Texas University Partners With MITRE On Ethical AI Research

The University of Texas at Austin and the MITRE Corporation, a non-profit research and development organization, have announced a new partnership aimed at accelerating the development of ethical AI research, as part of UT Austin’s Good Systems research challenge. 

Good Systems is one of three research challenges set out by UT Austin in 2019. Technologists, social scientists, and humanists have built and evaluated ethical AI systems in six core areas, including enhancing middle-skill work with human-like robotic tools, reducing misinformation through AI, smart cities, adding ethical considerations to public camera AI technologies, using AI to improve racial equality, and living with AI in day-to-day life. 

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“Good Systems is honored to partner with MITRE to work toward our shared goal of ensuring that AI will serve the public interest,” said Kenneth R. Fleischmann, founding chair of Good Systems and a professor in the University of Texas at Austin School of Information. “AI innovation should be leveraged to enhance our economic competitiveness and national security, and it is also critical that we harness the benefits of AI to steer toward a more equitable and just society.”

The MITRE Corporation invested $1 million into the Good Systems project, which UT Austin aims to use to expand team expertise and support a greater number of researchers. One driver of the work is that the widespread adoption of some AI technologies can cause adverse societal effects, among them job losses, increased economic inequality, infringements on privacy, overreliance on biased algorithms and data sets, and the disruption of elections and of the social fabric.

“As consequential use of AI increases, it is vital that we address safety, security and equity concerns,” said Douglas Robbins, vice president of engineering and prototyping at MITRE Labs. “We are thrilled to be working with UT Austin and Good Systems to advance the underlying science in these areas that will enable us to build AI systems that can reach their full potential.”