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  1. Modeling the Evolution of Legal Discretion. An Artificial Intelligence Approach.Ruth Kannai, Uri Schild & John Zeleznikow - 2007 - Ratio Juris 20 (4):530-558.
    Much legal research focuses on understanding how judicial decision-makers exercise their discretion. In this paper we examine the notion of legal or judicial discretion, and weaker and stronger forms of discretion. At all times our goal is to build cognitive models of the exercise of discretion, with a view to building computer software to model and primarily support decision-making. We observe that discretionary decision-making can best be modeled using three independent axes: bounded and unbounded, defined and undefined, and binary and (...)
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  • Integrating induction and deduction for finding evidence of discrimination.Salvatore Ruggieri, Dino Pedreschi & Franco Turini - 2010 - Artificial Intelligence and Law 18 (1):1-43.
    We present a reference model for finding evidence of discrimination in datasets of historical decision records in socially sensitive tasks, including access to credit, mortgage, insurance, labor market and other benefits. We formalize the process of direct and indirect discrimination discovery in a rule-based framework, by modelling protected-by-law groups, such as minorities or disadvantaged segments, and contexts where discrimination occurs. Classification rules, extracted from the historical records, allow for unveiling contexts of unlawful discrimination, where the degree of burden over protected-by-law (...)
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  • Intelligent Computer Evaluation of Offender’s Previous Record.Uri J. Schild & Ruth Kannai - 2005 - Artificial Intelligence and Law 13 (3-4):373-405.
    This paper considers the problem of how to evaluate an offender’s criminal record. This evaluation is part of the sentencing process carried out by a judge, and may be complicated in the case of offenders with a heavy record. We give a comprehensive overview of the approach to an offender’s past record in various (Western) countries, considering the two major approaches: desert-based and utilitarian. The paper describes the determination of the parameters involved in the evaluation, and the construction of a (...)
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  • An australian perspective on research and development required for the construction of applied legal decision support systems.John Zeleznikow - 2002 - Artificial Intelligence and Law 10 (4):237-260.
    At the Donald Berman Laboratory for Information Technology and Law, La TrobeUniversity Australia, we have been building legal decision support systems for a dozenyears. Whilst most of our energy has been devoted to conducting research in ArtificialIntelligence and Law, over the past few years we have increasingly focused uponbuilding legal decision support systems that have a commercial focus.In this paper we discuss the evolution of our systems. We begin with a discussion ofrule-based systems and discuss the transition to hybrid rule-based/case-based (...)
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  • Developing negotiation decision support systems that support mediators: A case study of the family_winner system. [REVIEW]Emilia Bellucci & John Zeleznikow - 2005 - Artificial Intelligence and Law 13 (2):233-271.
    Negotiation Support Systems have traditionally modelled the process of negotiation. They often rely on mathematical optimisation techniques and ignore heuristics and other methods derived from practice. Our goal is to develop systems capable of decision support to help resolve a given dispute. A system we have constructed, Family_Winner, uses empirical evidence to dynamically modify initial preferences throughout the negotiation process. It sequentially allocates issues using trade-offs and compensation opportunities inherent in the dispute.
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  • Arguing on the Toulmin Model: New Essays in Argument Analysis and Evaluation.David Hitchcock & Bart Verheij (eds.) - 2006 - Dordrecht, Netherland: Springer.
    In The Uses of Argument, Stephen Toulmin proposed a model for the layout of arguments: claim, data, warrant, qualifier, rebuttal, backing. Since then, Toulmin’s model has been appropriated, adapted and extended by researchers in speech communications, philosophy and artificial intelligence. This book assembles the best contemporary reflection in these fields, extending or challenging Toulmin’s ideas in ways that make fresh contributions to the theory of analysing and evaluating arguments.
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  • Artificial intelligence as law. [REVIEW]Bart Verheij - 2020 - Artificial Intelligence and Law 28 (2):181-206.
