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Most legal expert systems attempt to implement complex models of legal reasoning. But the utility of a legal expert system lies not in the extent to which it simulates a lawyer’s approach to a legal problem, but in the quality of its predictions and of its arguments. A complex model of legal reasoning is not necessary: a successful legal expert system can be based upon a simplified model of legal reasoning. Some researchers have based their systems upon a jurisprudential approach to the law, yet lawyers are patently able to operate without any jurisprudential insight. A useful legal expert system should be capable of producing advice similar to that which one might get from a lawyer, so it should operate at the same pragmatic level of abstraction as does a lawyer—not at the more philosophical level of jurisprudence. A legal expert system called SHYSTER has been developed to demonstrate that a useful legal expert system can be based upon a pragmatic approach to the law. SHYSTER has a simple representation structure which simplifies the problem of knowledge acquisition. Yet this structure is complex enough for SHYSTER to produce useful advice. SHYSTER is a case-based legal expert system (although it has been designed so that it can be linked with a rule-based system to form a hybrid legal expert system). Its advice is based upon an examination of, and an argument about, the similarities and differences between cases. SHYSTER attempts to model the way in which lawyers argue with cases, but it does not attempt to model the way in which lawyers decide which cases to use in those arguments. Instead, it employs statistical techniques to quantify the similarity between cases. It decides which cases to use in argument, and what prediction it will make, on the basis of that similarity measure. SHYSTER is of a general design: it can provide advice in areas of case law that have been specified by a legal expert using a specification language. Hence, it can operate in different legal domains. Four different, and disparate, areas of law have been specified for SHYSTER, and its operation has been tested in each of those domains. Testing of SHYSTER in these four domains indicates that it is exceptionally good at predicting results, and fairly good at choosing cases with which to construct its arguments. SHYSTER demonstrates the viability of a pragmatic approach to legal expert system design.
Most legal expert systems attempt to implement complex models of legal reasoning. This book argues that a complex model is unnecessary. It advocates a simpler, pragmatic approach in which the utility of a legal expert system is evaluated by reference, not to the extent to which it simulates a lawyer's approach to a legal problem, but to the quality of its predictions and of its arguments. The author describes the development of a legal expert system, called SHYSTER, which takes a pragmatic approach to case law. He discusses the testing of SHYSTER in four different and disparate areas of case law, and draws conclusions about the advantages and limitations of this approach to legal expert system development. Chapter 1 presents a critical analysis of previous work of relevance to the development of legal expert systems. Chapter 2 explains the pragmatic approach that was adopted in the development of SHYSTER. The implementation of SHYSTER is detailed using examples in chapter 3. Chapter 4 describes the testing of SHYSTER, and conclusions are drawn from those tests in chapter 5. Examples of SHYSTER's output are provided in appendices.
El volumen 9 de la LEFIS Series celebra el 25 aniversario de BILETA (British & Irish Law, Education and Technology Association). En él, estudiosos internacionales pioneros en Informática y Derecho procedentes de universidades australianas, británicas, estadounidenses, holandesas, noruegas y españolas analizan los éxitos y desafíos en la aplicación de las tecnologías de información al Derecho y a la práctica legal.
Provides fully commented and indexed listings of the ISO C source code for the SHYSTER legal expert system.
The Computerised Lawyer provides a comprehensive introduction to the technology and application of computers in law. Over the last 5 years it has become increasingly recognised that the skills associated with new technology are so important that proficie ncy in the field is now being viewed as an integral element in the education and skills development of all law students. New curriculums are being developed which incorporate the issues discussed in this book, and professionals will find the text useful and highly relevant. This book fulfils the need for a textbook which, whilst assuming no prior knowledge of computing, manages to cover all the key issues associated with information technology and its relevance to legal issues and practice. Philip Leith and Amanda Hoey have completely rewritten the first edition of this book to bring the reader an up-to-date text that will be important to everyone working with computers in law.
