How Not to Be Wrong: The Power of Mathematical Thinking

by Jordan Ellenberg

Then the math starts. Do the terrorists tend to make more status updates per day than the general population, or fewer, or on this metric do they look basically the same? Are there words that appear more frequently in their updates? Bands or teams or products they’re unusually prone or disinclined to like? Putting all this stuff together, you can assign to each user a score,* which represents your best estimate for the probability that the user has ties, or will have ties, to terrorist groups. It’s more or less the same thing Target does when they cross-reference your lotion and vitamin purchases to estimate how likely it is that you’re pregnant. There’s one important difference: pregnancy is very common, while terrorism is very rare. In almost all cases, the estimated probability that a given user would be a terrorist would be very small. So the result of the project wouldn’t be a Minority Report−style precrime center, where Facebook’s panoptic algorithm knows you’re going to do some crime before you do. Think of something much more modest: say, a list of a hundred thousand users about whom Facebook can say, with some degree of confidence, “People drawn from this group are about twice as likely as the typical Facebook user to be terrorists or terrorism supporters.” What would you do if you found out a guy on your block was on that list? Would you call the FBI?