Applications of artificial intelligence to legal informatics
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Artificial Intelligence and Law (AI and Law) is a subfield of Artificial Intelligence (AI) mainly concerned with applications of AI to legal informatics problems and original research on those problems. It is also concerned to contribute in the other direction: to export tools and techniques developed in the context of legal problems to AI in general. For example, theories of legal decision making, especially models of argumentation, have contributed to knowledge representation and reasoning, models of social organization based on norms have contributed to multi-agent systems, reasoning with legal cases has contributed to case-based reasoning and the need to store and retrieve large amounts of textual data has resulted in contributions to conceptual information retrieval and intelligent databases.
The roots of AI and Law can be found in a number of pieces of individual research, but during the 1980s an identifiable community began to form and in 1987 a biennial conference, the International Conference on AI and Law (ICAIL), was instituted[1]. This led to the foundation of the International Association for Artificial Intelligence and Law (IAAIL), to organize and convene subsequent ICAILs, and this in turn led to the foundation of the Artificial Intelligence and Law Journal, first published in 1992[2]. In Europe, the annual JURIX conferences (organised by the Jurix Foundation for Legal Knowledge Based Systems), began in 1988. Initially intended to bring together the Dutch-speaking (i.e. Dutch and Flemish) researchers, JURIX quickly developed into an international, primarily European, conference and since 2002 has regularly been held outside the Dutch speaking countries[3].
History
Although Loevinger (1948), Allen (1957) and Mehl (1958) anticipated several of the ideas that would become important in AI and Law, the first serious proposal for applying AI techniques to Law is usually taken to be Buchanan and Headrick (1970). Early work from this period includes Thorne McCarty’s influential TAXMAN project (e.g. McCarty 1977) in the USA and Ronald Stamper’s LEGOL (e.g. Stamper 1977) project in the UK. The former concerned the modeling of the majority and minority arguments in a US Tax law case (Eisner v Macomber), while the latter attempted to provide a formal model of the rules and regulations that govern an organization. Both of these topics remain important in AI and Law today.
Landmarks in the early 1980s include Carole Hafner’s work on conceptual retrieval (Hafner 1981), Anne Gardner’s work on contract law (e.g. Gardner 1983), Rissland’s work on legal hypotheticals (e.g. Rissland 1983) and the work at Imperial College, London on executable formalisations of legislation (e.g. Sergot et al 1986). Again these remain influential: Hafner’s work can be seen as the forerunner of legal ontologies.(e.g. Visser and Bench-Capon 1998). Gardner’s distinction between the large majority of easy cases (those which could be decided by the application of a set of rules) and the small minority of hard cases (where no rule applies, or rules are in conflict) remains relevant for distinguishing suitable practical applications from those of research significance. Rissland’s work, developed with Kevin Ashley into the HYPO system (Ashley 1991), which in turn developed into the CATO system (Aleven and Ashley 1997).. and which continues to provide a basis for the formalization of legal reasoning with cases described in terms of factors (Aleven and Ashley 1997, Prakken and Sartor 1998, Horty and Bench-Capon 2012). Formal representations of legislation continue to be significant, especially given the need to make legislation available on the world wide web (e.g. Sartor et al 2011).