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Flash back to early 2012. How likely is the Assad regime to fall? Arguments against a fall include (1) the regime has well-armed core supporters; (2) it has powerful regional allies. Arguments in favor of a fall include (1) the Syrian army is suffering massive defections; (2) the rebels have some momentum, with fighting reaching the capital. Suppose you weight the strength of these arguments, they feel roughly equal, and you settle on a probability of roughly 50%. But notice what’s missing? The time frame. It obviously matters. To use an extreme illustration, the probability of the regime falling in the next twenty-four hours must be less—likely a lot less—than the probability that it will fall in the next twenty-four months. To put this in Kahneman’s terms, the time frame is the “scope” of the forecast. So we asked one randomly selected group of superforecasters, “How likely is it that the Assad regime will fall in the next three months?” Another group was asked how likely it was in the next six months. We did the same experiment with regular forecasters. Kahneman predicted widespread “scope insensitivity.” Unconsciously, they would do a bait and switch, ducking the hard question that requires calibrating the probability to the time frame and tackling the easier question about the relative weight of the arguments for and against the regime’s downfall. The time frame would make no difference to the final answers, just as it made no difference whether 2,000, 20,000, or 200,000 migratory birds died. Mellers ran several studies and found that, exactly as Kahneman expected, the vast majority of forecasters were scope insensitive. Regular forecasters said there was a 40% chance Assad’s regime would fall over three months and a 41% chance it would fall over six months.
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Philip E. Tetlock (Superforecasting: The Art and Science of Prediction)