person
Gillian Hadfield
University of Toronto; 'regulatory markets' theorist
Legal scholar who proposed 'regulatory markets', governments require AI targets to purchase regulatory services from private regulators, as a scalable AI governance design. Canada CIFAR AI Chair.
Profile
expertise
Policy / meta
Specialises in AI policy, regulation, governance, philanthropy, or movement strategy. Reads the technical literature but does not produce it.
University of Toronto Schwartz Reisman; OpenAI. Senior policy researcher with legal and economic background. Not a technical AI contributor.
recognition
Field-leading
Widely known inside the AI and AI-safety community. Appears repeatedly in top venues, podcasts, or governance forums. Not a household name to outsiders.
Recognised in AI-governance and academic-law communities.
vintage
Deep-learning rise
Came up post-AlexNet. ImageNet, AlphaGo, transformer paper. DeepMind, Google Brain, FAIR establish the modern lab template.
Schwartz Reisman Institute founded 2019. Regulatory markets and AI law work in deep-learning era.
Hand-classified. See the board for the criteria and the full grid.
Strategy positions
Governance firstendorses
Lead with regulation, treaties, liability regimesArgues the standard harms-regulation paradigm is necessary but insufficient; proposes private regulatory markets as a scalable complement.
Regulatory markets require the targets of regulation to purchase regulatory services from a private regulator, which competes on quality of regulation.
Closest strategy neighbours
by jaccard overlapOther people whose strategy tags overlap with Gillian Hadfield's. Overlap is on tag identity, not stance; opposites can show up if they reference the same tags.
Record last updated 2026-04-24.