Think Again: The Power of Knowing What You Don't Know by Adam Grant (best e book reader for android txt) 📗

time-bound, with measurable, specific results. Will the current president of Iran still be in office in six months? Which soccer team will win the next World Cup? In the following year, will an individual or a company face criminal charges for an accident involving a self-driving vehicle?

Participants don’t just answer yes or no; they have to give their odds. It’s a systematic way of testing whether they know what they don’t know. They get scored months later on accuracy and calibration—earning points not just for giving the right answer, but also for having the right level of conviction. The best forecasters have confidence in their predictions that come true and doubt in their predictions that prove false.

On November 18, 2015, Jean-Pierre registered a prediction that stunned his opponents. A day earlier, a new question had popped up in an open forecasting tournament: in July 2016, who would win the U.S. Republican presidential primary? The options were Jeb Bush, Ben Carson, Ted Cruz, Carly Fiorina, Marco Rubio, Donald Trump, and none of the above. With eight months to go before the Republican National Convention, Trump was largely seen as a joke. His odds of becoming the Republican nominee were only 6 percent according to Nate Silver, the celebrated statistician behind the website FiveThirtyEight. When Jean-Pierre peered into his crystal ball, though, he decided Trump had a 68 percent chance of winning.

Jean-Pierre didn’t just excel in predicting the results of American events. His Brexit forecasts hovered in the 50 percent range when most of his competitors thought the referendum had little chance of passing. He successfully predicted that the incumbent would lose a presidential election in Senegal, even though the base rates of reelection were extremely high and other forecasters were expecting a decisive win. And he had, in fact, pegged Trump as the favorite long before pundits and pollsters even considered him a viable contender. “It’s striking,” Jean-Pierre wrote early on, back in 2015, that so many forecasters are “still in denial about his chances.”

Based on his performance, Jean-Pierre might be the world’s best election forecaster. His advantage: he thinks like a scientist. He’s passionately dispassionate. At various points in his life, Jean-Pierre has changed his political ideologies and religious beliefs.* He doesn’t come from a polling or statistics background; he’s a military historian, which means he has no stake in the way things have always been done in forecasting. The statisticians were attached to their views about how to aggregate polls. Jean-Pierre paid more attention to factors that were hard to measure and overlooked. For Trump, those included “Mastery at manipulating the media; Name recognition; and A winning issue (i.e., immigration and ‘the wall’).”

Even if forecasting isn’t your hobby, there’s a lot to be learned from studying how forecasters like Jean-Pierre form their opinions. My colleague Phil Tetlock finds that forecasting skill is less a matter of what we know than of how we think. When he and his collaborators studied a host of factors that predict excellence in forecasting, grit and ambition didn’t rise to the top. Neither did intelligence, which came in second. There was another factor that had roughly triple the predictive power of brainpower.

The single most important driver of forecasters’ success was how often they updated their beliefs. The best forecasters went through more rethinking cycles. They had the confident humility to doubt their judgments and the curiosity to discover new information that led them to revise their predictions.

A key question here is how much rethinking is necessary. Although the sweet spot will always vary from one person and situation to the next, the averages can give us a clue. A few years into their tournaments, typical competitors updated their predictions about twice per question. The superforecasters updated their predictions more than four times per question.

Think about how manageable that is. Better judgment doesn’t necessarily require hundreds or even dozens of updates. Just a few more efforts at rethinking can move the needle. It’s also worth noting, though, how unusual that level of rethinking is. How many of us can even remember the last time we admitted being wrong and revised our opinions accordingly? As journalist Kathryn Schulz observes, “Although small amounts of evidence are sufficient to make us draw conclusions, they are seldom sufficient to make us revise them.”

That’s where the best forecasters excelled: they were eager to think again. They saw their opinions more as hunches than as truths—as possibilities to entertain rather than facts to embrace. They questioned ideas before accepting them, and they were willing to keep questioning them even after accepting them. They were constantly seeking new information and better evidence—especially disconfirming evidence.

On Seinfeld, George Costanza famously said, “It’s not a lie if you believe it.” I might add that it doesn’t become the truth just because you believe it. It’s a sign of wisdom to avoid believing every thought that enters your mind. It’s a mark of emotional intelligence to avoid internalizing every feeling that enters your heart.

Ellis Rosen/The New Yorker Collection/The Cartoon Bank

Another of the world’s top forecasters is Kjirste Morrell. She’s obviously bright—she has a doctorate from MIT in mechanical engineering—but her academic and professional experience wasn’t exactly relevant to predicting world events. Her background was in human hip joint mechanics, designing better shoes, and building robotic wheelchairs. When I asked Kjirste what made her so good at forecasting, she replied, “There’s no benefit to me for being wrong for longer. It’s much better if I change my beliefs sooner, and it’s a good feeling to have that sense of a discovery, that surprise—I would think people would enjoy that.”

Kjirste hasn’t just figured out how to erase the pain of being wrong. She’s transformed it into a source of pleasure. She landed there through a form of classical conditioning, like when Pavlov’s dog learned to salivate at the sound of a bell. If being wrong repeatedly leads us to the right answer, the experience of being wrong itself can become joyful.

That doesn’t mean we’ll enjoy it