Computational law

Computational law is a branch of legal informatics concerned with the mechanization of legal reasoning (whether done by humans or by computers). [1] 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 , 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 where the handling of cases has been de facto rules.

From a pragmatic perspective, a computational law is capable of doing useful legal calculations, such as compliance checking, legal planning, regulatory analysis, and so forth. Some systems of this spell already exist. [2] TurboTaxis a good example. And the potential is particularly significant in recent years – 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 ).


Abstract: Compulsive science in the field of computational science and research in the field of computer science. [3] Further, AI and law and computational law do not seem to be easily separable. The forms that are speculated in a different way. This history will be sketch them as they were, attempting to show where they can be found.

By 1949, minor academic field aiming to Incorporate electronic and computational methods to legal problems HAD beens founded by American legal scholars, called Expired jurimetrics . [4] These methods have been widely applied to the application of “methods of science” to the law. 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 “. [5]These interests were published in 1959 to the founding of a journal, Modern Uses of Logic in Law , as a result of the applications of such techniques as mathematical logic, engineering, statistics, etc. to the legal study and development. [6] In 1966, this Journal was renamed as Jurimetrics . [7]Today, however, the paper and the meaning of the law are likely to be broadened beyond the scope of the application of computers and computational methods to law. Today the journal not only publishes articles on such practices as computational law, but has broadened jurisdiction over the use of social science in law or the policy implications [of] and legislative and administrative control of science. [8]

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 on the benefits of using computational methods for law such luminaries like AI Marvin Minsky . [9] [10] Mehl believed that the law could not be separated by two distinct, separable, types of machine. These were the “documentary or information machine”, which would provide the legal researcher quick access to relevant cases precedents and legal scholarship, [11]and the “consultation machine”, which would be “capable of answering any question over a large field of law”. [12] The latter type of machine would be able to get a job done by simply giving the “exact answer to a [legal] problem put to it”. [13]

By 1970, Mehl’s first type of machine, one that would have been able to retrieve information, had been made to be less considerate of fruitful intersections between AI and legal research. [14] There were, however, still hopes that this problem could not be avoided because of legal problems, as well as by law enforcement and legal remedies. reasoning. [15]By the late 1970s, computer science and the affordability of computer technology had been achieved in the past by American law firms. [16] [17] During this time, research Focused on Improving the goals of the early 1970s occurred, with programs like Taxman being white Worked on in order to Both bring Useful computer technology into the law as practical aids and to help Specify the exact nature of of legal concepts. [18]

Nonetheless, progress on the second type of machine, one that would more fully automate the law, while remaining relatively inert. [19] Research into machines that could answer questions in the way that Mehl’s consultation machine would pick up somewhat in the late 1970s and 1980s. A 1979 convention in Swansea , Wales marked the first international effort to make the most of artificial intelligence in the world. [20] [21] That said, little substantial progress seems to have been made in the following decade of the 1980s. [22] In a 1988 review of Anne Gardner’s bookAn Artificial Intelligence Approach to Legal Reasoning (1987), the Harvard academic scholarly legal scholar and scientist Edwina Rissland wrote that “She plays, in part, the role of pioneer, artificial intelligence (” AI “) techniques have not yet been widely applied to Gardner, and this review, first describe and define the field, then demonstrate a working model in the field of contract and acceptance. [23] Eight years after the Swansea conference had passed, and still existed, and still existed as “pioneer [s]”.

