Three Laws Blog: Law and Artificial Intelligence

Terzidou on The Use of Artificial Intelligence in the Judiciary and its Compliance with the Right to a Fair Trial @uni_lu

Kalliopi Terzidou, Universite du Luxembourg, Faculty of Law, Economics, and Finance, has published The Use of Artificial Intelligence in the Judiciary and its Compliance with the Right to a Fair Trial at 31 Journal of Judicial Administration 154 (2022). Here is the abstract.

European courts are increasingly investing in Artificial Intelligence (AI) applications for the automation of the administration of justice, to improve the efficiency and quality of the judiciary. However, AI can display considerable issues, such as opaqueness and unfair bias, resulting from the defective designing of their algorithms. This article explores the opportunities and risks of AI technology for court users – including judicial staff, legal representatives and litigants – by investigating proposed and developed applications by European judiciaries under the right to a fair trial. AI is found to pose certain risks to the independence and impartiality of the judiciary, as well as to the adversarial and public character of court proceedings, notwithstanding the opportunities for the improvement of access to courts. The regulatory solutions for the safe use of AI adopted by European judiciaries can encourage similar practices in other judiciaries, including Australia and the United States. Note: This publication is copyright. Other than for the purposes of and subject to the conditions prescribed under the Copyright Act 1968 (Cth), no part of it may in any form or by any means (electronic, mechanical, microcopying, photocopying, recording or otherwise) be reproduced, stored in a retrieval system or transmitted without prior written permission. Enquiries should be addressed to Thomson Reuters (Professional) Australia Limited. PO Box 3502, Rozelle NSW 2039. legal.thomsonreuters.com.au This article was first published by Thomson Reuters in the Journal of Judicial Administration and should be cited as Kalliopi Terzidou, The Use of Artificial Intelligence in the Judiciary and its Compliance with the Right to a Fair Trial, (2022) 31 JJA 154.

Eliot on The Dangers of Miscalculating Human Behavior Via Robo-Judges @LanceEliot

Lance B. Eliot, Stanford Center for Legal Informatics, has published The Dangers Of Miscalculating Human Behavior Via Robo-Judges. Here is the abstract.

There has been a trend lately of suggesting that robot judges (so-called robo-judges) will be able to determine the guilt of a defendant by merely using state-of-the-art sensory devices to watch and hear the accused. Besides the questionable aspects of whether this can or should be done, it also misportrays what AI-based judge-related systems might genuinely provide as an added value to adjudication.

Download the essay from SSRN at the link.

Eliot on Legal Argumentation and AI @LanceEliot

Lance B. Eliot, Stanford Center for Legal Informatics, has published Legal Argumentation and AI. Here is the abstract.

A mainstay of lawyers is their ability to undertake legal argumentation. This is a skill taught in law school and matured over the course of a legal career. AI is going to up the game, so to speak, by providing legal argumentation enablement. Attorneys need to ready themselves.

Download the essay from SSRN at the link.

McCarl on The Limits of Law and AI @UCinLawReview @UCLALawReview

Ryan McCarl, University of California, Los Angeles, School of Law, is publishing The Limits of Law and AI in volume 90 of the University of Cincinnati Law Review (2022). Here is the abstract.

For thirty years, scholars in the field of law and artificial intelligence (AI) have explored the extent to which tasks performed by lawyers and judges can be assisted by computers. This article describes the medium-term outlook for AI technologies and explains the obstacles to making legal work computable. I argue that while AI-based software is likely to improve legal research and support human decisionmaking, it is unlikely to replace traditional legal work or otherwise transform the practice of law.

Download the article from SSRN at the link.

Ranchordas on Experimental Regulations for AI: Sandboxes for Morals and Mores @SRanchordas @NomosVerlag

Sofia Ranchordas, University of Groningen; Yale Law School, Information Society Project, is publishing Experimental Regulations for AI: Sandboxes for Morals and Mores in volume 1 of Morals and Machines (2021). Here is the abstract.

