Towards A Framework for the Social Impact of Algorithms in Health Care

Oregon Convention Center 

Our ongoing work aims to build a framework for evaluating the social impact of algorithms in health care before they are deployed, rather than after they have been implemented and harms have occurred. We leverage advances in statistical machine learning and mathematical decision science modeling as well as qualitative research to prioritize equity considerations in our causal network model. Groups marginalized by the health care system already experience lower life expectancy and poorer health outcomes—algorithms could more frequently be contributing to improving health equity rather than harming it.