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  1. Liberals and conservatives rely on different sets of moral foundations.Jesse Graham, Jonathan Haidt & Brian A. Nosek - 2009 - Journal of Personality and Social Psychology 96 (5):1029-1046.
    How and why do moral judgments vary across the political spectrum? To test moral foundations theory, the authors developed several ways to measure people’s use of 5 sets of moral intuitions: Harm/care, Fairness/reciprocity, Ingroup/loyalty, Authority/respect, and Purity/sanctity. Across 4 studies using multiple methods, liberals consistently showed greater endorsement and use of the Harm/care and Fairness/reciprocity foundations compared to the other 3 foundations, whereas conservatives endorsed and used the 5 foundations more equally. This difference was observed in abstract assessments of the (...)
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  • Mapping the moral domain.Jesse Graham, Brian A. Nosek, Jonathan Haidt, Ravi Iyer, Spassena Koleva & Peter H. Ditto - 2011 - Journal of Personality and Social Psychology 101 (2):366-385.
    The moral domain is broader than the empathy and justice concerns assessed by existing measures of moral competence, and it is not just a subset of the values assessed by value inventories. To fill the need for reliable and theoretically grounded measurement of the full range of moral concerns, we developed the Moral Foundations Questionnaire on the basis of a theoretical model of 5 universally available sets of moral intuitions: Harm/Care, Fairness/Reciprocity, Ingroup/Loyalty, Authority/Respect, and Purity/Sanctity. We present evidence for the (...)
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  • A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law. [REVIEW]Trevor Bench-Capon, Michał Araszkiewicz, Kevin Ashley, Katie Atkinson, Floris Bex, Filipe Borges, Daniele Bourcier, Paul Bourgine, Jack G. Conrad, Enrico Francesconi, Thomas F. Gordon, Guido Governatori, Jochen L. Leidner, David D. Lewis, Ronald P. Loui, L. Thorne McCarty, Henry Prakken, Frank Schilder, Erich Schweighofer, Paul Thompson, Alex Tyrrell, Bart Verheij, Douglas N. Walton & Adam Z. Wyner - 2012 - Artificial Intelligence and Law 20 (3):215-319.
    We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of the development of AI and Law, while often offering some personal reactions and reflections. As a whole, the subsections build into (...)
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  • The Emotional Dog and Its Rational Tail: A Social Intuitionist Approach to Moral Judgment.Jonathan Haidt - 2001 - Psychological Review 108 (4):814-834.
    Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done (...)
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  • Reasons as Defaults.John Horty - 2007 - Philosophers' Imprint 7:1-28.
    The goal of this paper is to frame a theory of reasons--what they are, how they support actions or conclusions--using the tools of default logic. After sketching the basic account of reasons as provided by defaults, I show how it can be elaborated to deal with two more complicated issues: first, situations in which the priority relation among defaults, and so reasons as well, is itself established through default reasoning; second, the treatment of undercutting defeat and exclusionary reasons. Finally, and (...)
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  • An improved factor based approach to precedential constraint.Adam Rigoni - 2015 - Artificial Intelligence and Law 23 (2):133-160.
    In this article I argue for rule-based, non-monotonic theories of common law judicial reasoning and improve upon one such theory offered by Horty and Bench-Capon. The improvements reveal some of the interconnections between formal theories of judicial reasoning and traditional issues within jurisprudence regarding the notions of the ratio decidendi and obiter dicta. Though I do not purport to resolve the long-standing jurisprudential issues here, it is beneficial for theorists both of legal philosophy and formalizing legal reasoning to see where (...)
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  • Automatically classifying case texts and predicting outcomes.Kevin D. Ashley & Stefanie Brüninghaus - 2009 - Artificial Intelligence and Law 17 (2):125-165.
    Work on a computer program called SMILE + IBP (SMart Index Learner Plus Issue-Based Prediction) bridges case-based reasoning and extracting information from texts. The program addresses a technologically challenging task that is also very relevant from a legal viewpoint: to extract information from textual descriptions of the facts of decided cases and apply that information to predict the outcomes of new cases. The program attempts to automatically classify textual descriptions of the facts of legal problems in terms of Factors, a (...)
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  • An empirical investigation of reasoning with legal cases through theory construction and application.Alison Chorley & Trevor Bench-Capon - 2005 - Artificial Intelligence and Law 13 (3-4):323-371.
    In recent years several proposals to view reasoning with legal cases as theory construction have been advanced. The most detailed of these is that of Bench-Capon and Sartor, which uses facts, rules, values and preferences to build a theory designed to explain the decisions in a set of cases. In this paper we describe CATE (CAse Theory Editor), a tool intended to support the construction of theories as described by Bench-Capon and Sartor, and which produces executable code corresponding to a (...)
