DOCSLIB.ORG

© 2017 Thomson Reuters. No Claim to Original U.S. Government Works. 1 22 No. 3 Cyberspace Lawyer NL 1

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
© 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. AI and robots are exponentially becoming part of our daily life and the potentials of such technologies cannot be always controlled by humans. If you think about Google DeepMind project3 where AI is not programmed/taught to solve problems, but needs to learn itself how to solve problems. This means that we will reach a stage when machines will take decisions whose reasoning cannot be explained by humans! The call for regulations on artificial intelligence Ms. Rometti herself mentioned as part of her interview that a 4th revolution is around security and privacy, and how such issues might still derail the revolution the three components mentioned above have combined to create. And on this topic, it might not be a coincidence that the Legal Affairs Committee of the European Parliament approved a report4 calling the EU Commission for the introduction of a set of rules on robotics. Such rules include: Who is liable and how damages should be recovered? The Committee is for the introduction of strict liability rules for damages caused by requiring only proof that damage has occurred and the establishment of a causal link between the harmful behaviour of the robot and the damage suffered by the injured party. This would not sort the issue around the allocation of responsibilities for “autonomous” robots like Google DeepMind that did not receive instructions from the producer. And this is the reason why the Committee is proposing the introduction of a compulsory insurance scheme for robots producers or owners (e.g. in the case of producers of self- © 2017 Thomson Reuters. No claim to original U.S. Government Works. 1 Are you ready for Artificial Intelligence?, 22 No. 3 Cyberspace Lawyer NL 1 driving cars). The issue is whether such obligation would represent an additional cost that either would be borne by customers or would even prevent the development of technologies. Robots treated as humans? What sounds quite unusual and honestly a bit “scary” is that the Committee also calls for the introduction of a “legal status” for robots as electronic persons “with specific rights and obligations, including that of making good any damage they may cause, and applying electronic personality to cases where robots make smart autonomous decisions or otherwise interact with third parties independently.” The report does not fully clarify how such legal status should work in practice, but it seems like we are already attempting to distinguish the liability of the artificial intelligence itself separate from the one of its producer/owner. This shall be assessed on a case-by-case basis in relation to autonomous robots, but civil law rules definitely need to evolve in order to accept such principles. Are ethical rules needed? The Committee stressed the need of guiding ethical framework for the design, production and use of robots. This would operate in conjunction with a code of conduct for robotics engineers, of a code for research ethics committees when reviewing robotics protocols and of model licences for designers and users. My prediction is that most of the companies investing in the area shall sooner rather than later establish an internal ethical committee. But the issue is whether statutory laws on ethics are necessary since they might limit the growth of the sector. Privacy as a “currency” cannot affect individuals It is the first time that I see privacy associated to a “currency.” However, it is true that we provide our personal data to purchase services. And the matter is even more complicated in case of complex robots whose reasoning cannot be mapped. Such circumstance might trigger data protection issues. But it is important that the Committee called for guarantees necessary to ensure privacy and security also through the development of standards. The reaction from the industry The European Robotics Association immediately reacted to this report stating in a position paper5 that Whereas it is true that the “European industry could benefit from a coherent approach to regulation at European level” and companies would profit from legal certainty in some areas, over-regulation would hamper further progress. This poses a threat to the competitiveness not only of the robotics sector but also of the entire European manufacturing industry. This is the usual issue that is being discussed also in relation to the recent European consultation on rules for Internet of Things technologies. It can be hard to set so specific rules on technologies that are rapidly evolving. The concern is that regulations might risk to restrict investments in the sector, while in my view we should welcome regulations that create more certainty and foster innovation. © 2017 Thomson Reuters. No claim to original U.S. Government Works. 2 Are you ready for Artificial Intelligence?, 22 No. 3 Cyberspace Lawyer NL 1 Westlaw. © 2017 Thomson Reuters. No Claim to Orig. U.S. Govt. Works. Footnotes a0 Giulio Coraggio ([email protected]) is a Partner in the Milan office of DLA Piper. 1 See https://www.weforum.org/events/world-economic-forum-annual-meeting-2017/sessions/an-insight-an-idea-with- ginni-rometty. 2 See Justin McCurry, “Japanese company replaces office workers with artificial intelligence,” The Guardian, 5 Jan. 2017 (https://www.theguardian.com/technology/2017/jan/05/japanese-company-replaces-office-workers-artificial- intelligence-ai-fukoku-mutual-life-insurance). 3 See https://deepmind.com. 4 See http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//NONSGML%2BCOMPARL%2BPE- 582.443%2B01%2BDOC%2BPDF%2BV0//EN. 5 See http://www.eu-nited.net/robotics/upload/pdf/2016-10-27_PositionPaper_Civil_Law_Rules_of_Robotics.pdf. End of Document © 2017 Thomson Reuters. No claim to original U.S. Government Works. © 2017 Thomson Reuters. No claim to original U.S. Government Works. 3 ARTIFICIAL LEGAL INTELLIGENCE, 12 Harv. J.L. & Tech. 241 12 Harv. J.L. & Tech. 241 Harvard Journal of Law & Technology Fall, 1998 Book Note Stephen M. McJohna1 Copyright (c) 1998 by the President & Fellows of Harvard College; Stephen M. McJohn ARTIFICIAL LEGAL INTELLIGENCE By Pamela N. Gray Brookfield, VT: Dartmouth Publishing Co., 1997. Pp. 402. $76.95 (hard). ISBN 1-85521-266-8 WESTLAW LAWPRAC INDEX LIT -- Literature Reviews & Analyses Pamela Gray’s Artificial Legal Intelligence offers an imaginative, utopian view of the technological implementation of legal reasoning. After surveying a number of programs applying artificial intelligence techniques to legal reasoning, Artificial Legal Intelligence offers a vision of the law as a holistic entity on the verge of evolving into a codified computer system of legal services.1 In this vision, answers to legal questions would be as readily available online as stock quotes, soccer scores, and flight schedules. Artificial Legal Intelligence presents a thought-provoking approach to both computational models of legal reasoning and the use of evolutionary thinking about the law. Drawing on a prodigious amount of research, Gray looks beyond the rather technical approach common in the field and attempts to place artificial legal intelligence within the broad structure of legal history. This Note first summarizes Gray’s vision of a computerized artificial legal intelligence, a vision of developments in both technology and legal history. It next discusses how Gray’s concept of the future runs counter to trends in both artificial intelligence and legal theory in some important ways. At the same time, Gray’s book, by freeing itself from present technological constraints, provides a wider vision than many more technical discussions of artificial intelligence. In particular, her view of the evolution of law brings in social and cultural factors often ignored by discussions of legal *242 reasoning. The last part of this Note considers, more broadly, how evolutionary analysis can provide a fruitful method for analyzing legal reasoning. The broad scope
Load more

