Case-based reasoning and its implications for legal expert systems

1992 ◽  
Vol 1 (2-3) ◽  
pp. 113-208 ◽  
Author(s):  
Kevin D. Ashley
Author(s):  
Hajime Yoshino ◽  
Katsumi Nitta

Lawyers use a reasoning process known as legal reasoning to solve legal problems. Legal expert systems could potentially help lawyers solve legal problems more quick and adequately, enable students to study law at school or at home more easily, and help legal scholars and professionals analyze the law and legal systems more clearly and precisely.In 1992, Hajime Yoshino of Meiji Gakuin University started a “Legal Expert Systems” project. This “Legal Expert” project is funded by the Japanese Ministry of Education, Science and Culture and is scheduled to run from May 1992 to March 1998. Yoshino organized over 30 lawyers and computer scientists to clarify legal knowledge and develop legal expert systems.This project covers a wide range of technologies such as the analysis of legal knowledge, the analysis of legal rules on international trade (United Nations Convention on Contracts for International Sale of Goods (CISG)), legal knowledge representation, legal inference models, utility programs to develop legal knowledge bases, and user interfaces. This project, which ends in March 1998, will focus on developing comprehensive legal expert systems as the final product. In this issue, we present 12 papers written by “Legal Expert” project members.In this number, Hajime Yoshino gives are overview of the legal expert systems project, explaining its aims, objectives, and organization. Six papers that follow his introduction include three on case-based reasoning. Legal rules are given by ambiguous predicates, making it difficult sometimes to determine whether conditions for rules are satisfied by the facts given of an event. In such cases, lawyers often refer to old cases and generate hypotheses through analogical reasoning.Kaoru Hirota, Hajime Yoshino and Ming Qiang Xu apply fuzzy theory to case-based reasoning. A number of related systems have been developed, but most focus on qualitative similarities between old cases and the current case, and cannot measure quantitative similarities. Hirota et al. treat quantitative similarity by applying fuzzy theory, explaining their method using CISG examples.Ken Satoh developed a way to compute an interpretation of undefined propositions in a legal rule using adversarial case-based reasoning. He translated old cases giving possible interpretations for a proposition into clauses in abductive logic programming and introduced abducibles to reason dynamically about important factors in an old case to the interpretation suiting the user’s purpose.Yoshiaki Okubo and Makoto Haraguchi formalized a way of attacking legal argument. Assume that an opponent has constructed a legal argument by applying a statute with an analogical interpretation. From the viewpoint of legal stability, the same statue for similar cases should be applied with the same interpretation. We thereby create a hypothetical case similar to the case in question and examine whether the statue can be interpreted analogically. Such a hypothetically similar case is created with the help of a goal-dependent abstraction framework. If a precedent in which a statue has been applied to a case with a different interpretation – particularly complete interpretation – can be found, the opponent’s argument is attacked by pointing out the incoherence of its interpretation of the statue.Takashi Kanai and Susumu Kunifuji proposed a legal reasoning system using abductive logic programming that deals with ambiguities in described facts and exceptions not described in articles. They examined the problems to be solved to develop legal knowledge bases through abductive logic programming, e.g., how to select ambiguities to be treated in abductive reasoning, how to describe time relationships, and how to describe an exception in terms of the application of abductive logic programming to legal reasoning.Toshiko Wakaki, Ken Satoh, and Katsumi Nitta presented an approach of reasoning about dynamic preferences in the framework of circumscription based on logic programming. To treat dynamic preferences correctly is required in legal reasoning to handle metarules such as lex posterior. This has become a hotly discussed topic in legal reasoning and more general nonmonotic reasoning. Comparisons of their method, Brewka’s approach, and Prakken and Sartor’s approach are discussed.Hiroyuki Matsumoto proposed a general legal reasoning model and a way of describing legal knowledge systematically. He applied his method to Japanese Maritime Traffic Law.Six more papers are to be presented in the next number


2020 ◽  
Vol 7 (3) ◽  
pp. 471-494
Author(s):  
Katsumi NITTA ◽  
Ken SATOH

AbstractArtificial intelligence (AI) and law is an AI research area that has a history spanning more than 50 years. In the early stages, several legal-expert systems were developed. Legal-expert systems are tools designed to realize fair judgments in court. In addition to this research, as information and communication technologies and AI technologies have progressed, AI and law has broadened its view from legal-expert systems to legal analytics and, recently, a lot of machine-learning and text-processing techniques have been employed to analyze legal information. The research trends are the same in Japan as well and not only people involved with legal-expert systems, but also those involved with natural language processing as well as lawyers have become interested in AI and law. This report introduces the history of and the research activities on applying AI to the legal domain in Japan.


1987 ◽  
Vol 3 (1) ◽  
pp. 119-135 ◽  
Author(s):  
Graham Greenleaf ◽  
Andrew Mowbray ◽  
Alan Tyree

2011 ◽  
pp. 151-169
Author(s):  
Jorgen S. Svensson

The chapter will now start with a short introduction into the Dutch General Assistance Act, its administration and the problems concerned with that administration. Then, I will discuss the idea of expert systems support and present the results of several investigations into the application of expert systems, in this context. Given these results, some have been quick to argue that expert systems are indeed important and valuable tools in the administration of welfare state programs. The next section will present important arguments against too much optimism. Both from a legal scientific as well as from a social scientific perspective, objections against the use of expert systems have been formulated. On the one hand, these objections have to be taken seriously, because they clearly have some validity, and thus require attention when discussing the possibilities of expert systems. On the other, it is important to notice that these objections have not prevented the introduction of these systems in general assistance in the Netherlands. As I will then explain, the fact that expert systems are now accepted by the General Assistance administrations, has to do with several specific factors, which really have promoted the use of expert systems in this field. Factors that have to do with the specific role of national regulation, with the professional status of the bureaucrats and with the increased scrutiny under which the administrations now have to function. In the last section of this chapter, I will draw some conclusions with respect to the general applicability of legal expert systems in service provision and provide some arguments for the idea that expert systems will soon become an important technology in electronic service delivery.


1994 ◽  
Vol 9 (4) ◽  
pp. 355-381 ◽  
Author(s):  
Farhi Marir ◽  
Ian Watson

Case-Based Reasoning (CBR) is a fresh reasoning paradigm for the design of expert systems in domains that may not be appropriate for other reasoning paradigms such as model-based reasoning. As a result of this, and because of its resemblance to human reasoning, CBR has attracted increasing interest both from those experienced in developing expert systems and from novices. Although CBR is a relatively new discipline, there are an increasing number of papers and books being published on the subject. In this context, this bibliographic categorization is an accompanying paper to a review of CBR by the same authors. The objective of this paper is to help researchers quickly identify relevant references.


Author(s):  
Hajime Yoshino ◽  

Since 1992, about 30 Japanese lawyers and computer scientists have been intensively engaged in a project of systematizing and computerizing legal reasoning. This project is the Study of Development of a Legal Expert System - Exploration of Legal Knowledge Structure and Implementation of Legal Reasoning or, in short, the "Legal Expert" Project. In this paper, I would like to introduce the Legal Expert project, explaining the goals, study organizations and their tasks in constructing legal expert systems in Japan.


Ratio Juris ◽  
1990 ◽  
Vol 3 (2) ◽  
pp. 272-318
Author(s):  
LAYMAN E. ALLEN ◽  
SALLYANNE PAYTON ◽  
CHARLES S. SAXON

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