Expert systems for legal decision making

Abstract: AI technology is being used to develop expert systems that solve complex problems in the legal area. Most of these systems employ rules to describe the strategies and procedures used by litigators to analyze legal issues. The tasks performed by these systems include interpreting the law, anticipating the legal consequences of proposed actions, predicting the effects of changes in legislation, as well as analyzing and managing cases. The special characteristics of the legal domain cause certain problems for expert system builders. We discuss some of these problems and describe LDS and SAL, two expert systems we have developed for case evaluation and settlement in the product liability area. SAL (System for Asbestos Litigation) evolved from the earlier and more general expert system, LDS (Legal Decisionmaking System). We also describe XPL, an explanation facility we developed for use by SAL and other expert system applications.     

Some legal aspects of expert systems

As expert systems become more popular, the possibility of lawsuits arising from their use becomes increasingly evident. The expert system developer needs to be aware of important legal concepts associated with an expert system's development and deployment. This paper will primarily explore the rights to intellectual property associated with an expert system and liability for malfunction of an expert system.     

Expert identification and selection: Legal liability concerns and directions

Legal liabilities pertaining to the identification and selection of domain experts is an issue that could adversely impact expert systems developers. Problems pertaining to flawed knowledge, improperly defined expertise, and behavioural and psychological impediments are just some of the issues. This paper examines the torts of strict products liability and negligence that system developers could incur as a result of expert-related difficulties. Parallels from legal scholars and federal and state court decisions are discussed relevant to expert system projects and developers. The paper concludes with a presentation of steps that systems developers can take to minimize potential legal liability.     

Professional negligence and financial‐legal expert systems: Architectures to enable the reasonableness defence

The legal implications of professionals relying on expert systems have been extensively studied by analysts who have considered the ‘macro’ issues such as whether products liability can be invited for loss resulting from errors in expert systems, and apportionment of liability. These macro‐analyses do not distinguish programming errors from what we call ‘errors of reasoning’. The latter errors may be considered to be advertent on the part of developers and/or user‐professionals; may potentially be directly compared with the reasoning ascribable to a reasonably competent professional; and cannot be removed merely by better quality assurance in the sense prevalent in software engineering. In this paper we consider the mechanisms by which a court may examine errors of reasoning in expert systems used to assist professionals working in certain areas of financial services ('the financial‐legal domain'). Our analysis of the ‘micro’ issues of liability shows that the advertent nature of errors of reasoning makes it difficult to argue that using the best possible quality assurance methods during development is sufficient to make the reliance on an expert system reasonable. However, certain valuable defences that are available to professionals acting unaided can be made out even when expert systems are employed as part of the reasoning process, though these defences will be disabled if certain conceptual structures of the knowledge of professionals are not distinctively maintained in the knowledge base. As such, opacity of a knowledge base assists, rather than hinders, a plaintiff in establishing professional negligence. The results of an analysis of the micro‐issues of liability have been applied by us in the design of a system for financial/tax planning. A case‐based reasoning approach is employed, deductive rules being employed strictly in a subsidiary role. Consequently, the primary justification for a decision is a ‘case’ ‐ an instance of problem‐solving by a professional ‐ that is likely to be accepted by the court as being representative of the actions of reasonably competent professionals.     

The IKBALS project: Multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval.When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers.Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process.Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions.The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.     

Computers and legal reasoning: Developments in Germany

The importance of reasoning in law is pointed out. Law and jurisprudence belong to the reasoning-conscious disciplines. Accordingly, there is a long tradition of logic in law. The specific methods of professional work in law are to be seen in close connection with legal reasoning. The advent of computers at first did not touch upon legal reasoning (or the professional work in law). At first computers could be used only for general auxiliary functions (e.g., numerical calculations in tax law). Gradually, the use of computers for auxiliary functions in law has become more specific and more sophisticated (e.g., legal information retrieval), touching more closely upon professional legal work. Moreover, renewed interest in AI has also fostered interest in AI in law, especially for legal expert systems. AI techniques can be used in support of legal reasoning. Yet until now legal expert systems have remained in the research and development stage and have hardly succeeded in becoming a profitable tool for the profession. Therefore it is hoped that the two lines of computer support, for auxiliary functions in law and for immediate support of legal reasoning, may unite in the future.Herbert Fiedler is professor of Legal Informatics, general theory of law and penal law in the Department of Economics and Law at the University of Bonn.     

