Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. The ACLU released a report on Thursday revealing that Rekognition, Amazon's facial recognition tool, had falsely matched 28 members of Congress to mug shots. Members of the ACLU purchased the version of Rekognition that Amazon offers to the general public and ran public photos of every member of the House and Senate against a database of 25,000 arrest photos. The entire experiment costed $12.33, which, as ACLU attorney Jake Snow writes in a blogpost, is "less than a large pizza." Almost 40 percent of the representatives that Rekognition falsely matched were people of color, even though they make up only 20 percent of Congress.
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's facial recognition tool is being referred to as a'recipe for authoritarianism and disaster' after it was revealed to be used by law enforcement officials. Now experts say it raises even greater concerns, as the artificial intelligence used to power the technology could exhibit racial bias. Many are calling on Amazon to release data that shows they've trained the software to reduce bias, but it has yet to do so. A controversial facial recognition tool, dubbed Rekognition, marketed to police has been defended by its creator, online retailer Amazon. The controversy was spurred by a report from the American Civil Liberties Union (ACLU), which found that Amazon's facial recognition tool, dubbed'Rekognition', is being used by law enforcement agencies in Oregon and Florida.
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.
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.