Cities are adopting camera technologies, including public video cameras and sensors, that use AI to process visual data with the promise of improving services, enhancing management capabilities, and lowering costs. However, privacy is a core challenge to using the data, as the public lacks trust in how governments use camera-generated video data. This project focuses on investigating the social acceptance of cameras and video data and developing technical solutions that will satisfy privacy concerns, including blurring faces and other identifying information when using biometric data so that machine learning models can be trained to remove these privacy attributes from raw videos.
Team Members
School of Journalism and Media
Project Lead
Atlas Wang
Electrical and Computer Engineering
Project Co-Lead
Rhetoric and Writing
Texas Advanced Computing Center
Civil, Architectural and Environmental Engineering
Amy Sanders
School of Journalism and Media
Ciaran Trace
School of Information
Anita Varma
School of Journalism and Media
News
Videos
Documents
Select Publications
Sharon Strover, Maria Esteva, Tiancheng Cao, and Soyoung Park. “Public Policy Meets Public Surveillance.” AoIR Selected Papers of Internet Research.