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By Root 1050 0

—or spectacular success stories like the rise of Google and Facebook, what is perhaps most striking about them is that virtually nobody seems to have had any idea what was about to happen. In September 2008, for example, even as Lehman Brothers’ collapse was imminent, Treasury and Federal Reserve officials—who arguably had the best information available to anyone in the world—failed to anticipate the devastating freeze in global credit markets that followed. Conversely, in the late 1990s the founders of Google, Sergey Brin and Larry Page, tried to sell their company for $1.6M. Fortunately for them, nobody was interested, because Google went on to attain a market value of over $160 billion, or about 100,000 times what they and everybody else apparently thought it was worth only a few years earlier.5

Results like these seem to show that humans are simply bad at making predictions, but in fact that’s not quite right either. In reality there are all sorts of predictions that we could make very well if we chose to. I would bet, for example, that I could do a pretty good job of forecasting the weather in Santa Fe, New Mexico—in fact, I bet I would be correct more than 80 percent of the time. As impressive as that sounds compared to the lousy record of Tetlock’s experts, however, my ability to predict the weather in Santa Fe is not going to land me a job at the Weather Bureau. The problem is that in Santa Fe it is sunny roughly 300 days a year, so one can be right 300 days out of 365 simply by making the mindless prediction that “tomorrow it will be sunny.” Likewise, predictions that the United States will not go to war with Canada in the next decade or that the sun will continue to rise in the east are also likely to be accurate, but impress no one. The real problem of prediction, in other words, is not that we are universally good or bad at it, but rather that we are bad at distinguishing predictions that we can make reliably from those that we can’t.

LAPLACE’S DEMON

In a way this problem goes all the way back to Newton. Starting from his three laws of motion, along with his universal law of gravitation, Newton was able to derive not only Kepler’s laws of planetary motion but also the timing of the tides, the trajectories of projectiles, and a truly astonishing array of other natural phenomena. It was a singular scientific accomplishment, but it also set an expectation for what could be accomplished by mathematical laws that would prove difficult to match. The movements of the planets, the timing of the tides—these are amazing things to be able to predict. But aside from maybe the vibrations of electrons or the time required for light to travel a certain distance, they are also about the most predictable phenomena in all of nature. And yet, because predicting these movements was among the first problems that scientists and mathematicians set their sights on, and because they met with such stunning success, it was tempting to conclude that everything worked that way. As Newton himself wrote:

If only we could derive the other phenomena of nature from mechanical principles by the same kind of reasoning! For many things lead me to have a suspicion that all phenomena may depend on certain forces by which particles of bodies, by causes not yet known, either are impelled toward one another and cohere in regular figures, or are repelled from one another and recede.6

A century later, the French mathematician and astronomer Pierre-Simon Laplace pushed Newton’s vision to its logical extreme, claiming in effect that Newtonian mechanics had reduced the prediction of the future—even the future of the universe—to a matter of mere computation. Laplace envisioned an “intellect” that knew all the forces that “set nature in motion, and all positions of all items of which nature is composed.” Laplace went on, “for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes.”7

The “intellect” of Laplace’s imagination eventually received a name—“Laplace’s demon”—and it has been lurking around