The Joe Walker Podcast - Peter Turchin — Why Societies Fall Apart (And Why the US May Be Next)

Episode Date: August 30, 2023

Peter Turchin is a complexity scientist and one of the founders of cliodynamics — a new, cross-disciplinary field that applies mathematics and big data to test historical theories. Full transcript available at: jnwpod.com.See omnystudio.com/listener for privacy information.

Hello and welcome back to the show. Can we have a science of history? My guest thinks that we can. Peter Turchin is a complexity scientist who studies the history of large-scale societies. He's one of the more original thinkers I've encountered in the last few years, and I've referenced his concepts like elite overproduction often. Let me give you a couple of minutes of context on Peter and his ideas before we jump into the conversation.

So Peter is one of the founders of a young field called Clio Dynamics. In fact, Peter himself coined the term Clio Dynamics about 20 years ago. Clio is the Greek muse of history, dynamics, the science of change. Peter was originally a mathematical biologist before entering the social sciences, and he contends that we should test historical theories just like we test scientific ones. For example, it he contends that we should test historical theories just like we test scientific ones. For example, it's not satisfactory that we have roughly 200 explanations for the fall of Rome. We need to test them against the empirical data. Even better, can we find theories that describe the dynamics of complex human societies in general? Peter thinks that we

can. Even if the course of history is chaotic, he still thinks studying the dynamics of past societies can yield empirical regularities, patterns that we may want to influence in our own society. Of the many historical patterns that clear dynamicists purvey, the most consequential one, or at least the one that's the focus of this conversation, is structural demographic theory. Structural demographic theory made Peter famous a couple of years ago, but before I explain why, let me briefly outline what it is. Longtime listeners of the podcast may recall structural demographic theory from my interview with its founding father, Jack Goldstone, back in 2021. The essence of structural demographic theory was proposed by Goldstone all the way back in 1991,

but in the decades since, Peter Turchin has taken it forward, translating it into dynamical models expressed both as differential equations and agent-based simulations. In simple terms, Peter's refinement to structural demographic theory suggests that societies cycle through phases of integration marked by harmony and cooperation and disintegration marked by instability and political violence. No complex society has been spared from a disintegrative phase. But what causes this social disintegration? What are the red flashing lights that warn us of impending political instability? Peter likes to quote Arnold Toynbee that great empires die not by murder, but by suicide.

If we exclude external geopolitical factors, then the internal drivers of political instability are threefold, popular immiseration, overproduction of elites, and state weakness, with the most important driver being overproduction of elites. In disintegrative periods, Peter has found, collective political violence occurs roughly every 50 years. So why did this theory propel Peter, once a somewhat obscure academic, and I hope he doesn't mind me saying that, into the media spotlight? Well, some years ago, it dawned on him that all the indicators to the United States took an ominous turn in the 1970s, suggesting that 2020 would see an outbreak of political instability. Peter predicted as much in a now well-known Nature article in 2010.

Needless to say, his prediction seems to have been borne out. If you're concerned about the state of American, and for that matter, Western European society, and you enjoy books like Bob Putnam's The Upswing, Angus Deaton and Anne Case's Deaths of Despair and the Future of Capitalism, Piketty's Capital in the 21st Century, Tyler Cowen's The Great Stagnation, then you will probably also enjoy Turchin's work. Indeed, one way of viewing his work is as an attempt to unify these different perspectives under one theoretical framework. I traveled to Connecticut to record this conversation with Peter in person. I hope you enjoy.

Before we start the conversation, a quick notice, I'm doing a cross-promotion with the Clearer Thinking podcast. If you enjoy my podcast, I think you would also like the Clearer Thinking podcast with host Spencer Greenberg. It's a podcast about ideas that matter. I've listened to many of Spencer's episodes over the years. He has captivating intellectual conversations with fascinating guests. Recent guests on the Clearer Thinking podcast include Ilya Sutskova, the co-creator of ChatGPT, famed philosopher Peter Singer, and Reid Hoffman, the co-founder of LinkedIn. Give it a listen. You can find it wherever you get your podcasts. Just search for Clearer Thinking.

Peter Turchin, welcome to the podcast. I'm glad to be here. So Peter, I first encountered your work, I think in 2019, and I thought it provided one of the most compelling explanations of what I was witnessing in the US, albeit from the shores of Australia. And I've also had Jack Goldstone on the podcast in 2021. And I've kept in touch with him since then. I told him that we were doing this today. And then of course, you're the, I guess, the father of Cleo Dynamics. One of them. Yeah, one of them. And Cleo Dynamics is the application of big data and mathematical models to find patterns in history. But it does this in a non-naive way

that draws heavily on complex systems science. And you have a new book out called End Times. Before we discuss that and a bunch of other topics, I wanted to start with this broad question of whether a science of history is possible. So as you know, Karl Popper famously objected to the notion of a science of history. And I think his objection is best expressed in the preface to his book, The Poverty of Historicism, where he presents this neat little syllogism that essentially says, number one, the course of human history is strongly influenced by the growth of knowledge. Number two, we cannot predict by rational or scientific methods the future growth of our scientific knowledge, because if, for example,

someone in the Stone Age predicted the invention of the wheel, then ipso facto, they would just have invented it. And number three, we cannot therefore predict the future course of history. So what do you make of Popper's objection? Well, first of all, future is not predictable to an arbitrary degree of accuracy. We know that. We cannot even predict the weather two weeks from now. And that's a purely physical system which is completely understood how it operates because of what's known as mathematical chaos. So human societies are more complicated, more complex, and therefore accurate prediction in an arbitrary time in the future is impossible. So, for example, the famous foundation series by Isaac Asimov,

it is based at least the first volume before the mule appears on the scene, it is based on what we now understand is impossible to do. All right. But on the other hand, some things are predictable. First of all, we can do scientific prediction. We can extract predictions from different theories and use then what happens in the real world to test theories and reject some in favor

of others. Secondly, some aspects of societal dynamics are more predictable than others. So, in my book, I talk a lot about the structural trends, which are very important because these are the structural trends that undermine resilience of societies to shocks. And therefore, when we have low resilience, high fragility, that's when we expect the outbreaks of violence, including major ones like civil wars and revolutions to happen. But the actual timing of when such outbreaks happen depend very much on what we call triggers. Triggers could be a ruler assassination or a symbolic act like self-immolation, or it could be a bad harvest, a bad climate event.

So those triggers are very hard to predict. Probably they are unpredictable, especially because it depends, when it depends on the free will of a human individual. So we have to keep in mind that some things we can predict because they develop slowly and more or less regularly. Other things are not. And the actual course of history is a combination of those two things. So that's the first thing. But let's now get to objection of Karl Popper.

It is curious that he chose the evolution of technology as his example of why history, the future of human civilization, let's put it this way, is unpredictable, because that turns out to be one of the more predictable aspects of the future. I'll give you two examples. First of all, the Moore's Law. It's just amazing that it just keeps working, you know, many decades after it has been proposed. And Don Farmer, who published together with his colleagues a number of articles on the development of green technologies, for example. Those curves are quite predictable. example, on how military technology developed over the past few thousand years. And it is amenable both to analysis and to there is quite a lot of patterns. All right.

