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Doctors Warn That Med Students Are Surrendering Their Brains to Medical AIs That Are Even Worse than Regular Chatbots

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Why This Matters

The increasing reliance of medical students on AI tools raises concerns about the potential erosion of critical reasoning skills, which are essential for effective medical practice. The recent findings that specialized medical AI performs worse than general chatbots highlight the risks of overdependence on unreliable technology during training. This situation underscores the importance of maintaining foundational medical education to ensure competent future healthcare providers.

Key Takeaways

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It’s no secret that doctors across the world are using AI tools to do stuff from taking notes to looking up questions. But what about the next generation of doctors still in training? According to two medical professionals on the ground, the situation is looking pretty alarming.

With AI being used by med students, “the danger is not just deskilling but never-skilling,” write Simar Bajaj, a journalist and med student at the Stanford University School of Medicine, and Joseph Sakran, a trauma surgeon and executive vice-chair of surgery at Johns Hopkins Medicine, in an essay for The Guardian.

“Although a doctor who has forgotten how to reason is recoverable,” they added, “one who never learned how may not be.”

Bajaj and Sakran point to two alarming recent findings.

One is internal data showing that around two thirds of doctors in the US are using OpenEvidence, an AI chatbot specifically designed for clinicians. The technology is already prevalent and deeply woven into how medical professionals carry out their jobs.

The next is a new study published in the journal Nature Medicine that evaluated the reliability of these medical-specific large language models. Shockingly, the clinical AI tools performed worse at answering medical queries than general purpose chatbots like ChatGPT and Claude did, the work found. According to the authors, it performed about on par to Google’s AI Overviews, which are notorious for being wonky and inaccurate.

Even if AI tools may be handy for research — and putting aside the major questions over their reliability — they’re no substitute for relying on your brain, as fallible as it might be, because when you’re learning, “the struggle is the point.”

“For example, trainees once asked to build a list of potential diagnoses might struggle and offer an incomplete set, learning what they missed, sometimes painfully,” Bajaj and Sakran wrote. “Now, trainees can simply ask OpenEvidence and get a nearly perfect answer, complete with possibilities they might have never considered and none of the embarrassment of having overlooked them.”

Where AI is different from medical advances in the past is that it’s “not just expanding what doctors can see,” they wrote, “but inserting itself into the cognitive machinery that training is meant to build.”

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