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AI4J – Artificial Intelligence for Justice August 30, 2016 the Hague, the Netherlands Workshop at the 22Nd European Conference on Artificial Intelligence (ECAI 2016)

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AI4J – Artificial Intelligence for Justice August 30, 2016 the Hague, the Netherlands Workshop at the 22Nd European Conference on Artificial Intelligence (ECAI 2016) AI4J { Artificial Intelligence for Justice August 30, 2016 The Hague, The Netherlands Workshop at the 22nd European Conference on Artificial Intelligence (ECAI 2016) Workshop chairs Floris Bex Department of Information and Computing Sciences, Utrecht University Tom van Engers Leibniz Center for Law, Faculty of Law, University of Amsterdam Henry Prakken Faculty of Law, University of Groningen; Department of Information and Computing Sciences, Utrecht University Bart Verheij Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen Artificial intelligence is currently in the centre of attention of legal professionals. An abundance of startup companies explore the application of AI techniques in the domain of law, and there is even talk of artificially intelligent legal assistants disrupting the legal market space. Factors driving the increased attention for legal AI include: Technological breakthroughs in machine learning, natural language process- ing, ubiquitous computing, data science, and argumentation technology; The changing attitude towards technology in the legal domain; The much increased availability of legal data on the internet; The recent success of AI applications in the private and public domain; The success of technology supporting access to law, legal empowerment, and transparency; The increased need for norms embedded in technology (autonomous driving and warfare, big data analysis for crime fighting and counterterrorism). The aim of this workshop is to investigate opportunities and challenges in AI ap- plied to the law, with a particular focus on the relevance of the recent technological breakthroughs for AI & Law research and for legal practice. Questions addressed include the following: How can AI & Law research contribute to improving legal work in, for exam- ple, courts, law firms, public administration, police practice and businesses? How should AI & Law research change in light of the recent research break- throughs and technological developments? For example, how can traditional research on legal knowledge bases, legal reasoning and legal argument be combined with data science, machine learning and natural language pro- cessing? The law has been a longstanding application field for AI research. The biennial International conferences on AI & Law (ICAIL) started in 1987, the annual JURIX conferences on Legal Knowledge and Information Systems in 1988, and the journal Artificial Intelligence and Law was founded in 1992. Many ideas that are currently being commercially developed were first explored by AI & Law researchers, such as legal information retrieval, statistical analysis of legal data, automated con- tract drafting, automated processing of permit or welfare applications in public administration, and systems for regulatory compliance. Some particular topics of relevance to the focus of the workshop are: Open data, linked data, big data; e-Discovery; Legal argument mining; Automated contract drafting; Computable contracts; Decision support for legal, forensic and police practice; Computational law. Accepted papers (full, position and short) Sudhir Agarwal, Kevin Xu and John Moghtader 1 Toward Machine-Understandable Contracts Trevor Bench-Capon 9 Value-Based Reasoning and Norms Trevor Bench-Capon and Sanjay Modgil 18 Rules are Made to be Broken Floris Bex, Joeri Peters and Bas Testerink 22 A.I. for Online Criminal Complaints: from Natural Dialogues to Structured Scenarios Niels Netten, Susan van Den Braak, Sunil Choenni and Frans Leeuw 30 The Rise of Smart Justice: on the Role of AI in the Future of Legal Logistics Henry Prakken 34 On how AI & Law can Help Autonomous Systems Obey the Law: a Position Paper Livio Robaldo and Xin Sun 39 Reified Input/Output logic - a Position Paper Olga Shulayeva, Advaith Siddharthan and Adam Wyner 44 Recognizing Cited Facts and Principles in Legal Judgements Giovanni Sileno, Alexander Boer and Tom Van Engers 50 Reading Agendas Between the Lines, an Exercise Pieter Slootweg, Lloyd Rutledge, Lex Wedemeijer and Stef Joosten 57 The Implementation of Hohfeldian Legal Concepts with Semantic Web Technologies Robert van Doesburg, Tijs van der Storm and Tom van Engers 65 CALCULEMUS: Towards a Formal Language for the Interpretation of Normative Systems Marc van Opijnen and Cristiana Santos 70 On the Concept of Relevance in Legal Information Retrieval Bart Verheij 79 Formalizing Correct Evidential Reasoning with Arguments, Scenarios and Probabilities Invited speaker Karl Branting AI & Law from a Data-Centric Perspective Data-centric techniques are applicable both to