each other. And then over time we devel- detected additional mixture events like this modern human into Neanderthal, and then this other ones I didn't even talk about, like super divergent lineage going into Denisovans and like all this other stuff. And we still say, oh, the whole genome says Neanderthals and Denisovans are sisters, so that's the truth. Uh, and we've like patched it all together and gotten it all to work, and oh, you look at the mitochondrial DNA and the Y chromosome, and they have this odd pattern, and it's improbable, but we can get that to work if we invoke natural selection, you know, things like this. So, so you patch it all together. You make these ... So a little reminds one of, uh, sort of what happened in the ancient world where, uh, there was this idea that the, uh, sun revolves around the Earth. But it doesn't quite explain the movements of the planets properly, and so in order to get the movements of the planets to work right, uh, you know, the Ptolemy and astronomers would've m- made up these, uh, epicycles, these special like extra rotations and movements to make everything work about right. Uh, and it was such a convoluted model, and then when Copernicus, uh, and colleagues, you know, suggested instead that actually what's happening is everything's revolving around the sun, that it simplified things and made things ever so much simpler. So what w- the situation that was happening is that that as, as sort of, as astronomical information accumulated, it kept being contradictory to the standard model, but it could be made to work by proposing another complication and another complication-

Dwarkesh Patel 1:48:26 Mm-hmm

David Reich 1:48:26 ... and another complication. But you know, this is not like as like fantastic as, you know, proposing that everything revolves around the sun rather than the Earth.

Dwarkesh Patel 1:48:35 Right.

David Reich 1:48:35 But it is much simpler. Uh, and actually it explains many, many things.

Dwarkesh Patel 1:48:39 What, what, what is, um, counterintuitive or unexpected or hard to accept about, uh, this alternative model? Like what, what is the hesitation that people have for adopting this as the-

David Reich 1:48:51 I don't know. I mean, nobody's thinking about this model right now.

Dwarkesh Patel 1:48:53 Huh.

David Reich 1:48:54 So I mean, I don't know. It's just I think that, uh-I don't know. It seems like obviously a very natural model to me.

Dwarkesh Patel 1:49:02 Um, the reason I ask is, so Aristarchus, Ancient Greek, had the heliocentric theory, um, because he had done a bunch of observations about how far the Earth or ha- had deduced how far the Earth is from the Sun and had noticed other things. But it was not, um, adopted because his fellow Athenians were like, "Look, if we believe that the Earth revolves around the Sun, for it to be the case that we don't see relative movement of the stars to the Earth, the only possible explanation is that the stars are so far away that it is just incomprehensible and implausible." And so the heliocentric theory was dismissed. And the reason I... What I'm gonna try and ask is what is the equivalent of like, oh, for this to work, the stars had to be so far away that it's inconceivable, where, like, actually the stars are so far away.

David Reich 1:49:51 Uh-huh.

Dwarkesh Patel 1:49:51 And maybe we should adopt the, the, the implausible implication that this theory gives us.

David Reich 1:49:57 That's a great question. Uh, I think that we have to assume that there's a linkage between the cultural transformations in Africa and Eurasia at this time, and that's sort of not something that the community has really put together with the genetic data.

Dwarkesh Patel 1:50:12 Mm.

David Reich 1:50:13 So, uh, I think that there's this thread in the genetics about substructure in Africans, and then there's this whole world based on ancient DNA, and they've never put, been put together. So you know, the, nobody's put together the extensive, now extensive work on modern human substructure with the now extensive work based on ancient DNA of archaic human relationships to modern humans. And if you put them together, [laughs] you realize they line up in terms of their time, uh, of substructuring. So I think that, I don't know if that's improbable. It seems actually parsimonious to me, but yeah.

Dwarkesh Patel 1:50:46 Yeah. And it also seems significant that different groups of humans at this time were, um, capable of adopting Stone Age technology.

David Reich 1:50:56 Yes.

Dwarkesh Patel 1:50:56 That once one group had figured it out, the genetic difference between different human lineages was not so big that you could not show people how to use stone tools.

David Reich 1:51:05 Well, who knows? I mean, it could be that actually this was genetically driven.

Dwarkesh Patel 1:51:08 Mm.

