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277Evidence & decision making in the law: theoretical, computational and empirical approachesArtificial Intelligence and Law 28 (1): 1-5. 2020.
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200Evidential ReasoningIn G. Bongiovanni, Don Postema, A. Rotolo, G. Sartor, C. Valentini & D. Walton (eds.), Handbook in Legal Reasoning and Argumentation, Springer. pp. 447-493. 2011.The primary aim of this chapter is to explain the nature of evidential reasoning, the characteristic difficulties encountered, and the tools to address these difficulties. Our focus is on evidential reasoning in criminal cases. There is an extensive scholarly literature on these topics, and it is a secondary aim of the chapter to provide readers the means to find their way in historical and ongoing debates.
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157A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law (review)Artificial Intelligence and Law 20 (3): 215-319. 2012.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 a history of the l…Read more
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117Evaluating Arguments Based on Toulmin’s SchemeArgumentation 19 (3): 347-371. 2005.Toulmin’s scheme for the layout of arguments (1958, The Uses of Argument, Cambridge University Press, Cambridge) represents an influential tool for the analysis of arguments. The scheme enriches the traditional premises-conclusion model of arguments by distinguishing additional elements, like warrant, backing and rebuttal. The present paper contains a formal elaboration of Toulmin’s scheme, and extends it with a treatment of the formal evaluation of Toulmin-style arguments, which Toulmin did not…Read more
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115Solving a Murder Case by Asking Critical Questions: An Approach to Fact-Finding in Terms of Argumentation and Story Schemes (review)Argumentation 26 (3): 325-353. 2012.In this paper, we look at reasoning with evidence and facts in criminal cases. We show how this reasoning may be analysed in a dialectical way by means of critical questions that point to typical sources of doubt. We discuss critical questions about the evidential arguments adduced, about the narrative accounts of the facts considered, and about the way in which the arguments and narratives are connected in an analysis. Our treatment shows how two different types of knowledge, represented as sch…Read more
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104Dialectical argumentation with argumentation schemes: An approach to legal logic (review)Artificial Intelligence and Law 11 (2-3): 167-195. 2003.This paper describes an approach to legal logic based on the formal analysis of argumentation schemes. Argumentation schemes a notion borrowed from the .eld of argumentation theory - are a kind of generalized rules of inference, in the sense that they express that given certain premises a particular conclusion can be drawn. However, argumentation schemes need not concern strict, abstract, necessarily valid patterns of reasoning, but can be defeasible, concrete and contingently valid, i.e., valid…Read more
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91The Toulmin Model Today: Introduction to the Special Issue on Contemporary Work using Stephen Edelston Toulmin’s Layout of ArgumentsArgumentation 19 (3): 255-258. 2005.
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86How much does it help to know what she knows you know? An agent-based simulation studyArtificial Intelligence 200 (C): 67-92. 2013.
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75Strong admissibility for abstract dialectical frameworksArgument and Computation 13 (3): 249-289. 2022.dialectical frameworks have been introduced as a formalism for modeling argumentation allowing general logical satisfaction conditions and the relevant argument evaluation. Different criteria used to settle the acceptance of arguments are called semantics. Semantics of ADFs have so far mainly been defined based on the concept of admissibility. However, the notion of strongly admissible semantics studied for abstract argumentation frameworks has not yet been introduced for ADFs. In the current wo…Read more
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73Legal stories and the process of proofArtificial Intelligence and Law 21 (3): 253-278. 2013.In this paper, we continue our research on a hybrid narrative-argumentative approach to evidential reasoning in the law by showing the interaction between factual reasoning (providing a proof for ‘what happened’ in a case) and legal reasoning (making a decision based on the proof). First we extend the hybrid theory by making the connection with reasoning towards legal consequences. We then emphasise the role of legal stories (as opposed to the factual stories of the hybrid theory). Legal stories…Read more
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72Artificial intelligence as law (review)Artificial Intelligence and Law 28 (2): 181-206. 2020.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 g…Read more
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69In memoriam Douglas N. Walton: the influence of Doug Walton on AI and lawArtificial Intelligence and Law 28 (3): 281-326. 2020.Doug Walton, who died in January 2020, was a prolific author whose work in informal logic and argumentation had a profound influence on Artificial Intelligence, including Artificial Intelligence and Law. He was also very interested in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of the International Conference on AI and Law who have worked with him, describe his influence on their work.
