Amazon Rekognition falsely matches 28 Members of Congress
Amazon's Rekognition facial recognition system incorrectly identified 28 US members of Congress as people who had been arrested for a criminal offences , raising concerns about its use in law enforcement and other sensitive domains. T he American Civil Liberties Union (ACLU) released the results of a test showing that Rekognition falsely matched 28 members of the US Congress with mugshot photos of criminals, especially people of colour. Congressional members from both major political parties later expressed concern about Rekognition in a series (pdf) of letters to then Amazon CEO Jeff Bezos. Amazon responded by saying the Rekognition test had generated 80 percent confidence and that it recommended law enforcement only use matches rated at 95 percent confidence or higher. According to the ACLU, Amazon moved the goalpost by increasing the recommended confidence interval after the ACLU study was published. The incident raised questions about the accuracy and reliability of Amazon's Rekognition system and highlighted its potential impact on minority community civil liberties when used by law enforcement authorities. System 🤖 Amazon Rekognition 🔗 Operator: American Civil Liberties Union (ACLU) Developer: Ama zon/AWS Country: USA Sector: Politics Purpose: Identif y public figures Technology: Facial recognition Issue: Accuracy/reliability; Bias/discrimination; Human/civil rights; Privacy
- Date it happened
- 2018-07-01
- Organisation involved
- American Civil Liberties Union (ACLU)
- Product, system or model
- Amazon Rekognition
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