In this work it is argued that legal justification can best be studied from a procedural, dialogical point of view: legal statements are justified if the audience is convinced in an argumentative dialog. The formalized and implemented model DiaLaw guards the procedure in which two players aim at justifying statements. DiaLaw shows the advances and problems linked to procedural models of legal justification. Moreover, an instructive discussion of the different models of procedural justification is provided. It is stressed that in (...) legal justification not only logically compelling arguments should be considered, but also convincing arguments. Therefore DiaLaw also deals with the rhetorical, psychological aspects of argument. This book is relevant for scholars in legal theory, artificial intelligence, and argumentation, and can be used in graduate courses on AI and Law, and legal argumentation. (shrink)

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, (...) and the social values which justify those rules. Having given our view of these relationships, we present our formal model of them, and explain how theories can be constructed, compared and evaluated. We then show how previous work can be described in terms of our model, and discuss extensions to the basic model to accommodate particular features of previous work. We conclude by identifying some directions for future work. (shrink)

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)

The BankXX system models the process of perusing and gathering information for argument as a heuristic best-first search for relevant cases, theories, and other domain-specific information. As BankXX searches its heterogeneous and highly interconnected network of domain knowledge, information is incrementally analyzed and amalgamated into a dozen desirable ingredients for argument (called argument pieces), such as citations to cases, applications of legal theories, and references to prototypical factual scenarios. At the conclusion of the search, BankXX outputs the set of argument (...) pieces filled with harvested material relevant to the input problem situation.This research explores the appropriateness of the search paradigm as a framework for harvesting and mining information needed to make legal arguments. In this article, we describe how legal research fits the heuristic search framework and detail how this model is used in BankXX. We describe the BankXX program with emphasis on its representation of legal knowledge and legal argument. We describe the heuristic search mechanism and evaluation functions that drive the program. We give an extended example of the processing of BankXX on the facts of an actual legal case in BankXX's application domain — the good faith question of Chapter 13 personal bankruptcy law. We discuss closely related research on legal knowledge representation and retrieval and the use of search for case retrieval or tasks related to argument creation. Finally we review what we believe are the contributions of this research to the understanding of the diverse disciplines it addresses. (shrink)

Dung’s abstract argumentation frameworks have had a very significant role in the rise in interest in argumentation throughout this century. In this paper we will explore the impact of this seminal...

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 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 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, (...) and six apply machine learning techniques to a variety of legal applications. (shrink)

Legal analysis is a task underlying many forms of legal problem solving. In the Anglo-American legal system, legal analysis is based in part on legal precedents, previously decided cases. This paper describes a reduction-graph model of legal precedents that accounts for a key characteristic of legal precedents: a precedent's relevance to subsequent cases is determined by the theory under which the precedent is decided. This paper identifies the implementation requirements for legal analysis using the reduction-graph model of legal precedents and (...) describes GREBE, a program that satisfies these requirements. (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 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.

This paper revisits the challenge of Berman and Hafner’s “missing link” paper on representing teleological structure in case-based legal reasoning. It is noted that this was mainly an ontological challenge to represent some of what made legal reasoning distinctive, which was given less attention than factual similarity in the dominant AI and Law paradigm, deriving from HYPO. The response to their paper is noted and briefly evaluated. A parallel is drawn to a new challenge to provide deep structure to the (...) legal context of textual meaning, drawing on the forthcoming work of two Constitutional law scholars who appear to place some faith in the ways of thinking that AI and Law has developed. (shrink)

Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities (...) are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also be modelled.The proof theory of the system is stated in dialectical style, where a proof takes the form of a dialogue between a proponent and an opponent of an argument. An argument is shown to be justified if the proponent can make the opponent run out of moves in whatever way the opponent attacks. Despite this dialectical form, the system reflects a declarative, or relational approach to modelling legal argument. A basic assumption of this paper is that this approach complements two other lines of research in AI and Law, investigations of precedent-based reasoning and the development of procedural, or dialectical models of legal argument. (shrink)

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.