And now a few anecdotes. People tend to think that proposing new scientific explanations is somehow due to an individual genius. And I don't deny that many of those famous scientists, they were quite geniuses. You know, let's say we take the discovery of the laws of motion, or even better, the invention of calculus. So calculus was, in fact, invented by two separate mathematicians. Together, they were almost at the same time. And, in fact, there was a bitter feud between them as to who had the priority. Same thing, discovery. Even a better example is the discovery of genes, of genetics, Mendelian genetics.

Well, Gregor Mendel actually was the true discoverer. But he wrote his paper and he announced his discovery before the field was ready for it. And as a result of it, he was completely forgotten. Nobody knew about him. Until 40 years later, three separate scientists almost simultaneously discovered the gene. So, one of the three scientists who was the rediscoverer of genes, because he couldn't get priority, he dug up Gregor Mendel's article, basically saying, all right,

if I cannot be the one, then none of those guys will either. But the major point I'm making, let me just again step back. So, first of all, in the aggregate, we see that human technology develops in a fairly predictable way. That's one thing. And secondly, at the micro level, many of the discoveries, great scientific discoveries, such as calculus, genes, evolutionary theory by natural selection, they happen to happen at the same time. And that suggests that it is really not the individual genius, it's the collective action action of many scientists and thinkers who prepare the world for the next discovery. Yeah, I think I agree with that premise. Have you ever read Robert Merton's, the article he wrote for the New Scientist magazine in 1961 on this?

No, I don't think so. It's exactly on this question, but he goes through a bunch of anecdotes. It's interesting for why individual genius is kind of overrated in scientific history. And if you actually drill down, a lot of examples turn out to be pairs or groups of people. There is individuals and there is collective action. And so there is no tension really. It's a false dichotomy. Yes, it's a false dichotomy.

But it's also true to say that networks are like the air we breathe. So yeah, I agree with that premise, but what is the conclusion that you want me to infer from those micro examples? I want to... the conclusion that I'm working towards too is that evolution of technology is to a certain degree predictable. Not perfectly, but we can predict it to a certain degree. And we know that technology drives a lot of other historical processes. So, a year ago, we published an article in Science Advances where we looked at why large-scale complex societies evolved in human history. And it turns out that the engine is, the primary engine is between society competition, taking the form of warfare. I have a book called Outer Society, which explains this idea behind it. But what drives the intensification of warfare?

Military technology. And so that turns out to be the most important factor that drove the increase in social scale at which people are organized in states and empires. Okay, got it. So putting the question of the predictability of military technology to one side, because I don't know too much about that, I guess I want to attack your argument on three levels,

your argument around those examples. Please do. Examples of more than one person coming up with a discovery. So firstly, knowing that a technology will emerge is obviously not the same as knowing when it will emerge. And the question of timing involves a lot of contingency. For example, there are many examples, but one is Charles Babbage got pretty close

to inventing universal computing in the 1830s, but then was sort of plagued by interpersonal conflicts and a lack of funding, and so he couldn't really bring it to fruition. Another example, Francis Crick's autobiography mentions the fact that if he and Jim hadn't have discovered the double helix, it probably would have been another two or three years until one of the other competing research groups did. And timing really matters because technology interacts with contemporaneous other technologies as well as social factors in really complex ways.

So even if you have a pretty good handle on what is going to emerge, you don't know when. And that's as much of a problem as not knowing what will emerge. So that's my first rebuttal. Let me address that. Well, first of all, when we look at the evolution of human societies over the timescales of hundreds and thousands of years, what's two or three years? No prediction can be 100% accurate. So making a prediction which is 1% accurate, that's awfully good in my view, or even less than 1%.

That's one thing. Second thing, the Babbage engine is a good example of Gregor Mendel. Essentially he was ahead of his time. It wasn't just because of personal interactions and things like that. We now know that, in principle, his engine could have been built. But it was really beyond the bleeding edge. All right. And so that's why.

And there was, at that point, there was no need for it, right? Because, you know, what would it be used for? So engines, so his engines were perfected really during World War II and after because the computational capacities were needed, you know, to break codes, you codes, to do all kinds of things. And at that point, there was enough infrastructure for them. And also, at that point, the material science advanced to the point. We had vacuum tubes and things like that. So, I think your example, as they say, you, poor water on my meal. Your examples actually help my thesis,

especially if you keep in mind that 100% accuracy is unattainable. Therefore, we should not throw away the results, which give you awfully good accuracy, but not perfect accuracy. Okay, good rebuttals. Okay, what's your second point? So to say the future growth of scientific knowledge is unknowable is an ontological claim. To say it's merely unknown is an epistemic claim. And so let's assume the epistemic claim, which is the claim you're making, is correct.

It still seems to fail due to massive practical issues. Like I just don't know how we would ever make use of it because it would seem to imply you'd have to keep tabs on every proverbial entrepreneur working in their garage around the world. No, and that's the nice thing about Clio Dynamics is that without denying the important role of individuals, we have first focused on their movements at the meso and macro level. So, at the level of not individuals, but cooperating groups or whole societies, actually states, polities. All right? And at that level of aggregation, most of the time, individuals don't make a difference. So, I'll give you an example.

Here, whichever way I vote in the next presidential elections, the state of Connecticut is going to go for the Democratic candidate. And therefore, my action of free will will be completely buffered out, and it will not have any macro effect. On the other hand, if, let's say, Florida becomes the key state in which the decision, the final decision would be made on who wins, right? it, but one individual going out and canvassing neighborhoods, getting 10,000 people to swing their votes from one candidate to another, that could result in a macro-level result. So, what we are talking about, it is known in dynamical systems as sensitive dependence on initial conditions. But even systems which are chaotic, that generate these erratic trajectories from purely internal

causes, they are not a flattering of the butterfly, the proverbial flattering of a butterfly wings, is only going to create a major hurricane if the butterfly is in the right place at the right time. So millions of butterflies would be fluttering whatever they want. That would be no macro event, but one would have an effect. So again, it's the mixture of predictability and unpredictability. And individuals become influential because they happen to be in the right place at the right time. So, Mohamed Bouazizi, the fruit vendor who immolated himself in Tunisia, there are lots of other people who have immolated themselves.

There was a bunch of American veterans who immolated themselves to prevent the Vietnam War in 1965. There was no macro- level effect of them. So, and you don't know ahead of time who is going to have that macro level effect. Got it, okay, so this actually leads nicely onto the question of contingency. I'm gonna leave out my third rebuttal because it's kind of already addressed

by your responses to the first two. It was sort of about computational irreducibility. But actually, before I move to contingency, out of curiosity, do you think the course of history is fundamentally deterministic, even if it's not predictable? No. Okay. But because I believe in free will.

