Researchers, data scientists, and AI developers using big, pervasive data about people face a significant challenge: navigating norms and practices for ethical and trustworthy data use. In response, the six‐campus PERVADE project has conducted research with data scientists, data subjects, and regulators, and has discovered two entwined trust problems: participant unawareness of much research, and the relationship of social data (re)use to corporate datafication and surveillance. In response, we have developed a decision support tool for researchers, inspired by research practices in a related but perhaps surprising research discipline: ethnography. This talk will introduce PERVADE's research findings and the resulting decision support tool and discuss ways that researchers and developers working with pervasive data can incorporate reflection on awareness and power into their research.

Dr. 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 a co‐PI of the NSF Institute for Trustworthy Artificial Intelligence in Law & Society (TRAILS), and a co‐PI of the Values‐Centered Artificial Intelligence (VCAI) initiative at the University of Maryland. She was also recently 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. 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.

This lecture is part of the Ethically Speaking Series, An interdisciplinary speaker series on contemporary moral issues.