Communications of the ACM
Amazon Face Recognition Falsely Matches 28 Lawmakers With Mugshots, ACL Says
Amazon's facial recognition software incorrectly matched the faces of 28 U.S. legislators to images in a mugshot database.
Credit: Jim Lo Scalzo/EPA
A test of Amazon's facial recognition software incorrectly matched the faces of 28 U.S. legislators to images in a mugshot database, with people of color misidentified disproportionately, according to the American Civil Liberties Union (ACLU).
The organization assembled a face database and search tool from 25,000 public arrest photos, then cross-referenced that data with public photos of every member of Congress.
Eleven of the misidentified lawmakers were people of color, representing nearly 40% of those wrongly matched, even though minorities comprise only 20% of those in Congress.
Says the ACLU Foundation of Northern California's Jacob Snow, "Our test reinforces that face surveillance is not safe for government use." Amazon said the test’s results could “probably be improved” by increasing “confidence thresholds.”
From The Guardian
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