Ido Sivan-Sevilla (founder, PhD) is an assistant professor in UMD’s College of Information and affiliate professor in the School of Public Policy. He studies the governance of digital technologies, researching the design & implementation of tech policy issues through an array of methodologies including process-tracing analysis, computational text analysis, in-depth interviews, fuzzy-set qualitative comparative analysis (fsQCA), computational web scraping and vulnerability analysis, and social network analysis. For more information, see his website or email him directly.
Dr. Katie Shilton is a professor at the College of Information, where she studies technology and data ethics. She also leads the Ethics & Values in Design (EViD) Lab. She is a co-PI of the NSF and NIST-funded TRAILS Institute focused on trustworthy AI, and a co-PI of UMD’s Values Centered AI Initiative. 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 and designing experiential data ethics education.
Dr. Laura Fichtner is a post-doctoral researcher with the TRAILS institute where she researches how artificial intelligence technologies and particularly genAI can be developed and governed in a participatory and democratic manner. Prior to joining UMD, she received her doctorate from the University of Hamburg with a thesis on the politics of platform governance and the regulation of content moderation in Germany.
Dr. Amy Winecoff serves as a Senior Technologist in the AI Governance Lab at the Center for Democracy & Technology (CDT), where her work centers on creating technically-informed strategies to enhance AI governance, aimed at protecting the interests of individuals impacted by AI systems. Her research emphasizes building the foundations for robust governance, particularly in the areas of AI documentation and measurement. Her work has been featured in academic venues like RecSys, CHI, AIES, and First Monday, as well as in policy-focused publications through CDT and Tech Policy Press. She has also served as a responsible technology advisor for startup accelerators, and in her prior roles as a data scientist, she developed and deployed recommendation systems for e-commerce companies. She has also spent time as a research fellow at Princeton University’s Center for Information Technology Policy (CITP) and as an assistant professor at Bard College. Amy received her PhD in Psychology and Neuroscience from Duke University, which allows her to bring a social science lens to her work on AI governance.
