Trust between doctors and patients has long been considered a foundation of effective care.
The results of the MIT study, published in May in NEJM AI, highlight a growing concern in healthcare.
As large language models (LLMs) become more skilled at sounding like medical experts, patients may struggle to tell the difference between accurate guidance and dangerous misinformation.
Researchers at MIT Media Lab presented participants with answers to common medical questions from three sources: physician-written posts on an online healthcare platform, high-accuracy AI responses verified by doctors, and low-accuracy AI answers containing errors or inappropriate recommendations.
Participants found AI-generated responses more thorough and easier to understand than physicians' replies.
When the AI model was accurate, it scored significantly higher than human doctors across every measure of trust and satisfaction.
The team's concern deepened when the model was wrong. Low-accuracy AI-generated responses on average performed very similarly to doctors' responses.
The study revealed a contradiction: both medical experts and non-experts tended to rate AI-generated answers as more complete and accurate than those from doctors, yet they still preferred having a human physician involved in their care.
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