On October 31st, Emilee Rader, Associate Professor and AT&T Scholar from the Department of Media and Information at Michigan State University, gave a talk on the Implications of Beliefs about Derived Personal Data for Negotiating Digital Privacy Norms. During this talk, Professor Rader presented initial findings from two qualitative studies focused on determining users’ awareness of the inferences systems make about them, what users think systems have the ability to infer, and what users feel is permissible data for systems to know about them.

Based on her work, Rader argues that there is an imperceptible social dilemma related to systemic use of machine learning and aggregation of big data in order to generate inferences about individual users and that this dilemma complicates defining norms for digital privacy. Further complicating this issue is the fact that users may be unable to predict how machine learning algorithms will use their data and there may be future harmful uses of this data which are currently unimaginable.

In addition to digital privacy norms, Professor Rader’s work also encompasses identifying and understanding the issues emerging in sociotechnical systems as they become embedded, and essentially ubiquitous, in everyday life. A sociotechnical system is a system involving a triad of people, technology, and information in which all three components influence each other. This system cannot function correctly without the existence and influence of the three parts.

Dr. Rader earned her Ph.D. from the University of Michigan School of Information. She followed this with a two year postdoc at Northwestern in the Center for Technology and Social Behavior, where she was a recipient of the prestigious Computing Innovation postdoctoral fellowship awarded by the Computer Research Association. Prior to this, Rader earned her Master’s degree from the Carnegie Mellon Human Computer Interaction Institute. She also worked as part of an interdisciplinary research team focused on designing and evaluating mobile technologies at Motorola in the early 2000s. Rader has received funding for her work through multiple National Science Foundation (NSF) grants. The majority of her work is published in either human computer interaction or usable privacy and security venues.