ACLU: Amazon Face Recognition Falsely Matched 28 Congress Members with Others' Mugshots
"Amazon’s Face Recognition Falsely Matched 28 Members of Congress With Mugshots," By Jacob Snow, Technology & Civil Liberties Attorney, ACLU of Northern California, July 29, 2018.
Amazon’s face surveillance technology is the target of growing opposition nationwide, and today, there are 28 more causes for concern. In a test the ACLU recently conducted of the facial recognition tool, called “Rekognition,” the software incorrectly matched 28 members of Congress, identifying them as *other people who have been arrested for a crime.
The members of Congress who were falsely matched with the mugshot database we used in the test include Republicans and Democrats, men and women, and legislators of all ages, from all across the country. The false matches were disproportionately of people of color, including six members of the Congressional Black Caucus, among them civil rights legend Rep. John Lewis (D-Ga.). These results demonstrate why Congress should join the ACLU in calling for a moratorium on law enforcement use of face surveillance.
To conduct our test, we used the exact same facial recognition system that Amazon offers to the public, which anyone could use to scan for matches between images of faces. And running the entire test cost us $12.33 — less than a large pizza. Using Rekognition, we built a face database and search tool using 25,000 publicly available arrest photos. Then we searched that database against public photos of every current member of the House and Senate. We used the default match settings that Amazon sets for Rekognition.
In a recent letter to Amazon CEO Jeff Bezos, the Congressional Black Caucus expressed concern about the “profound negative unintended consequences” face surveillance could have for Black people, undocumented immigrants, and protesters. Our results validate this concern: 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...
Read More, https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28
Our test used AmazonRekognition to compare images of members of Congress with a database of mugshots. The results included 28 incorrect matches.
NYT, "Amazon Facial Recognition Wrongly Identifies 28 Lawmakers, ACLU," July 26, 2018.
https://www.msn.com/en-us/news/technology/amazon%e2%80%99s-facial-recognition-wrongly-identifies-28-lawmakers-aclu-says/ar-BBL4WWr