INFORMAZIONI SU QUESTO EPISODIO
In their sixth Reflections episode, Steve and Leon look back across five conversations (Sarah Rossetti, Jeff Smith of ONC, Hugo Campos, Fred Bennett, and Zak Kohane) and decide, deliberately, not to force a single grand theme. What surfaces anyway is one question asked five ways: as AI gets genuinely capable, what still has to be human, and what makes it trustworthy? They cover Rossetti's CONCERN system that models the nurse instead of the patient, ONC giving AI agents patient-like data rights, the tension between patient empowerment and black boxes you don't understand, the Minimum Trustable Product, and Kohane's method for measuring the values a healthcare AI actually acts on. A practical tour of where good is starting to look real.
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Stati Uniti
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ALTRI EPISODI IN QUESTO PODCAST
Raihan Faroqui trained in internal medicine and then went to work on the front desk. As VP of partnerships at Confido Health, he puts AI agents on the phone lines of what he says are about 1,500 outpatient practice sites, handling appointments, refills, insurance checks, and billing questions in tw…
In their seventh Reflections episode, and their fifty-first overall, Steve and Leon look back across six conversations: Mika Newton on interoperability that finally started working, Peter Embi on monitoring clinical AI after deployment, Vimla Patel on how clinicians actually reason, Renee Deehan on…
Chris Dymek came to healthcare informatics by way of philosophy, and she still thinks like a philosopher: the first question is what we actually mean. As Director of Digital Healthcare Research at AHRQ, she funded AI research, helped launch work on AI and patient safety, and wrote a request for inf…
Every technology healthcare has adopted moved through the same curve: a bleeding-edge few went first and documented what broke, and the majority followed. Large language models skipped that entirely. Jeremy Harper, a biomedical informatician who has worked at Epic, Ohio State, and Regenstrief, and …
Steve and Leon close Season 1 by looking back across all fifty-two episodes. They start with what surprised them (how fast conservative institutions adopted, and how slowly AI literacy is moving), then work through five conclusions a year of guests kept reaching independently: the models are no lon…
Dichiarazione di non responsabilità: Il podcast e la grafica incorporati in questa pagina provengono da Steven Labkoff, MD and Leon Rozenblit, JD, PhD, che è di proprietà del suo proprietario e non è affiliato o approvato da Listen Notes, Inc.
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