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62A hybrid formal theory of arguments, stories and criminal evidenceArtificial Intelligence and Law 18 (2): 123-152. 2010.This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one story-based. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of an e…Read more
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58Proof with and without probabilities: Correct evidential reasoning with presumptive arguments, coherent hypotheses and degrees of uncertaintyArtificial Intelligence and Law 25 (1): 127-154. 2017.Evidential reasoning is hard, and errors can lead to miscarriages of justice with serious consequences. Analytic methods for the correct handling of evidence come in different styles, typically focusing on one of three tools: arguments, scenarios or probabilities. Recent research used Bayesian networks for connecting arguments, scenarios, and probabilities. Well-known issues with Bayesian networks were encountered: More numbers are needed than are available, and there is a risk of misinterpretat…Read more
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54Douglas Walton: Argument Evaluation and Evidence: Springer, 2016, 286 pp (review)Argumentation 32 (2): 301-307. 2018.
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52Introduction to the special issue on Artificial Intelligence for JusticeArtificial Intelligence and Law 25 (1): 1-3. 2017.
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48A method for explaining Bayesian networks for legal evidence with scenariosArtificial Intelligence and Law 24 (3): 285-324. 2016.In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In this paper we propose a combination of two approaches, combining Bayesian networks with scenarios. Whereas a Bayesian network is a popular tool for an…Read more
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45An integrated view on rules and principlesArtificial Intelligence and Law 6 (1): 3-26. 1998.In the law, it is generally acknowledged that there are intuitive differences between reasoning with rules and reasoning with principles. For instance, a rule seems to lead directly to its conclusion if its condition is satisfied, while a principle seems to lead merely to a reason for its conclusion. However, the implications of these intuitive differences for the logical status of rules and principles remain controversial.A radical opinion has been put forward by Dworkin (1978). The intuitive d…Read more
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45Building Bayesian networks for legal evidence with narratives: a case study evaluationArtificial Intelligence and Law 22 (4): 375-421. 2014.In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge or jury. In previous work, techniques were proposed to represent narratives in a Bayesian network and to use narratives as a basis for systematizing th…Read more
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42Thirty years of Artificial Intelligence and Law: the first decade (review)Artificial Intelligence and Law 30 (4): 481-519. 2022.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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39Henry Prakken (1997). Logical tools for modelling legal argument. A study of defeasible reasoning in lawArtificial Intelligence and Law 8 (1): 35-65. 2000.
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37Research in progress: report on the ICAIL 2017 doctoral consortiumArtificial Intelligence and Law 26 (1): 49-97. 2018.This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences.
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33Jumping to ConclusionsIn Luis Farinas del Cerro, Andreas Herzig & Jerome Mengin (eds.), Logics in Artificial Intelligence, Springer. pp. 411--423. 2012.
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32On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games: 25 years laterArgument and Computation 11 (1-2): 1-14. 2020.
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31Douglas Walton, the new dialectic. Conversational contexts of argument. Toronto: University of toronto press (book review) (review)Artificial Intelligence and Law 9 (4): 305-313. 2001.
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25Analyzing the Simonshaven Case With and Without ProbabilitiesTopics in Cognitive Science 12 (4): 1175-1199. 2020.This paper is one in a series of rational analyses of the Dutch Simonshaven case, each using a different theoretical perspective. The theoretical perspectives discussed in the literature typically use arguments, scenarios, and probabilities, in various combinations. The theoretical perspective on evidential reasoning used in this paper has been designed to connect arguments, scenarios, and probabilities in a single formal modeling approach, in an attempt to investigate bridges between qualitativ…Read more
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21Argument & Computation Community Resources cornerArgument and Computation 10 (2): 105-105. 2019.
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18Book review: The dynamics of judicial proof. Computation, logic, and common sense (review)Artificial Intelligence and Law 11 (4): 299-303. 2003.