In today’s episode, Laura leads the discussion with a number of questions for Kadija about AI, machine learning, ethical decisions, fair health and the complexities that underline it all. Kadija’s research tackles health disparities through data and aims to make it is more inclusive and ethical. As Laura points out, data is easy to interrogate but how to get at those answers that could lead us to more fairness and prevent biases? Kadija reflects on the importance of insights and touches on the usefulness of anthropological frameworksto see through power hierarchies. She shares stories from her work in which social science often merges with more technical fields to produce results that help move the right direction in making data more ethical. Lastly, they share their expectation for the HealthTech panel and the overall conference.

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 earned a BA in Anthropology from Yale University, and a PhD in the Anthropology from The New School for Social Research. Before completing her PhD, she was a policy researcher at the Urban Institute where she studied how housing and neighborhoods impact well-being. She is currently a Researcher at the Data & Society Research Institute in New York where she leads the Fairness in Precision Medicine research study. She is also a Mozilla Fellow and will be examining how health information technologies address health disparities. 

Dr Laura Sobola is a Senior Consultant at Unai and has participated in management and delivery of healthcare related projects, as well as data science projects. She studied Human Genetics at Newcastle University and has a doctorate in biochemistry from University of Oxford. Recently, she has been researching and helping to implement an ethical framework for Unai, which has reignited her interest in ethics.