Volume 1 Spring Issue 1988 BOOKREVIEW AN ARTIFICIAL INTELLIGENCE APPROACH TO L E G A L R E A S O N I N G By Anne vonder Lieth Gardner Cambridge Massachusetts T h e MIT Press 1987 pp 193 Reviewed by Edwina L Rissland Anne Gardner is both a lawyer and a coruputer scientist She obtained her J D from Stanford in 1958 ar d her book is a revision of her 1984 dissertation submitted to Stanford s Department of Computer Science 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 I THE FIELD AI AND THE LAW A Artificial Intelligence Malwin Minsky in his preface to the collection Semantic Information Processing defined artificial intelligence as the science of making machines do things that would require intelligence if done by people u Better known successful applications have included playing chess identifying bacterial strains recognizing and manipulating structures built with childrens blocks and formulating concepts in set theory 2 Typical programming languages include LISP and PROLOG while typical specialties in AI research include case based reasoning expert rule based systems natural language processing nonmonotonic reasoning and learning from examples Above all the field is marked by its current diversity rapid growth and apparent potential2 Associate Professor of Computer and Information Science University of Massachusetts at Amherst Lecturer on Law Harvard LaW School Professor Rissland will serve as Program Chair for the second International Conference of Artificial Intelligenceand the Law currently scheduled for late Spring 1989 in London Asecond more technical version of this review will appear in the Fall 1988 issue ofA Magazine I SEMANTIC INFORMATION PROCESSING M Minsky ed 1968 2 See generally Waltz ArtificialIntelligence SCI AM Oct 1982 For a recent readable overview see Linden Putti gKnowledge to Work TIME March 28 1988 3 Optimism is founded in part upon parallel developments in ha dware and operating systems such as Intel s 386 and MicmsoR s OS 2 See e g Gralla Chips Offthe Old Block A History PC WEEK Jan 19 1988 at S 13 noting the AI capabilitiesof new microcomputers 224 Harvard Journal of Law and Technology Vol 1 B Attraction The law is an attractive domain for AI research for several reasons First the law has a tradition of examining its own reasoning process Second legal reasoning is stylized one reasons according to stare decisis with cases and by analogy Third much legal knowledge is readily accessible and relatively well structured codified and indexed Nevertheless it will not surprise and may even please lawyers to learn that the Restatement the Uniform Commercial Code and case law like the theories of legal reasoning proposed by Karl Llewellyn Ronald Dworkin Edward Levi and H L A Hart are of limited immediate use to AI programmers There is want amidst plenty because the central questions what we know and how we know it are answered only partially by such material and even these partial answers prove difficult to harness computationally Lawyers interest in AI techniques and software is nascent but concisely expressed in marketing terms Lawyers use tools that gather sift and or structure legal arguments in a cost effective manner LEXIS and WESTLAW which are essentially keywordbased programs siftinglarge full text databases operate at a level of sophistication far below that contemplated by AI programmers such as Alane Gardner Marek Sergot 4 my colleague Kevin Ashley 5 or m a n y others 6 Yet p r o d u c t s such as L E X I S a n d WESTLAW do indicate the potential ubiquity of legal analysis software and the symbiosis between computer science and legal research C The Hurdles Several specific familiar aspects of legal analysis that challenge AI may be noted First logical deduction alone cannot resolve all legal issues In Gardner s terms legal reasoning is a rule guided rather than rule governed activity p 3 Legal rules have the status more of heuristics than of theorems in that all rules have exceptions and rules may contradict Second the terms employed in legal discourse are open textured That is the meanings or definitions of many legal terms 4 Sergot Sadri The British Nationality Act as a Logic Program 29 COMMUNICATlONS OF THE ACM 370 1987l 5 Rissland Ashley A Case Based System for 7 ade Secrets Law PROC OF THE ANN CONF OF THEAM A FOR ARTIFICIAL INTELLIGENCE 60 1984 Ashley ModellingL galArgument Reasoning with Cases and Hypotheticals unpublished manuscript 6 See e g PROC OF THE FIRST INT L CONF ON ARTIFICIAL N rELLIGENCEAND LAW ACM 1987 Gardner herself offers an excellent bibliography pp 201 14 and presents in Chapter 4 a survey of the field complete through the spring of 1986 Spring 1988 Artificial Intelligence 225 and predicates are inherently indeterminate in the philosophical sense of natural kind classes Third legal questions commonly invite more than one answer yet legal argument is both time constrained and resource limited For while conflict disagreement and argument are part and parcel of the law 7 the law must provide a timely answer for one side or the other reached at a socially acceptable cost Finally in law the answers change Whether the change is incremental as in the mode of Kuhn s normal science or abrupt as in a Kuhnian paradigm shift a hard learning issues lurk close to the surface of the legal issues that AI programs attempt to resolve To accomodate even gradual change the algorithms must adapt to a dynamic knowledge base a shifting foundation of cases statutes and the indices rules and norms which manipulate them Eventually one must confront the change in predicates and in the representation itself either through the emergence of new legal concepts or through the substantial modification of old ones 9 In summary legal reasoning requires certain minimum capabilities 1 the ability to reason with cases and examples particularly through analogy 2 the ability to handle ill defined open textured predicates 3 the ability to handle exceptions 4 the ability to handle fundamental conflicts between rules and 5 the ability to handle change and nonmonotonicity 10 D Several Possible Approaches Each AI specialty mentioned in Section A above is described briefly below The distinctions drawn are noZ absolute these specialties are