This is a big question. You don't have complete empirical knowledge that free will is not just an illusion. So, this is a religious question. And I choose to believe that we have free will because that makes my life more meaningful and comfortable as a result of that you have. Just as an aside, one of the interesting things I was talking about with Stephen Wolfram was that determinism and free will aren't actually incompatible in his paradigm because basically like the rules by which a system evolves, say technology, are deterministic, but you can't take a shortcut to the outcome using your brains or methods of analysis because they're computationally as sophisticated as the systems that you're observing. So you don't know what's going to happen, but the rules by which the systems evolving

are deterministic. And in that space, I guess you can kind of call that free will. Yeah, well, or it becomes a philosophical question. I'm not a philosopher. I am a scientist. I want to see what are the practical consequences of our beliefs. Now, whether we do have or don't have free will, or whether history is perfectly deterministic or not,

is immaterial. Because even if history was completely deterministic, we would not be able to use that to predict perfectly the state of humanity, you know, hundreds of years in the future, because we know that human societies, it's a chaotic system. It suffers or enjoys the sensitive dependence on initial conditions. And since you cannot measure initial conditions so precisely, just think about what kind of apparatus

you would have to have in order to— Let's give an example using the climate. The reason climate is unpredictable is because we cannot measure precisely the temperatures and pressures across the Earth precisely enough to predict it months ahead. The reason is because your measuring apparatus will be larger than the Earth, and you still won't be able to get the initial conditions. So you're much better off putting your efforts into climate control rather than trying to measure it. Why measure it if you don't want to have rain on this particular day, or you want to have rain,

we have, you know how to make rain. You know, the Russians fly airplanes, and they clear during the May 9th demonstrations. If they want to have clear skies, then they just create a big patch of blue skies. So it's, you know, the physics behind that. And so my major point is that a prediction is overrated. If you're sitting on a condemned row and you know that you're going to be shot to death at crack of dawn, right, you have perfect predictability.

And it's completely useless predictability. You might rather want to know how you can escape that. You want to understand things so that we can actually nudge it or even engineer the outcomes that we want. And essentially, this is the long-term goal of cleo dynamics is to get, we are not there by any stretch of imagination—but we want to get to the point where we can actually use it to engineer better social outcomes than unfavorable outcomes that everybody agrees we don't want to have a civil war.

In the future, we will be able to use something like clear dynamics to prevent such bad outcomes. Yeah, I have a couple of questions just on that, but I'll save them for the end because there's some other context that I think we should bring out first. So a couple of questions on contingency. So as you've said, Peter, clear dynamics focuses on groups, not individuals. And that's not because you don't think contingency is important. It's just, it's difficult to know how to actually model it. But do you think it's in principle possible that you could one day somehow include the effect of remarkable individuals in the theoretical framework of clear dynamics? Or is it just naive to think that a fine-grained theory would ever be possible?

It's an empirical question. And in fact, one of the next steps that we are doing, I can tell you more about the historical databases that we are building. One of them is Crisis GB. So it's a database of past societies sliding into crisis and emerging from them. Now, we are approaching 200 cases, and eventually there will be 300 or more. forces behind collecting large number of case studies is that now we see that the entry into crisis is fairly channelized. It's like a ball rolling down a narrow valley.

There's only one place for the ball to go. But once you get to the cusp of the crisis, the whole bunch of different trajectories open up. So, see, I'm thinking as a dynamical scientist. All right, and so that's where we see a huge variability of outcomes, and that's why we need a lot of examples to, first, what we have done is characterize them statistically

to find out what is the frequency of really bad outcomes, good outcomes, and what's in between. But secondly, the next step that I want to pursue, assuming that I can get funding because this all takes quite a lot of work, is to build into our database the role and characteristics of different leaders. So it seems likely that leaders are important at these cusps. You were talking about this earlier. This is the trajectory divergence region, a small push may result in the trajectory going either to positive or to really catastrophic outcomes. And so, the characteristics of leaders, that's the next

interesting question that you can ask. What are the characteristics of leaders whose decisions lead to good outcomes, and what are characteristics of leaders whose decisions lead to catastrophic outcomes? Now, I don't know if we will find any signal in that data, but that's an empirical question. And we intend to find out. How do you think about the interplay between contingency and broad impersonal forces? So take World War I, for example, and we can quibble over the details of this example, but many historians argue that World War I

was a highly contingent event. And then that contingent event eventually sets the stage for all of these structural forces that lead to, arguably lead to World War II. In a way, you could argue that it's contingency all the way down. So how do you deal with that? Is your answer, again, well, you know, clear dynamics just looks at larger time scales and contingency can't really shape structures over those larger time scales? It can, of course. And so, again, we are back to the question of the limits to predictability. And in a dynamical systems approach, we can incorporate such contingencies in a reasonably straightforward way. So, the contingency itself or the event that has caused the trajectory to turn into a very different direction. It's not predictable, all right? But once that happens,

the trajectory starts running now in a more understandable and predictable way. So this is what you mean by contingency. Contingent on this event, right? So this event itself perhaps? So, this event itself, perhaps, is not predictable. But we can investigate the trajectories contingent on such events that resulted in macro changes. So, that's one thing. But the second thing, here's another metaphor from dynamical systems science that's useful. If you think about systems in chaotic regime, they are typically found on a strange attractor, which could be a very low-dimensional

attractor. So, if you kick the system in one of the sensitive places, then the next peak might disappear, or you know, or vice versa. Instead of not having a peak, you would have a peak, and things like that. So, there will be a macro level event. But the trajectory, after the

trajectory will go back, it will be still on the same strange attractor. So, what you have done, you have maybe delayed, let's say, a breakdown of the political system or advanced it. But you haven't really changed much of anything. This is my interpretation of World War I, is that if that Serbian nationalists didn't shoot Archie Duke, then something else would happen probably in a year, maybe two. Because we know that Germans were really worried about Russia. Russia had a miracle decade from the end of the revolution of 1907. Well, it was only seven years. The economy was growing at unprecedented rates very rapidly, and the German staff was very worried about Russia catching up and therefore they

were getting ready to have a preventive war. And so if Gavrilo Princip didn't assassinate Archdeok, somebody, something else would come along and trigger things. Not to belabor this point, but do you think there's any way in which we can use long-term and average tendencies to predict what will happen in a particular time and place? In a statistical sense, yes. I'll give you an example. For example, people have been very impressed that we had the summer of 2020, the huge riots, lots of people actually getting killed.

And then January 6th of 2021. And now things seem to be quieting down. The elections of 2022 went reasonably without major surprises and things like that. So does it mean that we are over? Here is where we can use the knowledge of statistical patterns to suggest that it is unlikely to be so. Because typically, these periods of political and social turbulence, they tend to last for many years. Sometimes systems collapse, of course, and you have 100 years of fragmentation and things like that.

But typically, the mode is between 10 and 20 years or so in the data that we have examined. And there are some good reasons why. But anyway, right now, just taking that as a statistical result, it means that it is unlikely that our society is so different from previous societies that all the turbulence will be over in just one year. That means that we are likely to see more turbulence during the 2020s. I am particularly worried about 2024. Right.

