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
3
Countries with reported events
—
Located 0 of 3 cases · 3 unknown
Languages in checked sources
1
Recorded for 3 of 3 cases
1Core concern
AI communicated, acted for, depicted or impersonated 1Contextual 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 3cases 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

2 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 2025
Reported severity Low
More filters: AI relation, use, setting, sources and responses
Clear filters

3 of 868 published cases

Export JSONExport CSV
Event date unknownEvent location unknownUnidentified AI-text detector

Ombudsman upholds autistic student's complaint over AI-misconduct zero mark from panel with detection-software report; student says provider later cleared them

A case summary published in July 2025 by the Office of the Independent Adjudicator for Higher Education (OIA), the independent student complaints scheme for England and Wales, describes a student with autism who was accused of including large sections of AI-generated content in an essay. The student denied using AI and submitted planning and notes. A disciplinary panel, which had the provider's AI detection software report and compared the essay with other work by the student, found academic misconduct and gave a mark of zero with any reassessment capped at a pass; the provider rejected the appeal, in which the student said the same software had earlier flagged another of their essays in a case where it had been agreed they had not used AI. The OIA found the complaint Justified: the panel had not properly considered the student's evidence, had not shared some evidence it relied on, and had not given sufficient reasons. It recommended reconsideration and changes to the provider's rules, and the student told the OIA that on reconsideration the provider decided there had been no misconduct. The provider and the software are not named.

Contextual tracker case Low reported severity Regulatory Action

AI involvement reported · Causal attribution supported · 2 sources · Added 23/10/2026

Event date unknownEvent location unknownUnidentified AI writing tool

Student complaints ombudsman finds a zero mark reasonable for a dissertation the student said was written with help from unacknowledged AI

A case summary published in July 2025 by the Office of the Independent Adjudicator for Higher Education (OIA), the independent student complaints scheme for England and Wales, describes a student who was called to a viva over concerns about a dissertation and told the examiners there that AI had been used to help write it. The student agreed the AI material was not referenced and had not declared the AI use on the form the provider required. A panel found academic misconduct and gave a mark of zero; the provider rejected the student's appeal. The student complained to the OIA, saying they received no credit for being honest about using AI or for the time and effort invested. The OIA found the complaint Not Justified, concluding that the provider followed its procedures, gave the student a fair opportunity to respond and applied a proportionate penalty. The summary does not name the provider, give the date of the events or say which AI tool was used.

AI relation unknown Low reported severity Regulatory Action

AI involvement reported · Causal attribution supported · 2 sources · Added 23/10/2026

Sept 2025Event location unknownRevolut chatbot

Ombudsman finds Revolut misled a customer after its chatbot said his loyalty points were worth £1,119 and confirmed a refund; compensation raised to £100

In September 2025 a Revolut customer asked the bank, through its chatbot, to cash in loyalty points he had earned through its spare change feature. According to the Financial Ombudsman Service's final decision (DRN-6062372), the chatbot first said the 1,119 points would be refunded as £22.38; four days later it told him the 1,119 points had a cash value of £1,119, offered that as a one-time goodwill gesture and confirmed it had processed the refund. A few hours later the chatbot said that information was wrong; a live agent then said the £1,119 refund was being processed, and the next day the chatbot said it had issued £22.38. Revolut upheld his complaint and paid £50. The ombudsman found that Revolut gave him the wrong information on several occasions that day, held that he was never entitled to £1,119, and directed Revolut to pay a further £50. The customer said the lost expected refund caused financial pressure, and gave a GP letter describing anxiety and insomnia.

Core concern Low reported severity Regulatory Action

AI involvement supported · Causal attribution supported · 1 source · Added 15/10/2026

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.