Computational law

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).

The regulations can just as well be the terms of contracts (e.g. delivery schedules, insurance covenants, real estate transactions, financial agreements).

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.

[9] 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.

[13] 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 [legal] problem put to it".

[14] 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.

[17][18] 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.

According to Thorne McCarty,[20] "these systems all have the following characteristics: They do backward chaining inference from a specified goal; they ask questions to elicit information from the user; and they produce a suggested answer along with a trace of the supporting legal rules."

Therefore, Gardner, and this review, first describe and define the field, then demonstrate a working model in the domain of contract offer and acceptance.

"[24] 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[s]".

Stephen Wolfram has said that: In Estonia, the government has been spearheading a 'robotic judge' initiative whereby chief data officer Ott Velsberg is implementing elements both adjacent and directly related to computational law.

Firstly, inspectors no longer verify the use of hay-field subsidies (that prevent forests) rather they use a deep-learning algorithm to validate the results from satellite comparison thus saving nearly a million dollars per annum.

[citation needed] Many current efforts in computational law are focused on the empirical analysis of legal decisions, and their relation to legislation.

Citation networks allow the use of graph traversal algorithms in order to relate cases to one another, as well as the use of various distance metrics to find mathematical relationships between them.

These analyses have made use of citations in Supreme Court majority opinions to build citation networks, and analyzed the patterns in these networks to identify meta-information about individual decisions, such as the importance of the decision, as well as general trends in judicial proceedings, such as the role of precedent over time.

This research has been used to provide commentary on the nature of the Code's change over time, which is characterized by an increase in size and in interdependence between sections.