Gillian Hadfield 2023 Senior Fellow
Affiliation Professor, University of Toronto Hard Problem Solved challenges of safety and control, human alignment and compatibility with increasingly powerful and capable AI and eventually AGI.

Gillian K. Hadfield, B.A. (Hons.) Queens, J.D., M.A., Ph.D. (Economics) Stanford, is Professor of Law and Professor of Strategic Management at the University of Toronto and holds the Schwartz Reisman Chair in Technology and Society and a CIFAR AI Chair at the Vector Institute for Artificial Intelligence in Toronto. She is the inaugural Director of the Schwartz Reisman Institute for Technology and Society, a faculty affiliate at the Center for Human-Compatible AI at the University of California Berkeley, and Senior Policy Advisor at OpenAI in San Francisco. 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. Her book Rules for a Flat World: Why Humans Invented Law and How to Reinvent It for a Complex Global Economy was published by Oxford University Press in 2017; a paperback edition with a new prologue on AI was published in 2020.

AI2050 Project

Normativity–the practice of classifying behaviors as either “ok” or “not ok” and then getting people to choose “ok” behaviors–is a defining feature of the human. As we build ever-more powerful AI systems, it becomes critical to understand the deep structure of human normative systems in order to build AI that is normatively competent: able to understand, respect, and participate in the complex process by which human rules, values, and norms are constituted, maintained, and adapted. The goal of Hadfield’s AI2050 project is to determine how to build such systems and ensure that this is how AI systems are in fact built.