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The Pandemic is Testing the Limits of Face Recognition


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Elements of faces that facial recognition program must learn, or identify.

Face recognition software started becoming more common years before the pandemic, and its potential flaws are well-documented.

Credit: Ms Tech/Pexels

At first glance, JB, an artist based in Los Angeles, perhaps doesn't look much like the picture on their driver's license. For one thing, the ID photo is from a few years ago. Hair that was once long and dark is now buzzed and bleached. And there's the fact that JB is transgender and has been taking testosterone for over two years, which has led to changing facial features, thicker eyebrows, and acne that wasn't there before. (They asked to be identified only by their first initials because of privacy concerns.)

JB lost a part-time retail job when the lockdowns hit last March and, like millions of other Americans, attempted to apply for unemployment benefits—never suspecting that their changing appearance would stand in the way. Months after submitting paperwork electronically, and making multiple calls to a hotline that went nowhere, JB was finally invited to use California's facial recognition system to verify their identity. But even after multiple tries, the system couldn't match JB's face and ID photo, shutting them out of the benefits they qualified for. Eventually, JB stopped trying: the process was too frustrating. 

Law enforcement and private businesses have used face recognition for years, but use of the technology in distributing government aid has expanded rapidly during the pandemic. States and federal agencies have turned to face recognition as a contactless, automated way of verifying the identity of people applying for unemployment and other public benefits.

From MIT Technology Review
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