PLEASE NOTE REVISED START TIME
The 2019 Meetings of the Canadian Law & Economics Association
Tory Public Lecture
presents
Gillian Hadfield
University of Toronto Faculty of Law
Why the Science of AI Needs a Science of Normativity
Friday September 20, 2019
1:30 PM - 2:30 PM
Room J140, Jackman Law Building
78 Queen’s Park
Normativity refers to the practice of classifying actions as either acceptable or not acceptable. Normative systems incentivize and coordinate actors in a group to choose actions that are deemed acceptable by that group. Social norms, ethics, and law and regulation are examples of normative systems. In this talk, I’ll explain why the invention and evolution of increasingly complex normative systems are central to understanding the extraordinary success of humans as a species. In particular, I’ll emphasize the role of normativity in coordinating humans’ ultrasociality and cooperation. The capacity to participate in ultrasocial cooperative behaviour is arguably the essence of human intelligence, as effectively all human tasks (participating in markets and the workplace, for example) require such behaviour. This suggests that understanding normative behaviour and normative systems is critical to the project of building artificial intelligence defined as machines capable of acting appropriately and with foresight in an environment (Nilsson 2010). Unfortunately, the science of normativity is highly underdeveloped: our existing approaches are dominated by descriptive and internal accounts rather than systemic, external, and predictive accounts. I’ll argue that researchers focused on building and regulating general intelligence should take on the task of rapidly raising the sophistication of our understanding of how normativity works, not only for the purpose of ensuring that AI is aligned with human values, but more fundamentally in order to build functioning systems that can integrate into human societies.
Gillian 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. She is the inaugural Director of the Schwartz Reisman Institute for Technology and Society. Her research is focused on innovative design for legal and dispute resolution systems in advanced and developing market economies; governance for artificial intelligence; the markets for law, lawyers, and dispute resolution; and contract law and theory. Professor Hadfield is a Faculty Affiliate at the Vector Institute for Artificial Intelligence in Toronto and at the Center for Human-Compatible AI at the University of California Berkeley and Senior Policy Advisor at OpenAI in San Francisco. 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.
For more information, please send an email to events.law@utoronto.ca.