David Reich 1:51:08 Right? Like, you know, the time to the... And we talked before about the time to the common ancestor of human genes. You know, there's nothing at f- you know, 100,000 years or 150,000 years, but there's a lot at 400,000 or 500,000 years.

Dwarkesh Patel 1:51:20 Yeah.

David Reich 1:51:20 So if, if that's what happens, and you have a mutation that occurs in the Caucasus or, you know, somewhere in the Middle East or Northeast Africa, and there's key genetic mutations that make people able to do this, and then this population expands, you know, and it moves into Europe, it's swamped by local genes, but there could be retention of those genes bec- through selection as it expands. So maybe what you're actually seeing is that actually there are genetic developments. Most of the discussion on this, I point, has been focused on the 50 to 100,000-year event. Uh, and this is like anatomically modern human behavior. But this is like, a lot of my archaeologists think this is an equally, if not more profoundly significant event in many ways. And why is that not the event that we should be talking about?

Dwarkesh Patel 1:52:03 Right. W- And then we know, y- you're talking about how there's no fixed differences between modern humans and the humans 50,000 years ago. Are there any... Do we know if there's any, uh, fixed differences between the people 50,000 years ago and the people 300,000 years ago?

David Reich 1:52:16 I think there are.

Dwarkesh Patel 1:52:17 Other than obviously these interbreedings.

David Reich 1:52:20 Well, I think if this is what we're talking about, which is, like, if you look at the genetic variation going back 300,000 or 400,000 years, then, uh, there are, do begin to be places where all modern humans share common ancestry 300,000 or 400,000 years ago, and that's another way of saying there begin to be fixed differences at that time depth. Um, so that is where you start seeing, uh, evidence for possible fixed differences.

Dwarkesh Patel 1:52:41 Mm.

David Reich 1:52:42 What's basically happening if everybody shares a common ancestor 400,000, 500,000 years ago is there's a single ancestor at that time, and if you compared it to another population, like, you know, these guys, they would descend from a different lineage, so any mutation that occurred ancestral to that single ancestor would be a fixed difference.

Dwarkesh Patel 1:52:57 Yeah.

David Reich 1:52:58 So, so this is the time at which you can begin to see fixed differences.

Dwarkesh Patel 1:53:02 But anatomically modern, cognitively modern humans exist by the beginning of the Middle Stone Age and before were breeding with, uh, this ancient group of Africans or breeding with Neanderthals.

David Reich 1:53:17 Anatomically modern humans occur exactly here. It's the same moment. This is when they occur, the people who, like, have skeletal features like ours, and Neanderthals appear exactly then.

Dwarkesh Patel 1:53:26 Oh.

David Reich 1:53:26 This is when it all happens. So, like, th- this is when we... There is this disconnect between anatomically modern humans in the skeletal record and between f- you know, behaviorally modern humans, which is 50,000 to 100,000 years ago. But anatomically modern humans appear at this time, and actually recognizable Neanderthals appear roughly around this time, too.

Dwarkesh Patel 1:53:44 Interesting. Interesting. But we don't know what exactly happens, if anything, between 200,000 years ago and 50,000 years ago that goes from just anatomical to anatomical mod- modernity-

David Reich 1:53:55 No

Dwarkesh Patel 1:53:55 ... to behavioral modernity.

David Reich 1:53:55 My understanding is no. You know, there begins to be, you know, they're v- busy making Levallois stone tools like Neanderthals for 200,000 years.

Dwarkesh Patel 1:54:02 Oh.

David Reich 1:54:03 Uh, and not more impressive than Neanderthals in any way.

Dwarkesh Patel 1:54:06 Interesting.

David Reich 1:54:06 Um, and in any obvious way, as I understand it. And then there begins to be in the archaeological record a quickening of sort of, you know, behavioral sort of traits, you know, which could be not genetic at all, or it could be genetic. Like, you know, there was, there's lots of arguments about this. Uh, but you know, people are obsessed with, you know, like we were obsessed with intelligence in the, earlier in our conversation, but people are obsessed with art and, you know-

Dwarkesh Patel 1:54:30 Right

David Reich 1:54:30 ... these things that seem important to us. But, like, who knows what's important.

Dwarkesh Patel 1:54:33 Yeah.

David Reich 1:54:34 Um, and yeah.