In the 1990s and early 2000s more progress occurred. Computational research generated insights for law. [24] The First International Conference on AI and the Law occurred in 1987, but it is in the 1990s and 2000s that the biannual conference began to be more deeply into the issues involved with work intersecting computational methods, AI, and law. [25] [26] [27] Classes began to be taught to undergraduates on the uses of computational methods to automating, understanding, and obeying the law. [28] Further, by 2005, Stanford computer scientists from the Stanford Logic group have devoted themselves to studying the uses of computational techniques to the law. [29]Computational methods in the field of advanced analysis of the legal profession in the field of computer science in the field of computational law and the future of computational law. As insight into what these scholars see in the law of the future of computational law, here is a quote from a recent conference on the “New Normal” for the legal profession:

“Over the last 5 years, in the fall of the Great Recession, the legal profession of the New Normal Notably, a series of forces related to change, globalization, and the pressure to do less (in Both corporate America and law firms) Has Changed Permanently the legal services industry. As one paper put it, firms are cutting back is hiring “in order pour augmenter efficiency, Improve profit margins, and Reduce costs customer.” Indeed, in ict recently Noted cutbacks, Weil Gotshal’s leaders remarkedthat it was supposed to come back to work, but came back to the end of the day. “” The New Normal provides lawyers with an opportunity to rethink and reimagine the role of lawyers in our economy and society. . To the extent that law firms enjoy, or still enjoy, the ability to bundle work together, which is coming to an end, as clients unbundle legal services and tasks. Moreover, in other cases, automation and technology can change the roles of lawyers, both requiring them to oversee processes and use technology (electronic discovery). The upside is not only greater efficiencies for society, but new possibilities for legal craftsmanship. The emerging craft of lawmaking in the New World is likely to require both entrepreneurs and professionals to enable them to add value to customers. There are emerging opportunities for “legal entrepreneurs” in a range of roles from legal process management to developing technologies to manage legal operations (such as overseeing automated processes) to supporting online dispute resolution processes. In other cases, effective legal training, finance, sales, IT, entrepreneurship, human resources, etc. can form a powerful combination of business development roles, financial operations roles, HR roles, etc.). In both cases, traditional legal skills will be prepared for these roles. But the proper training, which builds up the knowledge of the field, and the skills and knowledge of the field of work (eg, accounting), and professional skills (eg, working in teams) over those with a one-dimensional skill set. “[30]

Many see the results of the computational automation of law. For one thing, legal experts in the areas of contract training, business planning, and the prediction of rule changes. [8] For another thing, those with knowledge about computers and the potential for computational law. In this vein, it seems that machines like Mehl’s second type may come into existence. Stephen Wolfram has said that:

But then they got codified and parametrized. So they’re really just algorithms, which of course can be meta-computations on, which is what it has launched at a thousand hedge funds, and so on. Well, eventually one is going to be able to make computational all sorts of legal things, from mortgages to tax codes to perhaps even patents. Now to actually achieve that, one has to have many ways to represent many aspects of the real world, in all its messiness. Which is what the whole knowledge-based computing of Wolfram | Alpha is about. ” from mortgages to tax codes to perhaps even patents. Now to actually achieve that, one has to have many ways to represent many aspects of the real world, in all its messiness. Which is what the whole knowledge-based computing of Wolfram | Alpha is about. ” from mortgages to tax codes to perhaps even patents. Now to actually achieve that, one has to have many ways to represent many aspects of the real world, in all its messiness. Which is what the whole knowledge-based computing of Wolfram | Alpha is about. “[31]


Algorithmic law

There have been many attempts to create a machine readable or machine executable legal code . A machine readable code would simplify the analysis of legal code, allowing the rapid construction and analysis of databases, without the need for advanced text processing techniques. A machine executable format would allow the specifics of a case to be input, and would return the decision based on the case.

Legal readable machine code is already quite common. METAlex, [32] an XML -based standard proposed and developed by the Leibniz Center for Law of the University of Amsterdam , [33] is used by the governments of both the United Kingdom and the Netherlands to encode their laws. In the United States, an executive order issued by President Barack Obama in the May 2013 issue, which was not specific format was mentioned. [34]

Legal executable machine code is much less common. Notable among current efforts is the Hammurabi Project, [35] an attempt to rewrite parts of the United States legal code in such a way that a law can take facts as input and return decisions. The Hammurabi Project currently focuses on the following aspects of this type of specification, such as tax or immigration laws , in the long-term the developers of the Hammurabi Project plan to include as many laws as possible.

