40+ Authors, 9 Specialties, and a Book Written by the Next Generation of Doctors: Emily Leventhal and Rishma Jivan on The Physician's Guide to AI From Offcall and MD+
Episode Description
Emily Leventhal is a third-year MD-PhD student at the Icahn School of Medicine at Mount Sinai. Rishma Jivan is a fourth-year at Rush Medical College who spent years inside San Francisco health tech startups before going back to medical school. Together they co-led The Physician's Guide to AI, a nine-specialty e-book built with more than 40 physician authors, published in partnership with MD+.
In this episode of How I Doctor, Dr. Graham Walker sits down with Emily and Rishma to find out what medical training actually looks like from inside the AI shift. What's really happening on rotations, in the hallways, and in the conversations students are having with attendings who don't always know what to make of it.
They dig into the "hidden curriculum," the unwritten norms of medical training that AI is starting to help close for students who don't come from medical families, and why Rishma refuses to let herself trust an AI output without teaching herself to critique it first. Emily makes the case that AI won't just change how physicians practice, it will change which specialties students choose to go into at all. And both push back on the idea that relying on these tools is a shortcut, describing it instead as a discipline they're still building the rules for in real time.
This isn't about students skipping the hard parts of training. It's about a generation building the habits and guardrails the rest of medicine hasn't caught up to yet.
📖 Download The Physician's Guide to AI: https://www.amazon.com/dp/B0GY36B58Z
What You'll Learn
- Why every medical student is already using ChatGPT to prep for cases, and why that's different from the smaller group actually building AI tools.
- What the "hidden curriculum" is, and how AI is helping close that gap for students without a medical background in the family.
- How to guard against automation bias: the habit of verifying an AI output against its source before trusting a clinical recommendation.
- Why AI's impact on a specialty may become a real factor in how students choose where to train.
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📝 For a full transcript of this episode click HERE
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