Algorithmic Bias and the New Chicago School

Law, Innovation & Technology, Volume 14, Issue 1, 2022

The Chinese University of Hong Kong Faculty of Law Research Paper No. 2022-10

19 Pages Posted: 7 Apr 2022

See all articles by Jyh-An Lee

Jyh-An Lee

The Chinese University of Hong Kong (CUHK) - Faculty of Law

Date Written: March 29, 2022

Abstract

AI systems are increasingly deployed in both public and private sectors to independently make complicated decisions with far-reaching impact on individuals and the society. However, many AI algorithms are biased in the collection or processing of data, resulting in prejudiced decisions based on demographic features. Algorithmic biases occur because of the training data fed into the AI system or the design of algorithmic models. While most legal scholars propose a direct-regulation approach associated with right of explanation or transparency obligation, this article provides a different picture regarding how indirect regulation can be used to regulate algorithmic bias based on the New Chicago School framework developed by Lawrence Lessig. This article concludes that an effective regulatory approach toward algorithmic bias will be the right mixture of direct and indirect regulations through architecture, norms, market, and the law.

Keywords: algorithmic bias; automated decision making; artificial intelligence; explainable AI; New Chicago School

Suggested Citation

Lee, Jyh-An, Algorithmic Bias and the New Chicago School (March 29, 2022). Law, Innovation & Technology, Volume 14, Issue 1, 2022 , The Chinese University of Hong Kong Faculty of Law Research Paper No. 2022-10, Available at SSRN: https://ssrn.com/abstract=4069392

Jyh-An Lee (Contact Author)

The Chinese University of Hong Kong (CUHK) - Faculty of Law ( email )

6/F, Lee Shau Kee Building
Shatin, New Territories
Hong Kong

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