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AI can support medical decisions but should not replace doctors, experts say
AI chatbots can ace medical licensing exams but fail in real clinical settings, a Nature Medicine study found. Doctors must remain the decision-makers-AI is a research aid, not a diagnosis tool.
AI Chatbots Can Advise on Health Issues, But Doctors Must Make the Call
Large language models can score near-perfect marks on medical licensing exams and provide health advice to the public. Yet a study published in Nature Medicine found this capability doesn't translate to accurate performance in real-world medical settings.
Researchers at the National Institutes of Health discovered a similar gap. An AI model solved medical quiz questions designed to test clinicians' diagnostic abilities with high accuracy. When asked to explain its reasoning or describe medical images, the model made mistakes.
The findings highlight a critical distinction: AI can process information and pattern-match against training data. It cannot reliably explain its decisions or handle the visual reasoning that doctors perform daily.
How Users Can Get AI Wrong
The way people interact with AI chatbots affects the quality of responses they receive. Participants in the Nature Medicine study used varied strategies-some asked closed-ended questions that constrained possible answers, which shaped the advice they got back.
Users asking "Do I have strep throat?" receive different guidance than those describing symptoms in detail. Neither approach guarantees accuracy.
Privacy and Data Risks
Uploading medical information to AI tools carries privacy risks. While companies claim guardrails protect user data, how those protections work remains unclear to the public.
Uploading full medical records poses additional danger. These documents often contain sensitive information beyond the specific symptoms a person wants to discuss.
What AI Should and Shouldn't Do
AI works best as an educational tool. Someone researching a health condition can use a chatbot to understand symptoms, treatments, and when to seek care.
AI should not diagnose. It should not prescribe. It should not replace a doctor's judgment.
Integrating AI into healthcare requires addressing technical limitations, data challenges, and gaps in how people trust and use these tools. Doctors remain the decision-makers. AI remains a supplement.
For healthcare professionals, this means understanding where AI adds value-faster preliminary analysis, pattern recognition across large datasets-and where it falls short. The technology works best when humans remain in control.
Learn more about Generative AI and LLM applications and limitations, or explore AI for Healthcare to deepen your knowledge of how these systems integrate with clinical practice.