And so, Just because it's an election year. Because it's an election year? Because it's an election year in America, and we have two candidates who are both now under legal proceedings. Lawfare is going back and forth, and the rhetoric continues to escalate. And judging by previous crisis of previous past societies sliding into

crisis, it takes time. There is some inertia before people become ready to use

violence, start killing other people. And the heating up of rhetoric is a very telltale sign

that this is heating up. Now, I hope that I'm wrong because, you know, I live in this country and I don't want to have a civil war here. I'm too old for those types of things. But unfortunately, the chances are, now we're talking about statistical patterns, chances are that we have a few more years of turbulence ahead of us.

Yeah. And would you ever attach a specific probability to that, or would you just say verbally that it's likely or unlikely? We can. Of course, this would be contingent. So, assuming that our society is not terribly different, let's say, from the previous societies, then here is the probability. We just take the empirical distribution of times, and that gives us an estimate of what is likely to happen to us. In terms of the specific probability? Okay. So, I mean, so many of this crisis were done in seven years,

so many in eight, nine, ten, up to 20, 25, and so on. And so, this gives us an empirical estimate of the probability of the length that our crisis will take to resolve. Okay, some questions about data, big data, or what you call the, you know, the clear dynamic macroscope before we move to structural demographic theory and end times. You mentioned CrisisDB, and that's obviously part of SESHAT,

this incredible database that you and colleagues and a team of research assistants have assembled. So I'd love to ask a couple of questions about that. Firstly, how big is SESHAT? Well, it depends how you measure it. So classical SESHAT, and let me just explain that we started building this database more than 10 years ago. And the first set of questions was to test theories about how did large-scale complex societies evolve? Why does nearly 100% of humanity now live in large-scale societies, which is typical only of the last 5% of our evolutionary history?

All right, so Crisis DB is the next step now to understand, to test theories about why complex societies periodically break down. Now, back to classic SESHAT, we have about 450 societies, and it's spanning the past 10,000 years from quite small-scale societies such as Neolithic cultures all the way to states and great empires and up to 1800 or so. This database is for premodern societies. And for each of those, roughly speaking, 450. And by the way, the number keeps growing. So, we have another 150. So, we will be 600 societies very soon because we are adding that to the database. But anyway, to go back to the original set, for them, we have coded hundreds of variables

of which 160 are well-coded. All right, so multiply 160 by 500 roughly, and you get some idea about how much data records are. So, record is the value of this variable for this society. Now, but each Sashat record is like a pyramid. It has not only values, it also has some other stuff associated with it. So, for example, what's the certainty or uncertainty? Whether there is agreement or disagreement? What are the references? So, altogether, it blows up to hundreds of megabytes of information.

Imagine it can get quite difficult trying to convert historical evidence into digitized data that can then be fed into a clear dynamic model. Are there any stories you could share around that? Well, just to say that it was a process. And it turns out that some variables are easier to code. For example, one variable is, does this society have swords and what metal they are made of? So that turns out to be reasonably easy to determine. We may lack the data because, let's say,

there is no writing and very poor archeology. But at least you know how, if you have data, how we will, you know, for example, if you have enough burials, right, and there are no swords in burials, but other weapons are present, then we can conclude the high degree of probability that they did not have swords.

But other variables are much harder. So we had one of our research projects was on understanding the evolution of moralizing supernatural punishment. So, why did religions like Christianity taught that people get rewarded or punished in the afterlife? Or why did Buddhism teach that how you escape the cycle of, you know, of this terrible life and things like that? So there is a variety of theories. And that turned out to be quite contentious. And our first attempt did not work very well. So we had to essentially go back to the drawing board, redesign the approach,

and now it finally all got published about a year ago. So that's an example where things were quite involved. Just think about it. I mean, how do you code whether a religion is moralizing or not? It's a hard question. You know, it requires a lot of thinking. It requires very close work with experts who really understand those societies. But experts are not enough because each expert, they need to be able to understand what we mean by this. And most of them would not bother reading the definitions. And so that's why a member of the project has to work very closely with an expert to elicit the correct information. Yeah, it got me wondering, how much of a problem is it that labels and conceptual categories can vary across time and cultures. Exactly. From the very beginning, our definitions of variables were designed and then refined in

several cycles in such a way that they could be applicable both to Aztecs in Mexico, Chinese during the Bronze Age, French in the Medieval Ages, in Middle Ages. So, those definitions often had to be rewritten as we encountered new different societies. And then that's why it was so much work because then you had to go back and recode the data that we had already coded using the not so good definition. Right. It's an impressive project. Thanks. Well, this is the last question I had on data. I thought it was really interesting how the creative kind of proxies that you use,

obviously past societies didn't always have big government agencies or private pollsters churning out yearly statistics. And so you have to kind of get creative about how you estimate the variables you're interested in, like violence, population growth and decline, etc. A couple of examples we might just touch on. Roman coin hordes, how do they illustrate population decline? Yeah. So, essentially, some people, some numismaticists, people who study old coins, they noticed that there is a correlation between times of trouble and the number of hoards that you find.

And that makes a lot of sense because coin hoards are typically used as the store of wealth. And then at some point, this wealth, to be useful, has to be dug up and used. So, if a coin hoard was not dug up, that means that something terrible happened to the person who knew where it was buried. So, one possibility is that they just simply got killed. Yeah. Another one is that maybe they were driven into exile or enslaved, right, or something. So all of those are a result of violence, right? And so when we see in one year, you know, 50 hordes, whereas 10 years before there were only two or three, because accidents happen all the time.

Yeah. And so somebody, but when we see, when we make a curve of the frequency of hordes, that those curves trace quite closely the periods of internal violence or catastrophic invasion. So, sometimes external wars, typically external wars, if they happen around the periphery of a large state, they don't generate a huge amount of hordes because there are no armies marauding through. But civil wars are the primary producer of coin hordes.

Right. And it turns out to be a very good quantitative. Because if you think about it, how do you quantify how severe a civil war was? Well, perhaps by the number of people killed. All right. That seems to be a good metric. I mean, it's a horrible metric, but it's good for science. So the number of people who are killed has some kind of a relationship

to how many people who had buried hordes got killed. All right? And so in a relative sense, if the number of hordes increases tenfold, that suggests that there was roughly a tenfold increase in death rate. And that provides us with a quantitative proxy for the severity of civil wars. Yeah, yeah. Another one is, so data on height is a key measure of popular immiseration, which is a concept we'll discuss more generally shortly.

But this is kind of obvious, but can you just explain why height is such an important indicator of biological wellbeing? Yeah, so human height typically gets set by early 20s. And after that, by the way, sadly, we start shrinking. So I'm a little shorter than what I was 40 years ago. Well, you must have been very tall in your early 20s. Well, at the time, yes.

But now, of course, because of acceleration and everything, there are lots of much taller people. Anyway, so there are two growth spurts. The first one is the first five years or so. And the next one is the teenagers, different between males and females. But it turns out that both are important in determining your terminal height. All right, now, the variation between individuals in height is mostly genetic. But if you are looking at a population of the same genetic composition over time, then shrinking heights indicate times of miseration, which could happen

for a variety of reasons, mostly because people often have several reasons together. So, one of them is that people, children and teenagers don't get enough to eat. The second one is that they get sick all the time and because the organism needs energy to fight sickness or they're overworked. So all those measures of immeasuration result in declining population heights. And it is remarkable how sensitive this indicator is. It of course mostly gives us information about general population because the nobility and elites, their heights don't shrink. But then you see sometimes five, seven centimeter difference between nobility and peasants. This is a measure of inequality that you can get from skeletal material.

