Three Laws Blog: Law and Artificial Intelligence

McKay on Predicting Risk in Criminal Procedure @carolyn_mak

Carolyn McKay, University of Sydney Law School, is publishing Predicting Risk in Criminal Procedure: Actuarial Tools, Algorithms, AI and Judicial Decision-Making, in Predicting Risk in Criminal Procedure: Actuarial Tools, Algorithms, AI and Judicial Decision-Making' (C. McKay, ed. Current Issues in Criminal Justice, 2019 (Forthcoming)).

Risk assessments are conducted at a number of decision points in criminal procedure including in bail, sentencing and parole as well as in determining extended supervision and continuing detention orders of high risk offenders. Such risk assessments have traditionally been the function of the human discretion and intuition of judicial officers, based on clinical assessments, framed by legislation and common law principles, and encapsulating the concept of individualised justice. Yet the progressive technologisation of criminal procedure is witnessing the incursion of statistical, data-driven evaluations of risk. Human judicial evaluative functions are increasingly complemented by a range of actuarial, algorithmic, machine learning and Artificial Intelligence (AI) tools that purport to provide accurate predictive capabilities, and objective, consistent risk assessments. But ethical concerns have been raised globally regarding algorithms as proprietary products with in-built statistical bias as well as the diminution of judicial human evaluation in favour of the machine. This article focuses on risk assessment and what happens when decision-making is delegated to a predictive tool. Specifically, this article scrutinises the inscrutable proprietary nature of such risk tools and how that may render the calculation of the risk score opaque and unknowable to both the offender and the court.

Download the essay from SSRN at the link.

Barabas on Re-Imagining the Terms of "Ethical AI" in Criminal Law @chels_bar

Chelsea Barabas, MIT Media Lab, has published Beyond Bias: Re-Imagining the Terms of ‘Ethical AI’ in Criminal Law. Here is the abstract.

Data-driven decision-making regimes, often branded as “artificial intelligence,” are rapidly proliferating across the US criminal justice system as a means of predicting and managing the risk of crime and addressing accusations of discriminatory practices. These data regimes have come under increased scrutiny, as critics point out the myriad ways that they can reproduce or even amplify pre-existing biases in the criminal justice system. This essay examines contemporary debates regarding the use of “artificial intelligence” as a vehicle for criminal justice reform, by closely examining two general approaches to, what has been widely branded as, “algorithmic fairness” in criminal law: 1) the development of formal fairness criteria and accuracy measures that illustrate the trade-offs of different algorithmic interventions and 2) the development of “best practices” and managerialist standards for maintaining a baseline of accuracy, transparency and validity in these systems. The essay argues that attempts to render AI-branded tools more accurate by addressing narrow notions of “bias,” miss the deeper methodological and epistemological issues regarding the fairness of these tools. The key question is whether predictive tools reflect and reinforce punitive practices that drive disparate outcomes, and how data regimes interact with the penal ideology to naturalize these practices. The article concludes by calling for an abolitionist understanding of the role and function of the carceral state, in order to fundamentally reformulate the questions we ask, the way we characterize existing data, and how we identify and fill gaps in existing data regimes of the carceral state.

Download the article from SSRN at the link.

Mulligan on Revenge Against Robots @MulliganEsq

Christina Mulligan, Brooklyn Law School, has published Revenge Against Robots. Here is the abstract.

When a robot hurts a human, how should the legal system respond? Our first instinct might be to ask who should pay for the harm caused, perhaps deciding to rest legal liability with the robot’s hardware manufacturer or its programmers. But besides considering tort or criminal actions against corporate and human persons, legal actors might also target the most immediate source of the harm — the robot itself. By considering the role of revenge and psychological satisfaction in human disputes, this essay explores the benefits to human persons that could accrue through the corporeal punishment of robots. Along the way, the paper discusses dueling, deodands, free will, rogue gardeners, shooting down drones, and destroying printers with baseball bats.

Download the article from SSRN at the link.

The Use of AI In Sentencing: What Process Is Due

The New York Times discusses the part that an algorithm played in a defendant's sentencing. The issue is raising due process considerations, and the case is now before the U.S. Supreme Court.  More here.

