Amazon Face Recognition Falsely Matches 28 Lawmakers With Mugshots, ACLU Says

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."