How a bad facial AI recognition match led to a false arrest

Credit: Wallpaper Flare
Credit: Wallpaper Flare

On the Friday afternoon after Thanksgiving, Randal Quran Reid was driving his white Jeep to his mother’s home outside Atlanta when he was pulled over on a busy highway. A police officer approached his vehicle and asked for his driver’s license. Mr. Reid had left it at home, but he volunteered his name. After asking Mr. Reid if he had any weapons, the officer told him to step out of the Jeep and handcuffed him with the help of two other officers who had arrived.

“What did I do?” Mr. Reid asked. The officer said he had two theft warrants out of Baton Rouge and Jefferson Parish, a district on the outskirts of New Orleans. Mr. Reid was confused; he said he had never been to Louisiana.

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Mr. Reid’s wrongful arrest appears to be the result of a cascade of technologies — beginning with a bad facial recognition match — that are intended to make policing more effective and efficient but can also make it far too easy to apprehend the wrong person for a crime. None of the technologies are mentioned in official documents, and Mr. Reid was not told exactly why he had been arrested, a typical but troubling practice, according to legal experts and public defenders.

This is an excerpt. Read the full article here

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