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 last quarter century of the field, and provide some insights into where it has come from, where it is now, and where it might go. (shrink)

We propose simple nonlinear mathematical models for the legal concept of balancing of interests. Our aim is to bridge the gap between an abstract formalisation of a balancing decision while assuring consistency and ultimately legal certainty across cases. We focus on the conflict between the rights to privacy and to the protection of personal data in Art. 7 and Art. 8 of the EU Charter of Fundamental Rights (EUCh) against the right of access to information derived from Art. 11 EUCh. (...) These competing rights are denoted by ( \(i_1\) ) _right to privacy _ and ( \(i_2\) ) _access to information_; mathematically, their indices are respectively assigned by \(u_1\in [0,1]\) and \(u_2\in [0,1]\) subject to the constraint \(u_1+u_2=1\). This constraint allows us to use one single index _u_ to resolve the conflict through balancing. The outcome will be concluded by comparing the index _u_ with a prior given threshold \(u_0\). For simplicity, we assume that the balancing depends on only selected legal criteria such as the social status of affected person, and the sphere from which the information originated, which are represented as inputs of the models, called legal parameters. Additionally, we take “time” into consideration as a legal criterion, building on the European Court of Justice’s ruling on the right to be forgotten: by considering time as a legal parameter, we model how the outcome of the balancing changes over the passage of time. To catch the dependence of the outcome _u_ by these criteria as legal parameters, data were created by a fully-qualified lawyer. By comparison to other approaches based on machine learning, especially neural networks, this approach requires significantly less data. This might come at the price of higher abstraction and simplification, but also provides for higher transparency and explainability. Two mathematical models for _u_, a time-independent model and a time-dependent model, are proposed, that are fitted by using the data. (shrink)

The article considers two different interpretations of the reason model of precedent pioneered by John Horty. On a plausible interpretation of the reason model, past cases provide reasons to prioritize reasons favouring the same outcome as a past case over reasons favouring the opposing outcome. Here I consider the merits of this approach to the role of precedent in legal reasoning in comparison with a closely related view favoured by some legal theorists, according to which past cases provide reasons for (...) undercutting (or ‘excluding’) reasons favouring the opposing outcome. After embedding both accounts within a general default logic, I note some important differences between the two approaches that emerge as a result of plausible distinctions between rebutting and undercutting defeat in formal models of legal reasoning. These differences stem from the ‘preference independence’ of undercutting defeat. Undercutting reasons succeed in defeating opposing reasons irrespective of their relative strength. As a result, the two accounts differ in their account of the way in which precedents constrain judicial reasoning. I conclude by suggesting that the two approaches can be integrated within a single model, in which the distinction between undercutting and rebutting defeat is used to account for the distinction between strict and persuasive forms of precedential constraint. (shrink)

There are many benefits of using argumentation-based techniques in multi-agent systems, as clearly shown in the literature. Such benefits come not only from the expressiveness that argumentation-based techniques bring to agent communication but also from the reasoning and decision-making capabilities under conditions of conflicting and uncertain information that argumentation enables for autonomous agents. When developing multi-agent applications in which argumentation will be used to improve agent communication and reasoning, argumentation schemes are useful in addressing the requirements of the application domain (...) in regards to argumentation. In this work, we propose an argumentation framework that takes into account the particular structure of argumentation schemes at its core. This paper formally defines such a framework and experimentally evaluates its implementation for both argumentation-based reasoning and dialogues. (shrink)

In this paper we describe the impact that Walton’s conception of argumentation schemes had on AI and Law research. We will discuss developments in argumentation in AI and Law before Walton’s schemes became known in that community, and the issues that were current in that work. We will then show how Walton’s schemes provided a means of addressing all of those issues, and so supplied a unifying perspective from which to view argumentation in AI and Law.

