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This chapter enquires into the use of big data analytics and prediction of judgment to inform both law and legal decision-making. The main argument is that the use of data-driven ‘legal technologies’ may transform the ‘mode of existence’ of law as-we-know-it, whose characteristics depend on its text-based nature. To explain why and how computational ‘law’ would be different, the author deciphers the mathematical assumptions of machine learning and natural language processing, opening the black box of algorithmic ‘insights’ at the level of its underlying research design. This allows her to compare the force of such computational ‘law’ with the force of law as-we-know-it. She then identifies some of the challenges as to legal protection, demonstrating the need for ‘by design’ approaches to anchor rule of law safeguards in the architecture of computational ‘law’, clarifying how and why ‘legal protection by design’ is not equivalent with ‘legal by design’ or ‘techno-regulation’.

This paper is a draft entry for an encyclopedia. It aims to provide an overview rather than an in-depth discussion. To begin with, we need to come to terms with the question of what is meant with AI, avoiding both over- and underinclusive definitions. In section II, I first explore the definitional conundrum within the research domain of AI, followed by an account of how various public bodies that prepare AI legislation aim to define the scope of their object. In section III, I provide a brief overview of the different approaches to dedicated AI legislation by the OECD, the US, China and the EU. Finally, in section IV, I discuss the Brussels effect of the EU’s AI Act that may diffuse the EU approach across a variety of jurisdictions whose corporations wish to compete on the internal market of the EU.

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From a computer science perspective, bias may refer to the productive bias that enables ML, both at the level of picking the training set and at the level of training the algorithms. It reminds one of David Wolpert’s ‘no free lunch theorem’, if not of Humean scepticism or Gadamer’s acknowledgment of constitutive presumptions. This e.g. relates to the trade-off between the size of a training set, its relevance, the types of algorithms used, and the accuracy and/or speed of the results. From a societal perspective, bias may refer to unfair treatment or even unlawful discrimination. It is crucial to distinguish inherent computational bias from the unwarranted impact of unfair or wrongful bias, while teasing out where they meet and how they interact. This includes an inquiry into the ethical assessments of ML bias, based on the fact that ML applications are reconfiguring the ‘choice architectures’ of our online and offline environments. Finally, I will briefly argue that ethics will not do when confronting the framing powers of machine bias, highlighting the need to bring the design choice that determine these framing powers under the Rule of Law.

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This chapter confronts the foundational challenges posed to legal theory and legal philosophy by the surge of computational law. Two types of computational law are at stake. On the one hand we have artificial intelligence in the legal realm that will be addressed as data-driven law, and on the other hand we have the coding of self-executing contracts and regulation in the blockchain, as well as other types of automated decision making (ADM), addressed as code-driven law. Data-driven law raises problems due to its autonomic operations and the ensuing opacity of its reasoning. Code-driven law presents us with a conflation of regulation, execution and adjudication. Though such implications are very different, both types of computational law share assumptions based on the calculability and computability of legal practice and legal research. Facing the assumptions and implications of data- and code-driven law the chapter will first investigate the affordances of current, text-driven law, and relate some of the core tenets of the Rule of Law to those affordances. This will lead to an enquiry into three questions that informed this chapter: do code- and data-driven law transform the mode of existence of modern positive law, and if so how? do these new legal tools affect the checks and balances of the rule of law, and if so how? and, do they uproot legal protection, and if so how?

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This chapter considers the three major domains in law and the study of law: private, public, and criminal law. These domains have their own principles, vocabularies, and structures, each geared to the type of relationships they aim to regulate and constitute. This chapter first explains how these domains differ based on a set of conceptual distinctions, such as absolute and relative rights, legal subjects and legal objects, mandatory and default law. After describing law as a unity of primary and secondary rules and their underlying principles (in chapter 2), this chapter describes law as a system of legal relations between legal subjects, with regard to legal objects. This understanding provides the foundations for the introduction of the core structure, vocabulary, and underlying principles of each domain, highlighting the difference between supposedly horizontal relations in private law and the vertical relations of public and criminal law. This, for instance, connects with the prominence of the legality principle in constitutional, administrative, and criminal law, whereas individual autonomy, fairness, and societal trust inform the rules and principles of private law.

This chapter covers privacy and data protection. This entails a series of legal requirements for development and design, for the default settings, and for the employment of computer architectures. In addition, the chapter defines the right to privacy as a subjective right, attributed by objective law, which may be national (constitutional) law, international human rights law, or supranational law (EU fundamental rights law). The chapter first confronts the landscape of human rights law at the global, national, and EU level. It then inquires into the right of privacy, as guaranteed under the ECHR and the Charter of Fundamental Rights of the European Union (CFREU), and finally provides an extensive analysis of the new fundamental right to data protection, as guaranteed by the CFREU and protected by the General Data Protection Regulation (GDPR).