Dwarkesh Patel 1:54:35 Interesting. Cool. Um, thanks for the digression. [laughs]

David Reich 1:54:41 The work that I've been involved in has consistently shown that I was wrong in my biases coming into the work, and I've really been almost traumatized by this. Like again and again, I've come into a project with some kind of guess about what the data was showing, and then the data doesn't show that. So for example, when I got involved in the Neanderthal Genome Project anal- helping to analyze data, looking at how archaic Neanderthals were related to modern humans, I was part of a group of scientists who had established that non-Africans were a simple subset of African variation, and that there was no evidence at all of Neanderthal interbreeding into the ancestors of modern humans or other archaic interbreeding. Different analyses that I and, and very much more other people had done made it look like non-African variation was just a subset, a small sample of that in Africa, and that could have fully explained the data. And so that when I was involved in analyzing the Neanderthal DNA sequences, what happened was I found this very strong evidence of Neanderthals being more closely related to non-Africans than to Africans, and it was very surprising, and I thought it must be a mistake. I thought it was... I was quite incredulous. I thought it was unlikely to be true because other evidence that had been, uh, uh, that had been found before seemed to point in the other direction. And so I spent several years trying to make these results go away, as did my colleagues, and we just couldn't m- make the results go away. They just kept getting stronger, and this experience working on natural selection was the same. So what we had felt here was that what we were convinced of was that natural selection had been pretty quiescent in our species over the last several hundred thousand years. Therefore, if we look at patterns of variation in non-African people today, uh, or in any people today, we should see not a lot of selection going on. And indeed, the first ancient DNA studies beginning in two thousand and fifteen with this paper that we were involved in with Ian Matheson and colleagues, indeed, these papers seem to show relatively small numbers of genetic positions associated with natural selection. So in two thousand and fifteen, we analyzed data from about two hundred Europeans and Middle Easterners to try to understand frequency changes over time, and we compared those ancient people who were the sources of modern Europeans to people in Europe today, and we looked at frequency differences that were too extreme to be due to chance. And we were very excited to find twelve positions that we were convinced were highly different in frequency between Europeans today and what we would expect based on the history that, that, that we had, we and others had identified was the history relating modern to ancient Europeans. And so some of these were known, and some of these were not known, and this was very exciting. And we hoped that as the numbers of samples would increase and we would get higher resolution to be able to appreciate differences in frequencies over time, we hoped that this would make it possible to detect far more. And what was quite disappointing over the subsequent decade is that that didn't happen. So for example, the largest study of that type in two thousand and twenty-four by a group in Copenhagen analyzed the data, much better data than we had in two thousand and fifteen, and found only twenty-one positions that were highly different in frequency across time. And while that was exciting, it was almost twice as many as we had found in two thousand and fifteen. In a lot of ways it was disappointing 'cause the sample size and data quality had gone up so much, and yet this is all that was found. And so what that suggested is that we might be hitting an asymptote, and we might not be able to get beyond where we currently were, and that this approach to learning about biology sort of which would be v- was very promising in theory might actually not produce a high yield. That maybe in fact, natural selection was quiescent, and in fact, what the reason we're seeing so few changes is that actually there's not been a lot of adaptive directional selection. So that was the situation we found ourselves in until just a, a, a few years ago when we carried out this study in our research group led by Ali Akbari.

Speaker 1:58:42 Mm.

