Gillian Hadfield: Normative Infrastructure for AI Safety and Alignment

On Monday, March 4, 2024, Gillian Hadfield of the University of Toronto joined us to discuss new research, "Normative Infrastructure for AI Safety and Alignment."
Abstract
The great majority of AI safety and alignment efforts focus on identifying specific human values, preferences, or policies and finding ways either to embed those via AI training or finetuning or to impose them as standards on deployed systems. But all of these approaches are likely to be quite brittle and of short-lived success: human normative systems are complex, highly variable, and dynamic. In this talk I’ll present several ideas about how to build the normative infrastructure necessary for more robust AI alignment. These ideas include building the legal infrastructure need for agile governance, such as registration for frontier models, legal “personhood” for AI agents, and regulatory markets to recruit private sector innovation of regulatory technologies, and the technical infrastructure necessary to train AI systems to read and participate in our dynamic normative environments.