The standard model of precedential constraint holds that a court is equally free to modify a precedent of its own and a precedent of a superior court—overruling aside, it does not differentiate horizontal and vertical precedents. This paper shows that no model can capture the U.S. doctrine of precedent without making that distinction. A precise model is then developed that does just that. This requires situating precedent cases in a formal representation of a hierarchical legal structure, and adjusting the constraint (...) that a precedent imposes based on the relationship of the precedent court and the instant court. The paper closes with suggestions for further improvements of the model. (shrink)

Autonomous vehicles are one of the most spectacular recent developments of Artificial Intelligence. Among the problems that still need to be solved before they can fully autonomously participate in traffic is the one of making their behaviour conform to the traffic laws. This paper discusses this problem by way of a case study of Dutch traffic law. First it is discussed to what extent Dutch traffic law exhibits features that are traditionally said to pose challenges for AI & Law models, (...) such as exceptions, rule conflicts, open texture and vagueness, rule change, and the need for commonsense knowledge. Then three approaches to the design of law-conforming AV are evaluated in light of the challenges posed by Dutch traffic law, which includes an assessment of the usefulness of AI & Law models of nonmonotonic reasoning, argumentation and case-based reasoning. (shrink)

In this paper we consider persuasion in the context of practical reasoning, and discuss the problems associated with construing reasoning about actions in a manner similar to reasoning about beliefs. We propose a perspective on practical reasoning as presumptive justification of a course of action, along with critical questions of this justification, building on the account of Walton. From this perspective, we articulate an interaction protocol, which we call PARMA, for dialogues over proposed actions based on this theory. We outline (...) an axiomatic semantics for the PARMA Protocol, and discuss two implementations which use this protocol to mediate a discussion between humans. We then show how our proposal can be made computational within the framework of agents based on the Belief-Desire-Intention model, and illustrate this proposal with an example debate within a multi agent system. (shrink)

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 (...) the two projects interact. (shrink)

This paper examines the concept of coherence and its role in legal reasoning. First, it identifies some problem areas confronting coherence theories of legal reasoning about both disputed questions of fact and disputed questions of law. Second, with a view to solving these problems, it proposes a coherence model of legal reasoning. The main tenet of this coherence model is that a belief about the law and the facts under dispute is justified if it is “optimally coherent,” that is, if (...) it is such that an epistemically responsible legal decision-maker would have accepted it as justified by virtue of its coherence in like circumstances. Last, looking beyond the coherence theory, the paper explores the implications of the version of legal coherentism proposed for a general theory of legal reasoning and rationality. (shrink)

We present an argument-based formalism of contract dispute resolution following a modern view that the court would resolve a contract dispute by enforcing an interpretation of contract that reasonably represents the mutual intention of contract parties. Legal doctrines provide principles, rules and guidelines for the court to objectively arrive at such an interpretation. In this paper, we establish the appropriateness of the formalism by applying it to resolve disputes about performance relief with the legal doctrines of impossibility and frustration of (...) purpose in common laws of contract. The formalism is based on modular argumentation, a recently proposed extension of assumption-based argumentation for modelling contract dispute resolution. (shrink)

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 (...) set of classification concepts that capture stereotypical fact patterns that effect the strength of a legal claim, here trade secret misappropriation. Using these classifications, the program can evaluate and explain predictions about a problem’s outcome given a database of previously classified cases. This paper provides an extended example illustrating both functions, prediction by IBP and text classification by SMILE, and reports empirical evaluations of each. While IBP’s results are quite strong, and SMILE’s much weaker, SMILE + IBP still has some success predicting and explaining the outcomes of case scenarios input as texts. It marks the first time to our knowledge that a program can reason automatically about legal case texts. (shrink)

To create a programming environment for contract dispute resolution, we propose an extension of assumption-based argumentation into modular assumption-based argumentation in which different modules of argumentation representing different knowledge bases for reasoning about beliefs and facts and for representation and reasoning with the legal doctrines could be built and assembled together. A distinct novel feature of modular argumentation in compare with other modular logic-based systems like Prolog is that it allows references to different semantics in the same module at the (...) same time, a feature critically important for application of argumentation in legal domains like contract dispute resolution where the outcomes of court cases often depend on whether credulous or skeptical modes of reasoning were applied by the contract parties. We apply the new framework to model the doctrines of contract breach and mutual mistake. (shrink)

The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation LCBR. Ontologies for different systems allows comparison and contrast between them. OWL ontologies are standardised, machine-readable formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and to LCBR are discussed. Two LCBR systems (...) (AS-CATO, which is based on CATO, and IBP) are analysed in terms of basic and intermediate concepts. Central components of the OWL ontologies for these systems are presented, pointing out differences and similarities. The main novelty of the paper is the ontological analysis and representation in OWL of LCBR systems. The paper also emphasises the important issues concerning the representation and reasoning of intermediate concepts. (shrink)

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 in certain contexts or under certain (...) circumstances. A method is presented to analyze argumentation schemes and it is shown how argumentation schemes can be embedded in a formal model of dialectical argumentation. (shrink)

