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Full-Text Articles in Law
Oh No, Another Chatgpt Post: Incorporating Ai-Powered Chatbots Into Legal Research Exercises And Assignments, Olivia R. Smith Schlinck
Oh No, Another Chatgpt Post: Incorporating Ai-Powered Chatbots Into Legal Research Exercises And Assignments, Olivia R. Smith Schlinck
Library Staff Online Publications
Since it was launched at the end of November 2022, the discourse around ChatGPT and AI search tools has been unrelenting. What impact will AI-powered chatbots have on education? Will students submit ChatGPT-written essays and homework assignments? Will AI make lawyers obsolete? Look, this chatbot just passed the bar exam! Wait a minute—is this thing. . . sentient?
Generative Ai And Finding The Law, Paul D. Callister
Generative Ai And Finding The Law, Paul D. Callister
Faculty Works
Legal information science requires, among other things, principles and theories. The article states five principles or considerations that any discussion of generative AI large language models and their role in finding the law must include. The article concludes that law librarianship will increasingly become legal information science and require new paradigms. In addition to the five principles, the article applies ecological holistic media theory to understand the relationship of the legal community’s cognitive authority, institutions, techné (technology, medium and method), geopolitical factors, and the past and future to understand the changes in this information milieu. The article also explains …
Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon
Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon
Faculty Scholarship
The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …
A Human Being Wrote This Law Review Article: Gpt-3 And The Practice Of Law, Amy B. Cyphert
A Human Being Wrote This Law Review Article: Gpt-3 And The Practice Of Law, Amy B. Cyphert
Law Faculty Scholarship
Artificial intelligence tools can now “write” in such a sophisticated manner that they fool people into believing that a human wrote the text. None are better at writing than GPT-3, released in 2020 for beta testing and coming to commercial markets in 2021. GPT-3 was trained on a massive dataset that included scrapes of language from sources ranging from the NYTimes to Reddit boards. And so, it comes as no surprise that researchers have already documented incidences of bias where GPT-3 spews toxic language. But because GPT-3 is so good at “writing,” and can be easily trained to write in …
Law Library Blog (February 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Blog (February 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Newsletters/Blog
No abstract provided.
Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
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 Blog (November 2020): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Newsletters/Blog
No abstract provided.
Law, Artificial Intelligence, And Natural Language Processing: A Funny Thing Happened On The Way To My Search Results, Paul D. Callister
Law, Artificial Intelligence, And Natural Language Processing: A Funny Thing Happened On The Way To My Search Results, Paul D. Callister
Faculty Works
Renowned legal educator Roscoe Pound stated, “Law must be stable and yet it cannot stand still.” Yet, as Susan Nevelow Mart has demonstrated in a seminal article that the different online research services (Westlaw, Lexis Advance, Fastcase, Google Scholar, Ravel and Casetext) produce significantly different results when researching case law. Furthermore, a recent study of 325 federal courts of appeals decisions, revealed that only 16% of the cases cited in appellate briefs make it into the courts’ opinions. This does not exactly inspire confidence in legal research or its tools to maintain stability of the law. As Robert Berring foresaw, …
Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley
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 …
Computer Models For Legal Prediction, Kevin D. Ashley, Stephanie Bruninghaus
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
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
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. …