policies. When leaders rely only on a few to stay in control—as was the case for Leopold in the Congo—their best bet is to make the few fat and happy, even if that means making everyone else miserable. But let’s take this a step further.
Leopold, Mobutu Sese Seko, and Golda Meir were all powerful leaders, but (to state a most obvious but important fact) they were all people, too, and no different from the rest of us. Whether in government or business, we all want to keep our jobs, we all seek advantage in the accumulation of wealth or influence, and we all evaluate our self-interest, often ahead of such lofty ideas as the national interest or notions of corporate well-being.
With this in mind, if we were to turn back the clock, could we not have made some educated predictions that Leopold, the very same man, would behave differently as the head of the Belgian and Congolese states? Could we not have surmised that Mobutu Sese Seko would rule in the fashion that he did? Or that Churchill would lose power when the attention of the British people turned to postwar reconstruction and domestic matters? Or, in a completely different setting, could we see how a corporate partnership’s structure might encourage its members to overlook fraud? And wouldn’t knowing these things ahead of time be of some potential value?
I believe the answer to all of those questions is yes, which brings me to the very purpose of my work and to the principal claim of this book: that it is possible for us to anticipate actions, to predict the future, and, by looking for ways to change incentives, to engineer the future across a stunning range of considerations that involve human decision making. That’s not to say it’s easy, or that it’s a mere matter of anecdote and reflection—there’s hard science, theory, and some mind-bending arithmetic that come into play—but it is possible, and given what we’ve seen when humans in power run amok, whether in chateaus or boardrooms, it’s preferable to letting the chips fall where they may or to saving our better ideas, regrets, and outrage for when they usually appear—that is, when they’re too late.
Who am I that you should care what I think about these big questions? And why in the world should you take me seriously as a predictioneer?
It so happens I’ve been predicting future events for three decades, often in print before the fact, and mostly getting them right. Don’t get me wrong—I’m no soothsayer and I have no patience for crystal ball gazers, astrologers, or even most pundits. In my world, science, not mumbo-jumbo, is the way to anticipate people’s choices and their consequences for altering the future. I use game theory—we’ll talk later about what that means —to do just that for the U.S. government, big corporations, and sometimes ordinary folks too. In fact, I have made hundreds, even thousands of predictions—a great many of them in print, ready to be scrutinized by any naysayer. There is nothing uncanny about my ability to predict. Anyone can learn to use scientific reasoning to do what I do, and I’m going to show you a bit of how to do it right here. But first, let me fill you in a little bit about how I got into the prediction business.
I’m a political science professor at New York University, where I also run the Alexander Hamilton Center for Political Economy. The Center and all of my courses try to teach students how to solve problems with logic and evidence. The idea is to wean them from knee-jerk conclusions based on gut feel, personal opinions, simple linear reasoning, partisan preferences, or ideology. My colleagues at NYU and I are interested in training students to know how to address problems before they go out into the world. We don’t want them shaking things up without much insight into whether they’re helping to make matters better or worse.
Besides being a professor at NYU, I wear two other hats. I’m a senior fellow at the Hoover Institution at Stanford University. There my job is to think about finding solutions to policy problems. That side of my research is about putting the ideas I teach at NYU to good use by writing op-ed columns, articles, and books, some very technical and some, like this one, designed to spread the word. My third hat is as a partner in a small consuiting company, Mesquita & Roundell, LLC. M&R, as we call it, also uses some of the game theory models I’ve designed to advise people in the national security community and also in the private sector.
I didn’t set out to wear these three hats. The opportunity initially fell into my lap back in 1979 when an official at the State Department called me to ask my opinion about a government crisis in India. He wanted to know who was likely to be the next prime minister. At the time I was a professor of political science at the University of Rochester—where the application of game theory to political questions originated—and I had written my Ph.D. thesis at the University of Michigan about winning and losing strategies among India’s opposition parties. So the State Department official was asking me to be a pundit, to use my “expert” knowledge to speculate about the next Indian government.
It happened that I was on a Guggenheim fellowship at the time, working on a book about war. I had just designed a mathematical model for that project, as well as a little computer program to make calculations that were important for solving that model. The computer program provided a way to simulate decision making under stressful circumstances such as sometimes lead to war. It looked at the choices people could make and calculated the probability that they would get what they wanted if they chose one course of action (say, negotiations) or another (like war), weighting the probabilities by an estimate of how much the decision makers valued winning, losing, or intermediate compromise outcomes. Of course, it also recognized that they had to work out how others might respond to the choices they made.
Like every model, it needed data. The State Department’s phone call about India came in just as I was trying to figure out where to get data to feed into my war and peace model. The timing was perfect. The phone call got me thinking that maybe war and peace decisions really aren’t that different from everyday political confrontations. Sure, the stakes are higher—people get killed in wars—but then any politician seeking high office or about to lose high office sees the personal political stakes as pretty darn high. Probably all of us make similar calculations about how to advance our own well-being in any complex situation involving big risks and potentially big rewards, whether that involves politics, business, or daily life.
The State Department was pressing me for an answer and I wanted to help them. I also wanted to see how well my new model worked. I decided to find out whether the model could really be a useful tool to sort out the political infighting in India. Linking that model to Indian politics was a huge “Aha!” moment for me, one that would change the rest of my life.
I grabbed a yellow pad and picked my own brain, putting together the information the model needed. I wrote down a list of everyone I thought would try to influence the selection of India’s next government. For each of those people (political party leaders, members of India’s parliament, and some members of critical state governments) I also wrote down my estimate of how much clout each had, what their preference was between the various plausible candidates for prime minister, and how much they cared about trying to shape that choice. With just one page of my yellow pad filled with numbers, I had all the information the computer program needed to predict what would happen. I plugged those data into my little program and crunched the numbers overnight. When the computing was done the next morning—computers were slow in those days—I pored over the hundred or so pages of calculated values to see what the model’s predictions looked like.
I thought I had personal insight into what was going to happen in India. My “pundit” knowledge had led me to believe that a man named Jagjivan Ram would be the next prime minister. He was a popular and prominent politician who was better liked than his main rivals for the prime minister’s job. I was confident that he was untouchable—truly unbeatable—in the political arena, and not just in the sense of his caste status. He had paid his political dues and it seemed like his time had come. Many other India watchers thought the same thing. Imagine my
