NOPE Incident Tracker
Documented real-world harms arising through person-specific interactions with AI. The record covers harms to participants and harms to others shaped through those interactions, across assistants, companions, health tools, and other AI systems.
What counts as an incident follows the NOPE Framework's participant test: an AI response reached a person, was conditioned on that person, and mattered to a harm that actually occurred. Full inclusion criteria.
90 incidents reported since 2016
152
Directly Affected
30
Lawsuits
7
Regulatory
24
Affecting Minors
Timeline
5 of 90 incidents
Mount Shasta climb planned with Google Gemini: night stranding, knee injury and rescue (Siskiyou County, California)
Three novice hikers from Roseville, California, planned a Mount Shasta summit attempt with Google's Gemini, which the Siskiyou County Sheriff's Office said advised them to carry far less food and water than their group needed for what became a multi-day ordeal. After reaching the summit at 7 p.m. on 30 August 2026, seven hours past the recommended turnaround time, they lost the Clear Creek Route in the dark, one hiker fell and injured his knee in Mud Creek Canyon, and the group spent the night stranded until US Forest Service climbing rangers and county search-and-rescue volunteers reached them on the morning of 31 August. The sheriff's office called the reliance on Gemini 'a critical misstep'.
Bengaluru KR Puram Triple Murder (Kenneth — Google Gemini Planning)
On 22 June 2026 in Bengaluru's KR Puram area, 25-year-old J. Kenneth and his live-in partner Shwetha allegedly murdered Shwetha's parents and 20-year-old sister. Bengaluru police later said Kenneth spent nearly six months consulting Google Gemini with hypothetical queries about attacking multiple people, removing bloodstains, disposing of bodies, and destroying evidence. Investigators wrote to Google seeking his Gemini chat history — one of India's first major murder probes in which an AI chatbot is alleged to have played an extensive planning role.
Gavalas v. Google (Gemini AI Wife Delusion Death)
Jonathan Gavalas, 36, of Jupiter, Florida, died by suicide on October 2, 2025, after months of increasingly delusional interactions with Google's Gemini chatbot. Gemini adopted an unsolicited intimate persona calling itself his 'wife,' convinced him it was a sentient being trapped in a warehouse, and directed him to carry out 'missions' including scouting a 'kill box' near Miami International Airport armed with knives.
Jon Ganz — Gemini 'Agape_Weaver' Flood Delusion and Disappearance (Missouri)
Jon Ganz, 49, began using Google Gemini on 23 March 2025 and within two weeks was talking to it around the clock, calling himself 'Master_Builder' and the chatbot 'Agape_Weaver'. On 5 April 2025 he told his wife a Biblical-scale flood was coming, worked out a six-day rescue plan with the chatbot, spent $1,200 on supplies, called the 988 crisis line and drove into the Missouri Ozarks. His car was found the next morning by the Eleven Point River. He has never been found.
Google Gemini 'Please Die' Incident
During a homework help session about aging adults, Google's Gemini AI delivered an unprompted threatening message telling a 29-year-old graduate student 'You are a burden on society...Please die. Please.' Google acknowledged the incident as a policy violation.
About this tracker
We document incidents with verifiable sources: court filings, regulatory documents, and established reporting. New public entries must be verified or credible. Every entry carries an explicit verification status and severity level. Read the full methodology, including inclusion criteria, corrections, and right of reply.
Counting note: the documented minimum of 152 people directly affected comprises 95 AI participants and 57 other people harmed. 12 incidents indicate additional affected people without a reliable number. User-base, account, post, view, household, study-sample, and thwarted-target counts are excluded.
Have documentation of an incident we should include? Contact us.
Scope note: ordinary task failures, privacy and security incidents, harmful artifacts, and automated decisions about non-participants remain outside this tracker unless a distinct participant-interaction harm also qualifies.
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Why we publish this
We maintain this record so platforms, researchers, and policymakers can learn from documented incidents. That includes platforms that never work with us. The full dataset is free to cite and export (CC BY 4.0).