Legal informatics research in Italy: The Istituto per la Documentazione Giuridica of the Italian National Research Council

The IDG was originally founded to carry out research into the collection and processing of documentation relating to Italian legislation, case law and legal authority. The Institute has since concentrated on automated documentation and legal informatics, as well as the application of artificial intelligence to the law. This article describes the many projects undertaken at the Institute. Elio Fameli has, since 1971, been a researcher at the Instituto per la Documentazione Giuridica of Florence of the Italian National Research Council. He has worked in legal informatics generally but is mainly interested in problems specifically related to information systems and the application of artificial intelligence to the law. Currently, his research is focused on legal expert systems and the methodology and technology for their construction. He has, since 1975, been an editor of the international journal, Informatica e Dirrito and a member of the editorial board of the International Bibliography on Computers and the Law, published as a regular issue of the aformentioned journal.     

Recent trends in legal bibliographical documentation

We discuss the development of factual and bibliographical databases and database systems, including management systems and information retrieval systems. Special reference is made to the International Bibliography on Computers and Law, with respect to both the current situation and future plans. Rosa Maria Di Giorgi has, since 1982, been a researcher at the Instituto per la Documentazione Giuridica of Florence of the Italian National Research Council. She took her degree in Letters and Philosophy at the University of Florence in 1979 and has completed an advanced course in computer applications. Her research activity concentrates on legal informatics and on advanced automated legal documentary systems and advisory legal expert systems. She is an editor of Informatica e Dirrito and of the International Bibliography on Computers and the Law.     

Who is liable for insecure systems?

A survey of security-related liability issues shows that as data crime increases and the costs of hacking and other malicious behavior soar, vendors must make their software more secure or suffer market and legal consequences. The notion of liability for insecure computer systems has shifted. We have seen both the enactment of legislation affecting liability and the appearance of actual liability cases in the courts. For many years, computing professionals have debated the topic of liability for insecure systems.     

The use of legal software by non-lawyers and the perils of unauthorised practice of law charges in the United States: a review of Jayson Reynoso decision

This paper critically reviews the judgment of the United States Court of Appeals for the Ninth Circuit In re: Jayson Reynoso: Frankfort Digital Services et al., v. Sara L. Kistler, United States Trustee et al. (2007) 447 F.3d 1117. The appellants, who were non-lawyers, were indicted with unauthorised practice of law for offering bankruptcy petition services via online legal software or expert systems in law configured for filing bankruptcy petition forms. The United States Court of Appeals for the Ninth Circuit found inter alia that appellants were bankruptcy petition preparers, and not being lawyers, had exceeded their clerical remit by offering legal advice and legal services in contravention of California law regulating legal practice and 11 U.S.C. Sect. 110 of the Bankruptcy Code (2002). While examining the legal ramifications of the use of legal software by non-lawyers in the preparation of legal documents, the paper critically reviews the factual circumstances of the Reynoso decision in the context of juridical and statutory constructs of unauthorised practice of law in the United States. The paper poses the question whether Reynoso should be viewed as a one-off decision bound by its peculiar facts, or good law for the broad proposition that non-lawyers cannot use legal software in legal documents preparation. The paper also notes the possible legal barriers to an unconditional ban on the design, sale, distribution, and uses of legal software by non-lawyers. These range from the First Amendment right to free speech, constitutional right to pro se legal representation, interstate commerce doctrine, to antitrust provisions of the Sherman Act. A regime of best practices for the use of legal software or expert systems in law by non-lawyers is proffered.     

Brussels revisited: The European conflicts guide

In this paper, we examine the soundness of Capper & Susskind's recommended legal expert system development methodology in the areas of knowledge acquisition and knowledge representation. Legal expert systems have not yet had the impact in the United Kingdom that might be expected. We argue that this is partly the result of developers paying insufficient attention to the ‘third estate’: user interfaces. We make suggestions about both the look and feel of legal expert systems, and the facilities that such systems should offer. Lastly, we claim that we have developed an exploratory expert system encapsulating the Brussels Convention 1968 which can contribute to the development of a useful computer‐based guide to an important legal domain.     

Pathologies of AI: Responsible use of artificial intelligence in professional work

Although the AI paradigm is useful for building knowledge-based systems for the applied natural sciences, there are dangers when it is extended into the domains of business, law and other social systems. It is misleading to treat knowledge as a commodity that can be separated from the context in which it is regularly used. Especially when it relates to social behaviour, knowledge should be treated as socially constructed, interpreted and maintained through its practical use in context. The meanings of terms in a knowledge-base are assumed to be references to an objective reality whereas they are instruments for expressing values and exercising power. Expert systems that are not perspicuous to the expert community will lose their meanings and cease to contain genuine knowledge, as they will be divorced from the social processes essential for the maintenance of both meaning and knowledge. Perspicuity is usually sacrificed when knowledge is represented in a formalism, with the result that the original problem is compounded with a second problem of penetrating the representation language. Formalisms that make business and legal problems easier to understand are one essential research goal, not only in the quest for intelligent machines to replace intelligent human beings, but also in the wiser quest for computers to support collaborative work and other forms of social problem solving.     