David Reich 1:58:43 So, so what we did is we, uh, deployed a few, uh, innovations or changed, uh, to try to improve our power to detect, uh, natural selection. One of them is we just pumped a lot of data into the system, and so we increased the amount of data by about fourteenfold. Uh, and the main thing that we do in this study is we report data in this study from about ten thousand individuals, uh, with new data. So this is like a very big increase in the amount of data in the literature, uh, and, uh, the total dataset size of ancient individuals distributed over the last eighteen thousand years is about sixteen thousand people. So this is a large dataset. It's much larger than was previously possible, and when you have more data, you can estimate frequency changes with much more subtlety. And the data comes from only one part of the world, uh, which is Europe and the Middle East. Uh, it's not a more important part of the world than other places, but it's the place where maybe seventy or eighty percent of the data in the ancient DNA literature so far comes from due to historical reasons. And it provides us with a natural laboratory where we can see what happens over one place over time as environments change to the genome. It's really interesting to imagine doing this type of analysis in other parts of the world, and the comparative analyses are super important and interesting, but this study right now is about this one place in the world where we have particularly fantastic data. The other thing we did is we developed an entirely new methodology that hadn't been used in this area before, and the methodology is based on a technique that had been developed for finding risk factors for disease, um, in, uh, uh, in, in medical studies. Uh, and, uh, a simple way to explain it is we ask how to predict the genetic type a person has based on its pattern of relatedness to other people. So we'll have a dataset of about sixteen thousand ancient people and twenty-two thousand people if we include the ancient and modern people, and then we look at how closely related each of these twenty-two thousand people are to each other, and we predict the genetic type at each position in the DNA at ten million positions based on the pattern of relatedness to all of the other twenty-two thousand people.And then we ask if, if natural selection blowing the frequency of the mutation in the same direction in all the geographic places and at all times predicts the data a little bit better than just knowing the relatedness to all the other samples in the database. So we're simply asking, the alternative hypothesis is that selection has been blowing in the same direction at all times, and we simply ask if that explains the data better. And that's a s- a dumb assumption, uh, because of course the truth is that natural selection is gonna have changed in frequency over time. But we're just asking the simplest of questions, whether assuming a constant rate of selection explains the data more than not doing so.

Dwarkesh Patel 2:01:25 And ju- just to summarize to make sure I've understood, you're trying to make a model that predicts allele frequency changes over time.

David Reich 2:01:30 Right.

Dwarkesh Patel 2:01:31 And you have two different parts.

David Reich 2:01:32 Right.

Dwarkesh Patel 2:01:32 One part is this, uh, genetic related ne- relatedness matrix, which captures, um, how similar different genomes are to each other, and that should capture, um, the impact of different bottlenecks and of drift and of population admixtures and all those things which affect the entire genome.

David Reich 2:01:50 Correct.

Dwarkesh Patel 2:01:50 And, uh, then you have the separate thing which is like, okay, if we look at specific locations, can we just say that, "Oh, this location has been selected at whatever coefficient over time," um, and if we add some coefficient, it doesn't become easier to predict the allele frequency changes than you would've just seen from this other artifact which is only predicted, which is just looking at like, oh, if you look at the whole genome, are these guys in the same, you know, uh, are, have they gone through the same bottlenecks? Have they gone through the same drift, et cetera?

David Reich 2:02:21 That's precisely right.

Dwarkesh Patel 2:02:22 Okay. Um, okay, so what have you learned?

David Reich 2:02:26 So, uh, when we analyzed the data this way, we looked at 10 million positions in the DNA, uh, that, uh, in, in these 22,000 people, 16,000 of them were ancient. And we looked to see if there was more change in this consistent direction over time than you would expect by chance. And when we analyzed the data, we s- found many, many hundreds of places in the DNA that were changing too much, uh, over time in too consistent a way to be explained by chance. Now, there's a bit of a statistical problem in figuring out how many there are, because they're so densely packed that they're close to each other and they're interfering with each other. But when you try to piece them out and say, "Let's look at, let's count them only one in each place in the DNA and blo- blank out the others," we find at least about 479 positions that are all independently pushing in the same way. Uh, those positions are 99% confident that they're real. By another criteria of more than 50% confident that they're real, we think that about 3,800 positions are all pushing in the same direction. So this is like a crazy number of results given that in our work previously and other people's work, there were at most a couple of dozen-

Dwarkesh Patel 2:03:33 Mm

David Reich 2:03:33 ... discoveries coming from a single scan. So when we got this result, we were very surprised. We were, thought it must be wrong, and we spent the next couple of years trying to make the results go away, but they just got, kept getting stronger. And so what we were trying to do is to look for some kind of independent type of evidence to tell us whether these positions were real. And we stumbled on something really e- uh, powerful for this purpose that had not been used in this way before, and it relied on the fact that we had very large numbers of discoveries, like many hundreds of discoveries or even thousands. Uh, and so what we did is we took a completely independent data set, which was the corpus of genome-wide association studies. So these are studies that people have carried out in hundreds of thousands of people, looking for whether particular genetic mutations are more common in people with high blood pressure with, than with low blood pres- blood pressure or something like this. So we took the UK Biobank, which is about 500,000 people from Great Britain who have been measured for hundreds and hundreds of traits. The whole genomes of all these peoples have been sequenced. And for each of these traits, we could look whether each of these 10 million positions are connected to this trait in some way, in a convincing way. So in 10 million positions, about 15%, about 1.5 million pos- positions in the DNA are predictive of at least one of these several hundred traits. So then we could ask a question, f- is our natural selection signal or statistic, is it related to whether a ve- a mutation causes a high blood pressure or some other trait? So we slid our statistic for natural selection from upward, you know, to a value of one, a value of two, a value of three, a value of four, a value of five. And as we did that, the enrichment for genetic mutations that affect traits got higher and higher. So whereas it was only 15% when we didn't use our selection statistic, when we, uh, required the selection statistic to be above about five, uh, there was about a fivefold enrichment for mutations that cause traits.

