What happens when medical students rely on AI – and never develop their own judgment? | Simar Bajaj and Joseph Sakran
AI’s danger isn’t just in experts losing the ability to reason. It’s that trainees may never learn how to do so in the first place In healthcare, there’s growing concern over doctors becoming less clinically adept as they increasingly rely on AI tools. But what about the trainees – medical students, residents and fellows – who are using these tools before they’ve built their own clinical…
AI's danger extends beyond experts losing their ability to reason. A more troubling concern lies in the possibility that trainees, such as medical students, residents, and fellows, may never develop their own clinical judgment when they rely excessively on AI tools. In healthcare, there is growing worry that doctors are becoming less clinically adept due to their increasing dependence on AI.
However, the issue extends to trainees who use these tools before they have built their own clinical reasoning skills. The concept of "deskilling" refers to losing a previously acquired ability. In this case, the danger is not just deskilling, but "never-skilling." While a doctor who forgets how to reason can potentially recover that skill, one who never learned how to reason may be permanently compromised.
OpenEvidence, an AI chatbot specifically designed for clinicians, exemplifies this concern. Approximately two-thirds of US doctors actively utilize OpenEvidence, seeking assistance with puzzling symptoms, drug interactions, and clinical guidelines. These responses are generated within seconds, drawing upon the most recent research available.
Regrettably, trainees have also started using AI tools like OpenEvidence, but at an even more critical juncture in their medical education.
Written by urgent.news from The Guardian US's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
