The Right to Contest AI

92 Pages Posted: 18 Nov 2021 Last revised: 7 Dec 2021

See all articles by Margot E. Kaminski

Margot E. Kaminski

University of Colorado Law School; Yale University - Yale Information Society Project; University of Colorado at Boulder - Silicon Flatirons Center for Law, Technology, and Entrepreneurship

Jennifer M. Urban

University of California, Berkeley - School of Law

Date Written: November 16, 2021

Abstract

Artificial intelligence (AI) is increasingly used to make important decisions, from university admissions selections to loan determinations to the distribution of COVID-19 vaccines. These uses of AI raise a host of concerns about discrimination, accuracy, fairness, and accountability.

In the United States, recent proposals for regulating AI focus largely on ex ante and systemic governance. This Article argues instead—or really, in addition—for an individual right to contest AI decisions, modeled on due process but adapted for the digital age. The European Union, in fact, recognizes such a right, and a growing number of institutions around the world now call for its establishment. This Article argues that despite considerable differences between the United States and other countries,establishing the right to contest AI decisions here would be in keeping with a long tradition of due process theory.

This Article then fills a gap in the literature, establishing a theoretical scaffolding for discussing what a right to contest should look like in practice. This Article establishes four contestation archetypes that should serve as the bases of discussions of contestation both for the right to contest AI and in other policy contexts. The contestation archetypes vary along two axes: from contestation rules to standards and from emphasizing procedure to establishing substantive rights. This Article then discusses four processes that illustrate these archetypes in practice, including the first in depth consideration of the GDPR’s right to contestation for a U.S. audience. Finally, this Article integrates findings from these investigations to develop normative and practical guidance for establishing a right to contest AI.

Keywords: AI, algorithms, algorithmic accountability, due process, privacy, big data

Suggested Citation

Kaminski, Margot E. and Urban, Jennifer M., The Right to Contest AI (November 16, 2021). Columbia Law Review, Vol. 121, No. 7, 2021, U of Colorado Law Legal Studies Research Paper No. 21-30, Available at SSRN: https://ssrn.com/abstract=3965041

Margot E. Kaminski (Contact Author)

University of Colorado Law School ( email )

401 UCB
Boulder, CO 80309
United States

Yale University - Yale Information Society Project ( email )

127 Wall Street
New Haven, CT 06511
United States

University of Colorado at Boulder - Silicon Flatirons Center for Law, Technology, and Entrepreneurship ( email )

Wolf Law Building
2450 Kittredge Loop Road
Boulder, CO
United States

Jennifer M. Urban

University of California, Berkeley - School of Law ( email )

342 Boalt Hall, North Addition
Berkeley, CA 94720-7200
United States
(510) 642-7338 (Phone)

HOME PAGE: http://www.samuelsonclinic.org

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
960
Abstract Views
4,309
rank
33,627
PlumX Metrics