The Impact of Artificial Intelligence on Rules, Standards, and Judicial Discretion

35 Pages Posted: 1 Apr 2019 Last revised: 1 Feb 2020

See all articles by Frank Fagan

Frank Fagan

South Texas College of Law Houston; EDHEC Augmented Law Institute

Saul Levmore

University of Chicago Law School

Date Written: March 25, 2019

Abstract

Artificial intelligence (AI), and machine learning in particular, promises lawmakers greater specificity and fewer errors. Algorithmic lawmaking and judging will leverage models built from large stores of data that permit the creation and application of finely tuned rules. AI is therefore regarded as something that will bring about a movement from standards to rules. Drawing on contemporary data science, this Article shows that machine learning is less impressive when the past is unlike the future, as it is whenever new variables appear over time. In the absence of regularities, machine learning loses its advantage and, as a result, looser standards can become superior to rules. We apply this insight to bail and sentencing decisions, as well as familiar corporate and contract law rules. More generally, we show that a Human-AI combination can be superior to AI acting alone. Just as today’s judges overrule errors and outmoded precedent, tomorrow’s lawmakers will sensibly overrule AI in legal domains where the challenges of measurement are present. When measurement is straightforward and prediction is accurate, rules will prevail. When empirical limitations such as overfit, Simpson’s Paradox, and omitted variables make measurement difficult, AI should be trusted less and law should give way to standards.

Suggested Citation

Fagan, Frank and Levmore, Saul, The Impact of Artificial Intelligence on Rules, Standards, and Judicial Discretion (March 25, 2019). Southern California Law Review, Vol. 93, No. 1, pp. 1, 2019, U of Chicago, Public Law Working Paper No. 704, University of Chicago Coase-Sandor Institute for Law & Economics Research Paper No. 876, Available at SSRN: https://ssrn.com/abstract=3362563 or http://dx.doi.org/10.2139/ssrn.3362563

Frank Fagan

South Texas College of Law Houston

1303 San Jacinto Street
Houston, TX 77002
United States

EDHEC Augmented Law Institute

Roubaix, 59057
France

Saul Levmore (Contact Author)

University of Chicago Law School ( email )

1111 E. 60th St.
Chicago, IL 60637
United States
773-702-9590 (Phone)
773-702-0730 (Fax)

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