Inside Artsy’s Quest to Make You Love Art as Much as Music

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ARTSY, THE ONLINE art database, has an ambitious vision: A world in which art is as popular as music. It has pursued that goal since its founding in 2009—I heard the mantra repeated at least twice while visiting the company’s lower Manhattan office—and recently took a big step toward achieving it when it bought the data science startup ArtAdvisor.

Art and data science make for an unlikely pairing, but data is especially well suited to toppling a key barrier to making art as ubiquitous as music: taste. “More sophisticated taste just comes from spending more time with something, just like music or wine or film,” says Artsy CEO Carter Cleveland. “You start with what catches your interest, and then you spend more time with it, and then you get bored with the things you’ve heard or tasted ten times, so you look for those deeper levels.” In other words: Taste is simply a function of information. The more you have, the more finely tuned your sensibility. Artsy intends to expand your palate by turning the art world into a series of data points, to reveal what you might like.

Exactly how this will work remains to be seen, but it expands on Artsy’s Art Genome Project. That initiative, run by six art historians, involves assigning artists and their work “genes,” or traits. A Picasso painting from his Cubist period, for example, gets the Cubism gene applied at 100 percent. But a Mondrian that merely draws on Cubism might be assigned a value of 30 percent. The Art Genome Project creates a constellation of artists—27,000 to date—that fuels Artsy’s recommendations to its users. If you like Picasso, the genome might suggest that you’d also appreciate Tatiana Berg, a young Brooklyn artist who paints in big, gestural brushstrokes.

With ArtAdvisor in house, Artsy aspires to go beyond connecting styles, periods, and movements. It wants to create what it calls an art brain—a system that understands the whims and nuances of the art market much like an insider does. Cleveland uses a scenario to explain: A gallery shows a promising young painter. A MoMA curator suggests he might want to buy two pieces. The gallery owner mentions this to a collector, who now has a better sense of what the work might be worth. “That’s such a common thing you’d hear,” Cleveland says. “A lot of what we’re doing is figuring out how we capture that information in a structured way.”

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