Empirical analysis

Many recent efforts in computational law are focused on the empirical analysis of legal decisions, and their relation to legislation. These efforts usually make use of citation analysis , which examines patterns in quotations between works. Due to the widespread practice of legal quotation , it is possible to construct quotations indices and large graphs of legal precedent, called quotation networks. Citation networks allow the use of graph traversal algorithms in order to recount cases to one another, as well as the use of various distance metrics to find mathematical relationships between them. [36] [37] [38]These analyzes can reveal important overarching patterns and trends in judicial proceedings and the law is used. [39] [40]

There have been several breakthroughs in the analysis of judicial rulings in recent research on legal citation networks. These analyzes have made use of citations in the Supreme Court of Canada. such as the role of precedentover time. [36] [39] These analyzes have been used to predict which cases the Supreme Court will choose to consider. [39]

Another effort has examined United States Tax Court decisions, Tax Court decisions, opinions, and citations between the years of 1990 and 2008, and a quotation network from this database. This article discusses the extent to which this section of the tax code has been uncommonly reviewed, and that other sections of the code, such as those dealt with by “divorce, dependents, nonprofits, hobby and business expenses and losses” and “general definition”. of income, “were involved in the vast majority of disputes. [40]

Some research has been focused on hierarchical networks , in combination with citation networks, and the analysis of United States Code . This paper presents a number of aspects of the Code, including its size, the density of citations within and between sections of the Code, the type of language used in the Code, and how these features vary over time. This research has been used to provide information on the nature of the code, which is characterized by an increase in size and interdependence between sections. [37]


Visualization of legal code, and of the relations between various laws and decisions, is also a hot topic in computational law. Visualizations allow both professionals and the type to see large-scale relationships and patterns, which may be difficult to see by standard legal analysis or empirical analysis.

They are analyzed empirically as sub-sections of the network that are represented visually as a result. [36] However, there are still many technical problems in network visualization . The density of connections between nodes, and the sheer number of nodes in some cases, can make the visualization incomprehensible to humans. There are a variety of methods that can be used to describe the relationship between the two groups, and the relationship between these two groups, rather than between each node. [41]This allows the visualization to be readable, but the reduction in complexity can obscure relationships. Despite this limitation, visualization of legal quotation networks remains a popular field and practice.

Examples of tools

  1. OASIS Legal XML , UNDESA Akoma Ntoso , and CEN Metalex , which are standardizations created by legal and technical experts for the electronic exchange of legal data. [42]
  2. Creative Commons , which corresponds to custom-generated copyright licenses for internet content.
  3. Legal Analytics, which combines big data, critical expertise, and intuitive tools to deliver business intelligence and benchmarking solutions.
  4. Legal visualizations. Examples include Katz’s map of supreme court decisions [43] and Starger’s Opinion Lines for the Commerce Clause [44] and stare decisis . [45]

Online legal resources and databases

  1. PACER is an online repository of judicial rulings, maintained by the Federal Judiciary . [46]
  2. The Law Library of Congress maintains a comprehensive online repository of legal information, including legislation at the international, national, and state levels. [47]
  3. The Supreme Court Database is a comprehensive database containing information on decisions made by the Supreme Court from 1946 to the present. [48]
  4. The United States Reports contained detailed Supreme Court decision from 1791 to the near-present. [49]

See also

  • Artificial intelligence and law
  • Legal informatics
  • Legal expert systems
  • Robot lawyer


