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Introduction
See my web page at Rutgers:
http://www.cs.rutgers.edu/~mccarty/Welcome.html
Skills and Expertise
Additional affiliations
July 2011 - present
July 1981 - June 2011
Publications
Publications (81)
One of the main obstacles to progress in the field of artificial intelligence and law is the natural language barrier, but the technology of natural language processing has advanced recently. In this paper, we will show that a state-of-the-art statistical parser can handle even the complex syntactic constructions of an appellate court judge, and th...
Most of the chapters in this volume are concerned with the legal issues arising from the deployment of artificial intelligence in society, but this chapter looks at the flip side of the subject: the applications of artificial intelligence to the law itself. The author covers the history of the field, its theoretical foundations, and the prospects f...
This document was originally prepared as a position paper for two conferences: the first Workshop on Programming Languages and the Law (ProLaLa 2022), which was part of POPL 2022, in Philadelphia, in January, 2022, and the conference on Computational Legal Studies 2022, in Singapore, in March, 2022. The Slides and Notes for my presentations at thes...
This paper develops a theory of clustering and coding that combines a geometric model with a probabilistic model in a principled way. The geometric model is a Riemannian manifold with a Riemannian metric, gij(x)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \use...
This paper presents an extension and an elaboration of the theory of differential similarity, which was originally proposed in (McCarty, 2014, 2018, 2024). The goal is to develop an algorithm for clustering and coding that combines a geometric model with a probabilistic model in a principled way. For simplicity, the geometric model in the earlier p...
This paper develops a theory of clustering and coding that combines a geometric model with a probabilistic model in a principled way. The geometric model is a Riemannian manifold with a Riemannian metric, g ij (x), which we interpret as a measure of dissimilarity. The probabilistic model consists of a stochastic process with an invariant probabilit...
Slides for my presentation at ProLaLa 2022.
Slides for my presentation at CLS 2022.
Notes for my presentation at ProLaLa 2022.
Notes for my presentation at CLS 2022.
These are the Notes for my talk at the Workshop on Programming Languages and the Law (ProLaLa 2022), at POPL 2022.
These are the Slides for my talk at the Workshop on Programming Languages and the Law (ProLaLa 2022), at POPL 2022.
My first paper on a Language for Legal Discourse (LLD) was published at the International Conference on Artificial Intelligence and Law in 1989 [24]. I used the language subsequently for several small projects: [48] [28] [30] [31], and it motivated much of my theoretical work on Knowledge Representation and Reasoning in those years. At the time, no...
This paper presents an extension and an elaboration of the theory of differential similarity, which was originally proposed in [McC14, McC18]. The goal is to develop an algorithm for clustering and coding that combines a geometric model with a probabilis-tic model in a principled way. For simplicity, the geometric model in the earlier paper was res...
This paper presents an extension and an elaboration of the theory of differential similarity, which was originally proposed in [McC14, McC18]. The goal is to develop an algorithm for clustering and coding that combines a geometric model with a probabilistic model in a principled way. For simplicity, the geometric model in the earlier paper was rest...
This paper presents an extension and an elaboration of the theory of differential similarity, which was originally proposed in [McC14, McC18]. The goal is to develop an algorithm for clustering and coding that combines a geometric model with a probabilistic model in a principled way. For simplicity, the geometric model in the earlier paper was rest...
This paper develops a theory of clustering and coding which combines a geometric model with a probabilistic model in a principled way. The geometric model is a Riemannian manifold with a Riemannian metric, ${g}_{ij}({\bf x})$, which we interpret as a measure of dissimilarity. The probabilistic model consists of a stochastic process with an invarian...
Slides for a conference/lecture at the Laboratoire de Cyberjustice, Universite de Montreal, Canada, on April 19, 2018.
Video of the conference/lecture is available on YouTube:
https://youtu.be/E3aCE9JeRRM
This is a short paper to accompany my presentation at the Workshop on Artificial Intelligence in Legal Practice, at ICAIL 2017 in London on June 12, 2017. For the substance, you should follow the links in the footnotes and read the original sources, but this paper explains how the pieces fit together.
Slides for a presentation at the CUNY Graduate Center in Manhattan on April 25, 2017.