And by the way, all you have to do is a femur. If you have a femur, that's the big bone in your leg, upper leg, all right, that is closely correlated with overall height, and the femurs have pretty high probability of surviving. So you can estimate how population stature height, average height increased or decreased. Right. So you take the length of the femur, you use a table of correspondences, and then you just like average out the heights of each generation in a particular region.

That's right. Yeah. Yeah. There's this really remarkable fact in your book End Times about how one of the reasons we know why American work is fed so poorly in the 19th century is because the average height of native-born Americans declined by five centimeters. Yeah, exactly. Two inches. Yeah, two inches. Yeah. So another way bones can be used is to measure violence. And why is a high frequency of breaks on the left ulna, also known as the forearm, in skeletons good evidence of violence? Yeah, well, that's because I wish your listeners could see us. I could demonstrate it on you. No kidding. Yeah, well, if somebody, most people are right-handed. And so if somebody hits you with a club, you throw your arms up. And since they are right-handed, they will hit your left forearm.

Right? And so that's why it's a very. The other one is, of course, that is, you know, an arrowhead stuck in bones or just sitting inside your chest cavity, right? Not your, but the person who was killed by it. That's usually a good sign of violence. Exactly, yeah. Okay, so let's talk about structural demographic theory. Now, I guess just to put

this in context, there are many other empirical regularities in history that you've looked at across your body of work. And they're all fascinating. Sadly, we probably won't get time to talk about them all today. But for example's there's also you know besides secular cycles there is um the fact that huge empires tend to rise on step frontiers um that's really interesting there's like the auto catalytic models of religious conversion that's again fascinating but because we're speaking mainly about end times i figured today we'll just focus on on structural demographic those are the things that i talk about in my other books correct just to make sure that yeah there's no false advertisement yeah yeah yeah good point so

could you give a summary of structural demographic theory uh in general and I guess how you've kind of refined the theory yourself? Sure. So the first thing is that large-scale, complex societies, organized states, they've been around for about 5,000 years. And we now have enough data to show that they can experience long periods of internal peace and order. Notice, at the same time, they could be fighting quite fierce wars outside, but we're talking about internal, absence of internal wars.

Often about centuries, sometimes shorter, sometimes longer. But inevitably, such integrative periods, as you call them, they end and they get into end times or disintegrative periods. Why? The most common feature of societies in the pre-crisis period is what you call elite overproduction, the conditions of elite overproduction. So let me unpack that. First of all, who are the elites?

Simply put, small proportion of the population. Like 1% to 2%? 1% to 2% that concentrate social power in their hands. So think about the proverbial 1% here in the United States, all the things a bit complicated, we can get back to that, or the Mandarin class in Imperial China or military nobility in medieval France

and so on and so forth. And this is a very important point that there is no, typically there is no sharp boundary between elites and non-elites. It sort of grades. In the United States, the wealth is the best marker for the elite status. So, you can think about lower-ranked elites in the top 10% of the wealth distribution. Then you have 1%, and then you have 1% of 1%.

And so, obviously, the more wealth you have, the more power you have. And the same thing in the parallel political pyramid. Obviously, as you work your way down from the president to a lowly bureaucrat, the amount of power decreases. So, that's one important thing. But second important thing is in the dynamics. So how are elites reproduced and recruited? Typically, there are always more elite wannabes, in the jargon, elite aspirants, who are vying for a limited number of elite positions. And some competition for such positions is good, all right,

because it beats out better people. But it turns out that as competition becomes too intense, once you have 10, 20, 30 times, well, 2, 3, 4 times as many aspirants as the positions for them, that is a bad sign. So in my book, I use the game of musical chairs, modified musical chairs to explain this. So instead of, so I don't know if you're Australian listeners.

No, we know. Oh yeah, no, right. But so instead of, in the game, you start with 10 musical chairs and 11 contenders, right? But then instead of removing, and one loses.

But then instead of removing a chair, we add to the number of players. So we start with 11, then it's 15, 20, 30, 40. You know, you can imagine, just try to think what would happen in this situation. I predict that within like 10, 15, 20 minutes,

there will be fistfights, right? Because some people will want to break the rules. There's always some break, and that the rule-breaking will spread. And soon enough, you would have violence unless you're playing this game in Canada, because Canadians

don't fight. All right. But... And sorry, the rule-breaking spreads because, like, competition and cooperation are, like like an unstable... It's the outcome. So some competition is good, but too much competition is bad. Because that's what corrodes the rules of the game. Yeah.

Right? Humans are not agents, mathematical agents in game theoretic models who cannot break rules. Right? agents in game theoretic models who cannot break rules. Humans, when they see that they are not getting ahead, they will start breaking rules. Somebody will, and then it spreads. We saw this in real life during the elections of 2016, when there were 17 Republican candidates during the primaries. And one individual was very good at breaking rules and getting ahead in the game.

Everybody actually started—not everybody, most other candidates also started breaking rules, but they were not quite as successful in doing that. Since then—actually, even before then, the rule breaking started to happen because these conditions of elite overproduction, they started developing in the United States about 20 or more years ago. Okay, let's take a digression further down this path of elite overproduction, and then we can come back to structural demographic theory holistically. Okay. So, Peter, elite overproduction is probably the one idea of yours I've referenced most over the years.

And it's like one of those things that once you understand it, you start to see it everywhere. Maybe like more than you should see it, but it just... I see it everywhere, especially because we have it quite strongly developed in the States right now. Yeah, that's for sure. So, it'd be interesting to discuss some specific examples. but quite strongly developed in the States right now. Yeah, that's for sure. So it'd be interesting to discuss some specific examples.

How does a late overproduction predict cancel culture? Right. So in the United States, we have the ruling class is the coalition of wealth holders and credential holders. All right? So, unless you have wealth or become a self-made wealthy person, the route to political office is pretty clear. You want to get a law degree.

All right? But if you don't want to become president, but you just want to escape precarity, for example, get into the top 10%, then you also want an advanced degree. It could be a PhD, medical, doctor, and several others. All right. So as a result of elite war production, we have too many individuals who aspire for getting ahead.

And so they are all trying to get credentials that would increase their chances. Part of this, what we see is that some strategic individuals, but maybe not very nice ones, start thinking ahead, and therefore they want to clear the ranks of competitors a little bit. And so how do you do that? In the old times, and we actually do see this both in the 19th century and in the 17th century crisis, the elite aspirants would have jewels and kill each other using swords, pistols, or whatever. Nowadays, we are more civilized than that, so it's character assassination that works well. So, if you think about it, it's an ugly side of things. But you want to attack both the established elites, so professors, for example, because when a professor is fired, an extra place frees up. But also your competitors.

