Giovanni Sartor

We provide a logical analysis of private international law, a rather esoteric, but increasingly important, domain of the law. Private international law addresses overlaps and conflicts between legal systems by distributing cases between the authorities of such systems (jurisdiction) and establishing what rules these authorities have to apply to each case (choice of law). A formal model of the resulting interactions between legal systems is proposed based on modular argumentation. It is argued that this model may also be useful for governing the interactions between heterogeneous agents, belonging to different and differently regulated virtual societies, without recourse to a central regulatory agency. The model also provides for multiple interpretations concerning rules of private international law as well as substantive rules of the different legal systems.

This volume presents two Leibnizian writings, the Specimen of Philosophical Questions Collected from the Law and the Dissertation on Perplexing Cases. These works, originally published in 1664 and 1666, constitute, respectively, Leibniz's thesis for the title of Master of Philosophy and his doctoral dissertation in law. Besides providing evidence of the earliest development of Leibniz's thought and amazing anticipations of his mature views, they present a genuine intellectual interest, for the freshness and originality of Leibniz's reflections on a striking variety of logico-philosophical puzzles drawn from the law. The Specimen addresses puzzling issues resulting from apparent conflicts between law and philosophy (the latter broadly understood as comprising also mathematics, as well as empirical sciences). The Dissertation addresses cases whose solution is puzzling because of the convoluted logical form of legal dispositions and contractual clauses, or because of conflicting priorities between concurring parties. In each case, Leibniz dissects the problems with the greatest ingenuity, disentangling their different aspects, and proposing solutions always reasonable and sometimes surprising. And he does not refrain from peppering his intellectual acrobatics with some humorous comments. bbbbbb.

In this paper, we provide an analysis of the concept of legal personality and discuss whether personality may be conferred on artificial intelligence systems (AIs). Legal personality will be presented as a doctrinal category that holds together bundles of rights and obligations; as a result, we first frame it as a node of inferential links between factual preconditions and legal effects. However, this inferentialist reading does not account for the ‘background reasons’ of legal personality, i.e., it does not explain why we cluster different situations under this doctrinal category and how extra-legal information is integrated into it. We argue that one way to account for this background is to adopt a neoinstitutional perspective and to update the ontology of legal concepts with a further layer, the meta-institutional one. We finally argue that meta-institutional concepts can also support us in finding an equilibrium around the legal-policy choices that are involved in including (or not including) AIs among legal persons.

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.

Beginning with a concise reflection on the significance of digital sovereignty, this chapter describes and problematizes the Chinese social credit system in connection with the notion of digital sovereignty. It provides a synthetic illustration of the origin, evolution, essential characteristics, structure, explicit aims, and main limitations of the Chinese social credit system, taking into account the specific historical and ideological context in which the system has been designed and developed. On the basis of this description, the potentialities, still to be realised, of the use of artificial intelligence techniques in the different applications related to surveillance, evaluation, and sanctioning are assessed and discussed, in relation to the Chinese discourse on digital sovereignty. The last part of the chapter discusses the potential consequences of such a system in terms of individual rights, individual self-determination, and autonomy, which in turn influence the construction of the entire social fabric.

This chapter introduces a conceptual framework for qualitative risk assessment of AI, particularly in the context of the EU AI Act. The framework addresses the complexities of legal compliance and fundamental rights protection by integrating definitional balancing and defeasible reasoning. Definitional balancing employs proportionality analysis to resolve conflicts between competing rights, while defeasible reasoning accommodates the dynamic nature of legal decision-making. Our approach stresses the need for an analysis of AI deployment scenarios and for identifying potential legal violations and multi-layered impacts on fundamental rights. On the basis of this analysis, we provide philosophical foundations for a logical account of AI risk analysis. In particular, we consider the basic building blocks for conceptually grasping the interaction between AI deployment scenarios and fundamental rights, incorporating in defeasible reasoning definitional balancing and arguments about the contextual promotion or demotion of rights. This layered approach allows for more operative models of assessment of both high-risk AI systems and General Purpose AI (GPAI) systems, emphasizing the broader applicability of the latter. Future work aims to develop a formal model and effective algorithms to enhance AI risk assessment, bridging theoretical insights with practical applications to support responsible AI governance.