The Filter Bubble - Eli Pariser [14]
But how? In 2004, Google came up with an innovative strategy. It started providing other services, services that required users to log in. Gmail, its hugely popular e-mail service, was one of the first to roll out. The press focused on the ads that ran along Gmail’s sidebar, but it’s unlikely that those ads were the sole motive for launching the service. By getting people to log in, Google got its hands on an enormous pile of data—the hundreds of millions of e-mails Gmail users send and receive each day. And it could cross-reference each user’s e-mail and behavior on the site with the links he or she clicked in the Google search engine. Google Apps—a suite of online word-processing and spreadsheet-creation tools—served double duty: It undercut Microsoft, Google’s sworn enemy, and it provided yet another hook for people to stay logged in and continue sending click signals. All this data allowed Google to accelerate the process of building a theory of identity for each user—what topics each user was interested in, what links each person clicked.
By November 2008, Google had several patents for personalization algorithms—code that could figure out the groups to which an individual belongs and tailor his or her result to suit that group’s preference. The categories Google had in mind were pretty narrow: to illustrate its example in the patent, Google used the example of “all persons interested in collecting ancient shark teeth” and “all persons not interested in collecting ancient shark teeth.” People in the former category who searched for, say, “Great White incisors” would get different results from the latter.
Today, Google monitors every signal about us it can get its hands on. The power of this data can’t be underestimated: If Google sees that I log on first from New York, then from San Francisco, then from New York again, it knows I’m a bicoastal traveler and can adjust its results accordingly. By looking at what browser I use, it can make some guesses about my age and even perhaps my politics.
How much time you take between the moment you enter your query and the moment you click on a result sheds light on your personality. And of course, the terms you search for reveal a tremendous amount about your interests.
Even if you’re not logged in, Google is personalizing your search. The neighborhood—even the block—that you’re logging in from is available to Google, and it says a lot about who you are and what you’re interested in. A query for “Sox” coming from Wall Street is probably shorthand for the financial legislation “Sarbanes Oxley,” while across the Upper Bay in Staten Island it’s probably about baseball.
“People always make the assumption that we’re done with search,” said founder Page in 2009. “That’s very far from the case. We’re probably only 5 percent of the way there. We want to create the ultimate search engine that can understand anything.... Some people could call that artificial intelligence.”
In 2006, at an event called Google Press Day, CEO Eric Schmidt laid out Google’s five-year plan. One day, he said, Google would be able to answer questions such as “Which college should I go to?” “It will be some years before we can at least partially answer those questions. But the eventual outcome is ... that Google can answer a more hypothetical question.”
Facebook Everywhere
Google’s algorithms were unparalleled, but the challenge was to coax users into revealing their tastes and interests. In February 2004, working out of his Harvard dorm room, Mark Zuckerberg came up with an easier approach. Rather than sifting through click signals to figure out what people cared about, the plan behind his creation, Facebook, was to just flat out ask them.
Since he was a college freshman, Zuckerberg had been interested in what he called the “social graph”—the set of each person’s relationships. Feed a computer that data, and it could start to do some pretty interesting