So, you want to clear the ranks, you know, and increase your own chances. Right. and increase your own chances. And of course, this is not necessarily everybody who does this is consciously following this strategy. First of all, it could be more on a subconscious level. But secondly, once this game starts, once this elite reproduction game goes on, the norms of attacking competitors spread. And so then many people actually might do it in self-defense before they get accused. So this is the dynamic that results in the explosion of such, of cancel culture.

Right. So think about cancel culture is like dueling culture in previous more brutal times. Yeah. So to put it back into the musical chairs metaphor, if I can get someone canceled, that removes them from the game and makes it more likely that I'll get a seat. Exactly.

Could we view the replication crisis in psychology as a consequence of intra-elite competition? But only partly. Partly, this is the way that science advances by critiquing previous approaches that did not work very well. And as a result of that, some of it is normal scientific process. Criticism. In science, it's very important.

Criticism is very important. It's just to be effective at producing good science, you critique ideas, data, methods, but not people. Yeah. ideas, data, methods, but not people. Right now, as a result of this canceling culture, it's spread to attacking people

at homonym attacks, and that's the bad side of these critiques. So the crisis of psychology, it probably would have happened anyway, and of psychology, it probably would have happened anyway, and it had a positive effect on the quality of science. But as long as it would have been kept from ad hominem attacks.

Yeah. Is intra-elite competition fractal? So if the proportion of elite aspirants to elites gets out of control and there's a lot of competition between the 1%, is that also reflected in the 0.1%, the 0.01% and so on? Or is there like some threshold at which the competition kind of ceases? No, and we just saw a great example of that where Elon Musk and Zuckerberg were now, I doubt it will ever come to pass, but they are making serious sounds and noises that they want to fight each other in the cage. So, no, it's like with the turtles all the way down, basically. If that fight does come to pass, who are you putting your money on?

Cleodynamics does not have an insight on this. And it doesn't matter. Because just the fact that they're fighting is a sign of competition heating up. How is the degree of polygamy among elites connected to elite overproduction? Yeah, that's one of the very interesting, very robust results from our analysis. I mentioned that complex societies

go through these integrative phases, which are of variable length. And it turns out that in polygamous societies, the integrative phases are much shorter. Why? 100 years versus 300 years, isn't it? 100 years, that's for the whole thing, the whole cycle.

Oh, sorry. Because it's... So, typically, this is actually a result which was noticed back in the 14th century by the great Arab historian and sociologist. I'm not afraid to name him that way. Ibn Khaldun. Soon noticed that dynasties in Maghreb, North Africa where he lived, tend to last for only three or four generations. That would be 75 to 100 years.

Then they would be replaced by another group coming typically from outside of this state region along the Mediterranean border. So why? The reason is that if you have polygamous elites, that means that they produce children at a much more rapid pace. So think about Bin Laden's, for example, who has like 100 brothers or siblings or whatever. So that's a very powerful engine for driving elite overproduction up very rapidly. Yeah, it's fascinating. It made me wonder, is it in some sense possible

that the Western practice of rich people having less kids has been culturally selected for at the group level because it slows the rate of elite production and so makes those societies more stable? So, in fact, the number of children among the elites of Ant elites, is quite variable. It changes with time, and so this is a separate topic. But certainly, I argue in my work that monogamy spread as a result of cultural selection, not only I.

So people like Joe Hendrick, for example, also make this argument. And the reason is that polygamy generally is associated with negative effects at the society level. First of all, you run much shorter integrative phases, but also there are plenty of other things. In modern societies, we have good data. So, the crime rates, murder rates, for example, they are much higher. In polygamous societies, there are many negative effects. And so, this is what is sometimes known as selection by consequences. Monogamy, as far as we know, monogamy really was invented only once in Mediterranean amongst the Romans and Greeks.

All right. And it spread from there to the rest of the world. Recently, Turkey, for example, about 100 years ago, switched from polygamy to monogamy, even though they stayed a Muslim country. Japan is the same way, China. So all those societies were formerly polyg thought leaders, realized that switching to monogamy makes a society more cohesive, more cooperative, and better to compete against other societies. Right, right. Why are lawyers so dangerous? Well, it turns out that lawyers are the most common profession amongst revolutionaries. Lenin was a lawyer, Castro, Robespierre, Lincoln, Gandhi. Gandhi was not a revolutionary, but he was certainly

a very influential agent of change. So in the United States specifically, as I mentioned earlier, if you want to get into a political office, you want to get a law degree. And by the way, the best law degree apparently is from the Yale Law School. In fact, Yale Law School produces both people who are very successful, but also counter

elites, people, those elite aspirants who turn, who are frustrated and then turn away against- Like Stuart Rhodes. Stuart Rhodes, exactly. The founder and the leader of the Oath Keepers. He got Yale degree and several other populist politicians. All right. So, and the reason is, now, again, taking the case of the United States, you have a horrible overproduction

of lawyers. There are three times as many people getting low degrees as the positions for them. As a result of that, we see a really bizarre distribution of salaries that newly minted lawyers receive. I talk about this in my book, that there is one quarter get really huge hours, close to $200,000. And then more than half get like around between $50,000 and $70,000,

which is not enough to even pay off the debts that you have. And nobody in between. Bimodal. Yeah, it's bimodal. So this means that we know who get those chairs and those who don't get the chairs, all right? And so of those who don't get the chairs, they are ambitious, typically very smart,

well-organized, networked, energetic. The more of them are frustrated in their ambitions, the more they turn to breaking rules and starting revolutionary movements and something similar. Now, things are getting even worse because it turns out that chat GPT-4 already can automate 45% of what lawyers do. So instead of three to one, we soon will have six to one. Yeah, I hadn't made that connection. I hadn't updated on that actually. That's a good point. Lawyers is the second profession after, not office workers, they're secretaries, secretary types, whose work is going to be automated massively.

And as a result, it's going to be bad news unless we figure out where to put that energy in a productive manner. So many reasons to be pessimistic. As a side note, in terms of the significance of Yale Law School, I assume it's just a selection effect where it's the most prestigious law school. So that's where the elite aspirants choose to go. But I was curious whether you had ever actually looked into the law school and its curriculum specifically to see maybe there's like something going on. I have not. Yeah. I don't know why it's Yale

because it could be Princeton and or Columbia or whatever. Yeah. But it, yeah, it's an interesting question, but I don't know the answer to it. Yeah. In 2020, I actually tried to find some data on lawyers in the Australian context,

just in a very amateurish kind of way. I was just curious. Couldn't really find anything, but there was this study that I think Urbis did, where they looked at the number of solicitors practicing in Australia nationally, and that number had increased by about a third between 2011 and 2018, whereas the general population had grown by about half that rate. That's right.

Yeah. Yeah. So that would be interesting. Yeah, same thing we see in England in the run-up to the Civil War of the 17th century. We see the great

overproduction of Oxford, Cambridge graduates, and they had this course of law. Not course of law. They have this third degree, which was basically a law. Yeah, interesting. To get solicitor.

I forget what it's called. And the reason you know that, to bring this back to data, and I think Jack Goldstone wrote about this in Revolution and Rebellion. He's the one who found this factoid. Sitting on your shelf behind me. But you can look at the degrees, like measure the credentials.

