Hello, and welcome to the Coursera and Princeton University course on Global Systemic Risk. My name is Miguel Centeno. I'm a professor here at Princeton. And I've been working on this project for about the last five or six years. For many, many years, people wondered what were we talking about with global systemic risk? And then as of January 2020, with COVID, people started paying a little bit of attention. But let me try to explain what we mean by global systemic risk, and what we're going to be doing over this course. The first part of the course is pretty traditional lectures, me just talking at you. I'm afraid that there's really—we've done Zoom, we've done lots of things, there's really no other way around this. So you're going to have to get used to my face to a certain extent. The first part of the lectures we're going to talk about the three parts of the title. What do we mean by global, what do we mean by systemic, and what do we mean by risk? So you'll get a sense of what the phenomenon is that we're interested in. In the second part, we're going to look at specific domains where we might see global systemic risk, and we're going to look at trade, finance, epidemiology— and again, I want you to be thinking that there's lots of other possibilities. but these are just three that I know a little bit about, so I feel safe talking about them. And then we're going to finish up with a discussion of what this global systemic risk might lead to. We're going to have a discussion about comparative social collapse. What does it look like in history when we go back a couple thousand years? What are the cases of historical collapse? What are the cases where we might have expected collapse, and it didn't happen? And we're going to analyze that and see how the lessons from the global systemic risk can help us better understand, and one hopes, to avoid social collapse. Another part of the course are going to be these series of expert interviews. They're not going to be folded into the lectures. You will have the option of just watching these on specific sections. And I won't read you all these, but everything from epidemiology, to finance, to ecology, to network flows and queueing theory, to agriculture and water—all these are going to be folks that I've identified as some of the leading experts in the world on this, and they're going to be talking with us, and you'll be able to access these interviews. Again, if you're interested in an area, you can do it. If you're not, you can certainly skip it. So let's start. Why global? What is with this notion of global? And I want to emphasize that we're living with an unprecedented level of aggregation of social space. What do I mean by that? That is, where previously we could look at social spaces—the family, the clan, a village all the way up to a city— Now we really have to understand social phenomena on a global basis. No part is is divorced. We have to understand every single social phenomenon as occurring across the globe simultaneously. And what does that mean? It really means a new social science. One, social science has been basically built on the nation state. We're very good on the social science of particular countries. We might even be good about social science and about some regions. This is much harder. This requires that we have a sense—a continuous sense—of global history, so we can see and we can understand how what happens in one part of the world can affect what happens 3000 miles away. And there's probably no better indication of the aggregation than simple population count. So as you can see, the population of humanity was pretty, pretty standard, all the way to about the 15th century, when we get a small explosion, following the Black Death. And then in the 18th century, it goes up to 600 million, 1800, 990 million. We don't get to our first billion until late in the 19th century. And then notice how quickly it has gone up. Now, I illustrate this because what I want you to think about is the kind of tools or the kind of knowledge or the kinds of concepts that we would use to study the world, let's say at the year zero, okay? That we might be looking at the Roman Empire, we might be looking at the Han Empire in China, et cetera— Are those the same tools that we want to use when we've got a population of 7.7 billion in 2019? All right, so again, think of it as as the world is getting larger, we have to adjust our tools. We have to, in a sense, move sometimes from microscopes all the way to satellite telescopes. Now, this means that autarky is impossible. That is, no part of the world can escape a crisis in some other part. Again, we might have had trouble understanding this, but certainly after January 2020, we clearly understand that everyone is linked. We're all in this together. And even what we might say the bottom billion are linked. Yes, of course, the rich of the world are much more globalized, they're much more dependent on each other for their lifestyle. But even those are the very bottom that even 30 or 40 years ago, might have been pretty self sufficient, these days—because of food aid, for example, or the kinds of changes in agriculture that we've been talking about— that means that even those at the very, very bottom of the resource pyramid on the globe would be affected by any kind of disruption into a global system. Speaking of, why a system? The global system is a set of tightly-coupled interactions that together allow for the continued flow of—and these are just examples—information, money, goods, services, and people. Think about it, and here's a, I believe this is a petroleum refinery, which if you've ever driven by one, you know the complexity of the pipes, or if you've ever been in the heating, an AC ventilation system of a skyscraper, it looks something like this. Well, imagine globalization as the world's plumbing system, just thousands upon thousands of pipes, all flowing stuff, some with money, some with people, some with goods, some with services, some with TV shows, some with music, and they're all flowing simultaneously. Moreover, this is