Law Commons^™

Topic Modeling The President: Conventional And Computational Methods, J.B. Ruhl, John Nay, Jonathan Gilligan

Vanderbilt Law School Faculty Publications

Legal and policy scholars modeling direct actions into substantive topic classifications thus far have not employed computational methods. To compare the results of their conventional modeling methods with the computational method, we generated computational topic models of all direct actions over time periods other scholars have studied using conventional methods, and did the same for a case study of environmental-policy direct actions. Our computational model of all direct actions closely matched one of the two comprehensive empirical models developed using conventional methods. By contrast, our environmental-case-study model differed markedly from the only empirical topic model of environmental-policy direct actions using …

Artificial Intelligence In Health Care: Applications And Legal Implications, W. Nicholson Price Ii

Articles

Artificial intelligence (AI) is rapidly moving to change the healthcare system. Driven by the juxtaposition of big data and powerful machine learning techniques—terms I will explain momentarily—innovators have begun to develop tools to improve the process of clinical care, to advance medical research, and to improve efficiency. These tools rely on algorithms, programs created from healthcare data that can make predictions or recommendations. However, the algorithms themselves are often too complex for their reasoning to be understood or even stated explicitly. Such algorithms may be best described as “black-box.” This article briefly describes the concept of AI in medicine, including …

Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …

Siri-Ously 2.0: What Artificial Intelligence Reveals About The First Amendment, Toni M. Massaro, Helen Norton, Margot E. Kaminski

Publications

The First Amendment may protect speech by strong Artificial Intelligence (AI). In this Article, we support this provocative claim by expanding on earlier work, addressing significant concerns and challenges, and suggesting potential paths forward.

This is not a claim about the state of technology. Whether strong AI — as-yet-hypothetical machines that can actually think — will ever come to exist remains far from clear. It is instead a claim that discussing AI speech sheds light on key features of prevailing First Amendment doctrine and theory, including the surprising lack of humanness at its core.

Courts and commentators wrestling with free …

Copyright For Literate Robots, James Grimmelmann

Cornell Law Faculty Publications

Almost by accident, copyright has concluded that copyright law is for humans only: reading performed by computers doesn't count as infringement. Conceptually, this makes sense: copyright's ideal of romantic readership involves humans writing for other humans. But in an age when more and more manipulation of copyrighted works is carried out by automated processes, this split between human reading (infringement) and robotic reading (exempt) has odd consequences and creates its own tendencies toward a copyright system in which humans occupy a surprisingly peripheral place. This essay describes the shifts in fair use law that brought us here and reflects on …

Siri-Ously? Free Speech Rights And Artificial Intelligence, Toni M. Massaro, Helen Norton

Publications

Computers with communicative artificial intelligence (AI) are pushing First Amendment theory and doctrine in profound and novel ways. They are becoming increasingly self-directed and corporal in ways that may one day make it difficult to call the communication ours versus theirs. This, in turn, invites questions about whether the First Amendment ever will (or ever should) cover AI speech or speakers even absent a locatable and accountable human creator. In this Article, we explain why current free speech theory and doctrine pose surprisingly few barriers to this counterintuitive result; their elasticity suggests that speaker humanness no longer may be …

Future Of Ai And Law, Abby Cessna

Cornell Law School J.D. Student Research Papers

Technology has already transformed the way that law is practiced. The use of computers and digital legal resources, such as LexisNexis and Westlaw have been around for decades, but these are just some of the major technological advancements that have transformed law. For instance, it was groundbreaking for a law firm as prestigious as Orrick, Herrington & Sutcliffe to have a website in the late 1990's, which was getting around 5000 visits a week. Now law firms not only have websites but also use a variety of social media services to promote their firm and services. In addition to promoting …

Machine Learning And Law, Harry Surden

Publications

This Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some task. In general, machine learning algorithms are designed to detect patterns in data and then apply these patterns going forward to new data in order to automate particular tasks. Outside of law, machine learning techniques have been successfully applied to automate tasks that were once thought to necessitate human intelligence — for example language translation, fraud-detection, driving automobiles, facial recognition, and data-mining. If performing …

Computer Models For Legal Prediction, Kevin D. Ashley, Stephanie Bruninghaus

Articles

Computerized algorithms for predicting the outcomes of legal problems can extract and present information from particular databases of cases to guide the legal analysis of new problems. They can have practical value despite the limitations that make reliance on predictions risky for other real-world purposes such as estimating settlement values. An algorithm's ability to generate reasonable legal arguments also is important. In this article, computerized prediction algorithms are compared not only in terms of accuracy, but also in terms of their ability to explain predictions and to integrate predictions and arguments. Our approach, the Issue-Based Prediction algorithm, is a program …

Capturing The Dialectic Between Principles And Cases, Kevin D. Ashley

Articles

Theorists in ethics and law posit a dialectical relationship between principles and cases; abstract principles both inform and are informed by the decisions of specific cases. Until recently, however, it has not been possible to investigate or confirm this relationship empirically. This work involves a systematic study of a set of ethics cases written by a professional association's board of ethical review. Like judges, the board explains its decisions in opinions. It applies normative standards, namely principles from a code of ethics, and cites past cases. We hypothesized that the board's explanations of its decisions elaborated upon the meaning and …

Designing Electronic Casebooks That Talk Back: The Cato Program, Kevin D. Ashley

Articles

Electronic casebooks offer important benefits of flexibility in control of presentation, connectivity, and interactivity. These additional degrees of freedom, however, also threaten to overwhelm students. If casebook authors and instructors are to achieve their pedagogical goals, they will need new methods for guiding students. This paper presents three such methods developed in an intelligent tutoring environment for engaging students in legal role-playing, making abstract concepts explicit and manipulable, and supporting pedagogical dialogues. This environment is built around a program known as CATO, which employs artificial intelligence techniques to teach first-year law students how to make basic legal arguments with cases. …