Legal Profession Commons^™

The Unreasonable Effectiveness Of Large Language Models In Zero-Shot Semantic Annotation Of Legal Texts, Jaromir Savelka, Kevin D. Ashley

Articles

The emergence of ChatGPT has sensitized the general public, including the legal profession, to large language models' (LLMs) potential uses (e.g., document drafting, question answering, and summarization). Although recent studies have shown how well the technology performs in diverse semantic annotation tasks focused on legal texts, an influx of newer, more capable (GPT-4) or cost-effective (GPT-3.5-turbo) models requires another analysis. This paper addresses recent developments in the ability of LLMs to semantically annotate legal texts in zero-shot learning settings. Given the transition to mature generative AI systems, we examine the performance of GPT-4 and GPT-3.5-turbo(-16k), comparing it to the previous …

An Intelligent Path For Improving Diversity At Law Firms (Un)Artificially, Rimsha Syeda

Michigan Technology Law Review

Most law firms are struggling when it comes to diversity and inclusion. There are fewer women in law firms compared to men. The majority of lawyers—81%—are White, despite White people making up only about 65% of the law school population. Lawyers of color remain underrepresented with the historic high being only 28.32%. By comparison, 13.4% of the United States population is Black and 5.9% is Asian. The biases that perpetuate this lack of diversity in law firms begin during the hiring process and extend to associate retainment. For example, an applicant’s resume reveals a lot, including the prestige of the …

Rage Against The Machine: Who Is Responsible For Regulating Generative Artificial Intelligence In Domestic And Cross-Border Litigation?, S. I. Strong

Faculty Articles

In 2023, ChatGPT—an early form of generative artificial intelligence (AI) capable of creating entirely new content—took the world by storm. The first shock came when ChatGPT demonstrated its ability to pass the U.S. bar exam. Soon thereafter, the world learned that ChatGPT was being used by both lawyers and judges in actual litigation.

Some within the legal community find the use of generative AI in civil and criminal litigation entirely unproblematic. Others find generative AI troubling as a matter of due process and procedural fairness due to its propensity not only to misinterpret legitimate legal authorities but to create fictitious …

A New Metaphor: How Artificial Intelligence Links Legal Reasoning And Mathematical Thinking, Melissa E. Love Koenig, Colleen Mandell

Marquette Law Review

Artificial intelligence’s (AI’s) impact on the legal community expands exponentially each year. As AI advances, lawyers have more powerful tools to enhance their ability to research and analyze the law, as well as to draft contracts and other legal documents. Lawyers are already using tools powered by AI and are learning to shift their methodologies to take advantage of these enhancements. To continue to grow into their shifting role, lawyers should understand the relationship between AI, mathematics, and legal reasoning.

Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Law Library Blog (November 2020): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Law Library Blog (August 2019): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley

Articles

This paper examines impressive new applications of legal text analytics in automated contract review, litigation support, conceptual legal information retrieval, and legal question answering against the backdrop of some pressing technological constraints. First, artificial intelligence (Al) programs cannot read legal texts like lawyers can. Using statistical methods, Al can only extract some semantic information from legal texts. For example, it can use the extracted meanings to improve retrieval and ranking, but it cannot yet extract legal rules in logical form from statutory texts. Second, machine learning (ML) may yield answers, but it cannot explain its answers to legal questions or …

Teaching Law And Digital Age Legal Practice With An Ai And Law Seminar: Justice, Lawyering And Legal Education In The Digital Age, Kevin D. Ashley

Articles

A seminar on Artificial Intelligence ("Al") and Law can teach law students lessons about legal reasoning and legal practice in the digital age. Al and Law is a subfield of Al/computer science research that focuses on designing computer programs—computational models—that perform legal reasoning. These computational models are used in building tools to assist in legal practice and pedagogy and in studying legal reasoning in order to contribute to cognitive science and jurisprudence. Today, subject to a number of qualifications, computer programs can reason with legal rules, apply legal precedents, and even argue like a legal advocate.

This article provides a …

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. …