Facial recognition systems are still far from accurate, and yet government agencies continue to push for its deployment. To illustrate the existing flaws of the tech, the ACLU conducted another test of Amazon’s Rekognition software, which inaccurately identified one in five California lawmakers as matches to a mugshot database.
The test was detailed during a press conference on Tuesday in which San Francisco Assemblymember Phil Ting called for support of a bill that would ban the use of facial recognition in police body cameras. The ACLU ran 120 images of California lawmakers against a 25,000 image mugshot database using Amazon’s Rekognition software and found 26 matches, which included Ting.
“We wanted to run this as a demonstration about how this software is absolutely not ready for prime time,” Ting said during the press conference. “While we can laugh about it as legislators, it’s no laughing matter if you are an individual who is trying to get a job, if you are an individual trying to get a home, if you get falsely accused of an arrest, what happens, it could impact your ability to get employment, it absolutely impacts your ability to get housing. So there are real people who could have real impacts.”
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