Building and Testing the SHYSTER-MYCIN Hybrid Legal Expert System
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Use of Metods of Algebraic Programming for the Formal Verification of Legal Acts
UDC 004.2, 004.4 USE OF METODS OF ALGEBRAIC PROGRAMMING FOR THE FORMAL VERIFICATION OF LEGAL ACTS Volodymyr Peschanenko, Maksim Poltorackiy This article briefly describes the programmable tool for the analysis of a normative legal document. A mechanism for checking legal requirements is presented. The model of the legal document is proposed in the form of a set of special rules. Verification is provided by means of algebraic programming and methods of symbolic transformation. This approach allows us to analyze the legislative base of structural and logical errors, check the contradictions, completeness and integrity of legal acts. Presently, the mechanism of claster analysis of text, which makes it possible to identify the frequency of occurrence of various vague language constructs. Key words: law, algebraic programming, legal requirements, algebra of behavior. У цій статті коротко описується програмний інструмент для аналізу нормативно-правового документа. Існує механізм перевірки законних вимог. Модель правового документа представлена у вигляді набору спеціальних правил. Верифікація забезпечується за допомогою алгебраїчного програмування та методів символьного програмування. Цей підхід дозволяє проаналізувати законодавчу базу на наявність структурно логічних помилок, перевіряти правові вимоги на протиріччя, повноту та цілісність. Ключові слова: закон, алгебраїчне програмування, юридичні вимоги, алгебра поведінки. В этой статье кратко описывается программный инструмент для анализа нормативного правового документа. Представлен механизм -
The Devil in the Detail: Mitigating the Constitutional & Rule of Law Risks
Florida State University Law Review Volume 47 Issue 1 In Tribute to Talbot "Sandy" D'Alemberte Article 6 Fall 2019 The Devil in the Detail: Mitigating the Constitutional & Rule of Law Risks Associated with the Use of Artificial Intelligence in the Legal Domain Catrina Denvir Monash Business School, Monash University Tristan Fletcher Center for Artificial Intelligence, University College London Jonathan Hay Judge Business School, University of Cambridge Pascoe Pleasence Centre for Empirical Legal Studies, University College London Follow this and additional works at: https://ir.law.fsu.edu/lr Part of the Computer Law Commons, Constitutional Law Commons, and the Rule of Law Commons Recommended Citation Catrina Denvir, Tristan Fletcher, Jonathan Hay & Pascoe Pleasence, The Devil in the Detail: Mitigating the Constitutional & Rule of Law Risks Associated with the Use of Artificial Intelligence in the Legal Domain, 47 Fla. St. U. L. Rev. 29 (2019) . https://ir.law.fsu.edu/lr/vol47/iss1/6 This Article is brought to you for free and open access by Scholarship Repository. It has been accepted for inclusion in Florida State University Law Review by an authorized editor of Scholarship Repository. For more information, please contact [email protected]. THE DEVIL IN THE DETAIL: MITIGATING THE CONSTITUTIONAL & RULE OF LAW RISKS ASSOCIATED WITH THE USE OF ARTIFICIAL INTELLIGENCE IN THE LEGAL DOMAIN DR. CATRINA DENVIR* DR. TRISTAN FLETCHER** MR. JONATHAN HAY*** PROFESSOR PASCOE PLEASENCE**** ABSTRACT Over the last decade increased emphasis has been placed on the role that artificial intelligence (AI) will play in disrupting the practice of law. Although considerable attention has been given to the practical task of designing a computer to “think like a lawyer,” a number of related issues merit further inquiry. -
SHYSTER: a Pragmatic Legal Expert System