There was this explosion in enrollments at Cambridge and Oxford, which reached a peak in 1640, just on the eve of the Great Revolution. And then it declines back to pre-1600 levels by the middle of the 18th century that's right so this is the credential uh the race for credentials yeah and that's that's why it's a good proxy for uh elite overproduction yes just on australia

quickly have you ever looked into any Australian data generally? No. Okay. No, because keep in mind that getting all those studies, that's a lot of work. Yeah. Many months of work or sometimes even years. And so I have just published a blog post where we invite other people to start collecting such data. We published a methodology article for them to use as a guideline for data collection.

Okay. So, last question on elite overproduction, then we can come back to structural demographic theory more broadly. But I was wondering to what extent can a solution be to just increase the elasticity of the supply of elite positions? So you could think about this at an institutional level where, and this already exists to an extent, but the number of seats in parliament kind of just mechanically, or Congress mechanically increases with population size. Maybe we want to change the ratio or something so that they're even more elastic. Or you could think about it at a technological level. So we could create

outlets for elite frustration. So one example might be social media. And Tyler Cowen argued in one of his earlier books, What Price Fame, that fame remains positive sum at its current margins. So you could let more and more elites just get famous and for quite some time it won't become a zero-sum competition. What do you think about that idea? Well, yeah, keep in mind that people who are following the credential route, many of them don't necessarily want to become president and prime minister. They just want to get out of precarity. So, one way to choke off that supply is to get rid of immiseration. This is something that we want to talk next, I believe. Because the majority of population in the United States,

their well-being has been declining. That's one of the push factors that people want to get the credentials. And as a result of that, so many people now go into college that the college premium has been shrinking. And now it's essentially zero. All right. But there are many other things. So, for example, I'm very partial to historians.

I want to have more historians around. They may not like Clio Dynamics, but that's fine because just by being historians, they're churning out all the data that you want. So, why don't we take like half,

cut in half the horrendous budget for the military that we have in the United States, right? It was nearly a trillion dollars. And give some, even one-tenth part of that savings to just hire historians to give them stipends or something. So, all you have to do is publish good work. Hopefully more numbers, right? For us, but whatever. You know, something like that. Or, you know, maybe Elon Musk is right that we need to go to the planets and still provide an outlet for some ambitious people to, you know, to apply their energies elsewhere.

So in principle, once we start thinking about it, we don't want to increase the number of senators or something like that. That number should be really set by what is the optimum number for governing a country. But what we do want, we want to provide outlets for the energies of young people to have meaningful life and to make meaningful change,

positive change. And that is one of the reasons why we have so much difficulties is because there is, you know, we have, our societies have failed to expand the opportunities for bright, energetic, and ambitious people to apply themselves. Right. to apply themselves. It doesn't have to be that they would get more power, right? Just that could be a meaning in life could be achieved in other ways.

Yeah, that's interesting. Have you heard of the effective altruism movement? Yeah. That seems to be an outlet for very talented people to seek meaning and status within a certain community that doesn't necessarily rely on wealth or income. Yeah, actually, that just raises a more general question, which is what kind of cultural or social innovations could we create to provide that outlet?

So structural demographic theory strongly relies on the iron law of oligarchy. Yeah, let's talk about that a little bit, because I want to tie to the question of why... Or should we do popular emiseration? Yeah, but I can do it. I can wrap it in one sort of package. So the question is that, obviously, elite reproduction is something that develops at some times, but not others, right?

Because we have those integrative periods. So the question is, why? Why does elite overproduction develop? Well, the reason is that, let me just compress the long story into just a set of theses. Once societies run for several generations enjoying internal peace and order, the elites, the ruling class, tends to assume that that's an automatic thing, right? It does not need to be nurtured. And they are tempted to reconfigure the economy in ways which would work not for everybody's benefit, but for their own benefit.

And they can do it because they have power. So, this is the iron law of oligarchy. This has three bad consequences. First of all, this results in immiseration because you call it the wealth pump. It's the perverse wealth pump that takes from the poor and gives it to the rich. All right? And there are many ways to do it. But, for example, in the United States, by not increasing the minimum wage, by taking away the power of workers to organize and bargain with employers. So this is – and also by decreasing taxes on themselves. That's how they turned the wealth pump in the States in the 1970s.

All right. But this is a typical thing. This happens in medieval France, for example, or Rome, and so on and so forth. All right. So, then, first of all, this creates immiseration, the quality of life for the majority of population declines, and that drives their discontent and what you call mass mobilization potential. So that's one force undermining stability. Secondly, it results in overproduction of people with wealth. And many of those decide to go into the political arena. And so now you have the game of aspirant chairs

because in the United States, for example, the number of decamillionaires, people with $10 million or more of wealth, increased tenfold over the past 40 years. And so that created many more aspirants for positions in politics, such as Donald Trump, of course, but also Michael Bloomberg, or the failed ones like Steve Forbes, for example, and many more. And some of them run themselves and others run candidates. So we have overcrowding.

So that's the second problem. increasing immiseration, we now create another pump that essentially induces ambitious and energetic people from the immiserated class to try to get out of it. Right. Which drives the credential revolution because that's how you get out. And so that creates overproduction of people seeking credentials. To escape. Right. And so, as a result of that, we have overproduction of the wealthy people, overproduction of credentials, and they are the ones who eventually bring an end time to their societies. So this is how the wealth pump, immiseration, and overproduction, that's how they're connected

at the dynamical level. Yes. So I guess one of the key observations in that model is that crises aren't caused by the popular masses revolting, they're caused by the counter-elites who then kind of mobilize and co-opt the masses. And is the reason that the masses don't initiate revolutions

that they are, I guess, like less talented than the elites? Or is it simply that because it's a larger group, it makes collective action difficult, if not impossible? So it's organization. Why do we need elites at all, by the way? Because human society in order to function properly needs organization. That's why we are organized as states or in the business as firms and so on and so forth.

Now, the commoners are not organized. Think about the Jacquerie, you know, that very bloody peasant rebellion in France in the 14th century. They would happily have a revolution and overthrow nobles. In fact, they killed quite a lot of them. But then, as soon as the first organized and well-armed group of knights appeared on the horizon, they just throw them down and armor and weapons and things like that. And it's the same thing nowadays.

The elites, by definition, because social power means the capacity to organize. And that's why the without when elites are united in the state is strong, popular uprisings are happen, but they are very ineffective, and there is out a lot of bloodshed for the peasants themselves. Yeah. I'm curious about narratives that elites use to justify and defend popular immiseration to the workers themselves. So if the narrative used in the post-1970 period in a word was meritocracy, like the idea that, you know, hey hey don't get envious or resentful just work hard and you can be like us too so if that if that period used meritocracy as a narrative what what was the narrative during the first gilded age or at other points during disintegrative

phases have you are there any examples you Sure. Details of the ideologies change, but the end result is the same. So in the Gilded Age, that was social Darwinism, right? Some people were essentially genetically, you know, genetically worthy or, you know, equipped to be leaders and rich and so on and so forth. Before that, it was during the 17th century, it was God, basically, right? In many Protestant versions of the religion, you know, some people were preordained to be successful and others were not.

