Data scientists using big, pervasive data about people face a significant challenge: navigating norms and practices for ethical and trustworthy data use. The PERVADE project, National Science Foundation-funded research that spans six institutions, has conducted research with data scientists, data subjects, and regulators, and has discovered two entwined trust problems: participant unawareness of such research, and the relationship of social data research to corporate datafication and surveillance.
In response, we have developed a decision support tool for researchers, inspired by our empirical work, as well as research practices in a related but perhaps surprising research discipline: ethnography. This talk will introduce the decision support tool prototype, and discuss ways that data scientists can incorporate reflection on awareness and power into their research to support the development of trustworthy social data science.
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About Katie Shilton:
Katie Shilton is an associate professor in the College of Information Studies at the University of Maryland, College Park. Her research focuses on technology and data ethics. She is the PI of the PERVADE project, a multi-campus collaboration focused on big data research ethics. Other projects include improving online content moderation with human-in-the-loop machine learning techniques; analyzing values in audiology technologies and treatment models; and designing experiential data ethics education.
She is the founding co-director of the University of Maryland’s undergraduate major in social data science. Her work has been supported by multiple awards from the U.S. National Science Foundation. Katie received a B.A. from Oberlin College, a Master of Library and Information Science from UCLA, and a Ph.D. in Information Studies from UCLA.