An Edited Transcript of a Presentation at the Legal Quanta Symposium at Michigan State University College of Law on October 29, 2015.
https://hcommons.org/deposits/item/hc:36069/
This short discussion paper reviews my prior work (from 1998, 2007 and 2015) and proposes a research strategy to produce a computational summary of a legal case, which can be scaled up to a realistic legal corpus.
In a pair of papers from 1995 and 1997, I developed a computational theory of legal argument, but left open a question about the key concept of a "prototype." Contemporary trends in machine learning have now shed new light on the subject. In this paper, I will describe my recent work on "manifold learning," as well as some work in progress on "deep...
This is the Mathematica source code for the examples in Section 5.1. The code is executable in Mathematica Version 7.0, or higher, but if a Mathematica system is not available, the files can still be viewed using the Wolfram CDF Player, which can be downloaded from wolfram.com. In particular, the 3D graphics can be manipulated in the Wolfram CDF Pl...
This is the Mathematica source code for the examples in Section 5.2. The code is executable in Mathematica Version 7.0, or higher, but if a Mathematica system is not available, the files can still be viewed using the Wolfram CDF Player, which can be downloaded from wolfram.com. In particular, the 3D graphics can be manipulated in the Wolfram CDF Pl...
This is the Mathematica source code for the examples in Section 5.3. The code is executable in Mathematica Version 7.0, or higher, but if a Mathematica system is not available, the files can still be viewed using the Wolfram CDF Player, which can be downloaded from wolfram.com. In particular, the 3D graphics can be manipulated in the Wolfram CDF Pl...
In a pair of papers from 1995 and 1997, I developed a computational theory of legal argument, but left open a question about the key concept of a "prototype." Contemporary trends in machine learning have now shed new light on the subject. In this talk, I will describe my recent work on "manifold learning," as well as some work in progress on "deep...
We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of...
Quasi-Logical Forms (QLFs) for 211 sentences from Carter v. Exxon, 177 F.3d 197 (3d. Cir. 1999).
This article is an exercise in computational jurisprudence. It seems clear that the field of AI and Law should draw upon the insights of legal philosophers,whenever possible. But can the computational perspective offer anything inreturn? I will explore this question by focusing on the concept of OWNERSHIP, which has been debated in the jurisprudent...
Everyone knows that lawyers are trained in the art of argument. But what exactly does this mean? Is a legal argument a chain of valid inferences, grounded in authoritative rules? Or is it merely a chain of plausible inferences? Does it require the citation of cases, pro and con? Are there canons of correct, or acceptable, argumentation? Can lawyers...
Eisner v. Macomber, 252 U.S. 189 (1920 ), a corporate tax case, was the principal illustration of a theory of legal reasoning and legal argumentation proposed more than ten years ago. Although thetheory was described in some detail, using the vocabulary of prototypes and deformations, it was never fully implemented. There were two main problems: (1...
Eisner v. Macomber, 252 U.S. 189 (1920), a corporate tax case, was the principal illustration of a theory of legal reasoning and legal argumentation proposed more than ten years ago. Although the theory was described in some detail, using the vocabulary of prototypes and deformations, it was never fully implemented. There were two main problems: (1...
This paper analyzes a language for actions and the deontic modalities over
actions --- i.e., the modalities {\em permitted}, {\em forbidden} and {\em
obligatory}. The work is based on: (1) an action language that allows the
representation of concurrent and repetitive events; (2) a deontic language
that allows the representation of ``free choice...
This paper combines a system of deontic logic with a system for default reasoning to analyze a notorious philosophical problem: Chisholm’s Paradox. The basic approach is to write deontic rules with explicit exceptions, but we also consider the extent to which a set of implicit exceptions can be derived from the underlying deontic semantics.
Methods of Logic in Computer Science, Volume 1, Number 1, pp. 19-50 (1994).
Most of the work on inheritance hierarchies in recent years has had as its goal the design of general purpose algorithms that depend only on the topology of the inheritance network. This research has produced some important observations about the various strategies used in...
What does it mean to write an “efficient” theorem prover for first-order intuitionistic logic? This paper suggests a possible answer to the question, following the philosophy of logic programming. We decompose intuitionistic logic into two syntactically restricted subsets: (i) the class of simple embedded implications and (ii) the class of disjunct...