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 (...) theory. CATE has been used in a series of experiments intended to explore a number of issues relating to such theories, including how the theories should be constructed, how sets of values should be compared, and the representation of cases using structured values as opposed to factors. (shrink)

In this paper we apply a general account of practical reasoning to arguing about legal cases. In particular, we provide a reconstruction of the reasoning of the majority and dissenting opinions for a particular well-known case from property law. This is done through the use of Belief-Desire-Intention (BDI) agents to replicate the contrasting views involved in the actual decision. This reconstruction suggests that the reasoning involved can be separated into three distinct levels: factual and normative levels and a level connecting (...) the two, with conclusions at one level forming premises at the next. We begin by summarising our general approach, which uses instantiations of an argumentation scheme to provide presumptive justifications for actions, and critical questions to identify arguments which attack these justifications. These arguments and attacks are organised into argumentation frameworks to identify the status of individual arguments. We then discuss the levels of reasoning that occur in this reconstruction and the properties and significance of each of these levels. We illustrate the different levels with short examples and also include a discussion of the role of precedents within these levels of reasoning. (shrink)

This paper gives an account of dimensions in the reason model found in Horty : 1–33, 2011), Horty and Bench-Capon and Rigoni :133–160, 2015. doi: 10.1007/s10506-015-9166-x). The account is constructed with the purpose of rectifying problems with the approach to incorporating dimensions in Horty, namely, the problems arising from the collapse of the distinction between the reason model and the result model on that approach. Examination of the newly constructed theory revealed that the importance of dimensions in the reason model (...) lies in their ability to establish weighings between reasons/factors of the same polarity. This permits past cases to constrain future cases in ways they could not on the reason model with just factors. The paper then discusses how dimensions might be established from a case base and how dimensions that are incomplete in various aspects might be dealt with in the theory. It closes with comparisons to other work in the literature on AI and Law and suggestions for further improvement of the reason model. (shrink)

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 (...) of precedential constraint and An improved factor based approach to precedential constraint. After describing HYPO, in this introduction to the special issue I look at various aspects of its influence on AI and Law: the developments led by Rissland at Amherst; the developments led by Ashley in Pittsburgh; the expression of these ideas in terms of rule based systems, and their subsequent formalisation; value based theories, which were inspired by a critique of HYPO; and contemporary approaches which revive the idea of dimensions. (shrink)

The thesis of the paper holds that some future developments of argumentation theory may be inspired by the rich logico-methodological legacy of the Lvov–Warsaw School (LWS), the Polish research movement that was most active from 1895 to 1939. As a selection of ideas of the LWS which exploit both formal and pragmatic aspects of the force of argument, we present: Ajdukiewicz’s account of reasoning and inference, Bocheński’s analyses of superstitions or dogmas, and Frydman’s constructive approach to legal interpretation. This paper (...) does not aim at exhaustive elaboration of any of these topics or their usefulness in current discussions within argumentation theory. Rather, we intend to indicate chosen directions of a potentially fruitful research program for the emerging Polish School of Argumentation which would consist in application of methods and conceptions elaborated by the LWS to selected open problems of contemporary research on argumentation. (shrink)

This paper studies the use of hypothetical and value-based reasoning in US Supreme-Court cases concerning the United States Fourth Amendment. Drawing upon formal AI & Law models of legal argument a semi-formal reconstruction is given of parts of the Carney case, which has been studied previously in AI & law research on case-based reasoning. As part of the reconstruction, a semi-formal proposal is made for extending the formal AI & Law models with forms of metalevel reasoning in several argument schemes. (...) The result is compared with Rissland’s (1989) analysis in terms of dimensions and Ashley’s (2008) analysis in terms of his process model of legal argument with hypotheticals. (shrink)

This paper studies how legal choices, and in particular legislative determinations, need to consider multiple rights and values, and can be assessed accordingly. First it is argued that legal norms (and in particular constitutional right-norms) often prescribe the pursuit of goals, which may be in conflict one with another. Then a model of teleological reasoning is brought to bear on choices affecting different goals, among which those prescribed by constitutional norms. An analytical framework is provided for evaluating such choices with (...) regard to possible alternatives. The assessment of legislative choices according to proportionality is then considered, and is modelled using the provided analytical framework. Finally, the framework is expanded to include the ideas of reasonableness and institutional deference, and the corresponding margins of appreciation. (shrink)

The paper identifies some of the problems with legal systems and outlines the potential of AI technology for overcoming them. For expository purposes, this outline is based on a simplified epistemology of the primary functions of law. Social and philosophical impediments from the side of the legal community to taking advantage of the potential of this technology are discussed and strategic recommendations are given.

