Think Like a Freak

by Steven D. Levitt

Imagine you are a soccer player, a very fine one, and you’ve led your nation to the brink of a World Cup championship. All you must do now is make a single penalty kick. The odds are in your favor: roughly 75 percent of penalty kicks at the elite level are successful. The crowd bellows as you place the ball on the chalked penalty mark. The goal is a mere 12 yards away; it is 8 yards across and 8 feet high. The goalkeeper stares you down. Once the ball rockets off your boot, it will travel toward him at 80 miles per hour. At such a speed, he can ill afford to wait and see where you kick the ball; he must take a guess and fling his body in that direction. If the keeper guesses wrong, your odds rise to about 90 percent.

You must also choose between the left corner and the right. If you are a right-footed kicker, as most players are, going left is your “strong” side. That translates to more power and accuracy—but of course the keeper knows this too. That’s why keepers jump toward the kicker’s left corner 57 percent of the time, and to the right only 41.

keepers jump left 57 percent of the time and right 41 percent—which means they stay in the center only 2 times out of 100. A leaping keeper may of course still stop a ball aimed at the center, but how

often can that happen? If only you could see the data on all penalty kicks taken toward the center of the goal!

Okay, we just happen to have that: a kick toward the center, as risky as it may appear, is seven percentage points more likely t...

While a penalty kick aimed at the center of the goal is significantly more likely to succeed, only 17 percent of kicks are aimed there. Why so few? One reason is that at first glance, aiming center looks like a terrible idea. Kicking the ball straight at the goalkeeper? That just seems unnatural, an obvious violation of

If you follow this selfish incentive—protecting your own reputation by not doing something potentially foolish—you are more likely to kick toward a corner.

If you follow the communal incentive—trying to win the game for your nation even though you risk looking personally foolish—you will kick toward the center.

Sometimes in life, going straight up the middle is the bo...

Incentives are the cornerstone of modern life. And understanding them—or, often, deciphering them—is the key to understanding a problem, and how it might be solved. Knowing what to measure, and how to measure it, can make a complicated world less

The conventional wisdom is often wrong. And a blithe acceptance of it can lead to sloppy, wasteful, or even dangerous outcomes. Correlation does not equal causality.

When two things travel together, it is tempting to assume that one causes the other. Married people, for instance, are demonstrably happier

than single people; does this mean that marriage causes happiness? Not necessarily. The data suggest that happy people are more likely to get married in the first place. As one researcher memorably put i...

A growing body of research suggests that even the smartest people tend to seek out evidence that confirms what they already think, rather than new information that would give them a more robust view of reality.

It’s also tempting to run with a herd. Even on the most important issues of the day, we often adopt the views of our friends, families, and colleagues. (You’ll read more on this in Chapter 6.) On some level, this makes sense: it is easier to fall in line with what your family and friends think than to find new family and friends! But running with the herd means we are quick to embrace the status quo, slow to change our minds, and happy to delegate our thinking.

Because there is so much emotion attached to health care, it can be hard to see that it is, by and large, like any other part of the economy. But under a setup like the U.K.’s, health care is virtually the only part of the economy where individuals can go out and get nearly any service they need and pay close to zero, whether the actual cost of the procedure is $100 or $100,000. What’s wrong with that? When people don’t pay the true cost of something, they tend to consume it inefficiently.

Think of the last time you sat down at an all-you-can-eat restaurant. How likely were you to eat a bit more than normal? The same thing happens if health care is distributed in a similar fashion: people consume more of it than if they were charged the sticker price. This means the “worried well” crowd out the truly sick, wait times increase for everyone, and a massive share of the costs go to the

without much real advantage. This sort of overconsumption can be more easily tolerated when health care is only a small part of the economy. But with health-care costs approaching 10 percent of GDP in the U.K.—and nearly double that in the United Sta...

We tried to make our point with a thought experiment. We suggested to Mr. Cameron that he consider a similar policy in a different arena. What if, for instance, every Briton were also entitled to a free, unlimited, lifetime supply of transportation? That is, what if everyone were allowed to go down to the car dealership...

For most people, it is much harder to say I don’t know. That’s a shame, for until you can admit what you don’t yet know, it’s virtually impossible to learn what you need to.

These most expert of experts—96 percent of them had postgraduate training—“thought they knew more than they knew,” he says. How accurate were their predictions? They weren’t much better than “dart-throwing chimps,” as Tetlock often joked.

“Oh, the monkey-with-a-dartboard comparison, that comes back to haunt me all the time,” he says. “But with respect to how they did relative to, say, a baseline group of Berkeley undergraduates making predictions, they did somewhat better than that. Did they do better than an extrapolation algorithm? No, they did not.” Tetlock’s “extrapolation algorithm” is simply a computer programmed to predict “no change in current situation.” Which, if you think about it, is a computer’s way of saying “I don’t know.” A similar study by a firm called CXO Advisory Group covered more than 6,000 predictions by stock-market experts over several years. It found an overall accuracy rate of 47.4 percent. Again, the dart-throwing chimp likely would have done just as well—and, when you consider investment fees, at a fraction of the cost.

When asked to name the attributes of someone who is particularly bad at predicting, Tetlock needed just one word. “Dogmatism,” he says. That is, an unshakable belief they know something to be true...

have tracked prominent pundits find that they tend to be “massively overconfident,” in Tetlock’s words, even when their predictions prove stone-cold wrong. That is a lethal combination—cocky plus wrong—especially when...

than you ...

Tonight, our guest: Thomas Sargent, Nobel laureate in economics and one of the most-cited economists in the world. Professor Sargent, can you tell me what CD rates will be in two years? SARGENT: No.

And that’s it. As the Ally announcer points out, “If he can’t, no one can”—thus

It isn’t only that we know less than we pretend about the outside world; we don’t even know ourselves all that well. Most people are terrible at the seemingly simple task of assessing their own talents. As two psychologists recently put it in an academic journal: “Despite spending more time with themselves than with any other person, people often have surprisingly poor insight into their skills and abilities.”

Every time we pretend to know something, we are doing the same: protecting our own reputation rather than promoting the collective good.

Incentives can also explain why so many people are willing to predict the future. A huge payoff awaits anyone who makes a big and bold prediction that happens to come true. If you say the stock market will triple within twelve months and it actually does, you will be celebrated for years (and paid well for future predictions). What happens if the market crashes instead? No worries. Your prediction will already be forgotten. Since almost no one has a strong incentive to

keep track of everyone else’s bad predictions, it costs almost nothing to pretend you know what will happen in the future.

“If you’re unhappy and you have something to blame your unhappiness on—if it’s the government, or the economy, or something—then

then that kind of immunizes you against committing suicide,” he says. “It’s when you have no external cause to blame for your unhappiness that suicide becomes more likely. I’ve used this idea to explain why African-Americans have lower suicide rates, why blind people whose sight is restored often become suicidal, and why adolescent suicide rates often rise as their quality of life gets better.”

The key to learning is feedback. It is nearly impossible to learn anything without it.