Gillian K. Hadfield

Faculty Member

Professor of Law, Professor of Strategic Management, Faculty of Law, University of Toronto

Canada CIFAR Artificial Intelligence Chair

Gillian K. Hadfield is the Schwartz Reisman Chair in Technology and Society, professor of law and strategic management at the University of Toronto, and a Canada CIFAR AI Chair at the Vector Institute for Artificial Intelligence. Her current research is focused on innovative design for legal and regulatory systems for AI and other complex global technologies; computational models of human normative systems; and working with machine learning researchers to build ML systems that understand and respond to human norms. Hadfield was the inaugural director of the Schwartz Reisman Institute for Technology and Society from 2019 to 2023.

Research Interests

  • Human Normative Systems 
  • AI Alignment
  • Multi-Agent Systems 
  • Cooperative AI
  • AI Governance
  • Legal and Regulatory Design
  • Contracts
  • Institutional and Organizational Economics

Highlights

  • Founding Trustee of the Cooperative AI Foundation
  • Serves as a Senior Policy Advisor at OpenAI
  • Holds the Schwartz Reisman Chair in Technology and Society
  • Recipient of the Mundell Medal for Excellence in Legal Writing
  • Fellow of the Center for Advanced Study in the Behavioral Sciences at Stanford
  • Former President of the Society for Institutional and Organizational Economics
  • Former President of the Canadian Law and Economics Association

Publications

Managing ai risks in an era of rapid progress

Yoshua Bengio and Geoffrey Hinton and Andrew Yao and Dawn Song and Pieter Abbeel and Yuval Noah Harari and Ya-Qin Zhang and Lan Xue and Shai Shalev-Shwartz and Gillian Hadfield and Jeff Clune and Tegan Maharaj and Frank Hutter and Atılım Güneş Baydin and Sheila McIlraith and Qiqi Gao and Ashwin Acharya and David Krueger and Anca Dragan and Philip Torr and Stuart Russell and Daniel Kahneman and Jan Brauner and Sören Mindermann

2023

Judging facts, judging norms: Training machine learning models to judge humans requires a modified approach to labeling data

Aparna Balagopalan and David Madras and David H Yang and Dylan Hadfield-Menell and Gillian K Hadfield and Marzyeh Ghassemi

2023