Almost one in five AI-generated diagnoses (18%) were flat-out false or dangerously misleading when medical images were omitted from the query. GPT-5 also showed racial bias: in 77% of hypothetical chest X-ray cases involving young Black patients, it diagnosed sarcoidosis without further context.
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Expert: Carnegie Mellon University researchers, School of Computer Science Carnegie Mellon University School of Computer Science researchers found that when medical images were omitted from the query, almost one in five AI-generated diagnoses (18%) were flat-out false or dangerously misleading. The researchers warn that LLMs "don't possess genuine understanding or clinical reasoning... When they lack sufficient data or context, instead of admitting uncertainty, they sometimes invent information to fill the gap." The study also documented racial bias in GPT-5: in 77% of hypothetical chest X-ray cases involving young Black patients, the model diagnosed sarcoidosis without further context. A real physician would consider a wider differential diagnosis and order further tests before concluding — the AI instead filled the information gap with a confident, unsubstantiated answer. Source: https://www.thetechedvocate.org/this-one-thing-about-ai-chatbots-self-diagnosis-could-land-you-in-the-er/
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