A torrent of torsos. (Image: Adam Milner and Ben Snell)
Computers can do a lot. They can beat people at Go. They can draw strange squirrels. They are running a good chunk of the planet pretty much all on their own.
But, perhaps due to their own general lack of bodies, they cannot yet distinguish nipples from navels. Last night, a group of volunteers set out to change that, armed with a collection of about 10,000 shirtless selfies.
Torso Computer Club is the creation of Adam Milner and Ben Snell, both artists at Carnegie Mellon University. For the past few years, Milner has been collecting torsos from people he chats with on Grindr and other dating apps, creating a compendium of faceless self-presentation. "The torso image initially interested me because it seemed simultaneously vulnerable and distant or safe," he says.
After a few years of screengrabbing, he now has about 10,000 torsos. But he wasn't quite sure what to do with them until he met Snell, who thought it might be neat to use this huge dataset to train computers. "There aren't open source data sets of torsos just lying around the internet," Snell says.
Like #machinelearning? #torsos? #dumplings? Help label 1000s of nipples & navels this Tuesday 9/20 @creativeinquiry! pic.twitter.com/HGF26dV0qF
— Golan Levin (@golan) September 17, 2016
The volunteers of Torso Computer Club met up last night at the Frank-Ratchye Studio for Creative Inquiry in Pittsburgh, PA, and spent the evening classifying what Snell calls "topological landmarks on the body." Milner and Snell will use their work to train computers to do the same thing.
Although they are wary of their work falling into the wrong hands—Instagram, for example, could use it to beef up their censorship tools—they plan to continue on to loftier goals. "Can we use this massive set of data to construct a single three-dimensional torso—a near-physical manifestation of modern yet classical form?" asks Snell. "We might even be able to teach a computer to 'see' nipples and navels on its own."
"We want to continue mining this collection for the potential it has, though less as a tool and more as a form of provocation and speculation," says Snell. Adds Milner: "The more we work the more questions there are."
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