AWS Facial Recognition Platform Misidentified Over 100 Politicians as Criminals

upstart writes in with an IRC submission for RandomFactor:

AWS Facial Recognition Platform Misidentified Over 100 Politicians As Criminals:

Comparitech's Paul Bischoff found that Amazon's facial recognition platform misidentified an alarming number of people, and was racially biased.

Facial recognition technology is still misidentifying people at an alarming rate - even as it's being used by police departments to make arrests. In fact, Paul Bischoff, consumer privacy expert with Comparitech, found that Amazon's face recognition platform incorrectly misidentified more than 100 photos of US and UK lawmakers as criminals.

Rekognition, Amazon's cloud-based facial recognition platform that was first launched in 2016, has been sold and used by a number of United States government agencies, including ICE and Orlando, Florida police, as well as private entities. In comparing photos of a total of 1,959 US and UK lawmakers to subjects in an arrest database, Bischoff found that Rekognition misidentified at average of 32 members of Congress. That's four more than a similar experiment conducted by the American Civil Liberties Union (ACLU) - two years ago. Bischoff also found that the platform was racially biased, misidentifying non-white people at a higher rate than white people.

These findings have disturbing real-life implications. Last week, the ACLU shed light on Detroit citizen Robert Julian-Borchak Williams, who was arrested after a facial recognition system falsely matched his photo with security footage of a shoplifter.

Read more of this story at SoylentNews.