Designing AI to Advance Racial Equity

 

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


News


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.
Feb. 21, 2022
How AI Can Help Combat Systemic Racism
S. Craig Watkins looks beyond algorithm bias to an AI future where models more effectively deal with systemic inequality.

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