The use of artificial intelligence (AI) in medical education is becoming increasingly prevalent, with 81 percent of doctors and 90 percent of medical students in the United States now using forms of AI in their practice and education, according to the American Medical Association.
AI-augmented study is happening quickly, but it’s also raising concerns among educators that it may negatively affect clinical skills acquisition and undermine medical training.
Associate Professor David Kok, a radiation oncologist and medical educator, recently spoke at the Royal Australian and New Zealand College of Radiologists’ AI conference, #Intelligence26, about the risks of AI use in medical education and how to address them.
Kok noted that AI tools like ChatGPT can already pass UK and US medical examinations, which raises concerns about the future of medical education and patient trust in doctors’ abilities.
Kok emphasized that AI will not replace doctors in the foreseeable future, as it lacks essential higher-order skills like ethical judgment.
AI will likely reshape medical education, requiring a shift from vulnerable assessment types to more secure, supervised, and cognitively challenging ones.
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Kok highlighted AI’s limitations, including its lack of ethical judgment.
He also noted that AI’s strengths can lead to weaknesses, such as when an understanding of causation is required or when applications need to transfer to less defined contexts.
Kok used the example of driverless cars, which may work well in predictable environments but struggle in more unpredictable conditions.
Kok discussed the benefits of using AI in education, including personalized tutoring and increased learning efficiency.
However, he also noted that the integration of AI into medical training is accelerating faster than the educational frameworks designed to govern it, which can lead to deskilling and mis-skilling among clinicians.
Kok emphasized the importance of AI literacy in clinical education, so clinicians can effectively use, verify, and govern these technologies.
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Medical education will need to change to take advantage of AI’s benefits while applying guardrails to assure the integrity of the learning experience.
This may involve shifting from vulnerable assessment types to more secure ones, such as real-time assessments and work-place-based assessments.
Kok also highlighted the need for resourcing and systemic changes to support the integration of AI into medical education.
US clinician and academic Professor Ruth Carlos also spoke at the conference, cautioning about the potential dangers of over-reliance on AI and the importance of critical analysis in AI literacy.
It is essential for medical educators to address these concerns and ensure that AI is used in a way that benefits both doctors and patients.