Free How We Decide by Jonah Lehrer

traditional approaches is that these new programs find the optimal solutions by themselves. Nobody tells the computer how to organize the elevators. Instead, it methodically learns by running trials and focusing on its errors until, after a certain number of

trials, the elevators are running as efficiently as possible. The seemingly inevitable mistakes have disappeared.
    This programming method closely mirrors the activity of dopamine neurons. The brain's cells also measure the mismatch between expectation and outcome. They use their inevitable errors to improve performance; failure is eventually turned into success. Take, for example, an experiment known as the Iowa Gambling Task designed by the neuroscientists Antonio Damasio and Antoine Bechara. The game went as follows: a subject—"the player"—was given four decks of cards, two black and two red, and $2,000 of play money. Each card told the player whether he'd won or lost money. The subject was instructed to turn over a card from one of the four decks and to make as much money as possible.
    But the cards weren't distributed at random. The scientists had rigged the game. Two of the decks were full of high-risk cards. These decks had bigger payouts ($100), but also contained extravagant punishments ($1,250). The other two decks, by comparison, were staid and conservative. Although they had smaller payouts ($50), they rarely punished the player. If the gambler drew only from those two decks, he would come out way ahead.
    At first, the card-selection process was entirely haphazard. There was no reason to favor any specific deck, and so most people sampled from each pile, searching for the most lucrative cards. On average, people had to turn over about fifty cards before they began to draw solely from the profitable decks. It took about eighty cards before the average experimental subject could explain
why
he or she favored those decks. Logic is slow.
    But Damasio wasn't interested in logic; he was interested in emotion. While the gamblers in the experiment were playing the card game, they were hooked up to a machine that measured the electrical conductance of their skin. In general, higher levels of conductance signal nervousness and anxiety. What the scientists found was that after a player had drawn only ten cards, his hand got "nervous" when it reached for the negative decks. Although the subject still had little inkling of which card piles were the most lucrative, his emotions had developed an accurate sense of fear. The emotions knew which decks were dangerous. The subject's feelings figured out the game first.
    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