Towards physician-centered oversight of conversational diagnostic AI

In this episode, we discuss Towards physician-centered oversight of conversational diagnostic AI by Elahe Vedadi, David Barrett, Natalie Harris, Ellery Wulczyn, Shashir Reddy, Roma Ruparel, Mike Schaekermann, Tim Strother, Ryutaro Tanno, Yash Sharma, Jihyeon Lee, Cían Hughes, Dylan Slack, Anil Palepu, Jan Freyberg, Khaled Saab, Valentin Liévin, Wei-Hung Weng, Tao Tu, Yun Liu, Nenad Tomasev, Kavita Kulkarni, S. Sara Mahdavi, Kelvin Guu, Joëlle Barral, Dale R. Webster, James Manyika, Avinatan Hassidim, Katherine Chou, Yossi Matias, Pushmeet Kohli, Adam Rodman, Vivek Natarajan, Alan Karthikesalingam, David Stutz. The paper proposes g-AMIE, a multi-agent AI system that performs patient history intake within safety guardrails and then presents assessments to a primary care physician (PCP) for asynchronous oversight and final decision-making. In a randomized virtual study, g-AMIE outperformed nurse practitioners, physician assistants, and PCPs in intake quality and diagnostic recommendations, while enabling more time-efficient physician oversight. This demonstrates the potential for asynchronous human-AI collaboration in diagnostic care, maintaining safety and accountability.