Legal informatics is an area within information science.
The American Library Association defines informatics as "the study of the structure and properties of information, as well as the application of technology to the organization, storage, retrieval, and dissemination of information." Legal informatics therefore, pertains to the application of informatics within the context of the legal environment and as such involves law-related organizations (e.g., law offices, courts, and law schools) and users of information and information technologies within these organizations.
Policy issues Policy issues in legal informatics arise from the use of informational technologies in the implementation of law, such as the use of subpoenas for information found in emails, search queries, and social networks. Policy approaches to legal informatics issues vary throughout the world. For example, European countries tend to require the destruction or anonymization of data so that it cannot be used for discovery.
Technology Cloud computing The widespread introduction of cloud computing provides several benefits in delivering legal services. Legal service providers can use the Software as a Service model to earn a profit by charging customers a per-use or subscription fee. This model has several benefits over traditional bespoke services. Software as a service is much more scalable. Traditional bespoke models require an attorney to spend more of a limited resource (their time) on each additional client. Using Software as a Service, a legal service provider can put in effort once to develop the product and then use a much less limited resource (cloud computing power) to provide service to each additional customer. Software as a service can be used to complement traditional bespoke services by handling routine tasks, leaving an attorney free to concentrate on bespoke work. Software as a service can be delivered more conveniently because it does not require the legal service provider to be available at the same time as the customer.
Software as a service also complicates the attorney-client relationship in a way that may have implications for attorney–client privilege. The traditional delivery model makes it easy to create delineations of when attorney-client privilege attaches and when it does not. But in more complex models of legal service delivery other actors or automated processes may moderate the relationship between a client and their attorney making it difficult to tell which communications should be legally privileged.Chris Johnson, Leveraging Technology to Deliver Legal Services, 23 HARV. J.L. & TECH.259, 279 (2009).
Artificial intelligence
Artificial intelligence is employed in online dispute resolution platforms that use optimization algorithms and blind-bidding.David Allen Larson, "Brother, Can You Spare A Dime?" Technology Can Reduce Dispute Resolution Costs When Times Are Tough and Improve Outcomes, 11 Nev. L.J. 523, 550 (2011) Artificial intelligence is also frequently employed in modeling the legal ontology, "an explicit, formal, and general specification of a conceptualization of properties of and relations between objects in a given domain".
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.
History Although Loevinger,Loevinger, Lee. Jurimetrics--The Next Step Forward. Minn. L. Rev. 33 (1948): 455. AllenAllen, Layman E. Symbolic logic: A razor-edged tool for drafting and interpreting legal documents. Yale LJ 66 (1956): 833. and MehlMehl, L.Automation in the Legal World: From the Machine Processing of Legal Information to the" Law Machine,. Mechanisation of Thought Processes (1958): 757-787. 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.Buchanan, Bruce G., and Headrick, Thomas E. Some speculation about artificial intelligence and legal reasoning . Stanford Law Review (1970): 40-62. Early work from this period includes Thorne McCarty's influential TAXMAN projectMcCarty, L. Thorne. Reflections on" Taxman: An Experiment in Artificial Intelligence and Legal Reasoning. Harvard Law Review (1977): 837-893. in the US and Ronald Stamper's LEGOL projectStamper, Ronald K. The LEGOL 1 prototype system and language. The Computer Journal 20.2 (1977): 102-108. in the UK. Landmarks in the early 1980s include Carole Hafner's work on conceptual retrieval,Hafner, Carole D., (1981). Representing knowledge in an information retrieval system. in Oddy, R et al. (editors) (1981). Information Retrieval Research. London: Butterworths. Anne Gardner's work on contract law,Gardner, Anne The design of a legal analysis program. AAAI-83. 1983. Edwina Rissland's work on legal hypotheticalsRissland, Edwina L. Examples in Legal Reasoning: Legal Hypotheticals. IJCAI. 1983. and the work at Imperial College London on the representation of legislation by means of executable logic programs.Sergot, Marek J., et al. The British Nationality Act as a logic program. Communications of the ACM 29.5 (1986): 370–386.
