The ACLU also raised concerns about Amazon's Rekognition software in July 2018.
Wednesday's open letter dissects Wood and Punke's objections to the paper, concluding that it finds their response to the peer-reviewed paper"disappointing."
The signatories point out that, according to the study, Amazon had an error rate of approximately 31% when given women of color. It also took issue with binary gender classification methods, as they exclude non-binary genders. And they noted that Amazon has not disclosed who its Rekognition customers are, what its error rates are across different intersectional demographics, nor is the software subject to any kind of external audit.
Separately, civil rights organisation the ACLU has raised concerns about Rekognition in the past, and ran a test of the software in which it. The false matches disproportionately affected people of color. "If law enforcement is using Amazon Rekognition, it's not hard to imagine a police officer getting a 'match' indicating that a person has a previous concealed-weapon arrest, biasing the officer before an encounter even begins.
The open letter picked up on this argument, as a similar criticism was levelled by Amazon towards the original paper. The signatories write that systems like Rekognition have to be tested in real-world scenarios, and that police forces may not use or even be trained to understand Rekognition's"confidence" ratings.in which a Washington County Sheriff's Office public information officer said that police there,"do not set nor [...] utilize a confidence threshold.
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