Gillian Hadfield
Chair & Director of Schwartz Reisman Chair in Technology and Society, University of Toronto



(Wednesday, 21st May 2008)

Title : Legal Design and the Production of Law

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In these lectures, we will examine the problem of how law understood as an economic input is produced.  It is conventional to think of law as the product of the state—enacted by legislatures and regulators and enforced by judges.  Much law, however, is in fact produced by the interplay of the work of judges and lawyers and law can be produced by wholly private actors, much as other economic inputs are. 

In the first lecture, we will explore the process by which law is produced in courts through the interplay of the work of lawyers and judges, both in civil law and common law jurisdictions.
In the second lecture, we will examine the potential for law to be produced by private entities and offered as a product on commercial markets.
Both lectures will focus on how we should think about designing legal institutions to promote economic activity and growth.

Bibliographical references :

Must read reference : Gillian K. Hadfield. "The Levers of Legal Design: Institutional Determinants of the Quality of Law" Journal of Comparative Economics (2008).
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Nicola Gennaioli, Andrei Shleifer, "The Evolution of Common Law", Journal of Political Economy 2007 115:1, 43-68
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Lisa Bernstein, "Private Commercial Law in the Cotton Industry: Creating Cooperation through Rules, Norms, and Institutions", Michigan Law Review, Vol. 99, No. 7 (Jun., 2001), pp. 1724-1790
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Gillian K. Hadfield and Eric Talley. "On Public versus Private Provision of Corporate Law" Journal of Law, Economics and Organization 14 (2006): 137-163.
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(Monday, 15th May 2023)

Title : AI Governance: Normative Infrastructure for AI Alignment

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AI Governance: Normative Infrastructure for AI Alignment

This talk addresses questions of ‘governance’ of AI but from the perspective of what it means to build AI systems that can participate in (human) normative systems (like norms and laws). It integrates my work with Barry Weingast "Building Positive Economic Models of Normative Social Order" with my work on multiagent reinforcement learning systems. I’ll ground the talk in the basic questions of AI alignment—how do we make sure AI systems do what we want them to do?