How We Decide (8 page)

Neurologically impaired patients who were unable to experience any emotions at all—usually because of damaged orbitofrontal cortices—proved incapable of selecting the right cards. While most people made substantial amounts of money during the experiment, these purely rational people often went bankrupt and had to take out "loans" from the experimenter. Because these patients were unable to associate the bad decks with negative feelings—their hands never developed the symptoms of nervousness—they continued to draw equally from all four decks. When the mind is denied the emotional sting of losing, it never figures out how to win.

How do emotions become so accurate? How do they identify the lucrative decks so quickly? The answer returns us to dopamine, the molecular source of our feelings. By playing the Iowa Gambling Task with a person undergoing brain surgery for epilepsy—the patient was given local anesthesia but remained awake during the surgery—scientists at the University of Iowa and Caltech were able to watch the learning process unfold in real time. The scientists discovered that human brain cells are programmed just like TD-Gammon: they generate predictions about what will happen and then measure the difference between their expectations and the actual results. In the Iowa Gambling Task experiment, if a cellular prediction proved false—for example, if the player chose the bad deck—then the dopamine neurons immediately stopped firing. The player experienced a negative emotion and learned not to draw from that deck again. (Disappointment is educational.) However, if the prediction was accurate—if he got rewarded for choosing a lucrative card—then the player felt the pleasure of being correct, and that particular connection was reinforced. As a result, his neurons quickly learned how to make money. They had found the secret to winning the gambling game before the player could understand and explain the solution.

This is a crucial cognitive talent. Dopamine neurons automatically detect the subtle patterns that we would otherwise fail to notice; they assimilate all the data that we can't consciously comprehend. And then, once they come up with a set of refined predictions about how the world works, they translate these predictions into emotions. Let's say, for example, that you're given lots of information about how twenty different stocks have performed over a period of time. (The various share prices are displayed on a ticker tape at the bottom of a television screen, just as they appear on CNBC.) You'll soon discover that you have difficulty remembering all the financial data. If somebody asks you which stocks performed the best, you'll probably be unable to give a good answer. You can't process all the information. However, if you're asked which stocks trigger the best
feelings
—your emotional brain is now being quizzed—you'll suddenly be able to identify the best stocks. According to Tilmann Betsch, the psychologist who performed this clever little experiment, your emotions will "reveal a remarkable degree of sensitivity" to the actual performance of all of the different securities. The investments that rose in value will be associated with the most positive emotions, while the shares that went down in value will trigger a vague sense of unease. These wise yet inexplicable feelings are an essential part of the decision-making process. Even when we think we know nothing, our brains know something. That's what our feelings are trying to tell us.

This doesn't mean that people can coast on these cellular emotions. Dopamine neurons need to be continually trained and retrained, or else their predictive accuracy declines. Trusting one's emotions requires constant vigilance; intelligent intuition is the result of deliberate practice. What Cervantes said about proverbs—"They are short sentences drawn from long experience"—also applies to brain cells, but only if we use them properly.

Consider Bill Robertie. He's one of the only people in the world who's a world-class expert in three different games. (Imagine if Bo Jackson had played in the NBA in addition to the NFL and baseball's major leagues...) Robertie is a chess master and a former winner of the U.S. speed chess championship. He's a widely respected poker expert and best-selling author of several books on Texas hold'em. However, Robertie is best known for his backgammon skills. He has won the World Championship of Backgammon twice (a feat accomplished by only one other person), and is regularly ranked among the top twenty players in the world. In the early 1990s, when Gerald Tesauro was looking for a backgammon expert to compete against TD-Gammon, he chose Robertie. "He wanted the computer to learn from the best," Robertie says. "And I was the best."

Robertie is now in his early sixties, with a shock of graying hair, lidded eyes, and a pair of thick spectacles. He managed to turn a childhood obsession with chess into a lucrative career. When Robertie talks about games, he still speaks with the boyish enthusiasm of someone who can't quite believe that he gets to play for a living. "The first time I competed against TD-Gammon I was incredibly impressed," Robertie says. "It represented a big improvement over any other computer program I'd ever encountered. But I knew that I was still a better player. The next year, however, was a different story. The computer was now a really formidable opponent. It had learned how to play from playing me."

