Amazon's facial recognition software incorrectly matched the faces of 28 U.S. legislators to images in a mugshot database. A test of Amazon's facial recognition software incorrectly matched the faces of 28 U.S. legislators to images in a mugshot database, with people of color misidentified disproportionately, according to the American Civil Liberties Union (ACLU). The organization assembled a face database and search tool from 25,000 public arrest photos, then cross-referenced that data with public photos of every member of Congress. Eleven of the misidentified lawmakers were people of color, representing nearly 40% of those wrongly matched, even though minorities comprise only 20% of those in Congress. Says the ACLU Foundation of Northern California's Jacob Snow, "Our test reinforces that face surveillance is not safe for government use."

Amazon's facial recognition technology falsely identified 28 members of Congress as people who have been arrested for crimes, according to the American Civil Liberties Union (ACLU). The ACLU of Northern California's test of Amazon's controversial Rekognition software also found that people of color were disproportionately misidentified in a mugshot database, raising new concerns about racial bias and the potential for abuse by law enforcement. The report followed revelations in May that Amazon has been marketing and selling the Rekognition technology to police agencies, leading privacy advocates to urge CEO Jeff Bezos to stop providing the product to the government. "Our test reinforces that face surveillance is not safe for government use," Jacob Snow, a technology and civil liberties attorney at the ACLU Foundation of Northern California, said in a statement. "Face surveillance will be used to power discriminatory surveillance and policing that targets communities of color, immigrants, and activists. Once unleashed, that damage can't be undone."