Responsible AI

Block Center for Technology and Society

Carnegie Mellon has the expertise and ingenuity that is necessary to direct advances in AI toward social responsibility.

Artificial intelligence (AI) is already impacting many aspects of people’s lives and society at large. At CMU, we believe that AI must be designed, developed and deployed responsibly to ensure accountability and transparency, and lead toward a more just and equitable world.

Visit the Responsible AI Website

New developments in AI must support and lead to a more just and equitable world.

Carnegie Mellon has the expertise and ingenuity necessary to direct advances in AI toward social responsibility. CMU’s Responsible AI initiative brings together researchers and educators spanning computer science, engineering, decision sciences, philosophy, the arts, economics, psychology, public policy, statistics and business to make progress in:

  • Translating research to policy and social impact.
  • Building community and serving our local and global communities.
  • Offering hands-on and experiential educational and research opportunities for students, staff and faculty.
  • Working collaboratively with partners to develop and deploy AI methodologies and tools that enable learning, practice and research.

The Responsible AI initiative will evolve, in part, based on the interests and priorities of government, industry, nonprofit, and community partners. Activities will include education and training workshops, research projects, collaborative projects, and community events.

 View Printable Responsible AI Brochure

Responsible AI is a university-wide initiative housed at the Block Center, with support from the School of Computer Science, that draws on expertise from across Carnegie Mellon.

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Faculty Leads

Jodi Forlizzi, Herbert A. Simon Professor
Computer Science and HCII
Associate Dean for Diversity, Equity and Inclusion

Rayid Ghani, Professor
Machine Learning Department
Heinz College of Information Systems and Public Policy

Hoda Heidari, Assistant Professor
Machine Learning Department
Software and Societal Systems Department