Asked to identify a health condition from symptoms and recommend next steps, the LLM chatbot produced "a mix of good and bad information" — including wrong diagnoses and advice that failed to recognise when urgent help was needed.
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Expert: Dr Rebecca Payne; Andrew Bean, GP and co-author, University of Oxford; Lead author, Oxford Internet Institute In a study published in Nature Medicine, researchers from the University of Oxford's Internet Institute and Nuffield Department of Primary Care Health Sciences asked nearly 1,300 participants to identify potential health conditions and recommend a course of action — some using large language model (LLM) chatbots to get a potential diagnosis and next steps, others using more traditional methods such as seeing a GP. The chatbots delivered "a mix of good and bad information" that users struggled to distinguish: wrong diagnoses and responses that failed to recognise when urgent help was needed. The researchers concluded that while AI chatbots now "excel at standardised tests of medical knowledge", using them to make real medical decisions "would pose risks to real users seeking help with their own medical symptoms". Lead author Andrew Bean (Oxford Internet Institute) said the study showed that "interacting with humans poses a challenge" even for the top-performing LLMs. Co-author Dr Rebecca Payne, a GP, said: "Despite all the hype, AI just isn't ready to take on the role of the physician. Patients need to be aware that asking a large language model about their symptoms can be dangerous — giving wrong diagnoses and failing to recognise when urgent help is needed." Source: https://www.bbc.com/news/articles/cpd8l088x2xo
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