This article arises from Future Tense, a collaboration among Arizona State University, the New America Foundation, and Slate. On Feb. 29, Future Tense will host an event on the Make movement and do-it-yourself innovation in Washington, D.C. For more information and to sign up for the event, please visit the NAF website.
In the summer of 2007, I went to Calgary, Canada, to report on a startup. It was a heady time: Venture capital was plentiful, and the company, Cambrian House, was generating a lot of excitement. The previous year I’d written an article in Wired called “The Rise of Crowdsourcing,” which proclaimed the dawn of a new era: The many would soon do the work of the few; the crowd would display its vast wisdom in every area of human endeavor; the community would replace the company.
In the wake of the article, crowdsourcing became a buzzword and a flood of specious business plans started arriving in my inbox. Cambrian House seemed different. CEO Michael Sikorsky had built a large community of some 5,000 would-be entrepreneurs. Ideas for new software programs were suggested, discussed, then carefully culled through a rigorous voting process. People would cheerfully volunteer to work on the winning projects. Designers would design; coders would code; the biz dev folks would do whatever the hell biz dev people do. They would all be compensated in royalty points, IOUs that could be cashed in once the dough started rolling.
It was a radical rethinking of one of capitalism’s central assumptions—that labor is best organized from the top down, which is to say, by management. “It’s like the dark ages before Newton, when we mistook physics for magic,” Sikorsky told me. “We know there’s magic in crowdsourcing. We know it works. We just don’t know how it works.”
Except that ultimately, it didn’t work. A year after my visit, Cambrian House had failed to bring a single product to market. Crowds might self-organize, it seemed, but they didn’t necessarily do it well. (The company found later success by reinventing itself as Chaordix, which essentially provides a backend computer system for crowdsourcing projects at large companies.)
But the idea of totally reorganizing a labor market from the bottom up remained elusive. Crowdsourcing has ushered in dramatic changes to fields as disparate as graphic design, journalism, and corporate R&D, but it has yet to fundamentally challenge the top-down, command-and-control paradigm of how most of the world does business. Instead, crowdsourcing has become a best practice to accomplish discrete, often rudimentary tasks, such as designing logos or scouring government documents for scandalous malfeasance.
Recently, though, I’ve begun to see glimmers of that old magic in some novel experiments that occupy the nexus where crowdsourcing, games, and big data all meet.
Last year, the prestigious journal Nature Structural and Molecular Biology published an article that revealed the structure of an enzyme used by retroviruses similar to HIV. The achievement was widely viewed as a breakthrough. Who solved the riddle? A bunch of video gamers. Foldit, a novel experiment created by a group of scientists and game designers at the University of Washington, had asked the gamers—some still in middle school and few boasting a background in the sciences, much less microbiology—to determine the how proteins would fold in the enzyme. Within hours, thousands of people were both competing against (and collaborating with) one another. After three weeks, they had succeeded where the microbiologists and the computers had failed. “This is the first example I know of game players solving a long-standing scientific problem,” David Baker, a Foldit co-creator, wrote at the time.
It wasn’t to be the last. Foldit is humming along nicely and in January revealed an accurate model for another highly complex enzyme. Another of Foldit’s co-creators, Adrien Treuille, has gone on to start a similar game, eteRNA, in which gamers create designs for synthetic RNA. Every week eteRNA’s scientists actually create the top-scoring designs in the test tube. “When we can predict protein folding, we’re going to be able to build the equivalent of the airplane inside your body, and do amazing things.”
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