The Filter Bubble - Eli Pariser [38]
In a way, the filter bubble is a prosthetic solution horizon: It provides you with an information environment that’s highly relevant to whatever problem you’re working on. Often, this’ll be highly useful: When you search for “restaurant,” it’s likely that you’re also interested in near synonyms like “bistro” or “café.” But when the problem you’re solving requires the bisociation of ideas that are indirectly related—as when Page applied the logic of academic citation to the problem of Web search—the filter bubble may narrow your vision too much.
What’s more, some of the most important creative breakthroughs are spurred by the introduction of the entirely random ideas that filters are designed to rule out.
The word serendipity originates with the fairy tale “The Three Princes of Serendip,” who are continually setting out in search of one thing and finding another. In what researchers call the evolutionary view of innovation, this element of random chance isn’t just fortuitous, it’s necessary. Innovation requires serendipity.
Since the 1960s, a group of researchers, including Donald Campbell and Dean Simonton, has been pursuing the idea that at a cultural level the process of developing new ideas looks a lot like the process of developing new species. The evolutionary process can be summed up in four words: “Blind variation, selective retention.” Blind variation is the process by which mutations and accidents change genetic code, and it’s blind because it’s chaotic—it’s variation that doesn’t know where it’s going. There’s no intent behind it, nowhere in particular that it’s headed—it’s just the random recombination of genes. Selective retention is the process by which some of the results of blind variation—the offspring—are “retained” while others perish. When problems become acute enough for enough people, the argument goes, the random recombination of ideas in millions of heads will tend to produce a solution. In fact, it’ll tend to produce the same solution in multiple different heads around the same time.
The way we selectively combine ideas isn’t always blind: As Eysenck’s “solution horizon” suggests, we don’t try to solve our problems by combining every single idea with every other idea in our heads. But when it comes to really new ideas, innovation is in fact often blind. Aharon Kantorovich and Yuval Ne’eman are two historians of science whose work focuses on paradigm shifts, like the move from Newtonian to Einsteinian physics. They argue that “normal science”—the day-to-day process of experimentation and prediction—doesn’t benefit much from blind variation, because scientists tend to discard random combinations and strange data.
But in moments of major change, when our whole way of looking at the world shifts and recalibrates, serendipity is often at work. “Blind discovery is a necessary condition for scientific revolution,” they write, for a simple reason: The Einsteins and Copernicuses and Pasteurs of the world often have no idea what they’re looking for. The biggest breakthroughs are sometimes the ones that we least expect.
The filter bubble still offers the opportunity for some serendipity, of course. If you’re interested in football and local politics, you might still see a story about a play that gives you an idea about how to win the mayoral campaign. But overall, there will tend to be fewer random ideas around—that’s part of the point. For a quantified system like a personal filter, it’s nearly impossible to sort the usefully serendipitous and randomly provocative from the just plain irrelevant.
The second way