Early meetings of scholars included a one-off meeting at Swansea,Niblett, Bryan, ed. Computer science and law. CUP Archive, 1980. the series of conferences organized by IDG in Florencee.g. Ciampi, Costantino, and Martino, Antonio. Artificial intelligence and legal information systems. Elsevier Science Inc., 1982. and the workshops organised by Charles Walter at the University of Houston in 1984 and 1985.Walter, Charles. Computer power & legal language: the use of computational linguistics, artificial intelligence, & expert systems in the law. Greenwood Publishing Group Inc., 1988. In 1987 a biennial conference, the International Conference on AI and Law (ICAIL), was instituted.List of past ICAIL conferences This conference began to be seen as the main venue for publishing and the developing ideas within AI and Law,For a contemporary discussion of a selection of papers from the first thirteen conferences, see Bench-Capon, Trevor, et al. A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law. Artificial Intelligence and Law 20.3 (2012): 215-319. and it led to the foundation of the International Association for Artificial Intelligence and Law (IAAIL), to organize and convene subsequent ICAILs. This, in turn, led to the foundation of the Artificial Intelligence and Law Journal, first published in 1992.List of AI and Law journal volumes 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.List of Jurix conferences Since 2007 the JURISIN workshops have been held in Japan under the auspices of the Japanese Society for Artificial Intelligence.See the list of workshops on the Jurisin 2014 page
The interoperable legal documents standard Akoma Ntoso allows machine-driven processes to operate on the syntactic and semantic components of digital parliamentary, judicial and legislative documents, thus facilitating the development of high-quality information resources and forming a basis for AI tools. Its goal is to substantially enhance the performance, accountability, quality and openness of parliamentary and legislative operations based on best practices and guidance through machine-assisted drafting and machine-assisted (legal) analysis. Embedded in the environment of the semantic web, it forms the basis for a heterogenous yet interoperable ecosystem, with which these tools can operate and communicate, as well as for future applications and use cases based on digital law or rule representation.
In 2019, the city of Hangzhou, China established a pilot program artificial intelligence-based Internet Court to adjudicate disputes related to ecommerce and internet-related intellectual property claims. Parties appear before the court via videoconference and AI evaluates the evidence presented and applies relevant legal standards.
Scope Today, AI and law embrace a wide range of topics, including: Formal models of legal reasoning Computational models of argumentation and decision-making Computational models of evidential reasoning Legal reasoning in multi-agent systems Executable models of legislation Automatic legal text classification and summarization Automated information extraction from legal databases and texts Machine learning and data mining for e-discovery and other legal applications Conceptual or model-based legal information retrieval Lawbots to automate minor and repetitive legal tasks Risk assessment, pricing and timeline predictions of litigation using machine learning and artificial intelligence.
Formal models of legal reasoning Formal models of legal texts and legal reasoning have been used in AI and Law to clarify issues, to give a more precise understanding and to provide a basis for implementations. A variety of formalisms have been used, including propositional and predicate calculi; deontic, temporal and non-monotonic logics; and state transition diagrams. Prakken and SartorH. Prakken and G.Sartor, Law and logic: A review from an argumentation perspective, Artificial Intelligence. Available on-line June 2015. give a detailed and authoritative review of the use of logic and argumentation in AI and Law, together with a comprehensive set of references.
An important role of formal models is to remove ambiguity. In fact, legislation abounds with ambiguity: Because it is written in natural language there are no brackets and so the scope of connectives such as "and" and "or" can be unclear. "Unless" is also capable of several interpretations, and legal draftsman never write "if and only if", although this is often what they intend by "if". In perhaps the earliest use of logic to model law in AI and Law, Layman Allen advocated the use of propositional logic to resolve such syntactic ambiguities in a series of papers.
In the late 1970s and throughout the 1980s a significant strand of work on AI and Law involved the production of executable models of legislation, originating with Thorne McCarty's TAXMAN and Ronald Stamper's LEGOL. TAXMAN was used to model the majority and minority arguments in a US Tax law case (Eisner v Macomber), and was implemented in the micro-PLANNER programming language. LEGOL was used to provide a formal model of the rules and regulations that govern an organization, and was implemented in a condition-action rule language of the kind used for expert systems.