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  1. 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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  • How to justify a backing’s eligibility for a warrant: the justification of a legal interpretation in a hard case.Shiyang Yu & Xi Chen - 2023 - Artificial Intelligence and Law 31 (2):239-268.
    The Toulmin model has been proved useful in law and argumentation theory. This model describes the basic process in justifying a claim, which comprises six elements, i.e., claim (C), data (D), warrant (W), backing (B), qualifier (Q), and rebuttal (R). Specifically, in justifying a claim, one must put forward ‘data’ and a ‘warrant’, whereas the latter is authorized by ‘backing’. The force of the ‘claim’ being justified is represented by the ‘qualifier’, and the condition under which the claim cannot be (...)
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  • Teleological Justification of Argumentation Schemes.Douglas Walton & Giovanni Sartor - 2013 - Argumentation 27 (2):111-142.
    Argumentation schemes are forms of reasoning that are fallible but correctable within a self-correcting framework. Their use provides a basis for taking rational action or for reasonably accepting a conclusion as a tentative hypothesis, but they are not deductively valid. We argue that teleological reasoning can provide the basis for justifying the use of argument schemes both in monological and dialogical reasoning. We consider how such a teleological justification, besides being inspired by the aim of directing a bounded cognizer to (...)
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  • Jumping to a Conclusion: Fallacies and Standards of Proof.Douglas Walton & Thomas F. Gordon - 2009 - Informal Logic 29 (2):215-243.
    Five errors that fit under the category of jumping to a conclusion are identified: (1) arguing from premises that are insufficient as evidence to prove a conclusion (2) fallacious argument from ignorance, (3) arguing to a wrong conclusion, (4) using defeasible reasoning without being open to exceptions, and (5) overlooking/suppressing evidence. It is shown that jumping to a conclusion is best seen not as a fallacy itself, but as a more general category of faulty argumentation pattern underlying these errors and (...)
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  • Henry Prakken (1997). Logical tools for modelling legal argument. A study of defeasible reasoning in law.Bart Verheij - 2000 - Artificial Intelligence and Law 8 (1):35-65.
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  • Relating Carneades with abstract argumentation via the ASPIC+ framework for structured argumentation.Bas van Gijzel & Henry Prakken - 2012 - Argument and Computation 3 (1):21 - 47.
    Carneades is a recently proposed formalism for structured argumentation with varying proof standards, inspired by legal reasoning, but more generally applicable. Its distinctive feature is that each statement can be given its own proof standard, which is claimed to allow a more natural account of reasoning under burden of proof than existing formalisms for structured argumentation, in which proof standards are defined globally. In this article, the two formalisms are formally related by translating Carneades into the ASPIC+ framework for structured (...)
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  • Digital technologies and artificial intelligence’s present and foreseeable impact on lawyering, judging, policing and law enforcement.Ephraim Nissan - 2017 - AI and Society 32 (3):441-464.
    ‘AI & Law’ research has been around since the 1970s, even though with shifting emphasis. This is an overview of the contributions of digital technologies, both artificial intelligence and non-AI smart tools, to both the legal professions and the police. For example, we briefly consider text mining and case-automated summarization, tools supporting argumentation, tools concerning sentencing based on the technique of case-based reasoning, the role of abductive reasoning, research into applying AI to legal evidence, tools for fighting crime and tools (...)
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  • Dialectical models in artificial intelligence and law.Jaap Hage - 2000 - Artificial Intelligence and Law 8 (2-3):137-172.
    Dialogues and dialectics have come to playan important role in the field of ArtificialIntelligence and Law. This paper describes thelegal-theoretical and logical background of this role,and discusses the different services into whichdialogues are put. These services include:characterising logical operators, modelling thedefeasibility of legal reasoning, providing the basisfor legal justification and identifying legal issues,and establishing the law in concrete cases. Specialattention is given to the requirements oflaw-establishing dialogues.
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  • Comparing alternatives in the law.Jaap Hage - 2004 - Artificial Intelligence and Law 12 (3):181-225.
    This paper argues the thesis that a particular style of reasoning, qualitative comparative reasoning (QCR), plays a role in at least three areas of legal reasoning that are central in AI and law research, namely legal theory construction, case-based reasoning in the form of case comparison, and legal proof. The paper gives an informal exposition of one particular way to deal with QCR, based on the author’s previous work on reason-based logic (RBL). Then it contains a substantially adapted formalisation of (...)
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  • Assessing debate strategies via computational agents.Alec Grierson, David Moore & Tangming Yuan - 2010 - Argument and Computation 1 (3):215-248.
    This paper reports our research concerning dialogue strategies suitable for adoption by a human-computer debating system. We propose a set of strategic heuristics for a computer to adopt to enable it to function as a dialogue participant. In particular, we consider means of assessing the proposed strategy. A system involving two agents in dialogue with each other and a human-agent debate system are constructed and subsequently used to facilitate the evaluations. The evaluations suggest that the proposed strategy can enable the (...)
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  • The Carneades model of argument and burden of proof.Thomas F. Gordon, Henry Prakken & Douglas Walton - 2007 - Artificial Intelligence 171 (10-15):875-896.
    We present a formal, mathematical model of argument structure and evaluation, taking seriously the procedural and dialogical aspects of argumentation. The model applies proof standards to determine the acceptability of statements on an issue-by-issue basis. The model uses different types of premises (ordinary premises, assumptions and exceptions) and information about the dialectical status of statements (stated, questioned, accepted or rejected) to allow the burden of proof to be allocated to the proponent or the respondent, as appropriate, for each premise separately. (...)
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  • Introduction: Dialectical legal argument: Formal and informal models. [REVIEW]Eveline Feteris & Henry Prakken - 2000 - Artificial Intelligence and Law 8 (2-3):107-113.
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  • Law, logic, rhetoric: A procedural model of legal argumentation.Arno R. Lodder - 2004 - In S. Rahman (ed.), Logic, Epistemology, and the Unity of Science. Dordrecht: Kluwer Academic Publishers. pp. 569--588.
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