Alumnus; Industry Assistant Professor of Ethics and Engineering, NYU Tandon School of Engineering

Kadija Ferryman

Dr. Kadija Ferryman 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 currently 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. She completed postdoctoral training at the Data & Society Research Institute in New York, 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 BA in Anthropology from Yale University, and a PhD in Anthropology from The New School for Social Research.

All Work

  • report
    Data & Society
    Fairness in Precision Medicine is the first report to deeply examine the potential for biased and discriminatory outcomes in the emerging field of precision medicine; "the effort to collect, integrate and analyze multiple sources of data in order to develop individualized insights about health and disease." Read more
    February 2018
  • report
    Data & Society
    The Precision Medicine National Actor Map is the first visualization of the three major national precision medicine projects--All of Us Research Program, My Research Legacy, Project Baseline--and the network of institutions connected to them as grantees and sub-grantees. The map was developed for the Fairness in Precision Medicine initiative at Data & Society. Read more
    February 2018
  • report
    Data & Society
    What is Precision Medicine? is a general audience white paper by Dr. Kadija Ferryman and Mikaela Pitcan that introduces and outlines the emerging field of precision medicine; the effort to collect, integrate and analyze multiple sources of data in order to develop individualized insights about health and disease. Read more
    February 2018
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