AI and the Future of Racial Justice


AI-based technologies used by cities and organizations have been shown to exhibit racial bias, and yet, they can determine who gets access to employment, care, and adequate housing. This project seeks to understand the racial disparities in AI-based systems and design and implement solutions in the areas of public safety, transportation, and health. Engagement with local government offices, public agencies, industry, and communities is at the center of its effort to tackle the challenge of achieving racially equitable AI.


Team Members

Civil, Architectural and Environmental Engineering
Project Co-Lead


Sept. 20, 2023
Good Systems Awards Funding to Advance Ethical AI Research in Core Project Areas
Good Systems has awarded funding to five projects that investigate the ethical implications of AI technologies in society in the areas of racial justice, surveillance and privacy, smart cities, and community-robot interaction.
July 25, 2023
Poor Infrastructure in Houston’s Black Neighborhoods has Caused a Disproportionate Number of Pedestrian Crashes, New Study Says
Researchers at the University of Texas in Austin found that while majority-Black neighborhoods in Houston made up 14% of the area surveyed, those communities experienced 35% more pedestrian crashes than non-Black neighborhoods.
July 24, 2023
Houston's Black Neighborhoods Have a Disproportionate Number of Pedestrian Crashes, UT Study Finds
There is a direct line between under-investment in Black neighborhoods and the rising number of pedestrian crashes in those communities, Texas researchers found using Houston stats.



Select Publications

Angela J. Haddad, Aupal Mondal, Chandra R. Bhat, Angie Zhang, Madison C. Liao, Lisa J. Macias, Min Kyung Lee, and S. Craig Watkins. “Pedestrian Crash Frequency: Unpacking the Effects of Contributing Factors and Racial Disparities.” Accident Analysis & Prevention 182 (March 1, 2023).