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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
42
Countries with reported events
10
Located 33 of 42 cases · 9 unknown
Languages in checked sources
10
Recorded for 42 of 42 cases
38Core concern
AI communicated, acted for, depicted or impersonated 4Contextual cases
AI made a decision or claim about someone

1 case has no reviewed AI-to-person relation yet: 0 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.

0cases with a recorded lawsuit outcome 5cases with a recorded regulatory response 7cases involving minors

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

When events happened

42 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.

No known event years in this selection.

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42 of 404 published cases · page 3 of 3

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Event date unknownUnited KingdomUnidentified video tool

Ards and North Down, Northern Ireland: a person lost £250,000 to an investment fraud that began with an AI-generated video of a well-known financial personality

On 7 September 2026 the Police Service of Northern Ireland (PSNI) said a person in the Ards and North Down area had lost £250,000 in what it called a 'sophisticated and substantial' investment fraud. The victim first saw what appeared to be an AI-generated online video featuring a well-known personality from the financial sector promoting an investment with significant returns. After investing a small amount the victim was contacted on WhatsApp and encouraged to pay more, persuaded to open multiple online accounts, to allow the fraudsters remote access to a computer 'to assist with the investment', to borrow money to keep investing, and finally to make further payments to 'release' funds supposedly held in the investment. The PSNI did not name the personality; BBC News NI noted that fabricated endorsements of financial experts such as Martin Lewis, Peter Jones and Steven Bartlett circulate online.

Core concern High reported severity Investigation Opened

AI involvement reported · Causal attribution supported · 3 sources, 1 underlying account · Added 18/09/2026

Event date unknownUnited StatesFlock Safety license plate readers

San Jose: police officer fired after passing Flock license-plate-reader location data to a relative accused of domestic violence, who used it to find his accuser

San Jose's police chief announced on 11 September 2026 that an officer had been fired after accessing the department's Flock Safety automated license-plate-reader data on his personal phone and giving a vehicle's location to his cousin, a suspect in a domestic-violence case, who used it to locate the woman accusing him. The chief called it 'a betrayal of the public trust', said the officer was placed on leave, criminally investigated and referred to the district attorney, and that the case was submitted to California's peace-officer standards commission for decertification; neither the officer nor the cousin has been charged. The department has since barred access to the system from personal devices and is testing auditing tools. Neither the victim nor the officer is named in the inspected reports.

Contextual tracker case Medium reported severity Internal Action

AI involvement supported · Causal attribution supported · 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.

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