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Amazon's facial recognition tool misidentified 28 members of Congress in ACLU test

USATODAY - Tech Top Stories

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 System Mistakes Members of Congress for Mugshots

WIRED

Amazon touts its Rekognition facial recognition system as "simple and easy to use," encouraging customers to "detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases." And yet, in a study released Thursday by the American Civil Liberties Union, the technology managed to confuse photos of 28 members of Congress with publicly available mug shots. Given that Amazon actively markets Rekognition to law enforcement agencies across the US, that's simply not good enough. The ACLU study also illustrated the racial bias that plagues facial recognition today. "Nearly 40 percent of Rekognition's false matches in our test were of people of color, even though they make up only 20 percent of Congress," wrote ACLU attorney Jacob Snow.


Amazon's facial-recognition tool misidentified 28 lawmakers as people arrested for a crime, study finds

Washington Post - Technology News

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.


Amazon selling facial recognition software to police, records reveal

The Guardian

In the aftermath of the uprising in Ferguson, Missouri, over the killing of Michael Brown, police departments and policy makers around the country hit upon a supposed panacea to racist policing and police brutality: body-worn cameras. Many hailed the move as a victory for accountability. But among the few dissenters was Malkia Cyril, executive director of the Center for Media Justice and a leader in the Black Lives Matter network, who warned early and often that the cameras could become tools of surveillance against people of color because "body-worn cameras don't watch the police, they watch the community being policed, people like me". The scope and scale of that surveillance became clearer Tuesday, when the American Civil Liberties Union of Northern California released a collection of public records detailing how Amazon has been marketing and selling facial recognition software, called Amazon Rekognition, to law enforcement agencies. Amazon marketing materials promoted the idea of using Rekognition in conjunction with police body cameras in real time – exactly the outcome Cyril feared.


Amazon face recognition wrongly tagged lawmakers as police suspects, fueling racial bias concerns

FOX News

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.