Response to the UK White Paper: A pro-innovation approach to AI regulation

11 Pages Posted: 23 Jun 2023

See all articles by Chris Reed

Chris Reed

Queen Mary University of London, School of Law

Keri Grieman

Queen Mary University of London, School of Law; University of Oxford; The Alan Turing Institute

Date Written: June 14, 2023

Abstract

We propose a risk-based regulatory system for AI based on requiring those who develop and operate AI systems to explain and justify the steps they have taken to mitigate specified risks, and to operate their systems in accordance with those explanations.

Liability to compensate for losses caused by the AI has three bases:

* Failure to operate in accordance with the risk mitigation explanation
* Failure to perform to the same standard as a human counterpart
* Failure to take reasonable care in the development and operation of the AI, with a reversed burden of proof.

The regulatory scheme also provides for the possibility of regulatory sanctions in appropriate, high risk, cases.

Keywords: AI, Regulation, Liability, Risk

JEL Classification: K13, K2, K23, K29, K39, O38

Suggested Citation

Reed, Chris and Grieman, Keri, Response to the UK White Paper: A pro-innovation approach to AI regulation (June 14, 2023). Available at SSRN: https://ssrn.com/abstract=4478556 or http://dx.doi.org/10.2139/ssrn.4478556

Chris Reed (Contact Author)

Queen Mary University of London, School of Law ( email )

67-69 Lincoln’s Inn Fields
London, WC2A 3JB
United Kingdom

Keri Grieman

Queen Mary University of London, School of Law ( email )

Mile End Road
Lincoln's Inn Fields
London, London E1 4NS
United Kingdom

University of Oxford ( email )

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

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