Problems with Probability

Author:

Casey Anthony J1,Niblett Anthony2

Affiliation:

1. Donald M Ephraim Professor of Law and Economics and Faculty Director of the Center on Law and Finance, University of Chicago Law School, United States

2. Associate Professor, Faculty of Law, University of Toronto; Canada Research Chair in Law, Economics and Innovation and a faculty affiliate, Vector Institute of Artificial Intelligence, Toronto, Canada

Abstract

Some countries have explored the idea of using artificial intelligence (AI) systems to help triage the backlog of cases and facilitate the resolution of civil disputes. In theory, AI can accomplish this by establishing the facts of cases and predicting the outcomes of disputes. But the use of AI in the courtroom gives rise to new problems. AI technologies help solve prediction problems. These solutions are typically expressed as probabilities. How should judges incorporate these predictions in their decision making? There is no obviously correct approach for converting probabilistic predictions of legal outcomes into binary legal decisions. Any approach that does so has benefits and drawbacks. Importantly, a balance of probabilities approach – where liability is established if the AI predicts a likelihood of liability greater than 50 per cent and not otherwise – is not suitable when converting a predicted outcome into an actual outcome. Adopting this approach would significantly alter the outcomes of legal cases and have a dramatic and disruptive effect upon the law. The most notable disruption would be observed in settlement behaviour and outcomes.

Publisher

University of Toronto Press Inc. (UTPress)

Subject

Law,Sociology and Political Science

Reference42 articles.

1. See Ajay Agrawal, Joshua Gans & Avi Goldfarb, Power and Prediction: The Disruptive Economics of Artificial Intelligence (Boston: Harvard Business Review Press, 2022) [Agrawal, Gans & Goldfarb, Power and Prediction]; Ajay Agrawal, Joshua Gans & Avi Goldfarb, Prediction Machines: The Simple Economics of Artificial Intelligence (Boston: Harvard Business Review Press, 2018) [Agrawal, Gans & Goldfarb, Prediction Machines].

2. Of the 270,266 civil disputes that were resolved in 2019–20 in Ontario courts, 40,061 had taken longer than two years to resolve. This percentage (14.82 per cent) is not atypical across the past five years. See Statistics Canada, ‘Active Civil Court Cases, by Elapsed Time from Case Initiation to First Disposition, Canada and Selected Provinces and Territories’ (10 March 2022), online: Statistics Canada [perma.cc/9A2W-GWT2].

3. See Anthony Niblett & Albert H Yoon, ‘Unintended Consequences: The Regressive Effects of Increased Access to Courts’ (2017) 14:1 J Empirical Leg Stud 5 at 22.

4. See European Commission for the Efficiency of Justice, ‘CEPEJ Indicators on Efficiency’ (last updated 27 September 2022), online: Tableau Public [perma.cc/HD6F-3U4G] (in 2020, the average disposition of a civil law dispute in France was 637 days, while, in Italy, it was 674 days).

5. See Fausto Martin De Sanctis, ‘Artificial Intelligence and Innovation in Brazilian Justice’ (2021) 59:1 International Annals of Criminology 1 at 2–3.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3