    Information technology is so ubiquitous and AI’s progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be (...)
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  • Neural Networks in Legal Theory.Vadim Verenich - 2024 - Studia Humana 13 (3):41-51.
    This article explores the domain of legal analysis and its methodologies, emphasising the significance of generalisation in legal systems. It discusses the process of generalisation in relation to legal concepts and the development of ideal concepts that form the foundation of law. The article examines the role of logical induction and its similarities with semantic generalisation, highlighting their importance in legal decision-making. It also critiques the formal-deductive approach in legal practice and advocates for more adaptable models, incorporating fuzzy logic, non-monotonic (...)
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  • Thirty years of Artificial Intelligence and Law: Editor’s Introduction.Trevor Bench-Capon - 2022 - Artificial Intelligence and Law 30 (4):475-479.
    The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This special issue marks the 30th anniversary of the journal by reviewing the progress of the field through thirty commentaries on landmark papers and groups of papers from that journal.
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  • Thirty years of Artificial Intelligence and Law: the first decade. [REVIEW]Guido Governatori, Trevor Bench-Capon, Bart Verheij, Michał Araszkiewicz, Enrico Francesconi & Matthias Grabmair - 2022 - Artificial Intelligence and Law 30 (4):481-519.
    The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper provides commentaries on landmark papers from the first decade of that journal. The topics discussed include reasoning with cases, argumentation, normative reasoning, dialogue, representing legal knowledge and neural networks.
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  • Thirty years of artificial intelligence and law: the third decade.Serena Villata, Michal Araszkiewicz, Kevin Ashley, Trevor Bench-Capon, L. Karl Branting, Jack G. Conrad & Adam Wyner - 2022 - Artificial Intelligence and Law 30 (4):561-591.
    The first issue of Artificial Intelligence and Law journal was published in 1992. This paper offers some commentaries on papers drawn from the Journal’s third decade. They indicate a major shift within Artificial Intelligence, both generally and in AI and Law: away from symbolic techniques to those based on Machine Learning approaches, especially those based on Natural Language texts rather than feature sets. Eight papers are discussed: two concern the management and use of documents available on the World Wide Web, (...)
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  • Toulmin-based computational modelling of judicial discretion in sentencing.Andrew Vincent & John Zaleznikow - unknown
    A number of increasingly sophisticated technologies are now being used to support complex decision-making in a range of contexts. This paper reports on work undertaken to provide decision support in the discretionary domain of sentencing by referring to a recently created Toulmin argument based model that involves the interplay and weighting of relevant rule-based and discretionary factors used in a decisional process. Judicial discretion, particularly in the sentencing phase, is one of the mainstays of justice systems that favour individualised justice. (...)
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  • Using Toulmin Argumentation to develop an Online Dispute Resolution Environment.John Zeleznikow - unknown
    Our goal is to model reasoning in discretionary legal domains. To do so, we use Knowledge Discovery from Database Techniques. However there are obstacles to this approach, including difficulties in generating explanations once conclusions have been inferred, difficulties associated with the collection of sufficient data from past cases and difficulties associated with integrating two vastly different paradigms. Toulmin’s treatise on the uses of argument can be gainfully employed to construct legal decision support systems in discretionary domains. We show how we (...)
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  • Deliberative discourse and reasoning from generic argument structures.John L. Yearwood & Andrew Stranieri - 2009 - AI and Society 23 (3):353-377.
    In this article a dialectical model for practical reasoning within a community, based on the Generic/Actual Argument Model (GAAM) is advanced and its application to deliberative dialogue discussed. The GAAM, offers a dynamic template for structuring knowledge within a domain of discourse that is connected to and regulated by a community. The paper demonstrates how the community accepted generic argument structure acts to normatively influence both admissible reasoning and the progression of dialectical reasoning between participants. It is further demonstrated that (...)
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  • Book Review. [REVIEW]Paul Huygen - 2006 - Artificial Intelligence and Law 14 (1-2):143-150.
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