Recommended publications
  • 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
    [Show full text]
  • Building and Testing the SHYSTER-MYCIN Hybrid Legal Expert System
    TR-CS-03-01 Building and Testing the SHYSTER-MYCIN Hybrid Legal Expert System Thomas A. O’Callaghan, James Popple and Eric McCreath May 2003 Joint Computer Science Technical Report Series Department of Computer Science Faculty of Engineering and Information Technology Computer Sciences Laboratory Research School of Information Sciences and Engineering This technical report series is published jointly by the Department of Computer Science, Faculty of Engineering and Information Technology, and the Computer Sciences Laboratory, Research School of Information Sciences and Engineering, The Australian National University. Please direct correspondence regarding this series to: Technical Reports Department of Computer Science Faculty of Engineering and Information Technology The Australian National University Canberra ACT 0200 Australia or send email to: [email protected] A list of technical reports, including some abstracts and copies of some full reports may be found at: http://cs.anu.edu.au/techreports/ Recent reports in this series: TR-CS-02-06 Stephen M Blackburn and Kathryn S McKinley. Fast garbage collection without a long wait. November 2002. TR-CS-02-05 Peter Christen and Tim Churches. Febrl - freely extensible biomedical record linkage. October 2002. TR-CS-02-04 John N. Zigman and Ramesh Sankaranarayana. dJVM - a distributed JVM on a cluster. September 2002. TR-CS-02-03 Adam Czezowski and Peter Christen. How fast is -fast? Performance analysis of KDD applications using hardware performance counters on UltraSPARC-III. September 2002. TR-CS-02-02 Bill Clarke, Adam Czezowski, and Peter Strazdins. Implementation aspects of a SPARC V9 complete machine simulator. February 2002. TR-CS-02-01 Peter Christen and Adam Czezowski.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]