Combining Human and Artificial Intelligence for Analyzing Health Data

Artificial intelligence (AI) systems are increasingly capable of analyzing health data such as medical images (e.g., skin lesions) and test results (e.g., ECGs). However, because it can be difficult to determine when an AI-generated diagnosis should be trusted and acted upon—especially when it conflicts with a human-generated one—many AI systems are not utilized effectively, if at all. Similarly, advances in information technology have made it possible to quickly solicit multiple diagnoses from diverse groups of people throughout the world, but these technologies are underutilized because it is difficult to determine which of multiple diagnoses should be trusted and acted upon. Here, I propose a method of soliciting and combining multiple diagnoses that will harness the collective intelligence of both human and artificial intelligence for analyzing health data.