Dwarkesh Patel 2:05:29 Oh, sorry, what is a selection statistic?

David Reich 2:05:31 This is the statistic we use to measure whether a mutation is changing over time s- uh, significantly, uh, uh, in a non-zero way.

Dwarkesh Patel 2:05:41 Got it.

David Reich 2:05:41 So it's, it, it can be approximately thought of as a normally distributed statistic, a Gaussian statistic, uh, which is the number of standard deviations the statistical value is away from zero, where zero is the pos- is no natural selection.

Dwarkesh Patel 2:05:57 Got it.

David Reich 2:05:57 Uh, it's not exactly that, but it's close to that. And so if the statistic is above five, we see about a fivefold enrichment in mutations that affect a trait.

Dwarkesh Patel 2:06:07 Interesting.

David Reich 2:06:07 And so instead of 15% of the, uh, mutations that are, uh, th- at random affecting the trait, it's like 60 or 70 that are, are, are, are affecting the trait when we slide our statistic upward. And this is providing completely independent evidence that these sites are real, and as you slide above five, there's no more enrichment. So our interpretation of these results, uh, and that we were able to validate and show that these interpretations made sense using computer simulations of our process, our interpretation of this result is that once you slide the statistic above five, essentially all the signals of natural selection are real.

Dwarkesh Patel 2:06:45 Um, okay. And so just to make sure I understood, you're saying, look, in order to figure out what alleles are, been under selection, your model, uh-assign some statistics saying, "Oh, in order to explain why this allele has a specific frequency, we're gonna give it a selection statistic." Um, and independently, you know, we run these studies on modern populations where we say, "If you look at height or eye color, intelligence, whatever trait, what are the parts of the genome that are correlated with that trait?" And the higher statistic you give it, uh, in your study in order to explain allele frequency changes over time as a result of selection, the more probable it is that that region in the genome is associated with traits, uh, that have, like, some functional thing that we can measure.

David Reich 2:07:30 That's exactly right.

Dwarkesh Patel 2:07:32 Okay.

David Reich 2:07:32 And this is, like, a brilliant idea that Ali had, and it's, it's... it really abandons the traditional approach of assigning statistical significance to mutations that cause, uh, a trait, because we're just using an external piece of information, the p- the correlation to traits, uh, measured in a completely different way to read off the probability mutations are real. So we can ask how much enrichment for real signal is there given a particular selection statistic, and if it's halfway enriched to the plateau, the correct interpretation of that we're able to show is that 50% of the mutations are, are, are really selected. If it's three-quarters of the way toward the plateau, there's a three-quarters probability that the mutation is real. If there's a 99% of the way to the plateau, there's a 99% probability that's real.

Dwarkesh Patel 2:08:20 Mm.

David Reich 2:08:20 So that gives us a calibrated estimate of the probability that a particular position is really under natural selection. A, a major concern here is that actually what we're seeing is not that these mutations are really under selection, but rather that both association to a disease and, uh, our selection signal are due to some third thing that's causing both of them, which is a type of selection which is not what we're after, not selection to adapt to new environments, but what's called background selection, selection against newly arising bad mutations that are removed from the population that tend to be concentrated in genes. Genes are also the parts of the genome that tend to be associated to traits. And so this common process is causing both the enrichment for trait signals and is also causing the enrichment for selection signals-

Dwarkesh Patel 2:09:13 Yeah

David Reich 2:09:13 ... that we're observing. That's the concern. We were super concerned about this. So what we did is we repeated this enrichment analysis in slices of the DNA that all were affected to the same extent by background selection, by this reign of slightly bad mutations, and we get exactly the same pattern. We also repeated this experiment in just using mutations of the same frequencies, uh, uh, because there's different statistical power to detect these signals at different frequencies, and we see the same pattern where above a value of the selection statistic of around five, we get this plateau.

