A research center at Brown University focused on AI governance, policy, and socially responsible computing, housed within the Center for Technological Responsibility, Reimagination and Redesign (CNTR) at the Data Science Institute.
A research center at Brown University focused on AI governance, policy, and socially responsible computing, housed within the Center for Technological Responsibility, Reimagination and Redesign (CNTR) at the Data Science Institute.
People
Updated 05/18/26 · By grantmaking.aiCNTR Program Manager; CNTR AISLE Product Director
Director, Center for Technological Responsibility, Reimagination, and Redesign (CNTR) and lead for CNTR’s AI governance initiatives
Assistant Professor of the Practice in AI Governance and Policy; CNTR AISLE Policy Director
Funding Details
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Org Details
Updated 05/18/26 · By grantmaking.aiThe Brown University AI Governance Lab is the AI governance research arm of the Center for Technological Responsibility, Reimagination and Redesign (CNTR), a research center within Brown University's Data Science Institute. Founded in April 2024, CNTR's mission is to redefine computer science education, research, and technology to center the needs, problems, and aspirations of all people, especially those that technology has left behind.
The center is directed by Suresh Venkatasubramanian, Professor of Data Science, Computer Science, and Humanities at Brown. Venkatasubramanian previously served as Assistant Director for Science and Justice in the White House Office of Science and Technology Policy during the Biden-Harris administration, where he helped co-author the Blueprint for an AI Bill of Rights. He also serves as Deputy Director of Brown's Data Science Institute and co-directs the AI Research Institute on Interaction for AI Assistants (ARIA).
CNTR's flagship AI governance project is the CNTR AISLE Portal, launched in March 2026, which is a public database aggregating and analyzing AI legislation pending at the federal level and from all 50 US states. A team of 17 undergraduate and five graduate students evaluate bills using a structured framework of 159 questions spanning seven dimensions: accountability and transparency, data protection, bias and discrimination, labor force, institutional impacts, AI and education, and synthetic content. The portal launched with over 5,000 bills cataloged and approximately 100 evaluated.
Other major programs include the Legislation Lab, a semester-long experiential program training students to evaluate AI legislation; the Tech and Policy Summer School, an intensive nine-day program that received 267 applications for 14-16 spots in its inaugural cohort; the Socially Responsible Computing Curriculum Handbook developed by over 20 students; and research on sociotechnical evaluation of large language models.
The center's faculty includes Tomo Lazovich, Assistant Professor of the Practice in AI Governance and Policy, who leads the AISLE policy team, along with nine affiliated faculty members, five or more PhD students, and numerous undergraduate researchers. CNTR receives funding from the MacArthur Foundation, the Ford Foundation, the Public Interest Technology University Network, Brown's Data Science Institute, the Survival and Flourishing Fund, and anonymous donors.
Theory of Change
Updated 05/18/26 · By grantmaking.aiThe lab's theory of change centers on the belief that effective AI governance requires bridging the gap between technical understanding and policy making. By building tools to track and evaluate AI legislation (the AISLE portal), training the next generation of technically-informed policy analysts through experiential programs, producing research on algorithmic fairness and sociotechnical impacts of AI systems, and embedding responsible computing principles into computer science education, the lab aims to ensure that AI development and deployment are shaped by informed, rigorous policy frameworks that protect public interests and reduce harms from automated decision-making systems.
Grants Received
Updated 05/18/26 · By grantmaking.aiProjects
Updated 05/18/26 · By grantmaking.aiDiscussion
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