Artificial intelligence algorithms are everywhere in healthcare. They sort through patients’ data to predict who will develop medical conditions like heart disease or diabetes, they help doctors figure out which people in an emergency room are the sickest, and they screen medical images to find evidence of diseases. But even as AI algorithms become more important to medicine, they’re often invisible to people receiving care.
Artificial intelligence tools are complicated computer programs that suck in vast amounts of data, search for patterns or trajectories, and make a prediction or recommendation to help guide a decision. Sometimes, the way algorithms process all of the information they’re taking in is a black box inscrutable even to the people who designed the program. But even if a program isn’t a black box, the math can be so complex that it’s difficult for anyone who isn’t a data scientist to understand exactly what’s going on inside of it.
Patients don’t need to understand these algorithms at a data-scientist level, but it’s still useful for people to have a general idea of how AI-based healthcare tools work. That way, they can understand their limitations and ask questions about how they’re being used.