The Filter Bubble - Eli Pariser [77]
After the data has been crunched, the rest is easy. Want to search for two people—say your boyfriend and that overly friendly intern you suspect him of dallying with, or your employee and that executive who’s been trying to woo him away? Easy. Want to build a Facebook-style social graph by looking at who appears most often with whom? A cinch. Want to see which of your coworkers posted profiles on anonymous dating sites—or, for that matter, photos of themselves in various states of undress? Want to see what your new friend used to look like in his drugged out days? Want to find mobsters in the Witness Protection program, or spies in deep cover? The possibilities are nearly limitless.
To be sure, doing face recognition right takes an immense amount of computing power. The tool in Picasa is slow—on my laptop, it crunches for minutes. So for the time being, it may be too expensive to do it well for the whole Web. But face recognition has Moore’s law, one of the most powerful laws in computing, on its side: Every year, as processor speed per dollar doubles, it’ll get twice as cheap to do. Sooner or later, mass face recognition—perhaps even in real time, which would allow for recognition on security and video feeds—will roll out.
Facial recognition is especially significant because it’ll create a kind of privacy discontinuity. We’re used to a public semianonymity—while we know we may be spotted in a club or on the street, it’s unlikely that we will be. But as security-camera and camera-phone pictures become searchable by face, that expectation will slip away. Shops with cameras facing the doors—and aisles—will be able to watch precisely where individual customers wander, what they pick up, and how this correlates with the data already collected about them by firms like Acxiom. And this powerful set of data—where you go and what you do, as indicated by where your face shows up in the bitstream—can be used to provide ever more custom-tailored experiences.
It’s not just people that will be easier than ever to track. It’s also individual objects—what some researchers are calling the “Internet of things.”
As sci-fi author William Gibson once said, “The future is already here—it’s just not very evenly distributed.” It shows up in some places before others. And one of the places this particular aspect of the future has shown up first, oddly enough, is the Coca-Cola Village Amusement Park, a holiday village, theme park, and marketing event that opens seasonally in Israel. Sponsored by Facebook and Coke, the teenagers attending the park in the summer of 2010 were given bracelets containing a tiny piece of circuitry that allowed them to Like real-world objects. Wave the bracelet at the entrance to a ride, for example, and a status update posted to your account testifies that you’re about to embark. Take a picture of your friends with a special camera and wave the bracelet at it, and the photo’s posted with your identity already tagged.
Embedded in each bracelet is a radio-frequency identification (RFID) chip. RFID chips don’t need batteries, and there’s only one way to use them: call-and-response. Provide a little wireless electromagnetic power, and the chip chirps out a unique identifying code. Correlate the code with, say, a Facebook account, and you’re in business. A single chip can cost as little as $.07, and they’ll cost far less in the years to come.
Suddenly it’s possible for businesses to track each individual object they make across the globe. Affix a chip to an individual car part, and you can watch as the part travels to the car factory, gets assembled into a car, and makes its way to the show floor and then someone’s garage. No more inventory shrinkage, no more having to recall whole models of products because of the errors of one factory.
Conversely, RFID provides a framework by which a home could automatically inventory every object inside it—and track which objects are in which