Giovanni Sartor

Legal principles stated in judicial decisions are a key reference for judges and legal professionals. However, typically, decisions are long and complex documents. The automatic extraction of legal principles therein may thus be beneficial to many. Unfortunately, this is an under-investigated task for which few resources and implementations exist, especially with regard to EU law. To promote research in this domain, we develop a novel corpus of 64 judicial decisions on Fiscal State Aid by the CJEU (the Court of Justice of the European Union), in which legal principles are identified and tagged. With this new resource, we conduct extensive experimentation to identify the best combinations of representation methods, classifiers and data augmentation methods for the task at hand, obtaining an F1 score of 0.72. Additionally, we consider the collections of legal principles obtained by running the extractive task and collating the output paragraphs together. We show, through the use of lexical metrics and human evaluation, that the quality of generated collections is comparable to that of expert-made ones.

Abstract. In this paper I shall take an inferential approach to legality (legal validity), and consider how the legality of a norm can be inferred, and what can be inferred from it. In particular, I shall analyse legality policies, namely, conditionals conferring the quality of legality upon norms having certain properties, and I shall examine to what extent such conditionals need to be positivistic, so that legality is only dependant on social facts. Finally, I shall consider how legality is transmitted from norm to norm and whether the ultimate legality policies (the rules of recognition) of a legal system need to be constituted by social facts.

This chapter proposes a dialectical approach to legal interpretation, consisting of three dimensions: a formalization of the canons of interpretation in terms of argumentation schemes; a dialectical classification of interpretive schemes; and a logical and computational model for comparing the arguments pro and contra an interpretation. The traditional interpretive maxims or canons used in both common and civil law are translated into defeasible patterns of arguments, which can be evaluated through sets of corresponding critical questions. These interpretive argumentation schemes are classified in general categories and a distinction is drawn between schemes supporting and rebutting an interpretation. This framework allows conceiving statutory interpretation as a dialectical procedure consisting in weighing arguments pro and contra an interpretation. This procedure is formalized and represented computationally through tools from formal argumentation systems.

In this paper we will analyse the issue of defeasibility in the law, taking into account research carried out in philosophy, artificial intelligence and legal theory. We will adopt a very general idea of legal defeasibility, in which we will include all different ways in which certain legal conclusions may need to be abandoned, though no mistake was made in deriving them. We will argue that defeasibility in the law involves three different aspects, which we will call inference‐based defeasibility, process‐based defeasibility, and theory‐based defeasibility. Only the integration of these three perspectives allows us to provide a satisfactory account of the role of defeasibility in legal reasoning.

The paper argues for viewing legal validity as a doxastic obligation, i.e. as the obligation to accept a rule in legal reasoning. This notion of legal validity is shown to be both sufficient for the laywers' needs and neutral in regard to various theories of the grounds of validity, i.e. theories intended to identify what rules are legally valid, by proposing different grounds for attributing validity. All of these theories, rather then being alternative definitions of validity, presuppose the notion here provided.This notion is purely normative, but it allows for the construction of theories of the grounds of validity which give due importance to social expectations and institutions. As an example of how this may happen, one such theory is also provided. This theory, which is presented through a detailed example of a judicial debate, is based upon the recognition of the (instrumental) value of co-ordination, as the necessary way to achieve the most valuable purposes of the law.

Machines powered by artificial intelligence (AI) are increasingly taking over tasks previously performed by humans alone. In accomplishing such tasks, they may intentionally commit ‘AI crimes’, ie engage in behaviour which would be considered a crime if it were accomplished by humans. For instance, an advanced AI trading agent may—despite its designer’s best efforts—autonomously manipulate markets while lacking the properties for being held criminally responsible. In such cases (hard AI crimes) a criminal responsibility gap emerges since no agent (human or artificial) can be legitimately punished for this outcome. We aim to shift the ‘hard AI crime’ discussion from blame to deterrence and design an ‘AI deterrence paradigm’, separate from criminal law and inspired by the economic theory of crime. The homo economicus has come to life as a machina economica, which, even if cannot be meaningfully blamed, can nevertheless be effectively deterred since it internalises criminal sanctions as costs.

This chapter provides an analysis of defeasible legal reasoning as argumentation. It first provides a general account of the idea of defeasibility and introduces the idea of nonmonotonic reasoning. It then focuses on defeasible argumentation, considering how defeasible arguments can be constructed and how they can be defeated by rebutting and undercutting counterarguments. The dialectical interactions of defeasible arguments are further explored by focusing on reinstatement and reasoning about priorities. The idea of legal systems as the basis for argumentation frameworks is then investigated. The rationale for defeasibility in law is discussed, along with the possibility of using different approaches, such as revision or probability, to deal with uncertainty in legal reasoning. Finally, an account is provided of the emergence of theories of defeasibility in philosophy, logic, and legal theory.

This chapter is meant to address the extent to which value-based reasoning—as involved in balancing and proportionality—may include quantitative reasoning, according to arithmetic constraints. Relying on some work on cognitive and evolutionary psychology, it is argued that processing non-symbolic approximate magnitudes is a fundamental cognitive capacity, which is deployed also when we are reasoning with goals and values. A model is developed for determining the impact of alternative choice on multiple values, assessing the utilities so produced and merging these utilities into an overall evaluation, which may be used in comparisons. The model is applied to assessing legislative choice on rights and social values, according to proportionality. Finally, it is shown how proportionality assessments may be constrained by the requirement of consistency with precedents.

