Soft Law 2.0: An Agile and Effective Governance Approach for Artificial Intelligence

52 Pages Posted: 18 Jun 2023

See all articles by Gary E. Marchant

Gary E. Marchant

Arizona State University - College of Law

Carlos Ignacio Gutierrez

RAND Corporation, Pardee RAND Graduate School, Students; Arizona State University (ASU) - Sandra Day O'Connor College of Law; Future of Life Institute

Date Written: Deceember 8, 2022

Abstract

Artificial intelligence (AI) is the most transformative technology of our era, affecting every industry sector and aspect of our lives. While AI promises enormous benefits, some of which are already manifesting, AI also has the potential to create many risks and problems, some of which are already starting to appear. Traditional command-and-control government regulation, referred to as “hard law,” barely exists for AI, and following the pattern of other technologies, is likely to be adopted incrementally in a trickle that will extend over future decades. Thus, for now, and for the immediate future, AI will be primarily governed by “soft law,” which consists of a variety of instruments creating substantive expectations that are not directly enforceable by governments. The primary problem with soft law is that because it is not enforceable, there are doubts about its effectiveness. This article provides the results of a two-year study on how to make AI soft law more effective and credible. It first summarizes lessons from decades of soft law governance of other technologies, including biotechnology, nanotechnology, information and communication technologies, and environmental technology. Next it identifies, analyzes, and draws observations and insights from over 600 existing AI soft law programs. Finally, building on the previous two tasks, it proposes a new Soft Law 2.0 model that consists of a toolbox of thirteen different mechanisms that can be used to ensure that soft law measures are implemented as intended, which should help make AI soft law more effective and credible.

Keywords: Artificial Intelligence, governance, soft law

JEL Classification: K20, K29, K23, K32

Suggested Citation

Marchant, Gary E. and Gutierrez, Carlos Ignacio and Gutierrez, Carlos Ignacio, Soft Law 2.0: An Agile and Effective Governance Approach for Artificial Intelligence (Deceember 8, 2022). Minnesota Journal of Law, Science & Technology, Vol. 24, No. 2, 2023, Arizona State University Sandra Day O'Connor College of Law Legal Studies Research Paper No. 4473812, Available at SSRN: https://ssrn.com/abstract=4473812

Gary E. Marchant (Contact Author)

Arizona State University - College of Law ( email )

Box 877906
Tempe, AZ 85287-7906
United States
(480) 965-3246 (Phone)
(480) 965-2427 (Fax)

Carlos Ignacio Gutierrez

RAND Corporation, Pardee RAND Graduate School, Students ( email )

1776 Main Street
Santa Monica, CA 90401
United States

Arizona State University (ASU) - Sandra Day O'Connor College of Law ( email )

Box 877906
Tempe, AZ 85287-7906
United States

HOME PAGE: http://https://www.linkedin.com/in/carlosig/

Future of Life Institute ( email )

United States

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