The Filter Bubble - Eli Pariser [10]
And there was another problem: The perfect agent would presumably screen out most or all advertising. But since online commerce was driven by advertising, it seemed unlikely that these companies would roll out agents who would do such violence to their bottom line. It was more likely, Lanier wrote, that these agents would have double loyalties—bribable agents. “It’s not clear who they’re working for.”
It was a clear and plangent plea. But though it stirred up some chatter in online newsgroups, it didn’t persuade the software giants of this early Internet era. They were convinced by Negroponte’s logic: The company that figured out how to sift through the digital haystack for the nuggets of gold would win the future. They could see the attention crash coming, as the information options available to each person rose toward infinity. If you wanted to cash in, you needed to get people to tune in. And in an attention-scarce world, the best way to do that was to provide content that really spoke to each person’s idiosyncratic interests, desires, and needs. In the hallways and data centers of Silicon Valley, there was a new watchword: relevance.
Everyone was rushing to roll out an “intelligent” product. In Redmond, Microsoft released Bob—a whole operating system based on the agent concept, anchored by a strange cartoonish avatar with an uncanny resemblance to Bill Gates. In Cupertino, almost exactly a decade before the iPhone, Apple introduced the Newton, a “personal desktop assistant” whose core selling point was the agent lurking dutifully just under its beige surface.
As it turned out, the new intelligent products bombed. In chat groups and on e-mail lists, there was practically an industry of snark about Bob. Users couldn’t stand it. PC World named it one of the twenty-five worst tech products of all time. And the Apple Newton didn’t do much better: Though the company had invested over $100 million in developing the product, it sold poorly in the first six months of its existence. When you interacted with the intelligent agents of the midnineties, the problem quickly became evident: They just weren’t that smart.
Now, a decade and change later, intelligent agents are still nowhere to be seen. It looks as though Negroponte’s intelligent-agent revolution failed. We don’t wake up and brief an e-butler on our plans and desires for the day.
But that doesn’t mean they don’t exist. They’re just hidden. Personal intelligent agents lie under the surface of every Web site we go to. Every day, they’re getting smarter and more powerful, accumulating more information about who we are and what we’re interested in. As Lanier predicted, the agents don’t work only for us: They also work for software giants like Google, dispatching ads as well as content. Though they may lack Bob’s cartoon face, they steer an increasing proportion of our online activity.
In 1995 the race to provide personal relevance was just beginning. More than perhaps any other factor, it’s this quest that has shaped the Internet we know today.
The John Irving Problem
Jeff Bezos, the CEO of Amazon.com, was one of the first people to realize that you could harness the power of relevance to make a few billion dollars. Starting in 1994, his vision was to transport online bookselling “back to the days of the small bookseller who got to know you very well and would say things like, ‘I know you like John Irving, and guess what, here’s this new author, I think he’s a lot like John Irving,’” he told a biographer. But how to do that on a mass scale? To Bezos, Amazon needed to be “a sort of a small Artificial Intelligence company,” powered by algorithms capable of instantly matching customers and books.
In 1994, as a young computer scientist working for Wall Street firms, Bezos had been hired by a venture capitalist to come up with business ideas for the burgeoning Web space. He worked methodically, making a list of twenty products the team could theoretically sell online—music, clothing,