Project Summary

Cities are adopting camera technologies, including public video cameras and sensors, that use AI to process the 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.

Project Team

Sharon Strover (Lead, Journalism and Media), Maria Esteva (Co-Lead, Texas Advanced Computing Center); Atlas Wang (Co-Lead, Electrical and Computer Engineering), Al Bovik (Electrical and Computer Engineering), Casey Boyle (Rhetoric and Writing), Joydeep Ghosh (Electrical and Computer Engineering), Amy Sanders (Journalism and Media), Ted Lehr (City of Austin Center for Excellence and Innovation), Chris McConnell (Austin Transportation Department), Karla Taylor (Austin Transportation Department)