In the Middle Ages, the nobility said, because I had 10 generations of ancestors, therefore I'm deserving to live better than you. But the end result is obviously the same. It's the elites justifying their inequality, essentially. I see. Okay, so I think I've got about 25 questions left. I'll pick the five best ones and we'll try and get through them.

So in 2010, in this now famous Nature article, you predicted that the next decade is likely to be a period of growing instability in the United States and Western Europe. That prediction played out. Obviously, we had the kind of year from hell in 2020 in America. Question is, if the pandemic hadn't happened, do you think the prediction still would have played out? Possibly.

It would still play out, but the timing could have been delayed. That's the most likely thing. So epidemic was one of those triggers. But on the other hand, remember that those triggers also tend not to – their distribution tends to be much more frequent during the times of trouble. In fact, there is a very close correlation between end times and epidemics. They tend to happen much more likely during those disintegrative periods. Makes sense because people can't cooperate to prevent the spread of...

Typically, the well-being goes down, which makes people more susceptible to disease. Then you have globalizations because wealthy people drive trade and disease moves along the trade routes. So there is a variety of reasons why diseases tend to happen during those periods. I see. So before we move on to, I guess, like what we can do about all of this, is there anything else you'd say on either structural demographic theory generally or the trends that you've witnessed in the US specifically? No, I think let's, yeah, because we have limited time, let's address those questions.

Yeah. So at the beginning of the conversation, you mentioned that you've studied about 300 crises and some have fairly benign endings, some have disastrous endings. Of the kind of more optimistic cases you've looked at, do you know what caused those good endings? And to what extent are those near misses the result of individual agency or kind of heroic leaders versus like maybe they could be the result of structural forces that you just haven't detected yet? Well, it's both. Sometimes, so let's take the Chartist period in the 19th century British Empire. There was definitely some prosocial leaders and there were some antisocial leaders like Duke Wellington,

for example, the general who led British troops at Waterloo. He was a very conservative leader, had a huge amount of power and status because of this. Until he was out of the picture, really no reforms could go forward. So here we have an individual who had a negative effect. But also there are some structural things. The British Empire was huge. So first of all, they shipped millions of people to places like Australia. There was also immigration to North America.

And that relieved the labor oversupply and removed one of the engines driving the wealth pump. Secondly, they also shipped quite a bunch of surplus elites to positions in the empire. But those were all temporary mechanisms. This is sort of work to flatten the curve, if you know what I mean. It gave more time for the elites to put together, get rid of non-cooperating individuals like Wellington to address the deep causes of their problems. Of the crises that ended badly,

how many of those do you think, and you can answer this very roughly, but how many of those could have been averted had the elites at those times understood your theory? Now, this is a difficult question because most of these end times end up badly. So it suggests that in some situations, even people, you know, let's say you put me, you make me the czar in late 16th century in Russia.

Even though I understand now perfectly well what was going wrong, I would be unlikely to be able to do anything because, you know, persuading people that I know what the problem is. Yeah. You know, they would cut my head off before I would get very far.

So my guess is that there were many examples of good pro-social leaders who, in fact, understood at least intuitively the problem, but they just couldn't get enough other people to cooperate with them. And so the whole thing collapsed. I guess there's also this problem of things like hyperbolic discounting where elites can prioritize their short-term material interests over like the long-term risk of going down with the ship. That's right. Have you thought about reflexivity? So you mentioned that you know the the end goal of Kerr Dynamics is to presumably you know, transfer out of the ivory tower and persuade politicians and public policy

to take its ideas seriously, to have a positive influence in the world. So if it is successful, if that does happen, I mean, I guess I can say a couple of ways it could go. Maybe one is that people start, people take the theory seriously. They see like leading indicators for a disintegrative phase, and then they try to preempt it. Or alternatively, maybe they view the model as like somehow inevitable and that like reinforces it. So how do you think about those, how those dynamics feed back into the model?

And how would you actually model those dynamics? Well, we have already a prototype. Oh, wow. Where it's published an article. Okay. Where I run the forward, the trajectories, and we can look at what sort of nudges and changes need to be done. This is a prototype, so it should not be taken seriously, just to indicate where we need

to put more research effort to develop it into a more fully social engineering problem. I'm actually an optimist by nature. This time around, we missed the opportunity to head off the crisis, but I think for the next time the crisis comes around, by that point, I think that we will have much better theory and it will be possible to use it in a way to essentially get rid of those end times. Yeah. Okay. Three final questions. When did you read War and Peace? And was it compulsory reading in the Russian school system? Yeah. But I read it even before.

I actually read it four times. Wow. Yeah. The first time before for the class, then I read it again for enjoyment. And the fourth time I read it more recently when I was writing my book, Ages of Discord and Outer Society. Okay, so to what extent has your view on history

been influenced by Tolstoy? To some degree. More, yeah. To some degree. I don't take everything that he said 100%, but several of his ideas have been quite influential for me. Mainly his idea, which is similar to Isaac Asimov's idea in the foundation series, that you can make a lot of progress understanding the dynamics of societies by ignoring individuals and focusing on a macro level and MISO level dynamics. Right. And then I guess maybe his second idea to influence you is his version of Asabaya.

Asabaya. Asabaya, yeah. Yeah. Who's been your greatest intellectual influence? My father. Tell me about him. He was a physicist by education, but then he also, like myself, or rather me like him,

switched into cybernetics, more essentially fairly rarefied computer science, theoretical computer science. And he was a very remarkable individual, and he had a huge influence on my thinking. Final question. Complexity science applied to history reminds us that the veneer of civilization is thin and that seemingly stable civilizations, governments can kind of collapse overnight. As we kind of think about the American situation, what's your favorite example, or maybe you have a couple from history of revolutions or collapses that happened almost overnight?

Well, they usually don't happen overnight. There is some inertia. People need some time to psych themselves up for violence, at least normal people, not assassins or somebody like that. And so it typically takes days, weeks, sometimes months. But, yeah, probably since we are in the United States, we should think about 1860. In fact, the 1850s was a period when violence kept going up and up. And so we had bloody cancers and several other incidents. And then, and no Americans really believed that what would happen in the next, you know, five years

is that 600,000 people would get killed and a lot of real estate destroyed. And so when in South Carolina they attacked Fort Sumter, they clearly did not think that they would be completely devastated by this thing. This is the law of unintended consequences. All right. And so this is something that we, I agree with you, that complex societies are very fragile. We just don't understand. Most people who don't study history don't understand how fragile they are. Everybody thinks that this time is going to be different. We will not have. In fact, yeah, it's hard for me to imagine civil war in the United States. But it was hard for Americans in the 1850s to imagine civil war.

Just because you can't imagine it doesn't mean it's not going to happen. And I'm not saying that it's 100% going to happen. But the probability is more than zero. Peter Tershkin, I think I've got through about half of my questions. So we'll have to do this again sometime. But this has been such an interesting conversation. Thank you so much. My pleasure. Thanks so much for listening. Two quick things before you go. First, for show notes and the episode transcript, go to my website, jnwpod.com. That's jnwpod.com. And finally, if you think the conversations I'm having are worth

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