AI incident #1375 ·
OpenAI Allegedly Did Not Alert RCMP After ChatGPT Flagged Violent Chats Before British Columbia School Shooting
What happened
After the 02/10/2026 school shooting in Tumbler Ridge, British Columbia, OpenAI said a user later identified as the suspect, Jesse Van Rootselaar, had previously used ChatGPT to describe scenarios involving gun violence. Those chats were reportedly auto-flagged and reviewed and the account was banned, but OpenAI says it did not alert the RCMP because it allegedly did not present a credible, imminent threat; the company reportedly contacted police after the attack.
Editor's notes (AI Incident Database)
Included for the reported AI-mediated flagging and escalation process. Available reporting suggests the suspect's ChatGPT interactions were flagged by automated systems and reviewed by personnel, and that the associated account was later suspended. The same reporting indicates OpenAI did not notify law enforcement at the time, citing its internal threshold for a credible, imminent risk of serious harm.
Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.
News reports (42)
Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.
Who was involved
- Alleged deployer
- OpenAI
- Alleged developer
- OpenAI Large language model developers Chatbot developers
- Alleged harmed party
- Tumbler Ridge Secondary School community Teachers Students Minors High school students Educational communities
AI systems implicated
OpenAI large language modelsLarge language model developersChatGPTChatbot developersAI-enabled decision support systems
Classification (MIT AI Risk Repository taxonomy)
- Risk domain
- Socioeconomic & Environmental Harms
- Risk subdomain
- 6.5 Governance failure
- Causal entity
- Human
- Intent
- Other
- Timing
- Post-deployment
- Harm level
- —
- Sectors
- —
- Countries
- —
Risk entries describing this failure mode
Entries from the MIT AI Risk Repository coded to subdomain 6.5.
- Mobility
"Despite the promise of streamlined travel, AI also brings concerns about who is liable in case of accidents and which ethical principles autonomous transportation agents should follow when making decisions with a potent...
- Liability issues in case of accidents
"Despite the promise of streamlined travel, AI also brings concerns about who is liable in case of accidents and which ethical principles autonomous transportation agents should follow when making decisions with a potent...
- Faster scientific progress makes it harder for governance to keep pace with development
"Exacerbating these problems is that faster scientific progress would make it even harder for governance to keep pace with the deployment of new technologies. When these technologies are especially powerful or dangerous,...
- Type 1: Diffusion of responsibility
Societal-scale harm can arise from AI built by a diffuse collection of creators, where no one is uniquely accountable for the technology's creation or use, as in a classic "tragedy of the commons".
- Products Liability Law
"Like manufactured items like soda bottles, mechanized lawnmowers, pharmaceuticals, or cosmetic products, generative AI models can be viewed like a new form of digital products developed by tech companies and deployed wi...
- Institutional responsibilities
"Efforts to deploy advanced assistant technology in society, in a way that is broadly beneficial, can be viewed as a wicked problem (Rittel and Webber, 1973). Wicked problems are defined by the property that they do not...
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
"Another difficulty facing AI assistant systems is that it is challenging to develop metrics for evaluating particular aspects of benefits or harms caused by the assistant – especially in a sufficiently expansive sense,...
- Benchmarking (Cross-lingual data contamination)
"Models that have been trained on data encoded in multiple languages, such as LLMs trained on web-crawled data, may contain contamination that is obscured by translation [226]. The most basic form of this is when a bench...
Related incidents on the AI Incident Database
Linked by AIID editors or by its text-similarity model.
Incidents in the same risk subdomain
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- ChatGPT Was Alleged to Have Reinforced Pittsburgh Man's Stalking and Threats Against Women
- Sora Video Generator Has Reportedly Been Creating Biased Human Representations Across Race, Gender, and Disability
- GPT-2 Reportedly Reproduced Personal Data from Its Training Data