This paper argues that formal models of coherence are useful for constructing a legal epistemology. Two main formal approaches to coherence are examined: coherence-based models of belief revision and the theory of coherence as constraint satisfaction. It is shown that these approaches shed light on central aspects of a coherentist legal epistemology, such as the concept of coherence, the dynamics of coherentist justification in law, and the mechanisms whereby coherence may be built in the course of legal decision-making.

This paper proposes a formal top-level model of explaining the outputs of machine-learning-based decision-making applications and evaluates it experimentally with three data sets. The model draws on AI & law research on argumentation with cases, which models how lawyers draw analogies to past cases and discuss their relevant similarities and differences in terms of relevant factors and dimensions in the problem domain. A case-based approach is natural since the input data of machine-learning applications can be seen as cases. While the (...) approach is motivated by legal decision making, it also applies to other kinds of decision making, such as commercial decisions about loan applications or employee hiring, as long as the outcome is binary and the input conforms to this paper’s factor- or dimension format. The model is top-level in that it can be extended with more refined accounts of similarities and differences between cases. It is shown to overcome several limitations of similar argumentation-based explanation models, which only have binary features and do not represent the tendency of features towards particular outcomes. The results of the experimental evaluation studies indicate that the model may be feasible in practice, but that further development and experimentation is needed to confirm its usefulness as an explanation model. Main challenges here are selecting from a large number of possible explanations, reducing the number of features in the explanations and adding more meaningful information to them. It also remains to be investigated how suitable our approach is for explaining non-linear models. (shrink)

The paper provides an OWL ontology for legal cases with an instantiation of the legal case Popov v. Hayashi. The ontology makes explicit the conceptual knowledge of the legal case domain, supports reasoning about the domain, and can be used to annotate the text of cases, which in turn can be used to populate the ontology. A populated ontology is a case base which can be used for information retrieval, information extraction, and case based reasoning. The ontology contains not only (...) elements for indexing the case (e.g. the parties, jurisdiction, and date), but as well elements used to reason to a decision such as argument schemes and the components input to the schemes. We use the Protégé ontology editor and knowledge acquisition system, current guidelines for ontology development, and tools for visual and linguistic presentation of the ontology. (shrink)

The South China Sea territorial dispute has been a contentious issue in the international community. In the course of 3 years, China and the Philippines had undergone arbitral proceedings over the maritime rights and entitlements in the South China Sea. As the Permanent Court of Arbitration reached its decision, this paper aims to examine the interpretation process of the Arbitral Tribunal in the judgment of the South China Sea conflict between China and the Philippines. The primary objective of the study (...) is to reconstruct or explain how the Tribunal came up with its interpretation of the written arguments presented by the parties involved and to distinguish whether such reconstruction the Tribunal has successfully interpreted or made sense of the said arguments and submissions. Doing so would necessitate a pragmatic analysis– the relevance-theoretic account of human communication and cognition. Data analyzed include written submissions and arguments as well as the legal documents used during the arbitral process. Using content analysis, the data were evaluated through applying the tool of interpretation based on the criteria set by the three conditions of the relevance theory: logical condition, pragmatic condition, and condition of optimal relevance. This paper argues that in order for the addressee of an utterance, in this case the Arbitral Tribunal, to attain a successful interpretation, it should meet these three conditions. This study found that the reconstruction of the interpretation based on the three conditions showed that the Tribunal had attained a valid and correct interpretation of the Philippines’ and China’s arguments. Furthermore, the paper asserts that implied conclusion and the contextual assumptions can be a guiding principle for the cognitive comprehension or interpretation of legal texts. (shrink)

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.

