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It Ain't Me, Babe: Researchers Find Flaws In Police Facial Recognition Technology

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A researchers in the ID fraud unit of the North Carolina Department of Motor Vehicles examines photos in a facial recognition system.

Nearly half of all American adults have been entered into law enforcement facial recognition databases, despite many problems with the accuracy of the technology.

Credit: Gerry Broome/AP

Nearly half of all American adults have been entered into law enforcement facial recognition databases, according to a recent report from Georgetown University's law school. But there are many problems with the accuracy of the technology that could have an impact on a lot of innocent people.

There's a good chance your driver's license photo is in one of these databases. The report from the school's Center on Privacy & Technology says more than 117 million adults' photos are stored in them. Facial recognition can be used, for instance, when investigators have a picture of a suspect and they don't have a name.

They can run the photo through a facial recognition program to see if it matches any of the license photos. It's kind of like a very large digital version of a lineup, says Jonathan Frankle, a computer scientist and one of the authors of the report, titled "The Perpetual Line-Up."

"Instead of having a lineup of five people who've been brought in off the street to do this, the lineup is you. You're in that lineup all the time," he says. Frankle says the photos that police may have of a suspect aren't always that good — they're often from a security camera.

"Security cameras tend to be mounted on the ceiling," he says. "They get great views of the top of your head, not very great views of your face. And you can now imagine why this would be a very difficult task, why it's hard to get an accurate read on anybody's face and match them with their driver's license photo."

Frankle says the study also found evidence that facial recognition software didn't work as well with people who have dark skin. There's still limited research on why this is. Some critics say the developers aren't testing the software against a diverse enough group of faces. Or it could be lighting.

"Darker skin has less color contrast. And these algorithms rely on being able to pick out little patterns and color to be able to tell people apart," Frankle says.


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