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.
A test of Amazon's facial recognition technology by the ACLU has found it erroneously labelled those with darker skin colours as criminals more often. Bias in AI technology, when used by law enforcement, has raised concerns of infringing on civil rights by automated racial profiling. A 2010 study by researchers at NIST and the University of Texas in Dallas found that algorithms designed and tested in East Asia are better at recognising East Asians, while those designed in Western countries are more accurate at detecting Caucasians. The ACLU (American Civil Liberties Union) ran a test of Amazon's facial recognition technology on members of Congress to see if they match with a database of criminal mugshots. Amazon's Rekognition tool was used to compare pictures of all members of the House and Senate against 25,000 arrest photos, the false matches disproportionately affected members of the Congressional Black Caucus.
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 online facial recognition system incorrectly matched pictures of US Congress members to mugshots of suspected criminals in a study by the American Civil Liberties Union. The ACLU, a nonprofit headquartered in New York, has called for Congress to ban cops and Feds from using any sort of computer-powered facial recognition technology due to the fact that, well, it sucks. Amazon's AI-powered Rekognition service was previously criticized by the ACLU when it revealed the web giant was aggressively marketing its face-matching tech to police in Washington County, Oregon, and Orlando, Florida. Rekognition is touted by the Bezos Bunch as, among other applications, a way to identify people in real time from surveillance camera footage or from officers' body cameras. The results from the ACLU's latest probing showed that Rekognition mistook images of 28 members of Congress for mugshots of cuffed people suspected of crimes.