Australian researchers say they have developed a mathematical model to predict genocide. A Swiss sociologist has sifted through a century of news articles to predict when war will break out — both between and within countries. A Duke University lab builds software that it says can be used to forecast insurgencies. A team assembled by the Holocaust Museum is mining hate speech on Twitter as a way to anticipate outbreaks of political violence: It will be rolled out next year for the elections in Nigeria, which have frequently been marred by violence.
What makes these efforts so striking is that they rely on computing techniques — and sometimes huge amounts of computing power — to mash up all kinds of data, ranging from a country’s defense budget and infant mortality rate to the kinds of words used in news articles and Twitter posts.
None of this has yet produced a perfect crystal ball to foretell mass violence — and for good reason. “Events are rare, data we have is really noisy,” said Jay Ulfelder, a political scientist who is developing a web-based early warning system to forecast mass atrocities. “That makes it a particularly hard forecasting task.”
But social scientists are getting better at anticipating where trouble might start — or as Mr. Ulfelder put it, “assessing risks.” That explains why the United States intelligence community has been exploring the field for years. The government’s Political Instability Task Force, which Mr. Ulfelder helped to run for over a decade, tries to predict which countries are likely to witness civil unrest in the near term. Its data is not public, nor is information on how the government uses its predictions.
Duhigg notes the efforts Target must make not to “spook” customers with obvious behavioral-based targeting. Since the company wanted to target pregnant women who haven’t explicitly notified Target about their pregnancy, they had to use informational camouflage: “With the pregnancy products, though, we learned that some women react badly,” the executive said. “Then we started mixing in all these ads for things we knew pregnant women would never buy, so the baby ads looked random. We’d put an ad for a lawn mower next to diapers. We’d put a coupon for wineglasses next to infant clothes. That way, it looked like all the products were chosen by chance. “And we found out that as long as a pregnant woman thinks she hasn’t been spied on, she’ll use the coupons…. As long as we don’t spook her, it works.” … As long as Target camouflaged how much it knew, as long as the habit felt familiar, the new behavior took hold.
As with political scandal, what’s so bothersome about this less the targeting itself — though that is bad for reasons Turow details, more on that below — but the cover-up. Retailers don’t want transparency in their attempts to manipulate your behavior; they want to control how your habits evolve. They understand that the more you know about their techniques, the less effective they will be. And they try to justify themselves with the idea that they know better than us what we really want and their marketing techniques allow us to get out of our way to indulge ourselves how we really want and become who we really want to be. Thus Duhigg concludes with this quote from Target’s targeting guru: “Just wait. We’ll be sending you coupons for things you want before you even know you want them.” We’re supposed to think that is a good thing. We’re not supposed to think that the company is using the data it has collected on us to shape the possibilities of what we can become, to control the context in which we make our lives and understand ourselves.
Jurgenson coins the term ‘information camouflage’: companies that mine data about us, discern a pattern they can exploit, and then conceal that knowledge by randomizing the torrent of ads and promotions they send our way so they can conceal that they are on to us, since if we knew we’d change our mental filters.