A growing number of contact tracing apps are being developed to complement manual contact tracing. Yet, for these technological solutions to benefit public health, users must be willing to adopt these apps. While privacy was the main consideration of experts at the start of contact tracing app development, privacy is only one of many factors in users' decision to adopt these apps. In this talk I showcase the value of taking a descriptive ethics approach to setting best practices in this new domain. Descriptive ethics, introduced by the field of moral philosophy, determines best practices by learning directly from the user -- observing people’s preferences and inferring best practice from that behavior -- instead of exclusively relying on experts' normative decisions. This talk presents an empirically-validated framework of the inputs that factor into a user's decision to adopt COVID19 contact tracing apps, including app accuracy, privacy, benefits, and mobile costs. Using predictive models of users' likelihood to install COVID apps based on quantifications of these factors, I show how high the bar is for these apps to achieve adoption and suggest user-driven directions for ethically encouraging adoption.
About the speaker:
Dr. Elissa M. Redmiles is a faculty member and research group leader of the Digital Harm group at the Max Planck Institute for Software Systems. She additionally serves as a consultant and researcher at multiple institutions, including Microsoft Research and Facebook. Dr. Redmiles uses computational, economic, and social science methods to understand users’ security, privacy, and online safety-related decision-making processes. Her work has been featured in popular press publications such as Scientific American, Wired, Business Insider, Newsweek, Schneier on Security, and CNET and has been recognized with multiple Distinguished Paper Awards at USENIX Security and the John Karat Usable Privacy and Security Research Award. Dr. Redmiles received her B.S. (Cum Laude), M.S., and Ph.D. in Computer Science from the University of Maryland. As a graduate student, she was supported by a NSF Graduate Research Fellowship, a National Defense Science and Engineering Graduate Fellowship, and a Facebook Fellowship.
When: Tuesday, October 20, 2020 at 5:00 P.M. (17:00) CEST.
Where: Zoom https://tuwien.zoom.us/j/96389928143?pwd=UU5YRkNuRmdoWHV4MFBwMWRCcUErdz09
The talk will be streamed and recorded on our DIGHUM channel.
For further announcements and information about the events and speakers in the Lecture Series, see dighum.ec.tuwien.ac.at/lectures-program/