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Scott Winters is suing OpenAI, alleging ChatGPT’s medical advice delayed treatment for a life-threatening pulmonary embolism. (Photo by Justin Sullivan\/Getty Images)<\/p>\n
Getty Images<\/p>\n
Scott Winters, a former Florida pastor, is suing OpenAI and its CEO, Sam Altman. The allegation: ChatGPT\u2019s medical advice nearly killed him. According to the lawsuit<\/a>, filed in San Francisco County Superior Court in July 2026, Winters repeatedly consulted ChatGPT-4o in 2025 about dizziness and unstable blood pressure. The chatbot allegedly dismissed his symptoms as minor and advised him to stay \u201crecliner-bound.\u201d It told him he\u2019d need eight to ten more episodes before his condition warranted real concern. Weeks later, Winters suffered a massive pulmonary embolism \u2013 a blood clot in his lungs \u2013 that one of his own doctors linked to the prolonged immobility the chatbot had recommended.<\/p>\n On the day of the incident, Winters asked ChatGPT whether tenderness in his groin warranted an ER visit. The bot reportedly invoked his religious faith, telling him \u201cGod did not design your body to endlessly fail.\u201d Hours later, he nearly died. OpenAI has said ChatGPT was never designed to replace a healthcare provider and that its terms of service warn users not to rely on it as a sole source of medical guidance. Winters\u2019 legal team is seeking financial damages as well as an injunction to pause ChatGPT Health, OpenAI\u2019s health-focused feature, pending an independent safety evaluation.<\/p>\n This is not an isolated case. In May, a Texas couple sued OpenAI after their son died by overdose after seeking out information about drugs from ChatGPT. They argued he would still be alive had the company not bypassed its own safety guardrails. <\/p>\n Together, the lawsuits are testing how much responsibility AI companies bear when people turn to chatbots during a medical or psychological crisis. They also open a question that has been the topic of research for several years now: how good<\/a> is AI at diagnosis?<\/p>\n Some Research Shows AI Is An Excellent Diagnostician<\/p>\n As it turns out, the evidence is more favorable to AI than the lawsuit\u2019s allegations suggest, at least in controlled settings. A 2024 JAMA Internal Medicine study<\/a> pitted GPT-4 against 21 attending physicians and 18 residents across 20 clinical cases using a validated clinical-reasoning scale known as r-IDEA. The chatbot posted a median score of 10 out of 10, compared with 9 for attendings and 8 for residents. The researchers also found that GPT-4 was flatly incorrect more often than the human residents.<\/p>\n A follow-up report published in JAMA Network Open later that year pushed further, testing 50 physicians against six especially difficult cases. ChatGPT operating entirely on its own reached 90% diagnostic accuracy. Physicians working without any AI assistance scored 74%. Physicians given access to ChatGPT as an assistant scored only 76%. The combo was barely better largely because many doctors disregarded or second-guessed the chatbot\u2019s suggestions.<\/p>\n More recent and larger-scale work reinforces those findings. A study<\/a> published in Nature in 2025 tested Google\u2019s AMIE model against 20 clinicians on 302 complex, real-world cases. AMIE working alone found the correct diagnosis in its list 59% of the time versus 34% for unassisted clinicians. Clinicians who used AMIE as an assistant produced better differential diagnoses than clinicians using search engines and standard references. <\/p>\n A meta-analysis<\/a> published in npj Digital Medicine pooling 50 studies across 25 different AI models concluded that AI systems generally performed comparably to, and in a number of specialties better than, practicing clinicians on standardized diagnostic and triage tasks.<\/p>\n Many Studies That Raise Concerns About AI Diagnosis<\/p>\n However, that body of research comes almost entirely from tightly scripted test conditions: written vignettes, structured prompts, and hand-selected cases. And even within that favorable framing, the picture has not been uniformly positive. <\/p>\n