Computational law

Computational law is a branch of legal informatics concerned with the mechanization of legal reasoning (whether done by humans or by computers). It emphasizes explicit behavioral constraints and eschews implicit rules of conduct. Importantly, there is a commitment to a level of rigor in specifying laws that is sufficient to support entirely mechanical processing. Philosophically, computational law sits within the Legal Formalist school of jurisprudence. Given its emphasis on rigorously specified laws, computational law is most applicable in civil law settings, where laws are taken more or less literally. It is less applicable to legal systems based on common law, which provides more scope for unspecified normative considerations. However, even in common law systems, computational law still has relevance in the case of categorical statutes and in settings where the handling of cases has resulted in de facto rules. From a pragmatic perspective, computational law is important as the basis for computer systems capable of doing useful legal calculations, such as compliance checking, legal planning, regulatory analysis, and so forth. Some systems of this sort already exist. TurboTax is a good example. And the potential is particularly significant now due to recent technological advances – including the prevalence of the Internet in human interaction and the proliferation of embedded computer systems (such as smart phones, self-driving cars, and robots). Speculation about potential benefits to legal practice through applying methods from computational science and AI research to automate parts of the law date back at least to the middle 1940s. Further, AI and law and computational law do not seem easily separable, as perhaps most of AI research focusing on the law and its automation appears to utilize computational methods. The forms that speculation took are multiple and not all related in ways to readily show closeness to one another. This history will sketch them as they were, attempting to show relationships where they can be found to have existed. By 1949, a minor academic field aiming to incorporate electronic and computational methods to legal problems had been founded by American legal scholars, called jurimetrics. Though broadly said to be concerned with the application of the 'methods of science' to the law, these methods were actually of a quite specifically defined scope. Jurimetrics was to be 'concerned with such matters as the quantitative analysis of judicial behavior, the application of communication and information theory to legal expression, the use of mathematical logic in law, the retrieval of legal data by electronic and mechanical means, and the formulation of a calculus of legal predictability'. These interests led in 1959 to the founding a journal, Modern Uses of Logic in Law, as a forum wherein articles would be published about the applications of techniques such as mathematical logic, engineering, statistics, etc. to the legal study and development. In 1966, this Journal was renamed as Jurimetrics. Today, however, the journal and meaning of jurimetrics seems to have broadened far beyond what would fit under the areas of applications of computers and computational methods to law. Today the journal not only publishes articles on such practices as found in computational law, but has broadened jurimetrical concerns to mean also things like the use of social science in law or the 'policy implications and legislative and administrative control of science'. Independently in 1958, at the Conference for the Mechanization of Thought held at the National Physical Laboratory in Teddington, Middlesex, UK, the French jurist Lucien Mehl presented a paper both on the benefits of using computational methods for law and on the potential means to use such methods to automate law for a discussion that included AI luminaries like Marvin Minsky. Mehl believed that the law could by automated by two basic distinct, though not wholly separable, types of machine. These were the 'documentary or information machine', which would provide the legal researcher quick access to relevant case precedents and legal scholarship, and the 'consultation machine', which would be 'capable of answering any question put to it over a vast field of law'. The latter type of machine would be able to basically do much of a lawyer's job by simply giving the 'exact answer to a problem put to it'. By 1970, Mehl's first type of machine, one that would be able to retrieve information, had been accomplished but there seems to have been little consideration of further fruitful intersections between AI and legal research. There were, however, still hopes that computers could model the lawyer's thought processes through computational methods and then apply that capacity to solve legal problems, thus automating and improving legal services via increased efficiency as well as shedding light on the nature of legal reasoning. By the late 1970s, computer science and the affordability of computer technology had progressed enough that the retrieval of 'legal data by electronic and mechanical means' had been achieved by machines fitting Mehl's first type and were in common use in American law firms. During this time, research focused on improving the goals of the early 1970s occurred, with programs like Taxman being worked on in order to both bring useful computer technology into the law as practical aids and to help specify the exact nature of legal concepts. Nonetheless, progress on the second type of machine, one that would more fully automate the law, remained relatively inert. Research into machines that could answer questions in the way that Mehl's consultation machine would picked up somewhat in the late 1970s and 1980s. A 1979 convention in Swansea, Wales marked the first international effort solely to focus upon applying artificial intelligence research to legal problems in order to 'consider how computers can be used to discover and apply the legal norms embedded within the written sources of the law'. That said, little substantial progress seems to have been made in the following decade of the 1980s. In a 1988 review of Anne Gardner's book An Artificial Intelligence Approach to Legal Reasoning (1987), the Harvard academic legal scholar and computer scientist Edwina Rissland wrote that 'She plays, in part, the role of pioneer; artificial intelligence ('AI') techniques have not yet been widely applied to perform legal tasks. Therefore, Gardner, and this review, first describe and define the field, then demonstrate a working model in the domain of contract offer and acceptance.' Eight years after the Swansea conference had passed, and still AI and law researchers merely trying to delineate the field could be described by their own kind as 'pioneer'.