Augmented intelligence (AI) and related branches--such as machine learning and natural language processing--offer lots of promise for health care, but how can physicians and other health professionals distinguish between clinically safe and useful innovations and hot air? That question is at the heart of a recent JAMA Pediatrics editorial on machine learning, a branch of AI, that outlines some rules of thumb to help doctors tell the difference between hype and reliable research on machine learning in medicine. New health care AI policy adopted at the 2019 AMA Annual Meeting provides that AI should advance the quadruple aim--meaning that it "should enhance the patient experience of care and outcomes, improve population health, reduce overall costs for the health care system while increasing value, and support the professional satisfaction of physicians and the health care team." The AMA House of Delegates also adopted policy on the use of AI in medical education and physician training. This built on the foundation of the AMA's initial AI policies adopted last year that emphasized that the perspective of physicians needed to be heard as the technology continues to develop.