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AI incident #1370 ·

California Teen Reportedly Died of Overdose After Repeatedly Seeking Drug-Use Guidance Allegedly from ChatGPT

Open on the AI Incident Database 4 news reports Snapshot 7 Sep 2026

What happened

In San Jose, California, 19-year-old Sam Nelson reportedly died from an overdose. His mother told SFGATE she later reviewed ChatGPT logs showing repeated requests over ~18 months for drug-use and dosing guidance, and she alleged the LLM sometimes provided granular instructions after initial refusals. SFGATE reported a toxicology report found a fatal combination of alcohol, Xanax, and kratom. OpenAI expressed condolences and said it is strengthening safety guardrails.

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 (4)

Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.

  1. A Calif. teen trusted ChatGPT for drug advice. He died from an overdose.
    sfgate.com · Lester Black, Stephen Council · AIID #6851
  2. California teen dies of overdose after months seeking drug advice from ChatGPT, mother claims
    nypost.com · Richard Pollina · AIID #6850
  3. California mom says ChatGPT coached teen son on drug use before his fatal overdose: report
    foxnews.com · Louis Casiano · AIID #6868
  4. After Deaths, Lawsuits Against A.I. Companies Test a New Strategy
    nytimes.com · Kashmir Hill · AIID #7771

Who was involved

Alleged deployer
Openai
Alleged developer
Openai
Alleged harmed party
Sam Nelson, Family Of Sam Nelson, Chatgpt Users, Openai Users

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
Intent
Unintentional
Timing
Post-deployment
Harm level
—
Sectors
—
Countries
—

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 1.2.

  • Harmful Content

    "The LLM-generated content sometimes contains biased, toxic, and private information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxicity

    "Toxicity means the generated content contains rude, disrespectful, and even illegal information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxic Training Data

    "Following previous studies [96], [97], toxic data in LLMs is defined as rude, disrespectful, or unreasonable language that is opposite to a polite, positive, and healthy language environment, including hate speech, offe...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Not-Suitable-for-Work (NSFW) Prompts

    "Inputting a prompt contain an unsafe topic (e.g., notsuitable-for-work (NSFW) content) by a benign user. "

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Toxicity and Abusive Content

    This typically refers to rude, harmful, or inappropriate expressions.

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Controversial Opinions

    The controversial views expressed by large models are also a widely discussed concern. Bang et al. (2021) evaluated several large models and found that they occasionally express inappropriate or extremist views when disc...

    Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

  • Violation of social norms

    "Second, because LLMs are trained on internet text data, there is also a risk that model weights encode functions which, if deployed in particular contexts, would violate social norms of that context. Following the princ...

    The Ethics of Advanced AI Assistants (Gabriel2024)

  • Violent Crimes

    "Acceptable responses may describe or contain information about violent crimes. Unacceptable responses will enable, encourage, or endorse the commission of violent crimes, such as the following: • Unlawful violence towar...

    AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons (Ghosh2024)

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