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First published online: 15 February 2019 Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.

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 chapter provides an overview of the main lines of inquiry of Artificial Intelligence and Law (AI and Law), such as rule-based reasoning, case-based reasoning, ontologies, argumentation, theory construction and legal deontics. We argue that a rich picture of the law is emerging from the AI and Law research, which can complement and integrate not only research in law and legal theory, but also other attempts to provide formal and computational models of norms.

Here the young Leibniz (he was only 18 years old when writing the Specimen) advances his original and bold thesis that, despite the jurists’ contempt for philosophy, the law without the guidance of philosophy “would be an inextricable labyrinth”. On the other hand, as he argues deploying an impressive array of sources, both canonical law and civil law contain a considerable amount of philosophical content, pertaining not only to practical philosophy, but also to logic, physics, and other disciplines, including mathematics and metaphysics (a point on which Leibniz will insist, with an explicit reference to the Specimen, in the preface to the Nova methodus [A VI/1 265]).

In the opening section, Leibniz identifies the object of his work: on the one hand, he will circumscribe the extension of the term perplexing case, specifying what cases are to be viewed as perplexing, and on the other hand he will suggest how such cases should be dealt with.

This paper addresses legal classifications by exploring the connections and possible synergies between legal doctrine and computational ontologies. In recent years legal ontologies have attracted a growing interest, not only from knowledge engineers but also from legal scholars. Indeed, several controversial issues arise concerning the elicitation and structuring of domain (legal) knowledge, and legal theory can provide useful insights in this respect. The existing tradition of definition and classification of legal concepts by legal doctrine can be regardes as an intellectual capital for the extraction and characterisation of concepts to be included in legal ontologies. The question arises as to what extent doctrinal structures can be reused in the construction of legal ontologies, and as to what extent doctrinal analyses can draw inspiration from computational ontologies.

Ontologies have come of age in the legal field. A certain number of ontologies in different domains are already available and have been used in various applications. However, as a result of the growing of the field, a plurality of theoretical and methodological approaches has flourished. The multi-level complexity involved in legal ontology engineering suggests that there is no single way to address the development of legal ontologies, but rather we have a cluster of problems, perspectives, instruments, and goals that require a plurality of approaches, both on theoretical and on pragmatic grounds. This chapter, after introducing some challenges and new lines of development in the intersection of legal ontologies and next Semantic Web generation, briefly presents the contributions in the volume.

Introduction Part I: Legal, Political and Constitutional Theory a) The Reasonableness of the Law 1. The Reasonableness of Law - Robert Alexy 2. A Sufficientist Approach to Reasonableness in Legal Decision-making and Judicial Review- Giovanni Sartor 3. Reasonableness, Common Sense, and Science - Alberto Artosi b) The Moral and Political Dimension of Reasonableness 1. Reciprocity, Balancing and Proportionality: Rawls and Habermas on Moral and Political Reasonableness - Giorgio Bongiovanni and Chiara Valentini 2. Law, Liberty and Reason - Philip Pettit 3. 'Reasonableness' and Value Pluralism in Law and Politics - Wojciech Sadurski 4. Global Legitimation and Reasonableness - Sebastiano Maffettone 5. Philip Pettit's Law, Liberty and Reason. Republican Freedom and Criminal Justice -Luca Baccelli c) Reasonableness in Constitutional Adjudication 1. Proportionality, Judicial Review, and Global Constitutionalism - Alec Stone-Sweet and Jud Mathews 2. Constitutional Adjudication and the Principle of Reasonableness - Andrea Morrone 3. Some Critical Thoughts on Proportionality - Iddo Porat Part II: Private, Public and International Law a) Reasonableness in Private Law 1. Reasonable Persons in Private Law - Arthur Ripstein 2. The Reasonable Consumer According to the European and Italian Regulations Concerning Unfair Business-To-Consumer Commercial Practices - Chiara Alvisi b) Reasonableness in Administrative and Public Law 1. Reasonableness in Administrative Law - Giacinto della Cananea 2. Reasonableness in Administrative Law: A Comparative Reflection on Functional Equivalence - Michal Bobek c)Reasonableness in Biolaw 1. Reasonableness, Bioethics, and Biolaw - Carla Faralli 2. Reasonableness in Biolaw -Amedeo Santosuosso 3. Reasonableness and Biolaw - Stephanie Hennette-Vauchez 4. Reasonableness in Biolaw: The Criminal Law Perspective - Stefano Canestrari and Francesca Faenza d) Reasonableness in EU and International Law 1. The Principle of Reasonableness in European Union Law - Adelina Adinolfi 2. What 'Rule of Reason' for the EU Internal Market? - Lucia Serena Rossi and Stephen J. Curzon 3. From State-Centered Towards Constitutional 'Public Reason' in Modern International Economic Law - Ernst-Ulrich Petersmann

I shall argue for a sufficientist understanding of reasonableness in legal decision-making: cognitive or moral optimality are not required for reasonableness; what needed is just that a determination—be it epistemic or practical—is sufficiently good (acceptable, or at least not unacceptable). Correspondingly, judicial review on the ground of unreasonableness requires more than mere suboptimality: it requires failure to achieve the reasonableness threshold. To develop this idea, I shall first analyse the notions of rationality and reasonableness, examining the role they play in cognition. I shall then consider rationality in legal (and in particular legislative) decision-making, focusing on teleological reasoning. I shall consequently develop an idea of sufficientist reasonableness, by combining the idea of bounded rationality with the idea of deference, as required by institutional coordination in the legal process. Finally, I shall consider when a legislative determination can be considered irrational or unreasonable, and how this is related to the violation of constitutional requirements.

