Artificial intelligence (AI) and machine learning (ML) are increasingly used in healthcare to combat unsustainable spending and produce better outcomes with limited resources, but healthcare organizations (HCOs) must take steps to ensure they are actively mitigating and avoiding algorithmic bias.
While AI/ML has the potential to identify and combat disparities, it also has the potential to inadvertently perpetuate and exacerbate health inequities—despite apparent objectivity. In fact, algorithmic bias in healthcare is already pervasive. The Chicago Booth Center for Applied Artificial Intelligence states, “algorithmic bias is everywhere…Biased algorithms are deployed throughout the healthcare system, influencing clinical care, operational workflows, and policy.” (author abstract)