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 (...) justified is represented as the ‘rebuttal’. To further improve the model, (Goodnight, Informal Logic 15:41–52, 1993) points out that the selection of a backing needs justification, which he calls legitimation justification. However, how such justification is constituted has not yet been clarified. To identify legitimation justification, we separate it into two parts. One justifies a backing’s eligibility (legitimation justification 1 ; LJ 1 ); the other justifies its superiority over other eligible backings (legitimation justification 2 ; LJ 2 ). In this paper, we focus on LJ 1 and apply it to the legal justification (of judgements) in hard cases for illustration purposes. We submit that LJ 1 refers to the justification of the legal interpretation of a norm by its backing, which can be further separated into several orderable subjustifications. Taking the subjustification of a norm’s existence as an example, we show how it would be influenced by different positions in the philosophy of law. Taking the position of the theory of natural law, such subjustification is presented and evaluated. This paper aims not only to inform ongoing theoretical efforts to apply the Toulmin model in the legal field, but it also seeks to clarify the process in the justification of legal judgments in hard cases. It also offers background information for the possible construction of related AI systems. In our future work, LJ 2 and other subjustifications of LJ 1 will be discussed. (shrink)

Identifying, classifying, and analyzing arguments in legal discourse has been a prominent area of research since the inception of the argument mining field. However, there has been a major discrepancy between the way natural language processing (NLP) researchers model and annotate arguments in court decisions and the way legal experts understand and analyze legal argumentation. While computational approaches typically simplify arguments into generic premises and claims, arguments in legal research usually exhibit a rich typology that is important for gaining insights (...) into the particular case and applications of law in general. We address this problem and make several substantial contributions to move the field forward. First, we design a new annotation scheme for legal arguments in proceedings of the European Court of Human Rights (ECHR) that is deeply rooted in the theory and practice of legal argumentation research. Second, we compile and annotate a large corpus of 373 court decisions (2.3M tokens and 15k annotated argument spans). Finally, we train an argument mining model that outperforms state-of-the-art models in the legal NLP domain and provide a thorough expert-based evaluation. All datasets and source codes are available under open lincenses athttps://github.com/trusthlt/mining-legal-arguments. (shrink)

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.

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.

Planning problems arise in law when an individual (or corporation)wants to perform a sequence of actions that raises legal issues. Manylawyers make their living planning transactions, and a system thathelped them to solve these problems would be in demand.The designer of such a system in a common-law domain must addressseveral difficult issues, including the open-textured nature of legal rules,the relationship between legal rules and cases, the adversarial nature ofthe domain, and the role of argument. In addition, the system's design isconstrained (...) by the fact that the intended users are lawyers, and its operation and output must be convenient for lawyers to use.In this article, I describe a system called CHIRON that I have developed to explore solutions to these issues. This system develops simple plans from representations of statutes and cases in the domain of United States personal income tax planning. (shrink)

The Pleadings Game is a normative formalization and computational model of civil pleading, founded in Roberty Alexy''s discourse theory of legal argumentation. The consequences of arguments and counterarguments are modelled using Geffner and Pearl''s nonmonotonic logic,conditional entailment. Discourse in focussed using the concepts of issue and relevance. Conflicts between arguments can be resolved by arguing about the validity and priority of rules, at any level. The computational model is fully implemented and has been tested using examples from Article Nine of (...) the Uniform Commercial Code. (shrink)

In this paper I shall discuss the notion of argument, and the importanceof argument in AI and Law. I shall distinguish four areas where argument hasbeen applied: in modelling legal reasoning based on cases; in thepresentation and explanation of results from a rule based legal informationsystem; in the resolution of normative conflict and problems ofnon-monotonicity; and as a basis for dialogue games to support the modellingof the process of argument. The study of argument is held to offer prospectsof real progress (...) in the field of AI and law, and the purpose of this paperis to provide an overview of work, and the connection between the various strands. (shrink)

This paper provides a formal description of two legal domains. In addition, we describe the generation of various artificial datasets from these domains and explain the use of these datasets in pre...

A representation methodology for knowledge allowing multiple interpretations is described. It is based on the following conception of legal knowledge and its open texture. Since indeterminate, legal knowledge must be adapted to fit the circumstances of the cases to which it is applied. Whether a certain adaptation is lawful or not is measured by metaknowledge. But as this too is indeterminate, its adaptation to the case must be measured by metametaknowledge, etc. This hierarchical model of law is quite well-established and (...) may serve well as a basis for a legal knowledge system. To account for the indeterminacy of law such a system should support the construction of different arguments for and against various interpretations of legal sources. However, automatizing this reasoning fully is unsound since it would imply a restriction to arguments defending interpretations anticipated at programming time. Therefore, the system must be interactive and the user''s knowledge be furnished in a principled way. Contrary to the widespread opinion that classical logic is inadequate for representing open-textured knowledge, the framework outlined herein is given a formalization in first order logic. (shrink)

Much work on legal knowledge systems treats legal reasoning as arguments that lead from a description of the law and the facts of a case, to the legal conclusion for the case. The reasoning steps of the inference engine parallel the logical steps by means of which the legal conclusion is derived from the factual and legal premises. In short, the relation between the input and the output of a legal inference engine is a logical one. The truth of the (...) conclusion only depends on the premises, and is independent of the argument that leads to the conclusion.This paper opposes the logical approach, and defends a procedural approach to legal reasoning. Legal conclusions are not true or false independent of the reasoning process that ended in these conclusions. In critical cases this reasoning process consists of an adversarial procedure in which several parties are involved. The course of the argument determines whether the conclusion is true or false. The phenomenon of hard cases is used to demonstrate this essential procedural nature of legal reasoning. (shrink)