This carefully edited book presents examples of the successful application of Intelligent Systems techniques to practical problems. The invited contributions, written by international experts in their respective fields, clearly demonstrate what can be achieved when AI systems are used to solve real-world problems. The book covers the field of applied intelligent systems with a broad and deep selection of topics, such as object recognition, robotics, satellite weather prediction, or economics with an industrial focus. This book will be of interest to researchers interested in applied intelligent systems/AI, as well as to engineers and programmers in industry.
This book brings together critical legal analyses of ongoing global issues in the digital age by international lawyers in Asia. Digital revolution is the key to understanding the contemporary human society. In this book, the authors critically redefine the mainstream thinking and ideas of contemporary international legal issues that the global community is facing. Given the rapidly shifting global legal landscape and framework, they shed light on the theoretical and practical questions in international law and reexamine their global context. Such independent and forward-looking approach suggests the ideas to shaping the global common good in the future human society. In both theory and practice, this book is a useful guide to Asian law, politics, economy, and business providing a fair and balanced point of view.
This book represents the second phase of a multi-method, multi-study of the 'Information Systems Academic Discipline in Australia'. Drawing on Whitley's Theory of Scientific Change, the study analysed the degree of 'professionalisation' of the Information Systems Discipline, the overarching research question being 'To what extent is Information Systems a distinct and mature discipline in Australia?' The book chapters are structured around three main sections: a) the context of the study; b) the state case studies; and c) Australia-wide evidence and analysis. The book is crafted to be accessible to IS and non-IS types both within and outside of Australia. It represents a 'check point'; a snapshot at a point in time. As the first in a hoped for series of such snap-shots, it includes a brief history of IS in Australia, bringing us up to the time of this report. The editorial team comprises Guy Gable, architect and leader; Bob Smyth, project manager; Shirley Gregor, sponsor, host and co-theoretician; Roger Clarke, discipline memory; and Gail Ridley, theoretician. In phase two, the editors undertook to examine each component study, with a view to arriving at an Australia-wide perspective.
The International Conference on Case-Based Reasoning (ICCBR) is the pree- nent international meeting on case-based reasoning (CBR). ICCBR 2003 (http://www.iccbr.org/iccbr03/)isthe?fthinthisseriesofbiennialinter- tional conferences highlighting the most signi?cant contributions to the ?eld of CBR.TheconferencetookplacefromJune23throughJune26,2003attheN- wegian University of Science and Technology in Trondheim, Norway. Previous ICCBR conferences have been held in Vancouver, Canada (2001), Seeon, G- many (1999), Providence, Rhode Island, USA (1997), and Sesimbra, Portugal (1995). Day 1 of ICCBR 2003, Industry Day, provided hands-on experiences utilizing CBR in cutting-edge knowledge-management applications (e.g., help-desks,- business, and diagnostics). Day 2 featured topical workshops on CBR in the healthsciences,theimpactoflife-cyclemodelsonCBRsystems,mixed-initiative CBR, predicting time series with cases, and providing assistance with structured vs. unstructured cases. Days 3 and 4 comprised presentations and posters on theoretical and applied CBR research and deployed CBR applications, as well as invited talks from three distinguished scholars: David Leake, Indiana University, H ́ ector Munoz-Avila, ̃ Lehigh University, and Ellen Rilo?, University of Utah. The presentations and posters covered a wide range of CBR topics of in- rest both to practitioners and researchers, including case representation, si- larity, retrieval, adaptation, case library maintenance, multi-agent collaborative systems, data mining, soft computing, recommender systems, knowledge ma- gement, legal reasoning, software reuse and music.
Becoming Artificial is a collection of essays about the nature of humanity, technology, artifice, and the irreducible connections between them. Artificial Intelligence (AI) was once the stuff of pure fantasy. Ideas about machines that could think seemed as plausible as space travel or inexpensive communication technology. The last two decades have introduced a number of game-changing innovations that make discussion of AI no longer a mere armchair speculation, but rather a serious topic of debate for everyone who will be affected, from policy makers to an increasingly displaced workforce. The growth in power of AI algorithms and systems has sparked many thought-provoking questions: Is there something fundamental to being human or are humans simply biological computers? Will AI continue to assist us or eventually enslave us? Can self-driving cars be legally responsible for their actions? And most importantly, how can we chart a path for AI that ensures a humane and beneficial future for society?