Skip to main content
NOPE

NOPE · AI and people

AI incidents

Reports of AI-related harm and adverse experiences affecting people’s safety, wellbeing, rights and livelihoods. Explore what happened and the evidence available.

NOPE’s core concern is when AI communicates with a person, acts on their behalf, or depicts or impersonates them. The tracker also records consequential decisions, claims and privacy harms involving AI. Each case needs a described connection between AI use and the harm, including private information recorded into or disclosed to an AI service. Each account is reviewed for publication; claims may remain uncorroborated or disputed. How we review and count cases

Explore incidents Our scope and evidence

In this selection

Published cases
2
Countries with reported events
1
Located 2 of 2 cases · 0 unknown
Languages in checked sources
1
Recorded for 2 of 2 cases
2Core concern
AI communicated, acted for, depicted or impersonated 2Contextual cases
AI made a decision or claim about someone

These figures describe the cases collected by NOPE. Coverage varies with discovery, reporting and available evidence. They do not estimate how often AI-related harm occurs.

0cases with a recorded lawsuit outcome 0cases with a recorded regulatory response 0cases involving minors

Response counts currently use each case’s principal recorded outcome. Further proceedings may be described in its account.

When events happened

0 cases without a known event year

Cases in this selection, counted once in their first known event year. A series may continue beyond that year. Reporting and collection dates are excluded. NOPE has searched recent events more thoroughly than earlier years, so bar heights also reflect collection effort.

2 2026
Reported severity MediumLow
More filters: AI relation, use, setting, sources and responses
Clear filters

2 of 868 published cases

Export JSONExport CSV
8 Jan 2026United KingdomUnidentified facial recognition system

Southampton: Alvi Choudhury arrested at home on suspicion of a Milton Keynes burglary after a police retrospective facial recognition match, held nearly 10 hours, claiming damages

The Guardian, in a joint report with Liberty Investigates, reported on 25 February 2026 that Alvi Choudhury, a 26-year-old software engineer, was arrested at his home in Southampton in January 2026 on suspicion of a £3,000 burglary in Milton Keynes, about 100 miles away, and held in custody for nearly 10 hours. Thames Valley Police had used automated retrospective facial recognition software, which matched him with CCTV footage of the burglary suspect. Choudhury says the man in the footage looked about 10 years younger and had different features. Thames Valley Police wrote to him that the arrest may have been the result of bias within facial recognition technology, and told the Guardian that the decision rested on the investigating officers’ own visual assessment and was not influenced by racial profiling. Choudhury is claiming damages from Thames Valley Police and Hampshire Constabulary.

Contextual tracker case Medium reported severity

AI involvement supported · Causal attribution disputed · 4 sources, 3 underlying accounts · Added 29/09/2026

6 Aug 2026United KingdomFacewatch facial recognition

London shopper says staff told him Sainsbury's facial recognition flagged him as a shoplifter and he was escorted out; retailer blames human error

On 6 August 2026 Matt Arnold, a comedy promoter, was refused service at a self-service till in Sainsbury's East Dulwich store and escorted out by two managers, who cited an incident earlier in the week. He says a staff member told him he had been identified by the AI and that he saw a CCTV monitor alert with a red circle around his face as he left. Sainsbury's apologised the next day, said the cause was human error rather than the facial recognition technology, and paused its Facewatch system at the store while it investigates. Facewatch says a correct alert was sent and mishandled in store; the BBC reports Sainsbury's claim that staff targeted the wrong person after a separate flag. Whose face the system matched is unresolved.

Contextual tracker case Low reported severity Internal Action

AI involvement disputed · Causal attribution disputed · 2 sources · Added 16/09/2026

Cases may have several effects and sources. Mixed accounts qualify when they include a reported harm or adverse experience. People are counted within individual cases where sources support a number; we do not publish a collection-wide total of distinct people.

A source’s existence, the experience it reports and AI’s causal role are separate questions. A lawsuit records allegations unless a subsequent finding establishes them.

Methodology and corrections · Subscribe via RSS · Suggest a case or correction · Find support

Last dataset update: 23/10/2026. Dataset available under CC BY 4.0.