This paper proposes to model legal reasoning asdialectical theory-constructiondirected by teleology. Precedents are viewed asevidence to be explained throughtheories. So, given a background of factors andvalues, the parties in a case canbuild their theories by using a set of operators,which are called theory constructors.The objective of each party is to provide theoriesthat both explain the evidence (theprecedents) and support the decision wished by thatparty. This leads to theory-basedargumentation, i.e., a dialectical exchange ofcompeting theories, which support opposedoutcomes by explaining the same evidence and appealingto the same values. The winneris the party that can reply with a more coherent theoryto all theories of its adversary.

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.

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

This paper proposes an approach to investigate norm-governed learning agents which combines a logic-based formalism with an equation-based counterpart. This dual formalism enables us to describe the reasoning of such agents and their interactions using argumentation, and, at the same time, to capture systemic features using equations. The approach is applied to norm emergence and internalisation in systems of learning agents. The logical formalism is rooted into a probabilistic defeasible logic instantiating Dung’s argumentation framework. Rules of this logic are attached with probabilities to describe the agents’ minds and behaviours as well as uncertain environments. Then, the equation-based model for reinforcement learning, defined over this probability distribution, allows agents to adapt to their environment and self-organise

Statutory interpretation involves the reconstruction of the meaning of a legal statement when it cannot be considered as accepted or granted. This phenomenon needs to be considered not only from the legal and linguistic perspective, but also from the argumentative one - which focuses on the strategies for defending a controversial or doubtful viewpoint. This book draws upon linguistics, legal theory, computing, and dialectics to present an argumentation-based approach to statutory interpretation. By translating and summarizing the existing legal interpretative canons into eleven patterns of natural arguments - called argumentation schemes - the authors offer a system of argumentation strategies for developing, defending, assessing, and attacking an interpretation. Illustrated through major cases from both common and civil law, this methodology is summarized in diagrams and maps for application to computer sciences. These visuals help make the structures, strategies, and vulnerabilities of legal reasoning accessible to both legal professionals and laypeople.

This handbook offers a deep analysis of the main forms of legal reasoning and argumentation from both a logical-philosophical and legal perspective. These forms are covered in an exhaustive and critical fashion, and the handbook accordingly divides in three parts: the first one introduces and discusses the basic concepts of practical reasoning. The second one discusses the main general forms of reasoning and argumentation relevant for legal discourse. The third one looks at their application in law as well as at the different areas of legal reasoning. The handbook’s division in three parts reflects its conceptual architecture, since legal reasoning and argumentation are considered in relation to the more general types of reasoning.

This article models legal interpretation through argumentation and provides a logical analysis of interpretive arguments, their conflicts, and the resulting indeterminacies. Interpretive arguments are modelled as defeasible inferences, which can be challenged and defeated by counterarguments and be reinstated through further arguments. It is shown what claims are possibly (defensibly) or necessarily (justifiably) supported by the arguments constructible from a given interpretive basis, i.e., a set of interpretive canons coupled with reasons for their application. It is finally established under what conditions such arguments provide single outcomes or rather support alternative interpretive conclusions, thus leading to propositions of law whose truth‐value is undetermined.

The paper gives a formal reconstruction of some fundamental patterns of legal reasoning, intended to reconcile symbolic logic and argumentation theory. Legal norms are represented as unidirectional inference rules which can be combined into arguments. The value of each argument (its qualification as justified, defensible, or defeated) is determined by the importance of the rules it contains. Applicability arguments, intended to contest or support the applicability of norms, preference arguments, purporting to establish preference relations among norms, and interpretative arguments are also formalised. All those argument types are connected in a unitary model, which relates legal reasoning to the indeterminacy of legal systems, intended as the possibility to develop incompatible defensible arguments. The model is applied to permissive norms and normative hierarchies, and is implemented in a Prolog program.

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.

We shall introduce a set of fundamental legal concepts, providing a definition of each of them. This set will include, besides the usual deontic modalities (obligation, prohibition and permission), the following notions: obligative rights (rights related to other’s obligations), permissive rights, erga-omnes rights, normative conditionals, liability rights, different kinds of legal powers, potestative rights (rights to produce legal results), result-declarations (acts intended to produce legal determinations), and sources of the law.

I shall argue that software agents can be attributed cognitive states, since their behaviour can be best understood by adopting the intentional stance. These cognitive states are legally relevant when agents are delegated by their users to engage, without users’ review, in choices based on their the agents’ own knowledge. Consequently, both with regard to torts and to contracts, legal rules designed for humans can also be applied to software agents, even though the latter do not have rights and duties of their own. The implications of this approach in different areas of the law are then discussed, in particular with regard to contracts, torts, and personality.

This paper proposes an argumentation-based procedure for legal interpretation, by reinterpreting the traditional canons of textual interpretation in terms of argumentation schemes, which are then classified, formalized, and represented through argument visualization and evaluation tools. The problem of statutory interpretation is framed as one of weighing contested interpretations as pro and con arguments. The paper builds an interpretation procedure by formulating a set of argumentation schemes that can be used to comparatively evaluate the types of arguments used in cases of contested statutory interpretation in law. A simplified version of the Carneades Argumentation System is applied in a case analysis showing how the procedure works. A logical model for statutory interpretation is finally presented, covering pro-tanto and all-things-considered interpretive conclusions.