Dwarkesh Patel 2:09:49 So the thing that changed that allowed you to increase the amount of, uh, sequences you're generating by two orders of magnitude is just the statistical method you're using to identify which part is human? Or what exactly changed in 2014 and since then?

David Reich 2:10:01 So there's been a whole series of improvements. Um, I think that the, uh, the, the, the big ones have been the huge drop in sequencing cost-

Dwarkesh Patel 2:10:09 Yeah

David Reich 2:10:09 ... which made it possible to generate ancient DNA in the first place. So the drop in cost has been a millionfold, uh, since the late 2000s, uh, and another maybe one to two orders of magnitude from 2010 to today.

Dwarkesh Patel 2:10:21 Mm.

David Reich 2:10:21 Um, so that's one big change. Uh, another change has been in solution enrichment. So it's been this way of taking a sample that has very small percentages of human DNA but then suddenly creating, uh, a pro- a process that will mean that the great majority of the sequences that one's analyzing will be useful for analyses.

Dwarkesh Patel 2:10:39 Mm.

David Reich 2:10:39 And so the approach that we used was we took the DNA samples that we had, most of which were very low percentages of human DNA, less than 10%, often less than 1%, which is such a low proportion that it's prohibitively expensive to sequence them and to just brute force sequencing them given the technology that we had available at the time. And so we took these, uh, samples and washed them over a artificially synthesized set of short DNA fragments that targeted positions of the DNA that we were interested in analyzing. So this is more than a million positions that are highly variable in people, and we picked many of these to be biologically interesting. We had a whole set of known biological targets that affected traits in genome-wide association studies, which is the way that people look to see if there's particular genetic variants in modern people that cause, uh, that have particular impacts in phe- phenotypes and traits. And so what we did is we, uh, had this artificially synthesized set of, uh, uh, DNA fragments that we washed our ancient sample over, and it bound the parts of the DNA that we targeted, and the resulting sequence that we generated was very enriched for the parts of the genome that were informative about history. And even though only 10% or 1% of the DNA was human, it ended up that a very large fraction was from the parts of the genome that we were interested in.

Dwarkesh Patel 2:12:00 Mm.

David Reich 2:12:00 Uh, and it became economically efficient to do it.

Dwarkesh Patel 2:12:02 And, and sorry, what, what was the other 99% of the DNA?

David Reich 2:12:05 It's mostly microbial. So it's from bacteria and fungi that, uh, colonize, uh, a person's body after they die.

Dwarkesh Patel 2:12:13 Mm.

David Reich 2:12:13 Uh, depending on how they die, there'll be more or less of these bacteria and fungi. And so when you typically sequence DNA from a person, they'll just, it'll just be full of, of microbial sequence. Uh, sometimes the microbial sequence is very interesting, so it might be pathogens that, that, that, that a person died of. So there's, for example, uh, amazing, amazing work, uh, about, for ex- different plagues of malaria and Black Death and hepatitis B and so on that have been obtained from the sequences of these pathogens in people's teeth and other parts of their body-

Dwarkesh Patel 2:12:45 Mm

David Reich 2:12:45 ... when they died. Um, but we're focusing here on the human DNA. And, uh, so what we did is we, uh, this changed the amount of data that was possible to produce from tens per year to hundreds per year, and then we further roboticized and industrialized the process so that there were many hundreds or even thousands per year. And so just in our laboratory, we've been generating genome-scale data from, uh, more than 5,000 individuals per year. I know this is true also of several other laboratories in the world now. And this huge jump in data, this sort of semi-exponential or even super exponential jump in some cases, has made it possible to ask and answer questions. So while the f- we're, we're only on the order of 10 genome sequences, uh, from humans, uh, in 2010, there, this year it's passed more than 20,000 reported sequences. So there's several orders of magnitude increase, and the questions we were able to ask in 2014 are just not the same as the ones we can ask today.

Dwarkesh Patel 2:13:45 Yeah. Awesome. Excellent. David, thanks for your time.

David Reich 2:13:48 Thank you. Thank you, Dwarkesh.