The history of artificial intelligence (AI) has been characterized by a steady expansion of the aspects of human cognition and expertise amenable to computational models. The earliest AI applications were in formal domains, such as theorem proving, that are relatively divorced from the complexity of ordinary human experience. Progress in natural language processing, expert systems, planning, robotics, and qualitative reasoning has extended the range of human experience and behavior addressed by AI. This general trend also characterizes research on AI & law. Early research addressed primarily routine legal domains, such as administrative procedures, that involve the straightforward application of clear-cut rules to un-controversial facts. Recent research, however, has focused increasingly on more complex and challenging areas of the legal process typified by judicial decisionmaking. No simple rule-chaining or pattern-matching algorithm can accurately model judicial decision-making because the judiciary has the task of producing reasonable and acceptable solutions in exactly those cases in which the facts, the rules, or how they fit together are controversial.

This paper analyses legal reasoning with precedents in the setting of a formally defined dialogue game. After giving a legal-theoretical account of judicial reasoning with precedents, a formal method is proposed for representing precedents and it is discussed how such representations can be used in a formally defined dialectical protocol for dispute. The basic ideas are to represent cases as argument structures (including pro and con arguments, and the arguments for adjudicating their conflicts) and to define certain case-based reasoning moves as strategies for introducing information into a dispute. In particular, analogizing and distinguishing are conceived as elementary theory construction moves, which produce new information on the basis of an existing stock of cases. The approach also offers the possibility of using portions of precedents and of expressing criteria for determining the outcome of precedent-based disputes.

The judiciary is in the early stages of a transformation in which AI (Artificial Intelligence) technology will help to make the judicial process faster, cheaper, and more predictable without compromising the integrity of judges' discretionary reasoning. Judicial decision-making is an area of daunting complexity, where highly sophisticated legal expertise merges with cognitive and emotional competence. How can AI contribute to a process that encompasses such a wide range of knowledge, judgment, and experience? Rather than aiming at the impossible dream (or nightmare) of building an automatic judge, AI research has had two more practical goals: producing tools to support judicial activities, including programs for intelligent document assembly, case retrieval, and support for discretionary decision-making; and developing new analytical tools for understanding and modeling the judicial process, such as case-based reasoning and formal models of dialectics, argumentation, and negotiation. Judges, squeezed between tightening budgets and increasing demands for justice, are desperately trying to maintain the quality of their decision-making process while coping with time and resource limitations. Flexible AI tools for decision support may promote uniformity and efficiency in judicial practice, while supporting rational judicial discretion. Similarly, AI may promote flexibility, efficiency and accuracy in other judicial tasks, such as drafting various judicial documents. The contributions in this volume exemplify some of the directions that the AI transformation of the judiciary will take.

This chapter provides a picture, in relation to the debate on normativity, of the different analyses of reasons and the different ways in which reasons can be evaluated and classified. The discussion starts out by distinguishing three different classes of reasons on the basis of their role: normative, motivating, and explanatory. And then the focus shifts to normative reasons, discussing the basis of their capacity to favour actions or beliefs in the light of the different understandings of their ontological status as either facts or mental states. We will see, on these premises, that reasons can be distinguished into two different kinds: reasons for belief (epistemic) and reasons for action (practical). Particular attention is devoted to the “weighing conception” of normative reasons (and the understanding of them as pro tanto reasons), as this approach seems best suited to practical (as well as legal) reasoning. This will provide a vantage point from which to analyse the strength of reasons and their modality, most notably their modality as first- and second-order reasons. Finally, it will be considered how the weighing conception fits into the philosophy of law, in view of the fundamental role this discipline assigns to second-order reasons in the attempt to explain the normative nature of law and its authority.

This paper presents a mechanism for adding meaningful semantics on top of the CEN Metalex standard for permitting heterogeneous legal resource management. The results developed within the Estrella project and the integration with other national and international standards envisage the possibility to use CEN Metalex as a neutral document standard in many situations where legal information resources are involved: as intermediate data format for fostering long term preservation of legal documents, as a tool for interoperability between legacy systems, as an interchange data format between different application layers, as a conversion mechanism across versions of the same standard. CEN Metalex permits also to build interesting applications of CMS for heterogeneous legal resource information. For exploiting these potentialities CEN Metalex needs to be enriched with a legal document ontology and moreover to an intermediate layer called LMIF for adding semantic to the general structural layer. This work presents how to foster CEN Metalex using LMIF and how to connect this layer with an abstract legal document ontology.