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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 is wider: it also records consequential decisions and claims about people. 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
3
Countries with reported events
1
Located 3 of 3 cases · 0 unknown
Languages in checked sources
1
Recorded for 3 of 3 cases
1Core concern
AI communicated, acted for, depicted or impersonated 3Contextual 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.

2cases with a recorded lawsuit outcome 0cases with a recorded regulatory response 1cases 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.

1 20242 2025
Reported severity HighMedium
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3 of 404 published cases

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20 Oct 2025United StatesOmnilert gun detection

Baltimore County, Maryland: school AI gun alert on a bag of chips leads to police search of a student

On a Monday evening in October 2025 (20 October by the reports' weekday references) an AI gun detection system (Omnilert) used at Kenwood High School alerted on a student holding an empty bag of chips. Police responded and searched the student and found no weapon. The student told a local television station that officers made them kneel, handcuffed them and pointed a gun at them. The school district says its security department reviewed and canceled the alert after confirming there was no weapon, and a district spokesperson said the principal did not immediately realize the alert had been canceled. County councilmembers called for a review. No outcome of a review is established in the sources.

Contextual tracker case Medium reported severity Involving minors

AI involvement supported · Causal attribution supported · 3 sources, 2 underlying accounts · Added 29/09/2026

14 Feb 2024United StatesFlock Safety license plate readers

York County, South Carolina: Iraq War veteran Steven Melvin says deputies held him at gunpoint and made him kneel for more than five minutes outside his Lake Wylie apartment complex in February 2024 after a Flock license-plate reader misread his plate and flagged his BMW as stolen; he sued in June 2026

According to a lawsuit filed on 29 June 2026 and reported by The Herald (Rock Hill), a York County sheriff's deputy stopped Steven Melvin, 42, on 14 February 2024 as he pulled into his apartment complex near Lake Wylie, after receiving a Flock license-plate-reader alert that a stolen dark-coloured BMW sedan was in the area. The deputy approached Melvin's black BMW with his gun drawn and aimed at him and made him kneel with his hands over his head for more than five minutes; after calling for backup and checking his information, the deputy determined the car was not stolen. The camera had read the first letter of his South Carolina tag incorrectly, matching a stolen BMW one letter off. A sheriff's internal-affairs review in November 2024 found the deputy's actions reasonable and blamed an illegally tinted plate cover, for which Melvin received a verbal warning; an email cited in the filing says the cameras had read his plate correctly 13 times that month. Melvin says the stop caused him trauma and emotional distress. The sheriff's office removed the case to federal court in August 2026 and denies violating his rights.

Contextual tracker case Medium reported severity Lawsuit Filed

AI involvement reported · Causal attribution supported · 4 sources, 2 underlying accounts · Added 28/09/2026

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: 30/09/2026. Dataset available under CC BY 4.0.