Colloquium: Katie Shilton (University of Maryland)


Title: Intervening in Big Data: Values, Practices, and Tools for Pervasive Ethics

Abstract: Ethics and values to guide the creation, use, and curation of digital data have never felt more urgent. International debates have erupted over massive online data experiments, leaked datasets, and the definition of public data. Biased datasets feed algorithms that increasingly make decisions about people and their opportunities. The growth in the scale, scope, and speed of data gathering and use challenge traditional regulators, from IRBs to governments. This talk describes ongoing research to find places for ethical intervention in big data cultures. It describes research with stakeholders including data subjects, data users, and data regulators, and contrasts the ways these stakeholders grapple with ethics and values to guide their data practices. Drawing from this research, I suggest that information scientists can intervene to reorient big data’s future. From micro-scale levers to large-scale organizing, information scholars and practitioners are well-placed to advance a just, ethical approach to pervasive data.

Bio: Katie Shilton is an associate professor in the College of Information Studies at the University of Maryland, College Park. Her research explores ethics and policy for the design of information collections, systems and technologies. She is the PI of the PERVADE project, a multi-campus collaboration focused on big data research ethics. Other current projects include developing privacy-sensitive search for email collections; analyzing ethical cultures in computer security research; and building tools to facilitate ethics discussions in mobile application development. Her work has been supported by a Google Faculty Award and multiple awards from the U.S. National Science Foundation, including a CAREER award. She is a member of the Electronic Privacy and Information Center (EPIC) advisory board. 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.


1:15pm to 2:30pm


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