This paper presents a methodology to design and implement programs intended to decide cases, described as sets of factors, according to a theory of a particular domain based on a set of precedent cases relating to that domain. We useDialectical Frameworks, a recent development in AI knowledge representation, as the central feature of our design method. ADFs will play a role akin to that played by Entity–Relationship models in the design of database systems. First, we explain how the factor hierarchy (...) of the well-known legal reasoning system CATO can be used to instantiate an ADF for the domain of US Trade Secrets. This is intended to demonstrate the suitability of ADFs for expressing the design of legal cased based systems. The method is then applied to two other legal domains often used in the literature of AI and Law. In each domain, the design is provided by the domain analyst expressing the cases in terms of factors organised into an ADF from which an executable program can be implemented in a straightforward way by taking advantage of the closeness of the acceptance conditions of the ADF to components of an executable program. We evaluate the ease of implementation, the performance and efficacy of the resulting program, ease of refinement of the program and the transparency of the reasoning. This evaluation suggests ways in which factor based systems, which are limited by taking as their starting point the representation of cases as sets of factors and so abstracting away the particular facts, can be extended to address open issues in AI and Law by incorporating the case facts to improve the decision, and by considering justification and reasoning using portion of precedents. (shrink)

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. (...) The account presented is firmly based on a body of work that has emerged in AI and Law. This work is discussed, and there is a particular discussion of approaches based on theory construction, and how that work relates to the model described in this paper. (shrink)

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 (...) good for us. But how to establish proper safeguards for AI? One strong answer readily available is: consider the problems and solutions studied in AI & Law. AI & Law has worked on the design of social, explainable, responsible AI aligned with human values for decades already, AI & Law addresses the hardest problems across the breadth of AI (in reasoning, knowledge, learning and language), and AI & Law inspires new solutions (argumentation, schemes and norms, rules and cases, interpretation). It is argued that the study of AI as Law supports the development of an AI that is good for us, making AI & Law more relevant than ever. (shrink)

This paper reviews the history of AI & Law research from the perspective of argument schemes. It starts with the observation that logic, although very well applicable to legal reasoning when there is uncertainty, vagueness and disagreement, is too abstract to give a fully satisfactory classification of legal argument types. It therefore needs to be supplemented with an argument-scheme approach, which classifies arguments not according to their logical form but according to their content, in particular, according to the roles that (...) the various elements of an argument can play. This approach is then applied to legal reasoning, to identify some of the main legal argument schemes. It is also argued that much AI & Law research in fact employs the argument-scheme approach, although it usually is not presented as such. Finally, it is argued that the argument-scheme approach and the way it has been employed in AI & Law respects some of the main lessons to be learnt from Toulmin’s The Uses of Argument. (shrink)

I shall compare two views of legal concepts: as nodes in inferential nets and as categories in an ontology (a conceptual architecture). Firstly, I shall introduce the inferential approach, consider its implications, and distinguish the mere possession of an inferentially defined concept from the belief in the concept’s applicability, which also involves the acceptance of the concept’s constitutive inferences. For making this distinction, the inferential and eliminative analysis of legal concepts proposed by Alf Ross will be connected to the views (...) on theoretical concepts in science advanced by Frank Ramsey and Rudolf Carnap. Consequently, the mere comprehension of a legal concept will be distinguished from the application of the concept to a particular legal system, since application presupposes a doctrinal commitment, namely, the belief that the inferences constituting the concept hold in that system. Then, I shall consider how concepts can be characterised by defining the corresponding terms and placing them within an ontology. Finally, I shall argue that there is a tension between the inferential and the ontological approach, but that both need to be taken into account, to capture the meaning and the cognitive function of legal concepts. (shrink)

We reported a series of experiments carried out to confront the underlying intuitions of value-based argumentation frameworks (VAFs) with the intuitions of ordinary people. Our goal was twofold. On the one hand, we intended to test VAF as a descriptive theory of human argument evaluations. On the other, we aimed to gain new insights from empirical data that could serve to improve VAF as a normative model. The experiments showed that people’s acceptance of arguments deviates from VAF’s semantics and is (...) rather correlated with the importance given to the promoted values, independently of the perceptions of argument interactions through attacks and defeats. Furthermore, arguments were often perceived as promoting more than one value with different relative strengths. Individuals’ analyses of scenarios were also affected by external factors such as biases and arguments not explicit in the framework. Finally, we confirmed that objective acceptance, that is, the acceptance of arguments under any order of the values, was not a frequent behavior. Instead, participants tended to accept only the arguments that promoted the values they subscribe. (shrink)

ABSTRACTAccording to the prioritized reason model of precedent, precedential constraint is explained in terms of the need for decision-makers to reconcile their decisions with a settled priority order extracted from past cases. The prioritized reason model of precedent departs from the view that common law rules comprise protected reasons for action. In this article I show that a model utilizing protected reasons and the prioritized reason model of precedential constraint are, in an important sense, equivalent. I then offer some reflections (...) on the philosophical significance of this result. I argue that the protected reason model is consistent with the phenomenology of precedential constraint. I suggest an account of precedential reasoning that reconciles the prioritized reason and protected reason models. (shrink)