We propose a formal theory built upon an abstract argumentation framework for handling argumentation dynamics. To that end, we analyze the acceptability dynamics of arguments through the proposal of two different kinds of sets of arguments which are somehow responsible for the acceptability/rejection of a given argument. We develop a study of the consequences of breaking the construction of such sets towards the acceptance of an analyzed argument. This brings about the proposal of a novel change operation which allows to (...) determine which arguments should be removed from the framework so that another particular argument becomes accepted. Finally, the proposed model is formalized in the light of the theory of belief revision by characterizing the corresponding operations through constructive definition and an axiomatic characterization, connecting them through the corresponding representation theorem. The theoretical proposal constitutes the fundamentals for a system implementation in many dynamic domains of application. In particular, we show its application for handling the dynamics of legal interpretation. In that sense, this proposal constitutes a fundamental approach and theoretical justification to handle the dynamics of legal arguments through changes of interpretative canons. We show a possible concretisation of our abstract theory for the legal domain by analysing a real legal case from the Argentinean jurisprudence. Such a system would be capable of suggesting alternative critical points in the current state of affairs of a legal case towards pursuing a specific goal for which the case is being investigated. (shrink)

In this introduction I give an overview of Carole Hafner’s work and discuss the papers in this volume. The final section offers some more personal reminiscences of Carole and her contribution to the AI and Law community, from myself and other colleagues.

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.

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)

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)

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)

This paper proposes a model ofratio decidendi as a justification structure consisting of a series of reasoning steps, some of which relate abstract predicates to other abstract predicates and some of which relate abstract predicates to specific facts. This model satisfies an important set of characteristics ofratio decidendi identified from the jurisprudential literature. In particular, the model shows how the theory under which a case is decided controls its precedential effect. By contrast, a purely exemplar-based model ofratio decidendi fails to (...) account for the dependency of precedential effect on the theory of decision. (shrink)

In this article we evaluate the BankXX program from several perspectives. BankXX is a case-based legal argument program that retrieves cases and other legal knowledge pertinent to a legal argument through a combination of heuristic search and knowledge-based indexing. The program is described in detail in a companion article in Artificial Intelligence and Law 4: 1--71, 1996. Three perspectives are used to evaluate BankXX:(1) classical information retrieval measures of precision and recall applied against a hand-coded baseline; (2) knowledge-representation and case-based (...) reasoning, where the baseline is provided by the functionality of a well-known case-based argument program, HYPO (Ashley, 1990); and (3) search, in which the performance of BankXX run with various parameter settings, for instance, resource limits, is compared. In this article we report on an extensive series of experiments performed to evaluate the program. We also describe two additional experiments concerning(1) the program's search behavior; and (2) the use of a modified form of precision and recall based on case similarity. Finally we offer some general conclusions that might be drawn from these particular experiments. (shrink)

Computational models of relevance in case-based legal reasoning have traditionallybeen based on algorithms for comparing the facts and substantive legal issues of aprior case to those of a new case. In this paper we argue that robust models ofcase-based legal reasoning must also consider the broader social and jurisprudentialcontext in which legal precedents are decided. We analyze three aspects of legalcontext: the teleological relations that connect legal precedents to the socialvalues and policies they serve, the temporal relations between prior andsubsequent (...) cases in a legal domain, and the procedural posture of legal cases,which defines the scope of their precedential relevance. Using real examples drawnfrom appellate courts of New York and Massachusetts, we show with the courts' ownarguments that the doctrine of stare decisis (i.e., similar facts should lead to similar results) is subject to contextual constraints and influences. For each of the three aspects of legal context, we outline an expanded computational framework for case-based legal reasoning that encompasses the reasoning of the examples, and provides a foundation for generating a more robust set of legal arguments. (shrink)

In this paper we describe AGATHA, a program designed to automate the process of theory construction in case based domains. Given a seed case and a number of precedent cases, the program uses a set of argument moves to generate a search space for a dialogue between the parties to the dispute. Each move is associated with a set of theory constructors, and thus each point in the space can be associated with a theory intended to explain the seed case (...) and the other cases in the domain. The space is large and so an heuristic search method is needed. This paper describes two methods based on A* and alpha/beta pruning and also a series of experiments designed to explore the appropriateness of different evaluation functions, the most useful precedents to use as seed cases and the quality of the resulting theories. (shrink)