2 minutes reading time (317 words)

Big Brother's blind spot

Big Brother's blind spot
Netflix believes, algorithmically at least, that I am the kind of person who likes to watch "Dark TV Shows Featuring a Strong Female Lead." This picksome genre is never one that I that seek out intentionally, and I'm not sure it even represents my viewing habits. (Maybe I fell asleep watching The Killing one night?) It is an image of me that Netflix compiled from personal data it gathers, and, like a portrait taken slantwise and at a distance, much finer detail is missing. As it happens, television sometimes puts me to sleep; other times I stream a movie as I work on my laptop, and by the time I've finished typing and look back, the credits are rolling. Either way, the idea offered of me after my data has been mined is curiously off-base.

More than a decade ago, Netflix ushered in a cultural conversation about big data and algorithms with stunts like the Netflix Prize—an open competition to improve user rating predictions—and its eventual use of subscriber data to produce and cast the show House of Cards. Now, with Cambridge Analytica and driverless cars in the headlines, the artless future that some technology critics forecasted back then—movies cast by algorithms!—sounds quaint in comparison. For the time being, the stakes are low (rifle through streaming titles to find something good to watch), and the service declares the way it categorizes me—as a fan of the "Strong Female Lead"—rather than clandestinely populating the interface with lady detective shows. To be sure, there is plenty to criticize about its micro-targeting practices, but now that "surveillance capitalism" has eclipsed "big data" as the tech media buzzphrase of choice, at least its subscriber-based business model suggests the company has little incentive to partner with data brokers like Acxiom and Experian, to determine whether mine is a BoJack Horseman household or more apt to stream 13 Reasons Why.

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