Vol. 119 No. 7

Artificial Intelligence
Essay

RULEMAKING AND INSCRUTABLE AUTOMATED DECISION TOOLS

Katherine J. Strandburg*

Complex machine learning models derived from personal data are increasingly used in making decisions important to peoples’ lives. These automated decision tools are controversial, in part because their opera­tion is difficult for humans to grasp or explain. While scholars and policy­makers have begun grappling with these explainability concerns, the debate has focused on explanations to decision subjects. This Essay ar­gues that explainability[...]

Administrative Law
Keynote

KEYNOTE

Mariano-Florentino Cuéllar*

Introduction The majority of vehicles on California’s vast network of roads make con­siderable use of information technology. Although most are not yet capable of anything approaching fully autonomous driving, already it is possible to witness something like the following scene. A driver steering one vehicle spies a newer car’s reflection in the rear-view mirror. The […]

Artificial Intelligence
Essay

LAW’S HALO AND THE MORAL MACHINE

Bert I. Huang*

How will we assess the morality of decisions made by artificial intelli­gence—and will our judgments be swayed by what the law says? Focusing on a moral dilemma in which a driverless car chooses to sacrifice its passenger to save more people, this study offers evidence that our moral intuitions can be influenced by the presence of the law.

Artificial Intelligence
Essay

THE JUDICIAL DEMAND FOR EXPLAINABLE ARTIFICIAL INTELLIGENCE

Ashley Deeks*

A recurrent concern about machine learning algorithms is that they operate as “black boxes,” making it difficult to identify how and why the algorithms reach particular decisions, recommendations, or pre­dictions. Yet judges are confronting machine learning algorithms with in­creasing frequency, including in criminal, administrative, and civil cases. This Essay argues that judges should demand explanations for these algorithmic outcomes.[...]

Artificial Intelligence
CLR Forum

“CYBORG JUSTICE” AND THE RISK OF TECHNOLOGICAL-LEGAL LOCK-IN

Rebecca Crootof*

Introduction An Estonian team is designing an artificially-intelligent (AI) agent to adjudicate claims of €7,000 or less, with the aim of clearing case backlog. The pilot version will focus on contract disputes: An algorithm will ana­lyze uploaded documents to reach an initial decision, which can then be appealed to a human judge. This is but […]

Antitrust
Essay

DISRUPTIVE INCUMBENTS: PLATFORM COMPETITION IN AN AGE OF MACHINE LEARNING

C. Scott Hemphill*

Recent advances in machine learning have reinforced the competitive position of leading online platforms. This Essay identifies two important sources of platform rivalry and proposes ways to maximize their competitive potential under existing antitrust law. A nascent competitor is a threatening new entrant that, in time, might become a full-fledged platform rival. A platform’s acquisition of a nascent competitor should be prohibited as an unlawful[...]

Artificial Intelligence
Essay

WILL ARTIFICIAL INTELLIGENCE EAT THE LAW? THE RISE OF HYBRID SOCIAL-ORDERING SYSTEMS

Tim Wu*

Software has partially or fully displaced many former human activities, such as catching speeders or flying airplanes, and proven itself able to surpass humans in certain contests, like Chess and Go. What are the prospects for the displacement of human courts as the centerpiece of legal decisionmaking? Based on the case study of hate speech control on major tech platforms, particularly on Twitter and Facebook, this Essay suggests displacement of[...]

Artificial Intelligence
CLR Forum

RECOVERING TECH’S HUMANITY

Olivier Sylvain*

Introduction Tim Wu’s essay, Will Artificial Intelligence Eat the Law?, posits that automated decisionmaking systems may be taking the place of hu­man adjudication in social media content moderation. Conventional adjudi­cative processes, he explains, are too slow or clumsy to keep up with the speed and scale of online information flows. Their eclipse is immi­nent, inevitable, […]

Artificial Intelligence
Essay

AI SYSTEMS AS STATE ACTORS

Kate Crawford* & Jason Schultz**

Many legal scholars have explored how courts can apply legal doctrines, such as procedural due process and equal protection, directly to government actors when those actors deploy artificial intelligence (AI) systems. But very little attention has been given to how courts should hold private vendors of these technologies accountable when the government uses their AI tools in ways that violate the law. This is a concerning gap, given that governments[...]

Artificial Intelligence
Essay

MINDS, MACHINES, AND THE LAW: THE CASE OF VOLITION IN COPYRIGHT LAW

Mala Chatterjee* & Jeanne C. Fromer**

The increasing prevalence of ever-sophisticated technology permits machines to stand in for or augment humans in a growing number of contexts. The questions of whether, when, and how the so-called actions of machines can and should result in legal liability thus will also become more practically pressing. One important set of questions that the law will inevitably need to confront is whether machines can have mental states, or—at least—something[...]

Artificial Intelligence
Essay

SEX LEX MACHINA: INTIMACY AND ARTIFICIAL INTELLIGENCE

Jeannie Suk Gersen*

Sex robots are here. Created specifically to allow individuals to simulate erotic and romantic experiences with a seemingly alive and present human being, sex robots will soon force lawmakers to address the rise of digisexuality and the human–robot relationship. The extent to which intimacy between a human and robot can be regulated depends on how we characterize sex with robots—as a masturbatory act, an in­timate relationship, or nonconsensual[...]

Administrative Law
Essay

DATA-INFORMED DUTIES IN AI DEVELOPMENT

Frank Pasquale*

Law should help direct—and not merely constrain—the development of artificial intelligence (AI). One path to influence is the development of standards of care both supplemented and informed by rigorous regulatory guidance. Such standards are particularly important given the potential for inaccurate and inappropriate data to contaminate machine learning. Firms relying on faulty data can be required to compensate those harmed by that data use—and[...]