I'm in medical education, and the sheer volume of information we're expected to memorize is becoming overwhelming. There's a growing push to integrate AI tools as diagnostic aids, but I worry this is creating a gap between theoretical knowledge and practical, hands-on clinical reasoning. Are we training future doctors to be data managers rather than diagnosticians?
I worry the push to use AI as a diagnostic aid could drift training away from real clinical reasoning The fix is to teach students to use AI as a data partner while they still own their own judgment
Make the curriculum emphasize how to assess AI outputs for bias and uncertainty and how to explain that to patients in plain language
Use case based learning where AI surfaces hypotheses but students must justify a final decision with reasoning and tests
We also need standards for data quality and model governance so trainees learn to question inputs and limits
There should be research into patient outcomes with AI assisted decision making to guide medical education and policy in the future this should inform medical education curriculum 2025 and online medical education 2025