The Curse of “You May Also Like”: Algorithms and “big data” are good at figuring out what we like—and that may kill creativity.

Of all the startups that launched last year, Fuzz is certainly one of the most intriguing and the most overlooked. Describing itself as a “people-powered radio” that is completely “robot-free,” Fuzz bucks the trend toward ever greater reliance on algorithms in discovering new music. Fuzz celebrates the role played by human DJs—regular users who are invited to upload their own music to the site in order to create and share their own “radio stations.”

The idea—or, perhaps, hope—behind Fuzz is that human curators can still deliver something that algorithms cannot; it aspires to be the opposite of Pandora, in which the algorithms do all the heavy lifting. As its founder, Jeff Yasuda, told Bloomberg News last September, “there’s a big need for a curated type of experience and just getting back to the belief that the most compelling recommendations come from a human being.”

But while Fuzz’s launch attracted little attention, the growing role of algorithms in all stages of artistic production is becoming impossible to ignore. Most recently, this role was highlighted by Andrew Leonard, the technology critic for Salon, in an intriguing article about House of Cards, Netflix’s first foray into original programming. The series’ origin myth is by now well-known: Having studied its user logs, Netflix discovered that a remake of the British series of the same name could be a huge hit, especially if it also featured Kevin Spacey and was directed by David Fincher.

Excerpt from an article written by Evgeny Morozov at Slate. Continue THERE