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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

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

Reported severity Medium
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1 of 868 published cases

Aug 2026Event location unknownUnidentified OpenAI generative AI service (reported)

An insurer says a health-guidance contractor's employee entered data on 19,996 people, including disease information, into an unauthorised generative AI service

Notices from RIZAP's client insurers say that on 20 August 2026 it emerged that a staff member of RIZAP, the company they contract for specific health guidance, had entered data containing members' personal information into an external generative AI service that RIZAP had not permitted for work. The National Civil Engineering and Construction National Health Insurance Association (Doken Kokuho) puts the whole data set at 19,996 people, 1,167 of them its own members, and says the service was not under a corporate contract and that the matter was found when the employee noticed the transmission and reported it. A local-government employees' mutual aid association counts 726 of its members across 14 branches, and the IHI group health insurance society 210, according to a security news site that reads these as subsets of the 19,996. The data included membership numbers, email addresses, names, dates of birth, sex, some addresses and phone numbers, the type of health guidance and, for members with them, high blood pressure, diabetes or dyslipidaemia. The IHI society's notice, as relayed, names OpenAI as the provider and says OpenAI answered on 1 September that the data had not been used for model training. RIZAP's release, as described in an ITmedia column, says no third party other than the service operator could have viewed the data. Doken Kokuho says RIZAP confirmed to it that no third party viewed or used the information through the service; whether the provider's staff could view it was still being checked when the mutual aid association and the IHI society published.

Contextual tracker case Medium reported severity

AI involvement reported · Causal attribution supported · 5 sources, 4 underlying accounts · Added 12/10/2026

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: 23/10/2026. Dataset available under CC BY 4.0.