Look at Facebook, says Amie Stepanovich, director of the domestic surveillance project at the Electronic Privacy Information Center in Washington, D.C.
Facebook has the largest biometric database in the world — “and it’s all been formed by people voluntarily submitting pictures to Facebook and identifying who they belong to,” she says.
Theoretically, every time you label faces by tagging a picture, you’re chipping away at those two big challenges for universal facial recognition. First, you’re helping to build a super-database of labeled faces. Second, you’re uploading multiple versions of each person’s face, which can improve a system’s accuracy.
“If you had lots of photos of each person … you could build a model for Martin, a model for me, a model for other people. Now you have a custom-tuned model for each person,” Kumar, from the University of Washington, says.
Multiply that by a billion — a billion custom-tuned facial “models.”
Facebook would not answer NPR’s questions about what it does with facial recognition information; social media companies rarely talk about their internal systems.
But they’re surely aware of their huge database’s potential. Last year, Facebook bought Face.com, whose company’s founders had titled “Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition.”
On Facebook, for example, you can’t identify faces of people who aren’t already your “friends,” but she wonders if, behind the scenes, Facebook can do broader searches — say, at the request of the government.
“As we’re seeing specifically over the past few months, no matter how much a company attempts to protect your privacy, if they’re collecting information about you, that information is vulnerable to government search,” Stepanovich says.
Whether this is technically possible; Google, which offers the competing Google Plus service, also won’t comment on the record about the feasibility of broader face searches.
Kumar doubts anyone is doing universal searches of Facebook faces. He says the numbers are just too big.
However, if social media companies are able to narrow the search — say, if they can compare a photo with the facial models of everybody who “likes” NPR, or everybody who lives in Des Moines — then, you’d have the makings of a useful search tool Neeraj Kumar an expert in computer vision at the University of Washington said.