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Amazon's facial recognition matched 28 members of Congress to criminal mugshots
Amazon’s facial recognition matched 28 members of Congress to criminal mugshots
New ACLU test illustrates the limits of Amazon’s Rekognition system
Illustration by James Bareham / The Verge
By Russell Brandom@russellbrandom Jul 26, 2018, 8:02am EDT
The American Civil Liberties Union tested Amazon’s facial recognition system — and the results were not good. To test the system’s accuracy, the ACLU scanned the faces of all 535 members of congress against 25,000 public mugshots, using Amazon’s open Rekognition API. None of the members of Congress were in the mugshot lineup, but Amazon’s system generated 28 false matches, a finding that the ACLU says raises serious concerns about Rekognition’s use by police.
“An identification — whether accurate or not — could cost people their freedom or even their lives,” the group said in an accompanying statement. “Congress must take these threats seriously, hit the brakes, and enact a moratorium on law enforcement use of face recognition.”
Reached by The Verge, an Amazon spokesperson attributed the results to poor calibration. The ACLU’s tests were performed using Rekognition’s default confidence threshold of 80 percent — but Amazon says it recommends at least a 95 percent threshold for law enforcement applications where a false ID might have more significant consequences.
“While 80% confidence is an acceptable threshold for photos of hot dogs, chairs, animals, or other social media use cases,” the representative said, “it wouldn’t be appropriate for identifying individuals with a reasonable level of certainty.” Still, Rekognition does not enforce that recommendation during the setup process, and there’s nothing to prevent law enforcement agencies from using the default setting.
...
New ACLU test illustrates the limits of Amazon’s Rekognition system
Illustration by James Bareham / The Verge
By Russell Brandom@russellbrandom Jul 26, 2018, 8:02am EDT
The American Civil Liberties Union tested Amazon’s facial recognition system — and the results were not good. To test the system’s accuracy, the ACLU scanned the faces of all 535 members of congress against 25,000 public mugshots, using Amazon’s open Rekognition API. None of the members of Congress were in the mugshot lineup, but Amazon’s system generated 28 false matches, a finding that the ACLU says raises serious concerns about Rekognition’s use by police.
“An identification — whether accurate or not — could cost people their freedom or even their lives,” the group said in an accompanying statement. “Congress must take these threats seriously, hit the brakes, and enact a moratorium on law enforcement use of face recognition.”
Reached by The Verge, an Amazon spokesperson attributed the results to poor calibration. The ACLU’s tests were performed using Rekognition’s default confidence threshold of 80 percent — but Amazon says it recommends at least a 95 percent threshold for law enforcement applications where a false ID might have more significant consequences.
“While 80% confidence is an acceptable threshold for photos of hot dogs, chairs, animals, or other social media use cases,” the representative said, “it wouldn’t be appropriate for identifying individuals with a reasonable level of certainty.” Still, Rekognition does not enforce that recommendation during the setup process, and there’s nothing to prevent law enforcement agencies from using the default setting.
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More at link
5 replies
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The hits were accurate...
