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posted by janrinok on Saturday July 28 2018, @06:50PM   Printer-friendly
from the they're-criminals dept.

The American Civil Liberties Union, in an effort to demonstrate the dangers of face recognition technology, ran photos of members of Congress against a database of mug shots using Amazon Rekognition software. That test incorrectly identified 28 legislators as criminals (cue the jokes - yes, the Congress members were confirmed to be elsewhere at the time). They hope that demonstrating that this risk hits close to home will get Congress more interested in regulating the use of this technology.

The false matches were disproportionately of people of color, including six members of the Congressional Black Caucus, among them civil rights legend Rep. John Lewis (D-Ga.). These results demonstrate why Congress should join the ACLU in calling for a moratorium on law enforcement use of face surveillance.

[...] 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. Or an individual getting a knock on the door from law enforcement, and being questioned or having their home searched, based on a false identification.


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  • (Score: 5, Interesting) by JoeMerchant on Saturday July 28 2018, @09:04PM

    by JoeMerchant (3937) on Saturday July 28 2018, @09:04PM (#714102)

    10 years ago I had to give a PhD a lecture about how fallible his PC based fingerprint reader was and that, while we could use it as a convenience, there had to be a backup method of identification.

    Seems that this self styled "smartest guy in the room" had never experienced an inability to login with his PC fingerprint reader (happened about 10% of the time to about 30% of the population back then), so he believed what he saw on TV and movies that fingerprints were unique and infallible. They're good - when they're processed by experts they're very good, but with ~140 billion fingerprint patterns, just in the live human populations, and real world challenges of partial prints and fuzzy features they are not a unique, perfect identification tool.

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