Recent EU legislative and policy initiatives aim to offer flexible, innovation-friendly, and future-proof regulatory frameworks. Key examples are the EU Coordinated Plan on AI and the recently published EU AI Regulation Proposal which refer to the importance of experimenting with regulatory sandboxes so as to balance innovation in AI against its potential risks. Originally developed in the Fintech sector, regulatory sandboxes create a testbed for a selected number of innovative projects, by waiving otherwise applicable rules, guiding compliance, or customizing enforcement. Despite the burgeoning literature on regulatory sandboxes and the regulation of AI, the legal, methodological, and ethical challenges of regulatory sandboxes have remained understudied. This exploratory article delves into the some of the benefits and intricacies of employing experimental legal instruments in the context of the regulation of AI. This article’s contribution is twofold: first, it contextualizes the adoption of regulatory sandboxes in the broader discussion on experimental approaches to regulation; second, it offers a reflection on the steps ahead for the design and implementation of AI regulatory sandboxes.

Download the article from SSRN at the link.

Crootof on "Cyborg Justice" and the Risk of Technological-Legal Lock-In @RebeccaCrootof @yaleisp

Rebecca Crootof, University of Richmond School of Law; Yale University Information Society Project, is publishing 'Cyborg Justice' and the Risk of Technological-Legal Lock-In in the Columbia Law Review Forum (2019). Here is the abstract.

Although Artificial Intelligence (AI) is already of use to litigants and legal practitioners, we must be cautious and deliberate in incorporating AI into the common law judicial process. Human beings and machine systems process information and reach conclusions in fundamentally different ways, with AI being particularly ill-suited for the rule application and value balancing required of human judges. Nor will “cyborg justice”—hybrid human/AI judicial systems that attempt to marry the best of human and machine decisionmaking and minimize the drawbacks of both—be a panacea. While such systems would ideally maximize the strengths of human and machine intelligence, they might also magnify the drawbacks of both. They also raise distinct teaming risks associated with overtrust, undertrust, and interface design errors, as well as second-order structural side effects. One such side effect is “technological–legal lock-in.” Translating rules and decisionmaking procedures into algorithms grants them a new kind of permanency, which creates an additional barrier to legal evolution. In augmenting the common law’s extant conservative bent, hybrid human/AI judicial systems risk fostering legal stagnation and an attendant loss of judicial legitimacy.

Download the article from SSRN at the link.

Denno and Surujnath on Rise of the Machines: AI, Robotics, and the Reprogramming of Law @DeborahDenno

Deborah W. Denno, Fordham University School of Law, and Ryan Surujnath, BlackStone Group, G50 Capital Partners, have published Rise of the Machines: Artificial Intelligence, Robotics, and the Reprogramming of Law (Symposium Foreword) at 88 Fordham Law Review 381 (2019).

This Foreword provides an overview of Rise of the Machines: Artificial Intelligence, Robotics, and the Reprogramming of Law, a symposium hosted by the Fordham Law Review and cosponsored by the Fordham Law School’s Neuroscience and Law Center. As the Symposium spotlights, artificial intelligence (AI) and robotics are no longer the products of science fiction. AI is used by millions of people every day, from hedge fund managers to health-care professionals and even consumers of personalized assistants like Siri, Cortana, and Alexa. Neuroscience — “the branch of life sciences that studies the brain and nervous systems,” — is integral to AI development, as programmers seek to improve machines by understanding human thought patterns. Nonetheless, AI is something of a buzzword across the legal industry. There is still a certain mystique to the technology’s functionality that this Symposium intended to clarify while also assessing how it can affect legal regimes. In particular, this Symposium focused on problems posed by current and very near-future AI research and development with the aim to facilitate a dialogue among those who will shape the future of this impactful technology: neuroscientists, computer scientists, attorneys, and business professionals. As researchers continue to use neuroscience to make AI more “human” in its reasoning, the technology has encountered a range of human legal problems, including discrimination and bias, civil liability for risk-taking, and ownership of data and creative content. Regardless of the industry, ethical standards for the development of AI will be crucial. There is a popular adage in the world of computing: “garbage in, garbage out.” In essence, this idea tells us that flawed inputs will yield flawed results. It is an unfortunate reality that human beings are imperfect and susceptible to errors, biases, and prejudices. It is thus integral to reduce the impact that human judgments have on the tools we use. The transition to a world of algorithmic governance is not without its potential costs. As is particularly salient in the national discourse, it appears that our privacy is something of a premium. With the next great advancement in automated decision-making, individuals may stand to lose in privacy what they gain in convenience.