Via @FleurEJ

Donohue on Federal and State Use and Regulation of Unmanned Aircraft Systems @georgetownlaw

Laura Donohue, Georgetown University Law Center, is publishing A Tale of Two Sovereigns: Federal and State Use and Regulation of Unmanned Aircraft Systems in Handbook of Unmanned Aerial Vehicles (Kimon P. Valavanis and George J. Vachtsevanos, eds., 2017) (forthcoming). Here is the abstract.

Despite claims to the contrary, the Federal government is severely limited in what it can do to regulate unmanned aircraft systems (UAS). States, on the other hand, as governments of general jurisdiction, have expansive powers that they are already using to grapple with the questions posed by UAS related to privacy, crime, and public safety. This chapter outlines the evolution of federal measures, noting their limitations, before delving into three categories of state law, related to law enforcement, criminal measures, and regulatory regimes. The chapter then turns to the history of state sovereignty, looking at states’ jurisdiction over persons and land within their bounds, before turning to the limits of federal inter-state commerce authorities. With river navigation and aviation serving as the forerunners of federal power, the chapter distinguishes the types of questions that accompany UAS, arguing that it is in relation to adjacent airspace and non-economic activities where the federal government is at its weakest in any effort to regulate the states. Up to 500 feet above the ground, states have sovereignty, with authority over roads, land, and waterways. Within this domain, Federal Commerce Clause powers only occupy a narrow area, leaving state police powers the dominant framework for UAS. The chapter concludes by highlighting the advantages of having states take the lead for UAS, focusing on the risk to rights of allowing the federal government to move into this realm and underscoring the importance in the role of the states as incubators of innovation.

Download the essay from SSRN at the link.

Joh on Policing Police Robots @elizabeth_joh

Elizabeth E. Joh, University of California, Davis, School of Law, has published Policing Police Robots at 64 UCLA L. Rev. Discourse 516 (2016). Here is the abstract.

The possibility of police robots capable of lethal force and with some degree of autonomy raises questions about what sort of limits and regulations should be imposed on robotic policing. Police robotics raise special questions because of the powers entrusted to the police. This essay considers the law and policy implications of a future where police robots are sophisticated, cheap, and widespread. Drawing upon the rapidly developing body of robotics law scholarship, as well as upon technological advances developing in military robotics — from which domestic policing will surely borrow — we can anticipate well ahead of its practical adoption the kinds of regulatory challenges we will face with the future of robotic policing.

Download the article from SSRN at the link.

Dubai Is Adding Robot Police To Its Force

According to this article in Gulf News, Dubai plans to add its first AI police officer to law enforcement soon, and hopes to make robot police fully twenty-five percent of the total force by 2030. Now, no doughnut shop jokes, okay?  :-)

Defendant in Arkansas Murder Agrees To Release of Amazon Echo Data

From ArsTechnica, an update on that Arkansas murder trial, in which the prosecution is seeking access to data from Amazon's cloud. The issue? Did the defendant's Echo device "overhear" anything that might support the prosecution's case against him? Amazon has been resisting turning over the data, but the defendant has now agreed to its release. 

Stay, well, tuned.

Gless, Silverman, and Weigend on Self-Driving Cars and Criminal Liability

Sabine Gless, University of Basel, Emily Silverman, Max Planck Society for the Advancement of the Sciences, Max Planck Institute for Foreign and International Criminal Law, and Thomas Weigend, University of Cologne, have published If Robots Cause Harm, Who is to Blame? Self-Driving Cars and Criminal Liability. Here is the abstract.

The fact that robots, especially self-driving cars, have become part of our daily lives raises novel issues in criminal law. Robots can malfunction and cause serious harm. But as things stand today, they are not suitable recipients of criminal punishment, mainly because they cannot conceive of themselves as morally responsible agents and because they cannot understand the concept of retributive punishment. Humans who produce, program, market and employ robots are subject to criminal liability for intentional crime if they knowingly use a robot to cause harm to others. A person who allows a self-teaching robot to interact with humans can foresee that the robot might get out of control and cause harm. This fact alone may give rise to negligence liability. In light of the overall social benefits associated with the use of many of today's robots, however, the authors argue in favor of limiting the criminal liability of operators to situations where they neglect to undertake reasonable measures to control the risks emanating from robots.

Download the article from SSRN at the link.