The Curse of “You May Also Like”
Algorithms and “big data” are good at figuring out what we like—and that may kill creativity.
Watson—IBM's supercomputer—is about to start wading through thousands of legal and medical documents to make assessments that no lawyers or academics can (not with so many data to look through, anyway). If the goal is to analyze what has sold in the past and try to predict what, based on all these data points, is likely to sell in the future, Watson could easily expand into music, film, and books.
Alas, such expansion, while benefiting sales, might stall cultural innovation. Would Watson be able to predict—if it were around back then—the rise of the impressionist painting or of the futurist poetry or the new wave cinema? Would it have approved of Stravinsky? Big Data would have probably missed the Dada.
To understand the limits and opportunities of algorithms in the context of artistic creation, we need to understand that the latter usually consists of three elements: discovery, production, and recommendation. Startups like Fuzz target the last element—recommendation—hoping that some would rather be guided by humans than algorithms.
FiveBooks, a smart site for book-lovers, applies a Fuzz-like model to books; here, too, the logic is that humans can outperform the algorithms. Amazon has many great recommendations, but FiveBooks, with its picks from Paul Krugman, Harold Bloom, and Ian McEwan, is in a different league. Recommendation is where human-powered and algorithm-powered recommendations can probably coexist, at least for the foreseeable future, as users find the right balance between the two.
But when it comes to discovery of new talent and the subsequent production of their work, things look much gloomier. After all, recommendation matters only if there's great art to recommend. If that art is selected based on how likely it is to match the success of previous selections and if it's produced based on immediate feedback from the audience, sales might increase, but will anything truly radical emerge out of all this salesmanship?
The early signs are not very encouraging. Last December, the Global Times, China's English-language tabloid, ran a story on the local punk band Bear Warrior, which found an ingenious way to measure the audience response to their songs. Its lead singer is a graduate student majoring in precision instruments at a university in Beijing, so he designed a device—"POGO Thermometer”—that measures the intensity of the audience's dancing through a series of sensors embedded in the floor carpet in the music hall. The signals are then transmitted to a central computer where they are closely analyzed in order to improve future performances.
According to the Global Times, the band found that fans “started moving their bodies when the drums kicked in, and they danced the most energetically when he sang higher notes.” As its lead singer put it, “the data helps us understand how we can improve our performance to make the audience respond to our music like we intend.”
Perhaps, it would help improve their performance, but when did punk music become so nice? Making the audience happy is something for management consultants—not punk musicians!—to obsess about. The Sex Pistols would have only one use for that carpet and, rest assured, it wouldn't involve sensors of any kind. But the Sex Pistols, oblivious to feedback, launched a revolution, while Bear Warrior, at best, would launch a career.
This article arises from Future Tense, a collaboration among Arizona State University, the New America Foundation, and Slate. Future Tense explores the ways emerging technologies affect society, policy, and culture. To read more, visit the Future Tense blog and the Future Tense home page. You can also follow us on Twitter.
Evgeny Morozov a contributing editor at the New Republic and the author of the forthcoming To Save Everything, Click Here: The Folly of Technological Solutionism.