The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

out of a sample of 20,000 car trips, you’d gotten into just two minor accidents, and gotten to your destination safely the other 19,998 times. Those seem like pretty favorable odds. Why go through the inconvenience of calling a cab in the face of such overwhelming evidence? The problem, of course, is that of those 20,000 car trips, none occurred wh

One of the pervasive risks that we face in the information age, as I wrote in the introduction, is that even if the amount of knowledge in the world is increasing, the gap between what we know and what we think we know may be widening. This syndrome is often associated with very precise-seeming predictions that are not at all accurate.

Financial crises—and most other failures of prediction—stem from this false sense of confidence. Precise forecasts masquerade as accurate ones, and some of us get fooled and double-down our bets. It’s exactly when we think we have overcome the flaws in our judgment that something as powerful as the American economy can be brought to a screeching ha

If the fall of the Soviet empire seemed predictable after the fact, however, almost no mainstream political scientist had seen it coming. The few exceptions were often the subject of ridicule.8 If political scientists couldn’t predict the downfall of the Soviet Union—perhaps the most important event in the latter half of the twentieth century—then

Meanwhile, if the quantity of information is increasing by 2.5 quintillion bytes per day, the amount of useful information almost certainly isn’t. Most of it is just noise, and the noise is increasing faster than the signal.

“The fox knows many little things, but the hedgehog knows one big thing.”

These things aren’t exactly easy—many people get them wrong. But they aren’t hard either, and by doing them you may be able to make predictions 80 percent as reliable as those of the world’s foremost expert. Sometimes, however, it is not so much how good your predictions are in an absolute sense that matters but how good they are relative to the co

Our brains simplify and approximate just as much in everyday life. With experience, the simplifications and approximations will be a useful guide and will constitute our working knowledge.11 But they are not perfect, and we often do not realize how rough they are.

We have big brains, but we live in an incomprehensibly large universe. The virtue in thinking probabilistically is that you will force yourself to stop and smell the data—slow down, and consider the imperfections in your thinking. Over time, you should find that this makes your decision making better.