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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

In this selection

Published cases
5
Countries with reported events
3
Located 5 of 5 cases · 0 unknown
Languages in checked sources
1
Recorded for 5 of 5 cases

2 cases have no reviewed AI-to-person relation yet: 1 not yet reviewed and 1 reviewed as unknown. Show these cases

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.

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

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.

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5 of 741 published cases

17 Sept 2023United StatesUnidentified facial recognition system

Reno casino's facial recognition wrongly matched a patron to a barred man and police jailed him for about eleven hours, his federal lawsuit alleges

Jason Killinger, a UPS truck driver, alleges in a federal civil-rights complaint filed in July 2025 that on 17 September 2023 the Peppermill Casino in Reno reported to police that its AI facial recognition software had identified him as a man barred from the casino months earlier. According to the complaint, casino security handcuffed him, and the responding Reno police officer, told the system had found a 100 percent match, did not examine his other identification and took him to jail as an unidentified person, where fingerprints confirmed who he was. The complaint says he was handcuffed for about four hours, starting in the casino security office, spent about eleven hours in police and jail custody, and was treated the next day for bruised wrists. According to the complaint, he was then charged with trespassing, and a prosecutor dismissed the charge without prejudice at the bench trial. Casino.org reports that he settled a suit against the casino. In March 2026 the court let him add the City of Reno and a municipal liability claim over facial recognition policies, but refused a new wrongful arrest claim against the officer on qualified immunity grounds. In September 2026 the ACLU, the ACLU of Nevada and the Innocence Project filed a proposed amicus brief supporting him. His September 2026 motion for partial summary judgment says a Reno police detective later concluded that the match was wrong and that he and the barred man were different people, and it cites a declaration by a former casino security officer, who worked there from about October 2024, that the system often alerted at 100 percent on the wrong people; in a declaration reported by Casino.org, the officer said he had never known the system to misidentify anyone. The case is ongoing.

Contextual tracker case Medium reported severity Lawsuit Ongoing

AI involvement reported · Causal attribution alleged · 9 sources, 3 underlying accounts · Added 04/10/2026

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

Nov 2025United StatesChatGPT

Prosecutor: judge used ChatGPT citations in Oklahoma custody order later vacated

In November 2025 Stephens County Associate District Judge Lawrence Wheeler issued an order in a child paternity and custody case that denied one parent's request for a psychological evaluation of the other parent and reprimanded the requesting parent's attorney 'for stooping to such frivolous trial tactics'. The attorney challenged the order at the Oklahoma Supreme Court in February 2026, telling the justices that it relied on two cases that do not exist; the challenge was dismissed in March after Wheeler vacated the order, and he is no longer on the case. According to a 17 August 2026 letter from the Stephens County district attorney, Wheeler told the Oklahoma State Bureau of Investigation that he used ChatGPT for research and wrote the order himself, and that at least two citations in it produced by ChatGPT do not exist. The mother in the case told News 9 that learning the order's citations were allegedly fabricated was alarming because it concerned the custody of a child. The attorney general's office declined criminal prosecution; judicial discipline remains possible.

Contextual tracker case Low reported severity Investigation Opened

AI involvement supported · Causal attribution supported · 4 sources, 1 underlying account · Added 29/09/2026

24 Jul 2026 to 26 Jul 2026IndiaUnidentified facial recognition system

Delhi: the police facial-recognition system logged at least 25 people who were in Tihar, Mandoli or Rohini jails as present at the Jantar Mantar student protests (20 to 26 July 2026), with timestamps on 24 to 26 July, on a sworn list of 2,873 persons with 'criminal antecedents' that the Supreme Court allowed police to register a fresh FIR against (Indian Express investigation, 4 September 2026)

In an affidavit of 17 August 2026 before the Supreme Court of India, Delhi Police said its Facial Recognition System (FRS) had identified 2,873 people with criminal antecedents at the Jantar Mantar protests of 20 to 26 July 2026 (2,402 through its 'Crime Kundli' biometric database and 471 through other criminal records). On 1 September the Court quashed the FIRs against the student protesters but let the police proceed against the 2,873; the police say any action will follow field verification. The Indian Express checked the 205 listed people facing murder, attempted-murder, rape or child-sexual-offence charges against police, prison and court records and found that at least 25 of them (17 accused of murder, four of rape (two or three under POCSO; the Express's narrative and its list differ), four of attempted murder) were lodged in Delhi's Tihar, Mandoli or Rohini prisons when the system logged them at the protest site with timestamps on 24, 25 and 26 July; some had been in custody for years. Delhi Police told the newspaper that further verification of the 2,873 was pending and, in its affidavit, that no action is taken solely on a facial-recognition result and that field verification follows each match. The police disclosed in 2022, in reply to a Right to Information request, that it treats a match with an 80 per cent similarity score as positive. Whether any of the 25 has since been named in the fresh FIR or visited for verification is not reported.

Contextual tracker case Medium reported severity Investigation Opened

AI involvement reported · Causal attribution supported · 4 sources, 2 underlying accounts · Added 24/09/2026

14 Jul 2025 to 24 Dec 2025United StatesClearview AI facial recognition (reported)

Tennessee grandmother Angela Lipps jailed five months on an AI facial-recognition misidentification; charges dismissed after bank records placed her 1,200 miles away

On 14 July 2025, U.S. Marshals arrested Angela Lipps, a 50-year-old Tennessee grandmother, at gunpoint at her home while she was babysitting four children, on a nationwide-extradition North Dakota warrant: West Fargo police's AI facial-recognition technology had tied her to bank-fraud surveillance of a woman using a fake U.S. Army military ID to withdraw tens of thousands of dollars. She fought extradition for about three months in a Tennessee jail, was booked into Cass County, North Dakota on 30 October 2025 on four counts of unauthorized use of personal identifying information and four counts of theft, and was released on 24 December after her bank records showed her more than 1,200 miles away in Tennessee; charges were dismissed without prejudice. Fargo's police chief acknowledged 'incorrect assumptions' linked to the AI identification; an email obtained by KVLY shows six Fargo detectives were notified of her arrest in July, nearly five months before the department says it knew she was in custody. She lost her home, her car and her dog; her attorneys are pursuing potential civil-rights claims, with no lawsuit filed as of 31 March 2026. On 15 September 2026 she filed a $10 million federal civil-rights suit in the District of North Dakota against the City of Fargo and the detective, alleging he relied on a flawed facial-recognition match and ignored exculpatory evidence.

Contextual tracker case High reported severity Lawsuit Filed

AI involvement supported · Causal attribution supported · 5 sources, 3 underlying accounts · Added 15/09/2026

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.

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Last dataset update: 18/10/2026. Dataset available under CC BY 4.0.