Dr. Kadija Ferryman, a Data & Society affiliate, is an anthropologist who studies race, ethics, and policy in health technology. Specifically, her research examines how clinical racial correction/norming, algorithmic risk scoring, and disease prediction in genomics, digital medical records, and artificial intelligence technologies affect racial health inequities. She is core faculty at the Johns Hopkins Berman Institute of Bioethics and assistant professor in the Department of Health Policy and Management at the Bloomberg School of Public Health at Johns Hopkins University.  Ferryman completed her postdoctoral training at the Data & Society, where she led the Fairness in Precision Medicine research study, which examined the potential for bias and discrimination in predictive precision medicine. She earned a bachelor’s degree in anthropology from Yale University, and a PhD in anthropology from the New School for Social Research.