SHYSTER: A Pragmatic Legal Expert System JAMES DAVID POPPLE A thesis submitted for the degree of Doctor of Philosophy of The Australian National University April 1993 �c James Popple 1993 Doonesbury (page 131) copyright G. B. Trudeau Reprinted with permission of Universal Press Syndicate All rights reserved Earlier versions of some parts of this thesis have appeared in: Proceedings of the Thirteenth Australian Computer Science Conference �c Australian Computer Science Association 1990 Advances in Computing and Information: Proceedings of the International Conference on Computing and Information c International Conference on Computing and Information 1990 The Australian Computer Journal �c Australian Computer Society Inc. 1991 National Library of Australia Cataloguing-in-Publication entry Popple, James David, 1964– . SHYSTER: a pragmatic legal expert system. Bibliography. Includes indexes. ISBN 0 7315 1827 6. 1. SHYSTER (Computer file). 2. Law — Methodology — Data processing. 3. Expert systems (Computer science). I. Australian National University. Faculty of Engineering and Information Technology. Dept of Computer Science. II. Title. 340.11 Except where otherwise indicated, this thesis is my own original work. James Popple 29 April 1993 � \ shy.ster \�sh¯ıst (r) n -s [prob. after Scheuster fl1840 Am. attorney frequently rebuked in a New York court for pettifoggery] : one who is professionally unscrupulous esp. in the practice of law or politics ... Webster’s Third New International Dictionary (1961)1 � � � shyster (� a st (r)) ... [Of obscure origin. It might be f. shy a. (sense 7, disreputable) + -ster; but this sense of the adj. is app. not current in the U.S.] ... ‘A lawyer who practises in an unprofessional or tricky manner; especially, one who haunts the prisons and lower courts to prey on petty criminals; hence, any one who conducts his business in a tricky manner’ (Funk’s Stand. -
Spreadsheets for Legal Reasoning: the Continued Promise of Declarative Logic Programming in Law
Spreadsheets for Legal Reasoning: The Continued Promise of Declarative Logic Programming in Law by Jason Patrick Morris A thesis submitted in partial fulfillment of the requirements for the degree of Master of Laws In Faculty of Law and Department of Computing Science University of Alberta c Jason Patrick Morris, 2020 Abstract The legal services market is one in which there is too much demand, and too little supply. One method of increasing supply in a market is to increase ef- ficiency by automating. Automated legal services require the automation of legal reasoning. Declarative logic programming (DLP) has long been recog- nized as well-suited to the automation of legal reasoning. This dissertation reviews the legal academic literature surrounding the automation of legal ser- vices using DLP, which has been discussed primarily with regard to how it can be used to build \expert systems". This dissertation argues that most of the criticisms of the use of expert systems for automating legal services can be addressed by using modern DLP technologies, conceiving of the encoding as being representative of an interpretation of the law rather than the law's correct meaning, and increasing ease-of-use for non-programmers. The dissertation then proposes a set of 7 criteria of suitability for DLP tools developed from a legal services automation perspective. A survey of available tools is performed, comparing the available tools to these criteria. The dis- sertation advocates for the development of open source DLP tools that have both accessibility features (ease of use and price), and at least one of the five technical features. -
Kevin D. Ashley. January, 2018 1 CURRICULUM VITA
Kevin D. Ashley. January, 2018 1 CURRICULUM VITA Kevin Dean Ashley University Addresses: School of Law Learning Research and Development Center University of Pittsburgh University of Pittsburgh 3900 Forbes Avenue 3939 O'Hara Street Pittsburgh, Pennsylvania 15260 Pittsburgh, Pennsylvania 15260 (412) 648-1495 (412) 624-7496 Research Interests: My research interests in learning, law, and computer science are to: (1) Develop computational models of case-based reasoning (CBR) and argumentation in domains like law and practical ethics to better understand decision-making and as a basis for intelligent systems to educate students; (2) Develop techniques for linking computational models of legal reasoning with legal texts in order to facilitate acquiring knowledge in Artificial Intelligence (AI) programs and to assist legal practitioners; (3) Identify and analyze special legal problems posed by computer technology in such areas as intellectual property, commercial law, product liability, technology licensing, and privacy. Summary of Qualifications: Professor of Law and Intelligent Systems, University of Pittsburgh Senior Scientist, Learning Research and Development Center Adjunct Professor of Computer Science Fellow, American Association of Artificial