  1. Jump up^ Genesereth, Michael. “Computational Law – The Cop in the Backseat” .
  2. Jump up^ Np, nd Web. 16 June 2017. <>.
  3. Jump up^ 18 Rocky Mntn. L. Rev. 378 (1945-1946) Does the Law Need a Technological Revolution; Kelso, Louis O.
  4. Jump up^ 33 Minn. L. Rev. 455 (1948-1949) Jurimetrics – The Next Step Forward; Loevinger, Lee
  5. Jump up^ Loevinger, Lee. “Jurimetrics: The methodology of legal inquiry.” Law and Contemporary Problems(1963): 5-35. At 8.
  6. Jump up^ “About Jurimetrics.” About the Journal. American Bar Association Section of Science and Technology Law and the Center for Law, Science & Innovation, nd Web. Apr. 26 2014. <>.
  7. Jump up^ Ibid,
  8. ^ Jump up to:b Ibid.
  9. Jump up^ Mechanization of Thought Processes: Proceedings of a Held Symposium at the National Physical Laboratory on 24th, 25th, 26th and 27th November 1958. London: Her Majesty’s Stationery Office, 1959. Print.
  10. Jump up^ Niblett, Bryan. Computer Science and the Law: Inaugural Lecture of the Computer Science Professor Delivered at the College on January 25, 1977. Swansea, Wales: U College of Swansea, 1977. 7-8. Print.
  11. Jump up^ “Automation in the Legal World.” Mechanization of Thought Processes: Proceedings of a Symposium Held at the National Physical Laboratory on 24th, 25th, 26th and 27th November 1958. London: Her Majesty’s Stationery Office, 1959. 755-87. Print. At 759.
  12. Jump up^ “Automation in the Legal World.” Mechanization of Thought Processes: Proceedings of a Symposium Held at the National Physical Laboratory on 24th, 25th, 26th and 27th November 1958. London: Her Majesty’s Stationery Office, 1959. 755-87. Print. At 768-769.
  13. Jump up^ Ibid. 768.
  14. Jump up^ Some Speculation about Artificial Intelligence and Legal Reasoning Bruce G. Buchanan and Thomas E. Headrick,Stanford Law Review, Vol. 23, No. 1 (Nov. 1970), pp. 40-62. At p. 40.
  15. Jump up^ Some Speculation about Artificial Intelligence and Legal Reasoning Bruce G. Buchanan and Thomas E. HeadrickStanford Law Review, Vol. 23, No. 1 (Nov. 1970), pp. 40-62. At p. 51-60.
  16. Jump up^ Legal Decisions and Information Systems. Jon Bing and Trygve Harvold. Oslo, Norway: Universitets Forlaget; 1977
  17. Jump up^ Niblett, Bryan. Computer Science and Law. Cambridge: Cambridge UP, 1980. 7-8. Print.
  18. Jump up^ See, eg, L. Thorne McCarty,Reflections on Taxman: An Experiment in Artificial Intelligence and Legal Reasoning,90 Harv. L. Rev. 837-895 (1977).
  19. Jump up^ Supra, Niblett, p. 7-8.
  20. Jump up^ B. Niblett, editor. Computer Science and Law: An Advanced Course. Cambridge University Press, 1980. This volume is a record of the proceedings of a workshop held at the University College of Swansea, Wales, September 17-27, 1979.
  21. Jump up^ McCarty, L. Thorne. “Artificial Intelligence and Law: How to get there from here.” Ratio Juris3.2 (1990): 189-200. At 189.
  22. Jump up^ Though this is questionable. For an argument supporting, see McCarty, L. Thorne. “Artificial Intelligence and Law: How to get there from here.” Ratio Juris3.2 (1990): 189-200.
  23. Jump up^ Rissland, Edwina. “Artificial Intelligence and Legal Reasoning: A Discussion of the Field and Gardner’s Book.” AI Magazine9.3 (1988): 45.
  24. Jump up^ See, eg, Kades, Eric, “The Laws of Complexity & the Complexity of Laws: The Implications of Computational Complexity Theory for the Law” 49 Rutgers Law Review 403-484 (1997)
