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Breakout E - KEYNOTE III – The Impact of Digital Media on Health Equity

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Breakout E - Keynote III – The Impact of Digital Media on Health Equity 

Kadija Ferryman, PhD

Industry Assistant Professor, New York University Tandon School of Engineering

Dr. Kadija Ferryman is a cultural anthropologist who studies the social, cultural, and ethical implications of health information technologies. Specifically, her research examines the impacts of health risk prediction technologies as they relate to marginalized groups. She is currently a Researcher at the Data & Society Research Institute in New York where she leads the Fairness in Precision Medicine research study, which examines the potential for bias and discrimination in predictive precision medicine. She is also a Mozilla Fellow and will be examining how health information technologies address health disparities. 

William T. Riley, PhD (Moderator)

Director, Office of Behavioral and Social Sciences Research, National Institutes of Health

William (Bill) Riley is the Associate Director for Behavioral and Social Sciences Research, and Director of the Office of Behavioral and Social Sciences Research at the National Institutes of Health (NIH). During his 12 years at the NIH, he also served at the National Institute of Mental Health (NIMH), the National Heart, Lung, and Blood Institute (NHLBI), and the National Cancer Institute (NCI). He also holds an appointment as Professorial Lecturer in the School of Public Health at George Washington University. Dr. Riley’s research interests include behavioral assessment, technology-based interventions for health risk factors, and the application of engineering and computer science methodologies to the behavioral sciences.

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Breakout E - KEYNOTE III – The Impact of Digital Media on Health Equity
06/03/2020 at 2:15 PM (EDT)   |  30 minutes
06/03/2020 at 2:15 PM (EDT)   |  30 minutes The explosion and continued evolution of health information technologies have important social, cultural, and ethical implications for society. This presentation will examine how health information technologies impact health disparities and cautions to avoid the potential for bias and discrimination in predictive precision medicine.