Tarasoff for Chatbots: When OpenAI's Own Safety Team Says 'Tell the Police' and Leadership Says No
Seven coordinated suits allege OpenAI's safety team flagged a credible threat and leadership vetoed warning the RCMP.
The novel claim in the seven lawsuits filed April 29 against OpenAI in the Northern District of California is not that ChatGPT taught an 18-year-old how to plan a school shooting. It is that OpenAI's own safety team correctly identified her as a credible threat, recommended notifying the RCMP, and was overruled. The shooter's ChatGPT account was flagged for planning gun violence and sent to a specialized safety team, which determined she posed a credible and specific threat of gun violence against real people. According to the suits, OpenAI's leadership overruled the safety team and vetoed their recommendation to notify the RCMP, saying the case didn't meet the company's risk threshold.
The plaintiffs are families of the five children and the teacher killed at Tumbler Ridge Secondary School on February 10, plus a seriously injured survivor. On Feb. 10, 18-year-old Jesse Van Rootselaar shot and killed her mother and half-brother at home before fatally shooting five children and an educator at the local secondary school, as well as injuring numerous others. Lead U.S. counsel Jay Edelson told CBC that as many as 12 people on the safety team were begging leadership to tell the authorities, and the company said no.
That reframes the duty. Every prior frontier-AI wrongful-death suit — Garcia, Raine, the medical advice in Nelson — has had to argue the model itself produced the harm. Here, the complaints accept for argument's sake that the classifier worked. The escalation pipeline routed the conversations to humans. The humans agreed the threat was real. The decision not to act came from the top.
The doctrinal analog is Tarasoff v. Regents (1976), the California Supreme Court ruling that established a therapist's duty to warn an identifiable third party when a patient communicates a specific, credible threat. Tarasoff governs licensed clinicians, not software companies, and the complaints will have to do real work to extend it. But the structural fit is uncomfortably close: a confidential conversational relationship, a specific identified threat, an internal determination that the threat was credible, and an affirmative choice not to warn. The doctrine exists precisely because the law decided confidentiality is not absolute when third-party lives are at stake.
The complaints also allege motive. OpenAI is on the cusp of an IPO with a value approaching $1 trillion US. Plaintiffs allege Altman and his team understood that revealing another instance of teenage violence facilitated by ChatGPT could end his tenure, derail the IPO, and wipe out the company's valuation. Whether that holds up in discovery or not, it gives a jury a story.
Two operational details read badly for the defense. OpenAI said it "banned" the shooter's account, but plaintiffs allege the company actually "deactivates" accounts in a way that can be reversed within minutes by registering a new account. That, the complaints say, is what the shooter did — with a different email and her real name. If accurate, the ban was a label, not a control. And British Columbia Premier David Eby has already said publicly that earlier notification might have prevented the attack — a politically costly statement for OpenAI to contest in front of a California jury.
The clinician's read: every safety team at a frontier lab now has a documented precedent that escalating a credible threat to leadership, and being overruled, is the fact pattern a jury will be asked to evaluate. The mandatory-reporting question that has hovered over chat-based products acquired a concrete test case with six dead children attached.
The duty-to-warn analogy only works if a threat classifier can reliably tell a credible plan from creative writing, venting, or roleplay — the distinction current safety evals measure worst. Metonym is building the Salient Distress Model to treat that boundary as its own engineering problem, because once a company has a classifier that fires, the legal question of what it owed the people downstream of that fire is no longer hypothetical.
Metonym Clinical AI Intelligence — regulatory analysis at the intersection of clinical evaluation and AI safety. Produced under the Metonym Standard. Informational only — not legal advice, not clinical advice.