extracting information latent in legal document collections and to finessing some of the central challenges con- fronting logical models, including the practical difficulties of formalizing legal rules in logic at scale and the mismatch between legal predicates and ordinary parlance. This talk surveys data-centric techniques and applications, distinguishes legal tasks amenable to these techniques from those requiring logic-based analysis, and de- scribes the rapidly growing commercial interest in these techniques. Program committee Kevin Ashley, University of Pittsburgh, USA Katie Atkinson, University of Liverpool, UK Trevor Bench-Capon, University of Liverpool, UK Karl Branting, The MITRE Corporation, USA Pompeu Casanovas, Universitat Autnoma de Barcelona, Spain; Deakin University, Australia Jack G. Conrad, Thomson Reuters, USA Enrico Francesconi, ITTIG-CNR, Italy Tom Gordon, Fraunhofer FOKUS, Germany Guido Governatori, NICTA, Australia Matthias Grabmair, Intelligent Systems Program, University of Pittsburgh, USA Jeroen Keppens, Kings College London, UK David Lewis, Chicago, USA Monica Palmirani, CIRSFID, Italy Dory Reiling, Court of Amsterdam, The Netherlands Erich Schweighofer, University of Vienna, Austria Jaap van den Herik, Leiden University, The Netherlands Serena Villata, INRIA Sophia Antipolis, France Radboud Winkels, University of Amsterdam, The Netherlands Adam Wyner, University of Aberdeen, UK Financial support International Association for Artificial Intelligence and Law (IAAIL) JURIX Foundation for Legal Knowledge Based Systems (JURIX) BNVKI BeNeLux Vereniging voor Kunstmatige Intelligentie (BNVKI) ALICE Institute for Artificial Intelligence and Cognitive Engineering (ALICE) Toward Machine-Understandable Contracts Sudhir Agarwal1 and Kevin Xu 2 and John Moghtader 3 Abstract. We present Contract Definition Langauge, a novel clients as the declarative nature is closer to the way domain knowl- approach for defining contracts declaratively in a machine- edge is specified. understandable way to achieve better comprehensibility and higher 3. Executable: Computable contracts are executable like procedu- efficiency of reasoning, analysis and execution of contracts through ral code. Thus, computable contracts do not need to be translated higher degree of automation and interoperability. The effect of rep- to programmed in a traditional programming language which re- resenting contracts with our Contract Definition Language is not duces costs and errors as there is not need to manage two separate only a significant reduction of legal transaction costs, but it also versions (one for humans, another for machines) of the same con- opens a variety of new options to create better contracts. As a tract. proof of concept, we also present our modeling of two US statutes 4. Interoperable: Computable contracts are interoperable in the (FERPA/SOPIPA/COPAA and HIPAA) as well as our prototypes for sense that they use shared vocabulary for referring to real world validity checking and hypothetical analysis of contracts according to objects, thus enabling automating reasoning over multiple differ- those statues. ent contracts that may have interdependencies or even conflicting terms. 1 Introduction In this paper, we present an approach for formulating, analyzing, and executing contracts more efficiently and effectively by enabling The conventional view is that the automation of contract creation, a high degree of automation. We introduce a Logic Programming execution, and compliance is beyond the capabilities of today’s tech- based Contract Definition Language (CDL). CDL makes possible au- nologies. This view stems from a longstanding tradition of contract- tomated reasoning over legal substance. We have identified the fol- ing practices, where all terms and conditions are expressed and inter- lowing four types of reasoning tasks with contracts: preted in natural language, often in obtuse, inaccessible legalese that 1. Validity Check: Validity checking determines whether a contract can only be deciphered by lawyers and judges. Many legal scholars satisfies all the constraints it must satisfy. For example, a marriage have called for more usable, interactive tools to make better sense of contract between an adult and a minor is invalid in most countries contracts [1, 4, 8, 11, 14]. Contract scholars have defined a need for because the law of the countries does not allow such contracts. user-facing tools that would make contracts more understandable and Constraints that need to be satisfied can be defined with CDL as actionable [4, 12], as well as a more modular and machine-readable well. approach to future contracting practices [3, 15, 16]. 2. Hypothetical Analysis: In many cases, a user (e.g. a legal pro- The impetus for the Computable Contracts research at Stanford 4, fessional, a client, a customer, an employee etc.) wishes to under- and Computational Law 5 more broadly, is a vision where computers, stand
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