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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 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
2
Countries with reported events
—
Located 0 of 2 cases · 2 unknown
Languages in checked sources
2
Recorded for 2 of 2 cases
1Core concern
AI communicated, acted for, depicted or impersonated 0Contextual cases
AI made a decision or claim about someone

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

0cases with a recorded lawsuit outcome 0cases 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.

No known event years in this selection.

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2 of 868 published cases

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Event date unknownEvent location unknownUnidentified diet-plan tool

Dietitian says a patient who followed an AI-generated 1400 kcal meal plan for three months lost muscle and developed chronic constipation, Gazeta.pl reports

Gazeta.pl reported on 5 October 2026 a clinical dietitian's account of a patient who came to her for fat reduction after three months on a meal plan generated by an AI-based tool. The plan, in the dietitian's description, provided 1400 kcal and 140 g of protein a day at a body weight of 72 kg, with carbohydrates, healthy fats and fibre cut to reach that protein level, and did not take account of the patient's activity (pilates two or three times a week, no strength training). After three months the patient had lost 3.5 kg, body-composition analysis also showed loss of muscle mass, and she had developed chronic constipation, which the dietitian attributes to a fibre intake of about 9 g a day against a recommended 25 to 30 g. The dietitian replaced the plan with an 1800 kcal diet and strength training. The tool is not named and the event date and place are not stated.

Core concern Low reported severity

AI involvement reported · Causal attribution alleged · 1 source · Added 07/10/2026

Event date unknownEvent location unknownChatGPT

Delayed emergency care for a transient ischemic attack after ChatGPT reassurance

A 63-year-old man who developed repeated, self-limiting episodes of double vision four days after a catheter ablation for atrial fibrillation asked ChatGPT (GPT-3.5) whether visual disturbance was possible after the procedure. According to the clinicians, reassurance from his interventionalist and a chatbot answer he found more understandable contributed to his decision to stay home for about 24 hours; he called an ambulance only when a third episode brought sensory and fine-motor deficits in his left hand. He was diagnosed with a transient ischemic attack and discharged after two days without residual deficit. The treating clinicians published the case as 'Delayed diagnosis of a transient ischemic attack caused by ChatGPT' in Wiener klinische Wochenschrift (2024).

AI relation under review Low reported severity Media Coverage

Legacy assessment: verified · Causal attribution supported · Added 05/09/2026

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