When a professor caught her medical students using AI on their reflections, she did not call them lazy. She called them in. Kathleen Muldoon, a professor and medical educator, argues that students reaching for AI is a rational decision inside an irrational system, one that rewards performance over reflection. The real problem is not the student. It is a curriculum that makes humanity and honesty feel like things to survive, not practice.

⏱️ Chapters:
0:00 Introduction
0:18 The workshop where AI was banned for a reason
1:43 Why "kids these days" gets it completely wrong
3:07 How she knew it was AI without a detector
3:57 The conversation that started with "you are enough"
5:44 Why smart students put their energy elsewhere
7:47 Is it the student or the system rewarding them
9:18 The gray area nobody has figured out yet
10:05 What she would change with her next cohort
12:01 What students actually said when confronted
13:07 Why being wrong has to feel safe
15:02 Are medical educators really having this conversation
17:00 Can AI ever teach empathy
19:27 Take home messages

About this episode:
Kathleen Muldoon returns to discuss her KevinMD article on driving medical education reform through intellectual honesty. As a professor who runs workshops built on courageous conversations about bias, disparities, and the human side of medicine, she noticed her students increasingly outsourcing their reflective writing to AI, despite an explicit no-AI policy. Rather than treating it as academic dishonesty, she reframed it as a systems problem: students who feel like a number in a system full of gates and cutoffs will rationally direct their energy toward what gets rewarded, and the hidden curriculum speaks louder than the syllabus. She describes calling students in one by one, opening with the message that they are enough, and hearing without exception that they felt they were surviving a curriculum rather than thriving in it. She is candid about not having the answer yet, weighing whether to bring writing back into the workshop, drop it, or fully embrace AI with honest disclosure. She argues that AI cannot teach empathy, that it only comes from watching someone show up rough and raw and seeing the core value underneath, and that peers lifting each other up is what no algorithm can replace. Her closing challenge is blunt: we cannot build humane physicians in dehumanizing systems.

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