The ACLU put Amazon's Rekognition facial scanning software to the test and the results were more than a little troubling. Comparing "every current member of the House and Senate" against a database of 25,000 publicly available mugshots, Amazon's software identified 28 lawmakers as folks who'd been arrested for a crime. Given what we've seen about facial recognition's shortcomings, especially in regards to people of color, the following might not be all that surprising: The false matches included six members of the Congressional Black Caucus. "Nearly 40 percent of Rekognition's false matches were of people of color, even though they make up only 20 percent of Congress," according to the ACLU. We've already seen how the public has reacted to Amazon's face-scanning tech.
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.
Amazon's Rekognition facial surveillance technology has wrongly tagged 28 members of Congress as police suspects, the ACLU says. Amazon's Rekognition facial surveillance technology has wrongly tagged 28 members of Congress as police suspects, according to ACLU research, which notes that nearly 40 percent of the lawmakers identified by the system are people of color. In a blog post, Jacob Snow, technology and civil liberties attorney for the ACLU of Northern California, said that the false matches were made against a mugshot database. The matches were also disproportionately people of color, he said. These include six members of the Congressional Black Caucus, among them civil rights legend Rep. John Lewis, D-Ga.
Amazon.com's facial recognition tools incorrectly identified Rep. John Lewis (D-Ga.) and 27 other members of Congress as people arrested for a crime during a test commissioned by the American Civil Liberties Union of Northern California, the watchdog said Thursday. The ACLU said its findings show that Amazon's so-called Rekognition technology -- already in use at law-enforcement agencies in Oregon and Orlando -- is hampered by inaccuracies that disproportionately put people of color at risk and should prompt regulators to halt "law enforcement use of face surveillance." Amazon chief executive Jeffrey P. Bezos owns The Washington Post. For its test, the ACLU of Northern California created a database of 25,000 publicly available arrest photos, though the civil liberties watchdog did not give details about where it obtained the images or the kinds of individuals in the photos. It then used Amazon's Rekognition software to compare that database against photos of every member of the U.S. House and Senate.
SAN FRANCISCO -- Amazon's controversial facial recognition program, Rekognition, falsely identified 28 members of Congress during a test of the program by the American Civil Liberties Union, the civil rights group said Thursday. In its test, the ACLU scanned photos of all members of Congress and had the system compare them with a public database of 25,000 mugshots. The group used the default "confidence threshold" setting of 80 percent for Rekognition, meaning the test counted a face match at 80 percent certainty or more. At that setting, the system misidentified 28 members of Congress, a disproportionate number of whom were people of color, tagging them instead as entirely different people who have been arrested for a crime. The faces of members of Congress used in the test include Republicans and Democrats, men and women and legislators of all ages.