Regulatory Accountability for AI Governance Mechanisms: Coordinating Multiple Regulators

13 Pages Posted: 5 Jan 2021

Date Written: November 1, 2020


As autonomous and intelligent systems continue to grow in importance, key stakeholders from government, civil society, and the private sector have released draft governance frameworks for these technologies. This piece makes an argument for how one might construct a unified framework for thinking about accountability in the regulation of autonomous and intelligent systems. It proposes a simple, cost- based framework for deciding whether to add (or subtract) the n ’th regulatory body to the existing regulatory mix. The development of such a framework is important to ensure the optimal development of mixed regulatory systems. In a space that is evolving as quickly as automated systems accountability, a broad set of stakeholders make a broad set of demands as to which costs or harms should be addressed by regulation. As a result, there can be an impulse to continue to add on layers of regulation, without giving appropriate weight to the fresh costs that those layers themselves can create. This framework addresses that worry.

Keywords: regulation, accountability, AI, law and economics, bureaucracy

JEL Classification: K20, K30, K40

Suggested Citation

Hill, Adam Douglas, Regulatory Accountability for AI Governance Mechanisms: Coordinating Multiple Regulators (November 1, 2020). Available at SSRN: or

Adam Douglas Hill (Contact Author)

Facebook Inc ( email )

Menlo Park, CA 94025
United States

Research Fellow ( email )

102 South Hall
Berkeley, CA 94720-4600
United States

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