Download the article from SSRN at the link.

ICYMI: Kerr and Mathen on What Might Happen If We Discovered That Chief Justice Robots Were a Robot @ianrkerr @cmathen

ICYMI: Ian R. Kerr and Carissima Mathen, both of the University of Ottawa, Common Law Section, have published Chief Justice John Roberts is a Robot as a University of Ottawa Working Paper (2014). Here is the abstract.

This paper examines the implications of the use of artificial intelligence in judicial decision making. Designed around a counterfactual intended to provoke questions about the nature of judicial decision making and legal reasoning, the authors ask what would happen if it were discovered that the Chief Justice of the United States Supreme Court was a robot. Does it matter that many landmark legal decisions were made by an artificial intellect? Centered on the contention that judges do more than simply follow a wide and unimpeded path cleared by legislators and the framers of the constitution, the authors challenge readers to ask questions about legitimacy and the rule of law in the context of a contested understanding of the role of judges. These questions of legitimacy arise in three main areas: constitutional barriers, judicial fitness, and judging as a human endeavour. The authors find that the most fertile constitutional grounds for challenging an AI judge would be in the oath of office; on the other hand, a robot programmed to believe it is human cannot express the moral intent necessary to give meaning to a promissory act like swearing an oath. They also find that although an AI may be functionally able to perform the duties of a judge, it may not be able to follow rules and adopt the internal perspective necessary to meet the fitness requirements that are expected of human judges. Finally, the authors are skeptical of an AI’s ability to perform the inherently moral exercise of justification, which requires a judge to be a member of the community for which they adjudicate disputes. This paper is designed to examine the factors that come into play when considering the nature of judicial action, and to raise questions for the future of AI in the law.

Download the article from SSRN at the link.

Surden on AI and Law: An Overview and History @HarrySurden

Now available:  a lecture on Artificial Intelligence and Law, from Harry Surden, University of Colorado Law School. Watch it here. 

Lemley and Casey On Whether You Might Be a Robot @marklemley

Mark A. Lemley and Bryan Casey, both of Stanford Law School, have published You Might Be a Robot. Here is the abstract.

As robots and artificial intelligence (AI) increase their influence over society, policymakers are increasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots and AI — not even experts. What’s more, technological advances make it harder and harder each day to tell people from robots and robots from “dumb” machines. We’ve already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you’re reading this you’re (probably) not a robot, but certain laws might already treat you as one. Definitional challenges like these aren’t exclusive to robots and AI. But today, all signs indicate we’re approaching an inflection point. Whether it’s citywide bans of “robot sex brothels” or nationwide efforts to crack down on “ticket scalping bots,” we’re witnessing an explosion of interest in regulating robots, human enhancement technologies, and all things in between. And that, in turn, means that typological quandaries once confined to philosophy seminars can no longer be dismissed as academic. Want, for example, to crack down on foreign “influence campaigns” by regulating social media bots? Be careful not to define “bot” too broadly (like the California legislature recently did), or the supercomputer nestled in your pocket might just make you one. Want, instead, to promote traffic safety by regulating drivers? Be careful not to presume that only humans can drive (as our Federal Motor Vehicle Safety Standards do), or you may soon exclude the best drivers on the road. In this Article, we suggest that the problem isn’t simply that we haven’t hit upon the right definition. Instead, there may not be a “right” definition for the multifaceted, rapidly evolving technologies we call robots or AI. As we’ll demonstrate, even the most thoughtful of definitions risk being overbroad, underinclusive, or simply irrelevant in short order. Rather than trying in vain to find the perfect definition, we instead argue that policymakers should do as the great computer scientist, Alan Turing, did when confronted with the challenge of defining robots: embrace their ineffable nature. We offer several strategies to do so. First, whenever possible, laws should regulate behavior, not things (or as we put it, regulate verbs, not nouns). Second, where we must distinguish robots from other entities, the law should apply what we call Turing’s Razor, identifying robots on a case-by-case basis. Third, we offer six functional criteria for making these types of “I know it when I see it” determinations and argue that courts are generally better positioned than legislators to apply such standards. Finally, we argue that if we must have definitions rather than apply standards, they should be as short-term and contingent as possible. That, in turn, suggests regulators—not legislators—should play the defining role.

Download the article from SSRN at the link.