actually—this makes it much simpler than it is, because these pipes are, you know, the standard HVAC pipes, what's in one, or the volume in one, should not affect what's in the other. Think of these almost as plasma flows. Whereas flows down one pipe increase or decrease, that might have an effect on what's going on in the other pipes. So imagine the world as just this open-ended system of this huge plumbing system with all these various flows. And obviously, what goes in, it's going to affect what goes out. As it goes through, it's going to affect those around it. So we're living in the midst of this ever-expanding, and very much dynamic plumbing network. Now, complex systems are a particular kind of systems, complex adaptive systems arise endogenously out of the interactions of components, and have collective behaviors that could not be reduced to those of their components. What does that mean? It means that the system starts producing its own parts. That there is no grand creator, if you will, that has designed the system from scratch. The system, in a sense, through emergent order, through feedback and interaction, produces its own shape. And what's important here is that you can't tell what the system is going to do, you can't tell what the behavior of the system is going to do just by the characteristics of its parts. So you can't reduce it to its simplest part and say, "Well, we know what this is. This is what it's going to do." No, you have to understand how the various parts are interacting in producing, in a sense, a new reality. And these complex interactions create new dynamics that cannot be explained solely by the behavior of their constituents. And let me give you two examples. A sad one, that is a car pileup. Nobody designs a car pileup. A car pileup does not occur with somebody on top directing the cars. No, a car pileup happens as the various cars, each behaving individually, each responding to the other, end up producing this mess. On a much more benign basis, we can look at—and this dates me, I understand— but think of the second side of Abbey Road and the magic that occurs there. Now, if you look at the individual characteristics of George, Paul, Ringo, and John and we could add George Martin here as their producer, a very talented five people, but you would not expect those five people to produce that second side of Abbey Road. Something happened. Something happened inside the Abbey Road Studios that produced this kind of magic, just like something happens on an interstate, okay, with no one intending that can produce this kind of tragedy. Why risk? Well, globalization, as we will see, works pretty well for a lot of things. But it's also led to an increasing emphasis on efficiency in global systems. That is, we try to optimize everything. We want to make sure that every single machine works as well as it possibly could. An example of this is just-in-time inventory. You no longer have a warehouse full of widgets that are going to come in on one side or you're going to produce the car, or whatever it is, using those widgets. Now, those widgets, they're coming in the door just as you need them. That frees all your capital, it frees you all the real estate that you might have in a warehouse, et cetera. Now, this has increased productivity, and it's increased— it would lead into tremendous gains in productivity and profitability. But what it's made it, and again, think about this, as you make something tighter, as you make something better, as you make something operate more on the margins, its fragility is going to increase. And the perfect example of this is a wonderful book, Normal Accidents, published in 1982, by an ex-professor of mine, Charles Perrow, where he talked about the creating of systems, yes, that operated very, very, very well. But as you get them, as you coupled them tighter, and as you make them more complex, accidents become normal. So we've created these very fine machines, but machines that might not be able to last very long, or machines that could be altered by a very, very small perturbation. Systems can often give the appearance of stability, even as they're about to go into chaos, even as there fragility increases. One small drift, one small movement, okay, in a set of simulations can produce very, very different outcomes. So we want to look at the world system, or the global system, as this incredibly elaborate house of cards. And those house of cards look very, very solid. If a little kid or a pet sees the house of cards, they're not going to see how fragile it is. But of course, if you have a child reach into the house of cards, if you have a pet run into it, we'll see how that house of cards come tumbling down. Now, why are we studying all of this? We're studying all this because it's all interconnected, that a failure in one part can lead to failure in the others. This is a chart of the various risks that the world faces. Let me just read you a couple. Extreme weather events, water crises, interstate conflict, unemployment, technological advances, cyber attacks. Now, think of all of these, each one of these is bad enough. A water crisis is bad enough, a cyber attack is bad enough, fraud is bad enough. Now, imagine if they start occurring simultaneously, or much more likely, it they feed into each other. So for example, a failure of national governance might lead to a large scale involuntary migration as people try to escape this. This large involuntary migration might lead to social instability in its neighbors, which could then lead to a state collapse or a crisis. So again, we have to understand these crises, not as occurring isolatedly, they're not isolated geographically. They're not even isolated temporally, and they're certainly not isolated from other domains and other possible crises. Now, the reason why this is important, is because we all live in a newly-globalized world, okay, and we're going to talk about this. And we're going to address—I'm going to start by showing you what globalization is, and then we can see how it's a system and how there may be a risk to it.