The software program became a backgammon expert by studying its prediction errors. After making a few million mistakes, TD-Gammon was able to join the shortlist of computers, like Deep Blue, that are able to compete with the best human opponents. However, all of these brilliant machines come with a strict limitation: they can each master only one game. TD-Gammon can't play chess, and Deep Blue can't play backgammon. No computer has been able to master poker.

So how did Robertie get so good at such different games? At first glance, chess, backgammon, and poker seem to rely on very different cognitive skills. That's why most backgammon champions tend to play nothing but backgammon; most chess masters don't bother with card games; and most poker players couldn't tell a Latvian Gambit from a French Defense. And yet, Robertie manages to excel in all three domains. According to Robertie, his success has a simple explanation: "I know how to practice," he says. "I know how to make myself better."

In the early 1970s, when Robertie was still just a chess prodigy—he made a living by winning speed chess tournaments—he stumbled upon backgammon. "Right away, I fell in love with the game," he says. "Plus, there was a lot more money in backgammon than speed chess." Robertie bought a book on backgammon strategy, memorized a few opening moves, and then started to play. And play. And play. "You've got to get obsessed," he says. "You've got to reach the point where you're having dreams about the game."

After a few years of intense practice, Robertie had turned himself into one of the best backgammon players in the world. "I knew I was getting good when I could just glance at a board and know what I should do," Robertie says. "The game started to become very much a matter of aesthetics. My decisions increasingly depended on the look of things, so that I could contemplate a move and then see right away if it made my position look better or worse. You know how an art critic can look at a painting and just know if it's a good painting? I was the same way, only my painting was the backgammon board."

But Robertie didn't become a world champion just by playing a lot of backgammon. "It's not the quantity of practice, it's the
quality,
" he says. According to Robertie, the most effective way to get better is to focus on your mistakes. In other words, you need to consciously consider the errors being internalized by your dopamine neurons. After Robertie plays a chess match, or a poker hand, or a backgammon game, he painstakingly reviews what happened. Every decision is critiqued and analyzed. Should he have sent out his queen sooner? Tried to bluff with a pair of sevens? What if he had consolidated his backgammon blots? Even when Robertie wins—and he almost always wins—he insists on searching for his errors, dissecting those decisions that could have been a little bit better. He knows that self-criticism is the secret to self-improvement; negative feedback is the best kind. "That's one of the things I learned from TD-Gammon," Robertie says. "Here was a computer that did nothing but measure what it got wrong. That's all it did. And it was as good as me."

The physicist Niels Bohr once defined an expert as "a person who has made all the mistakes that can be made in a very narrow field." From the perspective of the brain, Bohr was absolutely right. Expertise is simply the wisdom that emerges from cellular error. Mistakes aren't things to be discouraged. On the contrary, they should be cultivated and carefully investigated.

Carol Dweck, a psychologist at Stanford, has spent decades demonstrating that one of the crucial ingredients of successful education is the ability to learn from mistakes. The same strategy that Robertie uses to excel at games is also an essential pedagogic tool. Unfortunately, children are often taught the exact opposite. Instead of praising kids for trying hard, teachers typically praise them for their innate intelligence (being smart). Dweck has shown that this type of encouragement actually backfires, since it leads students to see mistakes as signs of stupidity and not as the building blocks of knowledge. The regrettable outcome is that kids never learn how to learn.

Dweck's most famous study was conducted in twelve different New York City schools and involved more than four hundred fifth-graders. One at a time, the kids were removed from class and given a relatively easy test consisting of nonverbal puzzles. After the child finished the test, the researchers told the student his or her score and provided a single sentence of praise. Half of the kids were praised for their
intelligence.
"You must be smart at this," the researcher said. The other students were praised for their
effort:
"You must have worked really hard."

The students were then allowed to choose between two different subsequent tests. The first choice was described as a more difficult set of puzzles, but the kids were told that they'd learn a lot from attempting it. The other option was an easy test, similar to the test they'd just taken.

