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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

Explore incidents Our scope and evidence

In this selection

Published cases
3
Countries with reported events
2
Located 3 of 3 cases · 0 unknown
Languages in checked sources
1
Recorded for 3 of 3 cases
2Core 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

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.

3 2026
Reported severity Low
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3 of 741 published cases

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26 Mar 2026 to 19 Aug 2026AustraliaUnidentified AI drafting tool

Fair Work Commission orders former Aldi worker to pay A$1,230 costs after his AI-drafted unfair dismissal claim kept arguing the wrong date

On 19 August 2026 a Deputy President of Australia's Fair Work Commission ordered a self-represented former Aldi store worker to pay A$1,230 towards Aldi's legal costs. The decision records that his unfair dismissal application, lodged on the evening he was told of his dismissal on 26 March 2026, was obviously prepared using AI and still contained AI drafting notes, and that every email and document he filed was drafted using AI. He was notified of his dismissal three days short of the six-month minimum employment period. According to the decision, his AI-generated materials kept arguing about a different, irrelevant date (when the dismissal took effect), including after the Commission explained the correct test to him twice by email on 31 July 2026. He discontinued at the hearing on 5 August 2026. The Deputy President found that continuing after those warnings was unreasonable and said it was quite possible he had adopted AI as his quasi-legal adviser, while stating that using AI to draft submissions is not of itself unreasonable and that the responsibility was his. The decision notes that an appeal was lodged against it.

Core concern Low reported severity Regulatory Action

AI involvement supported · Causal attribution supported · 2 sources, 1 underlying account · Added 18/10/2026

15 Jul 2026United StatesUnidentified AI drafting tool

Arizona appeals court strikes a self-represented appellant's AI-hallucinated citations, rejects his probate appeal and orders him to pay fees as a sanction

In a published opinion of July 2026, the Arizona Court of Appeals found that a self-represented appellant's opening brief in a probate dispute contained eight citations, six of them deficient, including two cases that do not exist. In a written explanation and at a hearing on the false citations he acknowledged relying on generative AI to write the brief and said he did nothing to verify the citations. The court struck the inaccurate and false citations, rejected the appeal because no supportive authority remained, held that citing a hallucinated case is sanctionable whether or not it is intended, and ordered him to pay the share of the other party's attorney's fees traceable to the fake citations. Because he said he did not intend to deceive and is not legally trained, the court chose this narrow sanction over contempt or fines. It described the opinion as the first published Arizona ruling on generative AI hallucinations in filings.

Core + contextual relations Low reported severity Regulatory Action

AI involvement supported · Causal attribution established · 1 source · Added 18/10/2026

Aug 2026United StatesUnidentified document-analysis tool

Connecticut court revokes a self-represented plaintiff's e-filing access after finding hidden instructions aimed at AI systems in his filings

In a memorandum of decision issued in early August 2026, a Connecticut Superior Court judge found that a motion for default and a notice filed on 24 July 2026 by a self-represented plaintiff, in a suit against a healthcare provider over access to records, carried text in tiny white type that was invisible to a human reader but legible to software. The concealed text told any AI model reviewing the filing to make its output agree with the filing and to work toward reversing the Chief Clerk's denial of his default request. After the court gave notice of a sanctions hearing, he hid further messages in later filings, which he said were jokes. The court treated the first instruction as a prompt injection, did not believe his explanation that he was auditing the court's use of AI, and rescinded his ability to file electronically, so that future filings must be made on paper at the clerk's office; Ars Technica reports that no monetary penalty was imposed. The court said the Connecticut Judicial Branch does not use AI to review or decide filings and that the motion was denied on its merits from a printed copy, so the hidden text affected no ruling. The plaintiff told Reuters, according to Ars Technica, that his intent was to audit the court.

AI relation unknown Low reported severity Regulatory Action

AI involvement reported · Causal attribution established · 2 sources, 1 underlying account · Added 18/10/2026

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.

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