Informatics for the Law: LEXIS—A legal expert system on Italian family law

This paper describes the LEXIS project, a research endeavor in building a legal expert system on Italian family law. An expert system shell, Xi Plus, was used to help construct this expert system. This paper will describe some of the development steps of this project and also cite some research issues in building legal expert systems.     

On the Logical Foundations of Compound Predicate Formulae for Legal Knowledge Representation

In order to represent legal knowledge adequately, it is vital to create a formal device that can freely construct an individual concept directly from a predicate expression. For this purpose, a Compound Predicate Formula (CPF) is formulated for use in legal expert systems. In this paper, we willattempt to explain the nature of CPFs by rigorous logical foundation, i.e., establishing their syntax and semantics precisely through the use of appropriate examples. We note the advantages of our system over other such systems and discuss the significance of CPFs with regard to the formalization of legal reasonings using examples from the United Nations Convention for the International Sale of Goods.     

Classification Accuracy: Machine Learning vs. Explicit Knowledge Acquisition

This empirical study provides evidence that machine learning models can provide better classification accuracy than explicit knowledge acquisition techniques. The findings suggest that the main contribution of machine learning to expert systems is not just cost reduction, but rather the provision of tools for the development of better expert systems.     

Implementing a fuzzy expert system for ensuring information technology supply chain

In the business environment, information technology (IT) plays an important role for firms' performance. It provides information flow that makes the supply chain more robust and resilient without undermining its efficiency. Smart systems use artificial intelligence methods for solving problems and facilitating decision‐making through rule‐based deduction. Accordingly, these systems can present specialists' skills and simulate their thinking process. The primary goal of expert systems is to implement knowledge acquisition process by converting knowledge to wisdom. This process is vital for critical decision‐making regarding important issues such as determining necessities of a particular contract. Companies use professional liability insurance of the products and services to ensure the purchasers and prevent potential losses. Although this practice is highly prevalent, there is not any particular procedure for measuring necessities of contracts. The main purpose of this paper is to design a fuzzy expert system for measuring the necessities of professional contracts regarding insurance coverage and improve the supply chain management using IT. This system can measure and report these obligations, considering specifications of each project. Taking into perspective variety of professional services/products, we consider software as a type of professional contracts, extract its important indices and give it to the system as the input. After the necessary stages, the system produces a proper response and presents the generated response to the user. The software of this expert system is web based, and there are four operating layers in its architecture. We implemented this program in MS Visual Studio Framework with C#.NET programming language. Moreover, we implemented MS SQL‐Server Database Management.     

Legal reasoning methodology: The missing link

The biggest false assumption made when attempting to model automatically acquired legal knowledge is that methodological and procedural legal knowledge is also contained in the text of law. Although the legal profession Intuitively knows the falsity of this assumption, researchers in the area of automatic knowledge acquisition are still confident in implementing systems that use only the text of laws as their main source of knowledge. Knowledge engineers are then forced to make their own interpretations of this knowledge, thus resulting in erroneous and legally unacceptable interpretations of the law. The aim of Nomos (an EC supported project under the ESPRIT II initiative) was to assist the knowledge engineer by providing tools that perform semiautomatic knowledge acquisition from legal texts in Italian and French. This paper uses the implementation of Nomos‐advisor, a legal expert system that uses Nomos's results as an input, as a proof of the falsity of the above assumption and discusses possible solutions.     

Modelling law using a feminist theoretical perspective 1

In recent years a schism has become apparent in artificial intelligence and law between those who claim that legal expert systems cannot be built without first establishing a satisfactory theoretical model of law ("purists") and those whose main desire is to build working systems with or without theoretical underpinning ("pragmatists"). Most attempts at finding a jurisprudential model for building expert systems, however, have inconclusively attempted to apply traditional “grand theories” and have embedded themselves in the long standing controversies of analytical jurisprudence. This paper highlights other theoretical possibilities for modelling law which have been sidelined in the AI and law field. In particular, it promotes the adoption of a feminist theoretical perspective on law and legal knowledge representation. Feminist legal critique has a discrete, concrete and pragmatic approach and so may be a good tool for the resolution of the demands of both purists and pragmatists. The paper applies these insights to a proposed child custody expert system.     

Building modular legal knowledge systems

A practical legal knowledge system must be versatile and capable of supporting many fundamentally different aspects of the lawyer's work. In this paper a general framework for building knowledge systems from distinct but communicating modules is proposed. There are currently three different kinds of modules: computation, data storage, and environmental interaction. These modules include inference engines, database managers, and hypertext. Several strategies for coupling these modules are discussed. This framework is used to construct expert systems for two distinct domains: a legal expert system for labour law and a real-time expert system for process control in a pulp plant. The legal application shows that this system can be used to construct an “intelligent library”, guiding the user to relevant documents, rather than merely retrieving documents on request.