(Axios) – Health systems are under increasing pressure to embrace new artificial intelligence tools without a formal system for evaluating how well they work. Why it matters: Even AI developers can struggle to explain why a model makes a particular prediction or recommendation. That has big implications in clinical settings, where algorithm errors or bias can result in patient harm. (Read More)