Intelligence National Science Foundation Presidential Young Investigator M.A., Ph.D., Computer Science, University of Massachusetts J.D., Harvard Law School B.A., Philosophy, Princeton University Associate Attorney, White & Case, 14 Wall Street, New York City Visiting Scientist, IBM Thomas J. Watson Research Center Professional Academic and Research Experience: UNIVERSITY OF PITTSBURGH, Pittsburgh, Pennsylvania. Dates: September, 1989 through present. Current Joint Appointments: Professor of Law (with tenure), School of Law, September, 1998 Professor of Intelligent Systems, Graduate Program in Intelligent Systems, September, 1998 Senior Scientist, Learning Research and Development Center, October, 1998 Adjunct Professor of Computer Science, September, 1998. -
© 2017 Thomson Reuters. No Claim to Original U.S. Government Works. 1 22 No. 3 Cyberspace Lawyer NL 1
Are you ready for Artificial Intelligence?, 22 No. 3 Cyberspace Lawyer NL 1 22 No. 3 Cyberspace Lawyer NL 1 Cyberspace Lawyer | April 2017 Cyberspace Lawyer by Giulio Coraggioa0 Are you ready for Artificial Intelligence? Artificial intelligence is a massive opportunity, but triggers some risks which cannot be sorted through over-regulations that might damage the market. Three simultaneous technologic revolutions unleashing AI One of the main topics of the World Economic Forum 2017 was artificial intelligence (AI). I found extremely interesting the interview to Ginni Rometty, the Chairwoman, President and CEO of IBM.1 She said that we are in a unique period since there a three technologic revolutions happening simultaneously which make this point in time different from ever before • The rise of cloud computing; • The rise of data; and • The rise of mobility. Because of these three revolutions, there is a huge amount of information that cannot be dealt by humans, but we need systems that can deal with such data, reason around it and learn. This led to the rise of artificial intelligence. I have read a number of articles on how artificial intelligence might represent a threat for workers. It is quite recent the news about the Japanese insurance firm Fukoku Mutual Life Insurance that is making 34 employees redundant and replacing them with IBM’s Watson Explorer AI.2 But the point raised by Ms. Rometty is that AI does not replace humans, it does something that humans cannot physically do since no human would be able to deal with such massive amount of information and AI can reach results from which anyone can benefit. -
The Dilemma of Private Justice Systems: Big Data Sources, the Cloud and Predictive Analytics Anjanette H
Northwestern Journal of International Law & Business Volume 35 Issue 4 Ambassador Spring 2015 The Dilemma of Private Justice Systems: Big Data Sources, the Cloud and Predictive Analytics Anjanette H. Raymond Follow this and additional works at: http://scholarlycommons.law.northwestern.edu/njilb Recommended Citation Anjanette H. Raymond, The Dilemma of Private Justice Systems: Big Data Sources, the Cloud and Predictive Analytics, 35 Nw. J. Int'l L. & Bus. 1A (2015). http://scholarlycommons.law.northwestern.edu/njilb/vol35/iss4/1 This Article is brought to you for free and open access by Northwestern University School of Law Scholarly Commons. It has been accepted for inclusion in Northwestern Journal of International Law & Business by an authorized editor of Northwestern University School of Law Scholarly Commons. DOC3 (DO NOT DELETE) 9/22/17 1:11 PM Copyright 2017 by Anjanette H. Raymond Printed in the U.S.A. Northwestern Journal of International Law & Business Vol. 35, Ambassador The Dilemma of Private Justice Systems: Big Data Sources, the Cloud and Predictive Analytics Anjanette H. Raymond1 Abstract: In the age of big data, demanding customer expectations, and increasingly limited access to justice for small claims arising from online sales, business organizations are moving to enhanced online customer complaint platforms and insisting upon increased online justice resolution systems. At the same time, online businesses, even websites you fail to think of as a business, are moving from traditional analytics that provide a snapshot of the past, to solutions that provide an accurate picture of the present and a prediction of future trends. For many, predictive analytics is the wave of the future.