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  • HYPO's legacy: introduction to the virtual special issue.T. J. M. Bench-Capon - 2017 - Artificial Intelligence and Law 25 (2):205-250.
    This paper is an introduction to a virtual special issue of AI and Law exploring the legacy of the influential HYPO system of Rissland and Ashley. The papers included are: Arguments and cases: An inevitable intertwining, BankXX: Supporting legal arguments through heuristic retrieval, Modelling reasoning with precedents in a formal dialogue Game, A note on dimensions and factors, An empirical investigation of reasoning with legal cases through theory construction and application, Automatically classifying case texts and predicting outcomes, A factor-based definition (...)
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  • Common-law judicial reasoning and analogy.Adam Rigoni - 2014 - Legal Theory 20 (2):133-156.
    Proponents of strict rule-based theories of judicial reasoning in common-law systems have offered a number of criticisms of analogical alternatives. I explain these criticisms and show that at best they apply equally well to rule-based theories. Further, I show how the analogical theories explain a feature of judicial common-law reasoningthat rule-based theories ignore. Finally, I show that reason-based, analogical theories of common-law judicial reasoning, such as those offered by John Horty and Grant Lamond, offer especially strong rejoinders to the rule-theorist (...)
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  • A model of legal reasoning with cases incorporating theories and values.Trevor Bench-Capon & Giovanni Sartor - 2003 - Artificial Intelligence 150 (1-2):97-143.
    Reasoning with cases has been a primary focus of those working in AI and law who have attempted to model legal reasoning. In this paper we put forward a formal model of reasoning with cases which captures many of the insights from that previous work. We begin by stating our view of reasoning with cases as a process of constructing, evaluating and applying a theory. Central to our model is a view of the relationship between cases, rules based on cases, (...)
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  • Rules and reasons in the theory of precedent.John F. Horty - 2011 - Legal Theory 17 (1):1-33.
    The doctrine of precedent, as it has evolved within the common law, has at its heart a form of reasoning—broadly speaking, alogic—according to which the decisions of earlier courts in particular cases somehow generalize to constrain the decisions of later courts facing different cases, while still allowing these later courts a degree of freedom in responding to fresh circumstances. Although the techniques for arguing on the basis of precedent are taught early on in law schools, mastered with relative ease, and (...)
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  • The missing link revisited: The role of teleology in representing legal argument. [REVIEW]T. J. M. Bench-Capon - 2002 - Artificial Intelligence and Law 10 (1-3):79-94.
    In this paper I recapitulate the ideas of Berman and Hafner (1993) regarding the role of teleology in legal argument. I show how these ideas can be used to address some issues arising from more recent work on legal argument, and how this relates to ideas associated with the New Rhetoric of Perelman. I illustrate the points with a discussion of the classic problem of which vehicles should be allowed in parks.
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  • A factor-based definition of precedential constraint.John F. Horty & Trevor J. M. Bench-Capon - 2012 - Artificial Intelligence and Law 20 (2):181-214.
    This paper describes one way in which a precise reason model of precedent could be developed, based on the general idea that courts are constrained to reach a decision that is consistent with the assessment of the balance of reasons made in relevant earlier decisions. The account provided here has the additional advantage of showing how this reason model can be reconciled with the traditional idea that precedential constraint involves rules, as long as these rules are taken to be defeasible. (...)
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  • Reasoning with dimensions and magnitudes.John Horty - 2019 - Artificial Intelligence and Law 27 (3):309-345.
    This paper shows how two models of precedential constraint can be broadened to include legal information represented through dimensions. I begin by describing a standard representation of legal cases based on boolean factors alone, and then reviewing two models of constraint developed within this standard setting. The first is the “result model”, supporting only a fortiori reasoning. The second is the “reason model”, supporting a richer notion of constraint, since it allows the reasons behind a court’s decisions to be taken (...)
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  • (1 other version)A note on dimensions and factors.Edwina L. Rissland & Kevin D. Ashley - 2002 - Artificial Intelligence and Law 10 (1-3):65-77.
    In this short note, we discuss several aspectsof dimensions and the related constructof factors. We concentrate on those aspectsthat are relevant to articles in this specialissue, especially those dealing with the analysisof the wild animal cases discussed inBerman and Hafner's 1993 ICAIL article. We reviewthe basic ideas about dimensions,as used in HYPO, and point out differences withfactors, as used in subsequent systemslike CATO. Our goal is to correct certainmisconceptions that have arisen over the years.
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