When Dweck was designing the experiment, she'd expected the different forms of praise to have a rather modest effect. After all, it was just one sentence. But it soon became clear that the type of compliment given to the fifth-graders dramatically influenced their choice of tests. Of the group of kids that had been praised for their efforts, 90 percent chose the harder set of puzzles. However, of the kids that were praised for their intelligence, most went for the easier test. "When we praise children for their intelligence," Dweck wrote, "we tell them that this is the name of the game: Look smart, don't risk making mistakes."

Dweck's next set of experiments showed how this fear of failure actually inhibited learning. She gave the same fifth-graders yet another test. This test was designed to be extremely difficult—it was originally written for eighth-graders—but Dweck wanted to see how the kids would respond to the challenge. The students who had been praised for their efforts in the initial test worked hard at figuring out the puzzles. "They got very involved," Dweck says. "Many of them remarked, unprovoked, 'This is my favorite test.'" Kids that had initially been praised for their smarts, on the other hand, were easily discouraged. Their inevitable mistakes were seen as signs of failure: perhaps they really weren't smart after all. After taking this difficult test, the two groups of students had to choose between looking at the exams of kids who did worse than them and looking at the exams of those who did better. Students praised for their intelligence almost always chose to bolster their self-esteem by comparing themselves with students who had performed worse on the test. In contrast, kids praised for their hard work were more interested in the higher-scoring exams. They wanted to understand their mistakes, to learn from their errors, to figure out how to do better.

The final round of tests was the same difficulty level as the initial test. Nevertheless, students who'd been praised for their efforts exhibited significant improvement, raising their average score by 30 percent. Because these kids were willing to challenge themselves, even if it meant failing at first, they ended up performing at a much higher level. This result was even more impressive when compared with students who'd been randomly assigned to the "smart" group; they saw their scores drop by an average of nearly 20 percent. The experience of failure had been so discouraging for the "smart" kids that they actually regressed.

The problem with praising kids for their innate intelligence—the "smart" compliment—is that it misrepresents the neural reality of education. It encourages kids to avoid the most useful kind of learning activities, which is learning from mistakes. Unless you experience the unpleasant symptoms of being wrong, your brain will never revise its models. Before your neurons can succeed, they must repeatedly fail. There are no shortcuts for this painstaking process.

This insight doesn't apply only to fifth-graders solving puzzles; it applies to everyone. Over time, the brain's flexible cells become the source of expertise. Although we tend to think of experts as being weighed down by information, their intelligence dependent on a vast amount of explicit knowledge, experts are actually profoundly intuitive. When an expert evaluates a situation, he doesn't systematically compare all the available options or consciously analyze the relevant information. He doesn't rely on elaborate spreadsheets or long lists of pros and cons. Instead, the expert naturally depends on the emotions generated by his dopamine neurons. His prediction errors have been translated into useful knowledge, which allows him to tap into a set of accurate feelings he can't begin to explain.

The best experts embrace this intuitive style of thinking. Bill Robertie makes difficult backgammon decisions by just "looking" at the board. Thanks to his rigorous practice techniques, he's confident that his mind has already internalized the ideal moves. Garry Kasparov, the chess grand master, obsessively studied his past matches, looking for the slightest imperfection, but when it came time to play a chess game, he said he played by instinct, "by smell, by feel." After Herb Stein finishes shooting a soap opera episode, he immediately goes home and reviews the rough cut. "I watch the whole thing," Stein says, "and I just take notes. I'm looking really hard for my mistakes. I pretty much always want to find thirty mistakes, thirty things that I could have done better. If I can't find thirty, then I'm not looking hard enough." These mistakes are usually little things, so minor that nobody else would notice. But Stein knows that the only way to get it right the next time is to study what he got wrong this time. Tom Brady spends hours watching game tape every week, critically looking at each of his passing decisions, but when he's standing in the pocket he knows that he can't hesitate before making a throw. It's not an accident that all of these experts have converged on such a similar method. They have figured out how to take advantage of their mental machinery, to steal as much wisdom as possible from their inevitable errors.