An investigation details how a Georgia man was wrongfully arrested based on a bad facial recognition match and other tech meant to make policing more effective
Because of a bad facial recognition match and other hidden technology, Randal Reid spent nearly a week in jail …
New York Times
Context & Ripple Effects
The Times' investigation into Randal Reid closes the loop on a case first reported in January: a Louisiana warrant built on a bad facial recognition match jailed a Georgia resident for nearly a week in a state he had never visited. What the new reporting adds is that facial recognition was not acting alone — layered 'hidden' policing technologies compounded the error before any human caught it.
Reid and people like him bear the direct cost — days of jail, cross-state warrants, and legal battles to clear names that machines mislabeled; his case hands plaintiffs and civil-liberties lawyers another concrete, well-documented example for suits against police agencies and tool vendors.
Police departments that treat a facial-recognition hit as probable cause rather than a lead now have their practice named in national print, raising immediate internal-review and policy questions at the agencies involved.
Second-order effects
Departments under scrutiny will face pressure to require independent corroboration before warrants, and vendors of these tools will be pushed toward disclosure requirements since the technologies operated invisibly to both the suspect and, reportedly, parts of the process itself.
Insurers, city attorneys, and elected officials become secondary actors: each wrongful-arrest suit converts an abstract accuracy debate into municipal liability, pricing the risk of match-only arrests into procurement decisions.
Third-order effects
If the pattern holds — isolated wrongful arrests accumulating into documented multi-state practice — the likely structural outcome is statutory or regulatory limits on facial recognition's role in policing, following the same arc by which other surveillance tools acquired warrant standards; several states already restrict adjacent automated systems.
The deeper shift is about human-in-the-loop doctrine: courts and legislatures would have to decide whether an algorithmic match can ever constitute evidence on its own, a question automation-bias research suggests current procedures answer badly.
The trend: Facial recognition is drifting from investigative tip to de facto arrest authority in US policing, and each documented wrongful arrest raises the odds that law, not vendor policy, sets its limits.
In Nov, a GA man was arrested for a crime in LA, a state he said he'd never been to. He spent 6 days in jail. We found his arrest was based on a wrong facial recognition match and supported by a cascade of technologies intended to make policing easier. https://www.nytimes.com/...
So lets talk about how tech and AI and journalism use Black people the most for their “content” when they have historically failed at chronicling them and how eager so many are to allow them to fail aka the articles avoiding that Clearview and AI are girded in NAzism https://twit…
The algorithms are biased because they use data from biased human beings. Use of facial recognition by the police NEEDS TO STOP https://twitter.com/...
Shady facial recognition technology like Clearview AI has hugely disproportionate consequences for Black Americans. My Fourth Amendment Is Not For Sale Act would ban the use of this technology by law enforcement and stop these severe miscarriages of justice. https://twitter.com/.…
This right here is the kind of story that keeps me up at night, makes me terrified to travel or just exist in public. And this is only going to happen more frequently as this technology screams forward with no concern for its ethical use. https://twitter.com/...
That is one example of a dangerous ML application deployed in the wild. But I've seen discussions of when it's ok to nuke an AI data center, bc “saving humanity”. We need to leave room in public space for serious arguments, by competent people (hint: it ain't Elon). https://twitt…
“'There's a lot of secrecy about all of these surveillance technologies and the ways that they're used...This case is a perfect example that even when the tool works as intended, if the underlying data is flawed it can still harm innocent people.'” #algorithmicbias #ClearviewAI h…
As AI becomes ubiquitous in policing, we still have zero assurance that police have the insight needed to audit or even vaguely understand the tech they use to justify arresting people Won't be long until a Palantir cop-preneur sells a “faster” e-warrant system with AI-approvals …
Read this story about cops hiding their use of face recognition from the judiciary and the man they wrongfully arrested. Now try believing cops will follow rules regulating face recognition. They won't. Ban it. https://twitter.com/...
For the last three months, @RMac18 & I have been trying to get to the bottom of exactly why a man in Georgia was jailed for stealing purses in Louisiana, a state he'd never been to. It started with facial recognition and snowballed from there. https://www.nytimes.com/... https://…