Download this Paper Open PDF in Browser

Regulation by Machine

7 Pages Posted: 2 Dec 2016 Last revised: 6 Dec 2016

Benjamin Alarie

University of Toronto - Faculty of Law

Anthony Niblett

University of Toronto - Faculty of Law

Albert Yoon

University of Toronto - Faculty of Law

Date Written: December 1, 2016

Abstract

Legal scholars investigating artificial intelligence are preoccupied with regulation. The literature has largely focused on the need for humans to regulate the behavior of automated systems. In this paper, we focus on the converse: how artificially intelligent systems can serve to regulate human behavior. The shortcomings of human-led regulation are clear. We argue that machine learning technology can address some of these limitations. We provide examples of how machine learning can predict how courts would decide legal disputes more cheaply and accurately than human regulators. This allows regulators to streamline operations, providing fast, accurate, consistent, and reliable ex ante regulatory advice and rulings. We further explore how machine learning technology might soon be used to refine laws and reduce errors.

Keywords: machine learning, artificial intelligence, regulation

JEL Classification: K00, K10, K20, K23

Suggested Citation

Alarie, Benjamin and Niblett, Anthony and Yoon, Albert, Regulation by Machine (December 1, 2016). Available at SSRN: https://ssrn.com/abstract=2878950 or http://dx.doi.org/10.2139/ssrn.2878950

Benjamin Alarie

University of Toronto - Faculty of Law ( email )

Jackman Law Building
78 Queen's Park
Toronto, Ontario M5S 2C5
Canada
416-946-8205 (Phone)
416-978-7899 (Fax)

HOME PAGE: http://www.law.utoronto.ca/faculty-staff/full-time-faculty/benjamin-alarie

Anthony Niblett (Contact Author)

University of Toronto - Faculty of Law ( email )

78 and 84 Queen's Park
Toronto, Ontario M5S 2C5
Canada

Albert Yoon

University of Toronto - Faculty of Law ( email )

78 and 84 Queen's Park
Toronto, Ontario M5S 2C5
Canada

Paper statistics

Downloads
349
Rank
72,085
Abstract Views
1,530