This paper is a study of circumscription, not in classical logic, as usual, but in intuitionistic logic. We first review the intuitionistic circumscription of Horn clause logic programs, which was discussed in previous work, and we then consider the larger class of embedded implications . The ordinary circumscription axiom turns out to be inappropr...
In this paper, we propose an intuitionistic semantics for negation-as-failure in logic programs. The basic idea is to work with the completion of the program, not in classical logic, but in intuitionistic (or, more precisely, minimal) logic. Moreover, we consider two forms of completion: (1) first-order predicate completion, as defined by Clark, wh...
This is the second in a series of workshops that are bringing together researchers from the theoretical end of both the logic programming and artificial intelligence communities to discuss their mutual interests. This workshop emphasizes the relationship between logic programming and non-monotonic reasoning.
Topics Stable Semantics • Autoepistemic...
We use second-order intuitionistic logic for two purposes in this paper: first, to formulate a large class of circumscriptive queries about logic programs; and second, to formulate a class of induction schemata that can be used to answer these queries. Then, applying the techniques of intuitionistic logic programming, we develop an interpreter (wri...
In this paper, we view planning as a special case of reasoning about indefinite actions. We treat actions as predicates defined over a linear temporal order. This formalism permits the representation of concurrent activity. Suppose we have a set of abstract actions defined by Horn clauses from a set of basic actions. Let us assume that an abstract...
In this paper we present a novel explanation of the source of indefinite information in common sense reasoning: Indefinite information arises from reports about the world expressed in terms of concepts that have been defined using only definite rules. Adopting this point of view, we show that first-order logic is insufficiently expressive to handle...
Intuitionistic logic programming is an extension of Horn-clause logic programming in which implications may appear "embedded" on the right-hand side of a rule. Thus, rules of the form A(x) ← [B(x) ← C(x)] are allowed. These rules are called embedded implications . In this paper, we develop a language in which negation-as-failure is combined with em...
This paper offers a survey of the current state of Artificial Intelligence and Law, and makes recommendations for future research. Two main areas of investigation are discussed: the practical work on intelligent legal information systems, and the theoretical work on computational models of legal reasoning. In both areas, the knowledge representatio...
This paper develops a declarative language with intuitionistic semantics which expresses exactly the generic database queries. Syntactically, the language is an extension of Datalog (function-free Horn logic) which allows rules themselves to appear in the bodies of other rules. Such rules are called embedded implications. Several researchers have s...
An abstract is not available.
Clausal intuitionistic logic is an extension of Horn-clause logic which permits the appearance of negations and embedded implications on the right-hand side of a rule, and interprets these new rules intuitionistically in a set of partial models. In this article the second of a pair, clausal intuitionistic logic, is shown to have a tableau proof pro...
Since the advent of Horn-clause logic programming in the mid 1970's, there have been numerous attempts to extend the expressive power of Horn-clause logic while preserving some of its attractive computational properties. This article, the first of a pair, presents a clausal language that extends Horn-clause logic by adding negations and embedded im...
This paper presents Explanation-Based Generalization as an augmentation of resolution theorem proving for Horn Clause Logic. The corresponding implementation, PROLOG-EBG, performs generalization as a byproduct of standard PROLOG theorem proving. This results in very a concise (four-clause) implementation of EBG. The propagation of consistent variab...
This article describes a formal semantics for the deontic concepts -- the concepts of permission and obligation — which arises naturally from the representations used in artificial intelligence systems Instead of treating deontic logic as a branch of modal logic, with the standard possible worlds semantics, we first develop a language for describin...
One of tha principal goals of tha TAXMAN project is to develop a theory about the structure and dynamics of legal concapts, using corporate tax law as an experimental problem domain In this paper we describe the "prototype* plus-deformation" model of legal conceptual structure a concept is represented here by a prototypical description plus a seque...
The literature on computer-based consultation systems has often suggested the possibility of building an expert system in the field of law, but it is only recently that several researchers have begun to explore this possibility seriously. For this session, we have assembled summaries of six major projects on the applications of artificial intellige...
After introducing some basic techniques of semantic information processing developed in the field of artificial intelligence, Professor McCarty describes a computer program using such techniques which enables a computer to apply to certain fact situations concepts of the area of the taxation of corporate reorganizations. He considers both the prese...
This is the original version of my article on TAXMAN, before it was edited by the Harvard Law Review. It was published in the German journal: Datenverarbeitung im Recht.