Cases or examples can be often explained by the interplay of arguments in favour or against their outcomes. This paper addresses the problem of finding explanations for a collection of cases where an explanation is a labelled argumentation graph consistent with the cases, and a case is represented as a statement labelling. The focus is on semi-abstract argumentation graphs specifying attack and subargument relations between arguments, along with particular complete argument labellings taken from probabilistic argumentation where arguments can be excluded. (...) The framework and computational considerations lead to an iterated local iterative deepening depth-first search to collect ‘interesting’ semi-abstract argumentation graphs consistent with a collection of statement labellings. Finally, the framework is illustrated and evaluated with a proof-of-concept implementation. (shrink)

The research described here explores the idea of using Supreme Court oral arguments as pedagogical examples in first year classes to help students learn the role of hypothetical reasoning in law. The article presents examples of patterns of reasoning with hypotheticals in appellate legal argument and in the legal classroom and a process model of hypothetical reasoning that relates them to work in cognitive science and Artificial Intelligence. The process model describes the relationships between an advocate’s proposed test for deciding (...) a case or issue, the facts of the hypothetical and of the case to be decided, and the often conflicting legal principles and policies underlying the issue. The process model of hypothetical reasoning has been partially implemented in a computerized teaching environment, LARGO (“Legal ARgument Graph Observer”) that helps students identify, analyze, and reflect on episodes of hypothetical reasoning in oral argument transcripts. Using LARGO, students reconstruct examples of hypothetical reasoning in the oral arguments by representing them in simple diagrams that focus students on the proposed test, the hypothetical challenge to the test, and the responses to the challenge. The program analyzes the diagrams and provides feedback to help students complete the diagrams and reflect on the significance of the hypothetical reasoning in the argument. The article reports the results of experiments evaluating instruction of first year law students at the University of Pittsburgh using the LARGO program as applied to Supreme Court personal jurisdiction cases. The learning results so far have been mixed. Instruction with LARGO has been shown to help law student volunteers with lower LSAT scores learn skills and knowledge regarding hypothetical reasoning better than a text-based approach, but not when the students were required to participate. On the other hand, the diagrams students produce with LARGO have been shown to have some diagnostic value, distinguishing among law students on the basis of LSAT scores, posttest performance, and years in law school. This lends support to the underlying model of hypothetical argument and suggests using LARGO as a pedagogically diagnostic tool. (shrink)

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.

The first issue of Artificial Intelligence and Law journal was published in 1992. This paper provides commentaries on nine significant papers drawn from the Journal’s second decade. Four of the papers relate to reasoning with legal cases, introducing contextual considerations, predicting outcomes on the basis of natural language descriptions of the cases, comparing different ways of representing cases, and formalising precedential reasoning. One introduces a method of analysing arguments that was to become very widely used in AI and Law, namely (...) argumentation schemes. Two relate to ontologies for the representation of legal concepts and two take advantage of the increasing availability of legal corpora in this decade, to automate document summarisation and for the mining of arguments. (shrink)

The third of Berman and Hafner’s early nineties papers on reasoning with legal cases concerned temporal context, in particular the evolution of case law doctrine over time in response to new cases and against a changing background of social values and purposes. In this paper we consider the ways in which changes in case law doctrine can be accommodated in a recently proposed methodology for encapsulating case law theories, and relate these changes the sources of change identified by Berman and (...) Hafner. (shrink)

Carole Hafner’s scholarship on the conceptual organization of case law knowledge bases was an original approach to distilling a library’s worth of cases into a manageable subset that any given legal researcher could review. Her approach applied concept indexation and concept search based on an annotation model of three interacting components combined with a system of expert legal reasoning to aid in the retrieval of pertinent case law. Despite the clear value this tripartite approach would afford to researchers in search (...) of cases with similar fact patterns and desired outcomes, this approach has not been applied consistently in the intervening years since its introduction. Specifically, the conceptual representation of domain concepts and the case frames were not pursued by researchers, and they were not applied by the legal case indexing services that came to dominate the electronic case law market. Advances since Hafner’s original scholarship in the form of digitized case law and related materials; computer science analytical protocols; and more advanced forms of artificial intelligence approaches present the question of whether Hafner’s COC model could move from the hypothetical to the real. (shrink)