Protecting Your Privacy in a Data-Driven World

Title: Protecting Your Privacy in a Data-Driven World
(https://www.clairemckaybowen.com/book.html)
Speaker: Claire McKay Bowen, PhD, Principal Research Associate, Urban Institute
Chair: Stephanie S. Shipp, Professor, University of Virginia
Date: Tuesday, 11 January 2022
Time: 1:00PM – 2:00PM EST

Abstract: At what point does the sacrifice of our personal information outweigh the public good? If public policymakers had access to our personal and confidential data, they could make more evidence-based, data-informed decisions that could accelerate economic recovery and improve COVID-19 vaccine distribution. However, access to personal data comes at a steep privacy cost for contributors, especially underrepresented groups.

Protecting Your Privacy in a Data-Driven World is a practical, nontechnical guide that explains the importance of balancing these competing needs and calls for careful consideration of how data are collected and disseminated by our government and the private sector. Not addressing these concerns can harm the same communities that policymakers are trying to protect through data privacy and confidentiality legislation.
The topics covered in Protecting Your Privacy in a Data-Driven World will be outlined in the talk with plenty of time left for questions.

About the speaker: Dr. Claire McKay Bowen is a Principal Research Associate at the Urban Institute. Her research focuses on developing and assessing the quality of differentially private data synthesis methods and science communication. She holds a BS in mathematics and physics from Idaho State University and an MS and PhD in statistics from the University of Notre Dame. After completing her PhD, she worked at Los Alamos National Laboratory, where she investigated cosmic ray effects on supercomputers. In 2021, the Committee of Presidents of Statistical Societies (COPSS) identified her as an emerging leader in statistics for her “contributions to the development and broad dissemination of Statistics and Data Science methods and concepts, particularly in the emerging field of Data Privacy, and for leadership of technical initiatives, professional development activities, and educational programs.”

For additional information about this event, please contact Yan Li (yli6 [at] umd [dot] edu), WSS Methodology Program Chair.