#ai responsibility

[onlytiktoks]

[alwaysbewoke]

Last summer, as a spike in violent crime hit New Orleans, the city council voted to allow police to use facial-recognition software to track down suspects. It was billed as an effective, fair tool to ID criminals quickly. A year after the system went online, data show the results have been almost exactly the opposite. Records obtained and analyzed by POLITICO show the practice failed to ID suspects a majority of the time and is disproportionately used on Black people. We reviewed nearly a year’s worth of New Orleans facial recognition requests, sent for serious felony crimes including murder and armed robbery. In that time, New Orleans PD sent 19 requests. Of the 15 that went through: 14 were for Black suspects 9 failed to make a match Half of the 6 matches were wrong 1 arrest was made While it hasn’t led to any false arrests, police facial identification in New Orleans appears to confirm what civil rights advocates have argued for years: that it amplifies, rather than corrects, the underlying human biases of the authorities that use them. U.S. lawmakers of both parties have tried for years to limit how police can use facial recognition, but have yet to enact any laws. Some states have passed limited rules, like those preventing its use on body cameras in California or banning its use in schools in New York. A few left-leaning cities have fully banned law enforcement use of the technology. For two years, in the wake of the George Floyd protests, New Orleans was one of them. “This department hung their hat on this,” said New Orleans Councilmember At-Large JP Morrell, a Democrat who voted against lifting the ban and has seen the NOPD data. Its use of the system, he says, has been “wholly ineffective and pretty obviously racist.” (NOPD denies that its usage of facial recognition is racially biased). Politically, New Orleans’ City Council is split on facial recognition, but a slim majority of its members — alongside the police, mayor and local businesses — still support its use, despite the results of the past year.

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[zinkmagmore-blog]

Explore AI Ethics: understand bias, protect privacy, and demand accountability. Let’s shape AI to be fair, transparent, and responsible for a better future. #AIEthics #BiasInAI #DataPrivacy #ResponsibleAI #TechForGood #EthicalAI

AI Ethics 101