Amazon’s response to ACLU facial recognition study using Congress member photos: Full text

Amazon CEO Jeff BezosGetty/Chip SomodevillaAmazon is under fire after the American Civil Liberties Union performed an experiment using its facial recognition software. The ACLU found that it incorrectly identified 28 members of Congress as people who had previously been arrested.

When we reached out to Amazon for its response to a Thursday report from the ACLU about its Rekognition software, a spokesperson provided a statement saying that its software is designed to be used in conjunction with humans, and that the ACLU used the wrong settings for its study.

Amazon’s full statement has been reproduced below:

We have seen customers use the image and video analysis capabilities of Amazon Rekognition in ways that materially benefit both society (e.g. preventing human trafficking, inhibiting child exploitation, reuniting missing children with their families, and building educational apps for children), and organizations (enhancing security through multi-factor authentication, finding images more easily, or preventing package theft). We remain excited about how image and video analysis can be a driver for good in the world, including in the public sector and law enforcement.”

“With regard to this recent test of Amazon Rekognition by the ACLU, we think that the results could probably be improved by following best practices around setting the confidence thresholds (this is the percentage likelihood that Rekognition found a match) used in the test. While 80% confidence is an acceptable threshold for photos of hot dogs, chairs, animals, or other social media use cases, it wouldn’t be appropriate for identifying individuals with a reasonable level of certainty. When using facial recognition for law enforcement activities, we guide customers to set a threshold of at least 95% or higher.”

“Finally, it is worth noting that in real world scenarios, Amazon Rekognition is almost exclusively used to help narrow the field and allow humans to expeditiously review and consider options using their judgement (and not to make fully autonomous decisions), where it can help find lost children, restrict human trafficking, or prevent crimes.