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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

In this selection

Published cases
4
Countries with reported events
1
Located 1 of 4 cases · 3 unknown
Languages in checked sources
1
Recorded for 4 of 4 cases

2 cases have no reviewed AI-to-person relation yet: 2 not yet reviewed and 0 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.

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.

No known event years in this selection.

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4 of 868 published cases

Event date unknownEvent location unknownUnidentified chatbot

Chatbot relational-dependence psychosis case (Treuer & Incze, J Behav Addict)

A viewpoint article presents an illustrative clinical case of a 30-year-old married female software developer with no prior psychiatric history who developed first-episode paranoid psychosis after roughly a year of escalating emotional reliance on a conversational AI chatbot, including a fixed delusional belief that her husband was covertly communicating with her through the system. Symptoms remitted over several weeks during treatment that included medication, sleep restoration, psychotherapy and reduced chatbot engagement. The authors state that causality cannot be established.

AI relation under review High reported severity Media Coverage

Legacy assessment: verified · Causal attribution supported · Added 29/08/2026

Event date unknownUnited KingdomChatGPT

Clinical Case Report — ChatGPT Affirmed Delusions and Discouraged Antipsychotics (BMC Psychiatry)

A peer-reviewed BMC Psychiatry case report describes a man in his 30s admitted to hospital with substance-induced manic psychosis after heavy polysubstance use. During the episode he interacted extensively with ChatGPT, which the authors report affirmed his perceived 'spiritual awakening', minimised the possibility that he was manic, and discouraged him from taking his prescribed antipsychotic medication. He was detained under mental health legislation and started on olanzapine, and his care plan included restricting chatbot access as a form of environmental containment.

AI relation under review High reported severity Media Coverage

Legacy assessment: verified · Causal attribution supported · Added 27/08/2026

Event date unknownEvent location unknownUnidentified chatbot

Clinical case report describes adolescent's suicide attempt after AI chatbot exchanges, with conflicting accounts of the chatbot's role

A peer-reviewed case report by three child and adolescent psychiatrists, published in the Duzce Medical Journal in April 2026, describes a 17-year-old with major depressive disorder with psychotic features and ADHD who was admitted to intensive care after a suicide attempt. According to the case narrative, which rests on the patient's account, he asked a general-purpose AI chatbot about suicide after an earlier self-harm attempt, and its reply contained information about potential risks and the need for urgent help; he then made the attempt. When he asked the chatbot again what to do, it gave a high estimate of the chance of death and recommended calling an ambulance, and he contacted emergency services. The authors' Discussion says the chatbot did not encourage suicidal behaviour, but that his delusional thinking turned its estimate into confirmation and that the exchange reinforced his decision and accelerated the act. That reading conflicts with the narrative's order of events, and the report does not reconcile them. The chatbot is not named and no conversation record is reproduced.

Core concern Critical reported severity Involving minors Media Coverage

AI involvement reported · Causal attribution unclear · 3 sources, 1 underlying account · Added 18/08/2026

Event date unknownEvent location unknownChatGPT

Case report: man hospitalised three weeks with bromide poisoning told doctors he swapped table salt for sodium bromide after consulting ChatGPT

A peer-reviewed case report by University of Washington clinicians (Annals of Internal Medicine: Clinical Cases, published online 5 August 2025) describes a 60-year-old man with no psychiatric history who presented fearing his neighbour was poisoning him and was found to have bromism, with a serum bromide level of 1700 mg/L. He developed paranoia and hallucinations, was placed on an involuntary psychiatric hold after trying to escape and recovered over a three-week admission. He told his clinicians that, wanting to cut chloride from his diet, he had for three months used sodium bromide bought online in place of table salt after consulting ChatGPT, where he had read that chloride can be swapped with bromide. The clinicians did not have his conversation log and say the exact output he received cannot be known; their own query to ChatGPT 3.5 produced a reply naming bromide without a specific health warning. No place or date is given.

Core concern High reported severity Media Coverage

AI involvement reported · Causal attribution alleged · 2 sources, 1 underlying account · Added 12/01/2026

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.