written by: Kevin Johnson, MD, MS, University Professor of Biomedical Informatics, Computer Science, Pediatrics, and Science Communication at the University of Pennsylvania; Vice President of Applied Clinical Informatics in the University of Pennsylvania Health System

Artificial intelligence (AI) isn’t new: The first neural network computer appeared in the early 1950s. Hype about AI revved up in the 1970s, but early iterations of AI stalled out through a combination of too much hype, too much complexity, and too little attention to the human element.

We can learn from prior AI failures, not to mention failures of EHR implementation, to successfully integrate certain types of AI into daily healthcare operations. We will not solve the clinician burnout crisis or achieve equity in healthcare using AI alone, but strategic applications of AI can assist us in both areas.

The cornerstones of successful AI implementation will be people: Those who envision, lead, and train, and those who reskill, adapt, and integrate AI tools into frontline care, whether for administrative or for patient-facing purposes.

Four Main Types of AI

Right now, generally speaking, AI works in one of four ways:  read full article