  25. Jump up^ Rissland, EL, Ashley, KD, & Loui, RP (2003). AI and Law: A fruitful synergy. Artificial Intelligence, 150 (1-2), 1-15.
  26. Jump up^ Bench-Capon, Trevor, Michał Araszkiewicz, Kevin Ashley, Katie Atkinson, Bex Floris, Filipe Borges, Daniele Bourcier 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, no. 3 (2012): 215-319.
  27. Jump up^ See “International Conference on Artificial Intelligence and Law (ICAIL).” International Conference on AI and Law (ICAIL). The DBLP Computer Science Bibliography, nd Web. 24 Apr. 2014. <>. The quote includes all past conferences and links to their contents. It appears that during the 1990s the number of papers presented, talks given, etc. 1987 and 1989, respectively.
  28. Jump up^ See, eg, this syllabus from Stanford for CS 204 Computers and Law. Genesereth, Michael R. “CS 204: Computers and Law.” CS204: Computers and Law. Stanford University, nd Web. 23 Apr. 2014. <>.
  29. Jump up^ “Stanford Computational Law.” Stanford Computational Law. Stanford University, nd Web. 24 Apr. 2014. <>
  30. Jump up^ “The Future of Innovation Law School (Conference @ColoradoLaw).” Computational Legal Studies. Np, nd Web. Apr. 18 2014. < >.
  31. Jump up^ Wolfram, Stephen. “Talking about the Computational Future at SXSW 2013-Stephen Wolfram Blog.” Stephen Wolfram Blog RSS. Np, Mar. 19, 2013. Web. Apr. 17 2014. <>.
  32. Jump up^ [1]
  33. Jump up^ “University of Amsterdam Digital Academic Repository” .
  34. Jump up^ The White House. Office of the Press Secretary. Executive Order – Making Open and Read the New Default for Government Information. Np, 09 May 2013. Web.
  35. Jump up^ “The Hammurabi Project” .
  36. ^ Jump up to:c Fowler, JH, Johnson TR, JF Spriggs, S. Jeon, and PJ Wahlbeck. “Network Analysis and the Law: Measuring the Legal Importance of Precedents at the US Supreme Court.” Political Analysis 15.3 (2006): 324-46. Print.
  37. ^ Jump up to:b Bommarito, Michael J., and Daniel Katz. “A Mathematical Approach to the Study of the United States Code.” Physica A: Statistical Mechanics and Its Applications 389.19 (2010): 4195-200. Print.
  38. Jump up^ Bommarito, Michael J., Daniel Martin Katz, Jonathan L. Zelner, and James H. Fowler. “Distance Measures for Dynamic Citation Networks.” Physica A: Statistical Mechanics and Its Applications389.19 (2010): 4201-208. Print.
  39. ^ Jump up to:c Fowler, James H., and Sangick Jeon. “The Authority of Supreme Court Precedent.” Social Networks 30.1 (2008): 16-30. Print.
  40. ^ Jump up to:b Bommarito, Michael J. “Empirical Survey of the Population of US Tax Court Written Decisions, An.” Go. Tax Rev. 30 (2010): 523.
  41. Jump up^ Shneiderman, Ben, and Aleks Aris. “Network Visualization by Semantic Substrates.” IEEE Transactions on Visualization and Computer Graphics12.5 (2006): 733-40. Print.
  42. Jump up^ “Legal XML” .
  43. Jump up^ Katz, Author Daniel Martin (4 May 2010). “Visualizing Temporal Patterns in the United States Supreme Court’s Network of Citations” .
  44. Jump up^ Starger, Colin P. (30 June 2012). “A Visual Guide to NFIB v. Sebelius: Competing Trade Clause Opinion Lines 1789-2012”. SSRN  2097161  – via
  45. Jump up^ Starger, Colin P. (16 April 2012). “Expanding Stare Decisis: The Role of Precedent in the Unfolding Dialectic of Brady v. Maryland”. SSRN  2040881  – via
  46. Jump up^
  47. Jump up^
  48. Jump up^
  49. Jump up^