How AI-powered tech landed man in jail with scant evidence--AP

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By GARANCE BURKE, MARTHA MENDOZA, JULIET LINDERMAN and MICHAEL TARM

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Williams was jailed last August, accused of killing a young man from the neighborhood who asked him for a ride during a night of unrest over police brutality in May. But the key evidence against Williams didn't come from an eyewitness or an informant; it came from a clip of noiseless security video showing a car driving through an intersection, and a loud bang picked up by a network of surveillance microphones. Prosecutors said technology powered by a secret algorithm that analyzed noises detected by the sensors indicated Williams shot and killed the man.

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Williams' experience highlights the real-world impacts of society's growing reliance on algorithms to help make consequential decisions about many aspects of public life. Nowhere is this more apparent than in law enforcement, which has turned to technology companies like gunshot detection firm ShotSpotter to battle crime. ShotSpotter evidence has increasingly been admitted in court cases around the country, now totaling some 200. ShotSpotter's website says it's "a leader in precision policing technology solutions" that helps stop gun violence by using "sensors, algorithms and artificial intelligence" to classify 14 million sounds in its proprietary database as gunshots or something else.

But an Associated Press investigation, based on a review of thousands of internal documents, emails, presentations and confidential contracts, along with interviews with dozens of public defenders in communities where ShotSpotter has been deployed, has identified a number of serious flaws in using ShotSpotter as evidentiary support for prosecutors.

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Another report...from the UK.


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This page contains a single entry by Leonard E. Sienko, Jr. published on August 23, 2021 4:26 PM.

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