Prediction is one of the pleasures of life. Conversation would wither without it. “It won’t last. She’ll dump him in a month.” If you’re wrong, no one will call you on it, because being right or wrong isn’t really the point. The point is that you think he’s not worthy of her, and the prediction is just a way of enhancing your judgment with a pleasant prevision of doom. Unless you’re putting money on it, nothing is at stake except your reputation for wisdom in matters of the heart. If a month goes by and they’re still together, the deadline can be extended without penalty. “She’ll leave him, trust me. It’s only a matter of time.” They get married: “Funny things happen. You never know.” You still weren’t wrong. Either the marriage is a bad one—you erred in the right direction—or you got beaten by a low-probability outcome.

It is the somewhat gratifying lesson of Philip Tetlock’s new book, “Expert Political Judgment: How Good Is It? How Can We Know?” (Princeton; $35), that people who make prediction their business—people who appear as experts on television, get quoted in newspaper articles, advise governments and businesses, and participate in punditry roundtables—are no better than the rest of us. When they’re wrong, they’re rarely held accountable, and they rarely admit it, either. They insist that they were just off on timing, or blindsided by an improbable event, or almost right, or wrong for the right reasons. They have the same repertoire of self-justifications that everyone has, and are no more inclined than anyone else to revise their beliefs about the way the world works, or ought to work, just because they made a mistake. No one is paying you for your gratuitous opinions about other people, but the experts are being paid, and Tetlock claims that the better known and more frequently quoted they are, the less reliable their guesses about the future are likely to be. The accuracy of an expert’s predictions actually has an inverse relationship to his or her self-confidence, renown, and, beyond a certain point, depth of knowledge. People who follow current events by reading the papers and newsmagazines regularly can guess what is likely to happen about as accurately as the specialists whom the papers quote. Our system of expertise is completely inside out: it rewards bad judgments over good ones.

“Expert Political Judgment” is not a work of media criticism. Tetlock is a psychologist—he teaches at Berkeley—and his conclusions are based on a long-term study that he began twenty years ago. He picked two hundred and eighty-four people who made their living “commenting or offering advice on political and economic trends,” and he started asking them to assess the probability that various things would or would not come to pass, both in the areas of the world in which they specialized and in areas about which they were not expert. Would there be a nonviolent end to apartheid in South Africa? Would Gorbachev be ousted in a coup? Would the United States go to war in the Persian Gulf? Would Canada disintegrate? (Many experts believed that it would, on the ground that Quebec would succeed in seceding.) And so on. By the end of the study, in 2003, the experts had made 82,361 forecasts. Tetlock also asked questions designed to determine how they reached their judgments, how they reacted when their predictions proved to be wrong, how they evaluated new information that did not support their views, and how they assessed the probability that rival theories and predictions were accurate.

Tetlock got a statistical handle on his task by putting most of the forecasting questions into a “three possible futures” form. The respondents were asked to rate the probability of three alternative outcomes: the persistence of the status quo, more of something (political freedom, economic growth), or less of something (repression, recession). And he measured his experts on two dimensions: how good they were at guessing probabilities (did all the things they said had an x per cent chance of happening happen x per cent of the time?), and how accurate they were at predicting specific outcomes. The results were unimpressive. On the first scale, the experts performed worse than they would have if they had simply assigned an equal probability to all three outcomes—if they had given each possible future a thirty-three-per-cent chance of occurring. Human beings who spend their lives studying the state of the world, in other words, are poorer forecasters than dart-throwing monkeys, who would have distributed their picks evenly over the three choices.

Tetlock also found that specialists are not significantly more reliable than non-specialists in guessing what is going to happen in the region they study. Knowing a little might make someone a more reliable forecaster, but Tetlock found that knowing a lot can actually make a person less reliable. “We reach the point of diminishing marginal predictive returns for knowledge disconcertingly quickly,” he reports. “In this age of academic hyperspecialization, there is no reason for supposing that contributors to top journals—distinguished political scientists, area study specialists, economists, and so on—are any better than journalists or attentive readers of the New York Times in ‘reading’ emerging situations.” And the more famous the forecaster the more overblown the forecasts. “Experts in demand,” Tetlock says, “were more overconfident than their colleagues who eked out existences far from the limelight.”

People who are not experts in the psychology of expertise are likely (I predict) to find Tetlock’s results a surprise and a matter for concern. For psychologists, though, nothing could be less surprising. “Expert Political Judgment” is just one of more than a hundred studies that have pitted experts against statistical or actuarial formulas, and in almost all of those studies the people either do no better than the formulas or do worse. In one study, college counsellors were given information about a group of high-school students and asked to predict their freshman grades in college. The counsellors had access to test scores, grades, the results of personality and vocational tests, and personal statements from the students, whom they were also permitted to interview. Predictions that were produced by a formula using just test scores and grades were more accurate. There are also many studies showing that expertise and experience do not make someone a better reader of the evidence. In one, data from a test used to diagnose brain damage were given to a group of clinical psychologists and their secretaries. The psychologists’ diagnoses were no better than the secretaries’.

The experts’ trouble in Tetlock’s study is exactly the trouble that all human beings have: we fall in love with our hunches, and we really, really hate to be wrong. Tetlock describes an experiment that he witnessed thirty years ago in a Yale classroom. A rat was put in a T-shaped maze. Food was placed in either the right or the left transept of the T in a random sequence such that, over the long run, the food was on the left sixty per cent of the time and on the right forty per cent. Neither the students nor (needless to say) the rat was told these frequencies. The students were asked to predict on which side of the T the food would appear each time. The rat eventually figured out that the food was on the left side more often than the right, and it therefore nearly always went to the left, scoring roughly sixty per cent—D, but a passing grade. The students looked for patterns of left-right placement, and ended up scoring only fifty-two per cent, an F. The rat, having no reputation to begin with, was not embarrassed about being wrong two out of every five tries. But Yale students, who do have reputations, searched for a hidden order in the sequence. They couldn’t deal with forty-per-cent error, so they ended up with almost fifty-per-cent error.

The expert-prediction game is not much different. When television pundits make predictions, the more ingenious their forecasts the greater their cachet. An arresting new prediction means that the expert has discovered a set of interlocking causes that no one else has spotted, and that could lead to an outcome that the conventional wisdom is ignoring. On shows like “The McLaughlin Group,” these experts never lose their reputations, or their jobs, because long shots are their business. More serious commentators differ from the pundits only in the degree of showmanship. These serious experts—the think tankers and area-studies professors—are not entirely out to entertain, but they are a little out to entertain, and both their status as experts and their appeal as performers require them to predict futures that are not obvious to the viewer. The producer of the show does not want you and me to sit there listening to an expert and thinking, I could have said that. The expert also suffers from knowing too much: the more facts an expert has, the more information is available to be enlisted in support of his or her pet theories, and the more chains of causation he or she can find beguiling. This helps explain why specialists fail to outguess non-specialists. The odds tend to be with the obvious.

Tetlock’s experts were also no different from the rest of us when it came to learning from their mistakes. Most people tend to dismiss new information that doesn’t fit with what they already believe. Tetlock found that his experts used a double standard: they were much tougher in assessing the validity of information that undercut their theory than they were in crediting information that supported it. The same deficiency leads liberals to read only The Nation and conservatives to read only National Review. We are not natural falsificationists: we would rather find more reasons for believing what we already believe than look for reasons that we might be wrong. In the terms of Karl Popper’s famous example, to verify our intuition that all swans are white we look for lots more white swans, when what we should really be looking for is one black swan.