AI Review Framework

The AI Review Framework for Trustworthy AI Systems was developed by the Yale AI Steering Committee to evaluate new uses of AI technology at Yale. The Committee was charged in fall 2025 by the Offices of the Provost and Institutional Risk Management to provide guidance and oversight across campus to ensure harmonized review and management of AI development and deployment at the university, ensuring alignment with the university’s mission, ethical standards, and regulatory requirements.  The Framework is intended to guide Yale’s AI governance bodies in their reviews and provide guidance for AI development or use by the Yale community. Yale’s senior leaders approved the Framework with the goal of encouraging experimentation and implementation of AI systems by articulating clear principles for trustworthiness. 

Access the Artificial Intelligence Review Framework for Trustworthy Artificial Intelligence Systems

Committees Involved in AI Governance

The Committee was charged in fall 2025 by the Offices of the Provost and Institutional Risk Management to provide guidance and oversight across campus to ensure harmonized review and management of AI development and deployment at the university, ensuring alignment with the university’s mission, ethical standards, and regulatory requirements. 

This group considers AI-specific approval requests, typically referred by the Data Governance Executive Council, that raise new or sensitive questions. Discussing each case will help to clarify principles and guidelines for future use cases.

Reviews proposals involving use of University administrative data and projects impacting teaching and learning outside Yale School of Medicine. Learn more here. 

Reviews human research projects examining the effectiveness or safety of AI technologies OR development of AI tools (when AI is not the focus of the study but rather a tool to collect data or provide assistance in reaching the research goals, the review of the AI is limited and includes ensuring SPA has been completed and contractual agreements are in place). Learn more here. 

Reviews proposals that involve disclosure of clinical data to third parties including uses cases where third parties may ingest clinical data for AI training purposes. Learn more here. 

Develops a Digital Stewardship Framework—a foundational set of principles, responsibilities, and policy recommendations that will guide the sustainable development, management, and preservation of Yale Library’s priority digital collections. Building on this foundation, the committee will then create a comprehensive Digital Collections Strategy—a forward-looking plan that defines the vision, priorities, and roadmap for how Yale Library curates, preserves, delivers, and enables discovery and use of its digital collections. Learn more here. 

Review use cases and recommend process/policy changes for social science data. Learn more here. 

Reviews AI use cases involving clinical workflows or those interfacing with YNHHS systems. Learn more here. Learn more here. 

Reviews and provides consultation on academic, administrative, and research AI software (both homegrown and commercial), as well as AI projects and use cases in the health sciences, excluding those involving clinical decision support or requiring YNHHS review. Learn more here. 

AI Steering Committee 

Megan Margraff, Chief Data Officer
Jennifer Frederick, Associate Provost for Academic Initiatives
Rosina Mummolo, Assistant General Counsel, Office of the General Counsel
Wies Rafi, Associate CIO, Health Science Information Technology Services
Frank Mathew, Assistant VP and Deputy CIO, Information Technology Services
Jeremy Rosenberg, Chief Information Security Officer
Susan Bouregy, Chief Privacy Officer
Monika Lau, Director, Human Research Protection Program
Chris Hanson, Senior Director, Institutional Compliance and Enterprise Risk Management
Bhramar Mukherjee, Chair, AI Faculty Working Group
John Lafferty, Professor of Statistics and Data Science
L.A. Paul, Professor of Philosophy and Professor of Cognitive Science
Nisheeth Vishnoi, Professor of Computer Science
Lisa Messeri, Associate Professor of Anthropology 

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