Balancing the Tradeoff between Regulation and Innovation for Artificial Intelligence: An Analysis of Top-down Command and Control and Bottom-up Self-Regulatory Approaches

29 Pages Posted: 28 Sep 2022 Last revised: 12 Dec 2022

See all articles by Keith Jin Deng Chan

Keith Jin Deng Chan

The Hong Kong University of Science and Technology

Gleb Papyshev

The Hong Kong University of Science and Technology

Masaru Yarime

The Hong Kong University of Science and Technology - Division of Public Policy; The University of Tokyo - Graduate School of Public Policy; University College London - Department of Science, Technology, Engineering and Public Policy

Date Written: October 20, 2022

Abstract

In response to the rapid development of AI, several governments have established a variety of regulatory interventions for this technology. While some countries prioritize consumer protection through stringent regulation, others promote innovation by adopting a more hands-off approach. However, this tradeoff has not been analyzed systematically. We developed an economic theory on how the welfare-maximizing level of regulatory stringency for AI depends on various institutional parameters. Our game-theoretic model is motivated and built upon the comparison of regulatory documents for AI from the EU, the UK, the US, Russia, and China. The results show that if a government strives to find the right balance between innovation and consumer protection to maximize actual consumer welfare, stringent regulation is optimal when foreign competition is either high or low, whereas light-touch regulation is optimal when foreign competition is intermediate. Meanwhile, minimal regulation is rationalizable only if a government prioritizes other objectives in its agenda, such as maximizing innovation, domestic producer surplus, or perceived consumer welfare.

Keywords: AI regulation, AI ethics, innovation, consumer protection, game theory

JEL Classification: D04, L51, L86, O31

Suggested Citation

Chan, Keith Jin Deng and Papyshev, Gleb and Yarime, Masaru, Balancing the Tradeoff between Regulation and Innovation for Artificial Intelligence: An Analysis of Top-down Command and Control and Bottom-up Self-Regulatory Approaches (October 20, 2022). Available at SSRN: https://ssrn.com/abstract=4223016 or http://dx.doi.org/10.2139/ssrn.4223016

Gleb Papyshev

The Hong Kong University of Science and Technology ( email )

Clearwater Bay
Kowloon, 999999
Hong Kong

Masaru Yarime

The Hong Kong University of Science and Technology - Division of Public Policy ( email )

Room 4611, PPOL, HKUST
Clear Water Bay, Kowloon
Hong Kong
Hong Kong

HOME PAGE: http://yarime.net/

The University of Tokyo - Graduate School of Public Policy ( email )

Hongo 7-3-1
Bunkyo-ku
Tokyo, 113-0033
Japan

HOME PAGE: http://yarime.net/

University College London - Department of Science, Technology, Engineering and Public Policy ( email )

Gower Street
London, WC1E 6BT
United Kingdom

HOME PAGE: http://yarime.net

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