This chapter faces the question of law's ‘mode of existence’, by asking what law does—and how. To accomplish this, the chapter explains the concept of the ‘sources of law’ and the nature of legal reasoning, notably the attribution of legal effect when specified legal conditions apply. The crucial distinction between primary (regulative) and secondary (constitutive) rules is discussed, thus demonstrating that law is not a ‘bag of rules’ but a dynamic architecture of legal norms (rules and principles). Finally, we address the question of the relationship between law, democracy, and the rule of law. To qualify as law, a normative framework must aim to sustain, develop, and balance certain values—even though they may be incompatible in concrete cases. These constitutive values are defined as legal certainty, justice, and instrumentality.

This concluding chapter investigates the distinction between law, code, and ethics, as well as their interrelationship and their interaction. It is intended for those interested in the nexus of law and ethics, in the light of code- and data-driven information and communication infrastructures (ICIs). One of the main differences between law and ethics is that law provides closure whereas ethics remains in the realm of reflection as it lacks the force of law. However, a second difference turns the previous statement inside out: whereas law and the rule of law introduce checks and balances and demand democratic participation (at least in constitutional democracies), ethics may be decided by tech developers or behind the closed doors of the board room of corporate business enterprise. It can thus obtain the force of technology. Paradoxically, once ethics gains the force of technology, the space for the practice of ethics is reduced.

This book introduces law to computer scientists. Computer scientists develop, protect, and maintain computing systems in the broad sense of that term, whether hardware, software, or data. They may be focused on e.g. digital security, or on embedded systems, or on software science. The aim of this book is to convey the internal logic of legal practice, firmly grounded in legal theory. It attempts to bridge the gap between two scientific practices, and probe the middle ground to present a reasonably coherent picture of the grammar and vocabulary of law and the rule of law. This attempt is geared toward those with no wish to become lawyers but who are nevertheless forced to consider the salience of legal rights and obligations. Simultaneously, this book aims to help lawyers to review their own trade. It is a volume on law in an onlife world, presenting a coherent picture of how modern law operates, how it emerged in the context of printed text, and how it confronts its new, data-driven environment.

This chapter considers legal personhood for artificial agents. It engages with the legal issues of autonomous systems, asking the question whether (and if so, under what conditions) such systems should be given the status of a legal subject, capable of acting in law and/or being held liable in law. The main reason for considering this option is the rise of semi-autonomous systems that display unpredictable behaviour, causing harm not foreseeable by those who developed, sold, or deployed them. Under current law it might be difficult to establish liability for such harm. To investigate these issues, the chapter explains the concepts of legal subjectivity and legal agency, before inquiring into the nature of artificial agency. Finally, the chapter assesses whether attributing legal personhood to artificial agents would solve the problem of private law liability for harm caused by semi-autonomous systems.

This chapter is an introduction to the domain of intellectual property (IP) rights, notably copyright. For computer scientists, the most relevant part of copyright law concerns copyright on computer programs, or software. Copyright on software is the enabling precondition for the General Public Licence (GPL) and the open source initiative. Before discussing copyright on software, however, this chapter first investigates the position of IP law in the context of constitutional democracy and clarifies that IP law is private law. From there, the chapter provides an overview of the various types of IP that are most relevant, after which it turns to the history, objectives, and scope of copyright protection. Finally, this chapter discusses EU copyright law and the issues of open source and free access.

This chapter turns to international and supranational law. It focuses on international law in the context of the Council of Europe (CoE) and on supranational law in the context of the European Union (EU). The chapter first discusses the concept of jurisdiction and its formative status in national, international, and supranational law, after which it provides a more in-depth overview of international law and supranational law. This involves a discussion of the relationship between national constitutions and the binding force of international treaties, the role of consent and custom in the force of international law, and the legal effect of fundamental principles and mandatory law that no state can ignore. Next, the special case of the supranational EU jurisdiction is introduced, notably the distribution of sovereignty between the member states and the Union and the most important legislative instruments: regulations and directives. Finally, the mutually constitutive relationship between internal and external sovereignty is connected with the idea of an international rule of law that addresses states as fiduciary agents of the international legal order.

This chapter explores the legal framework regarding cybercrime, with a focus on Europe. In the case of cybercrime, competent authorities face a moving target, as technological developments, both on the side of perpetrators and on the side of policing and forensics, often outwit prevalent and tested strategies against traditional crime. This chapter first raises the question of what makes cybercrime ‘cyber’, and then introduces the international and supranational legal frameworks that are meant to cope with cybercrime, with a focus on the Cybercrime Convention. Finally, the chapter offers a reflection on the image of the weighing scale where it comes to balancing safety and security against rights and freedoms.

This chapter focuses on how machine learning (ML) and distributed ledger technologies (DLTs) change the environment of the law, the substance of legal goods, and on the extent to which these changes affect legal protection. ML applications, for example, can decide a person's credit worthiness or employability. Moreover, DLTs can, for instance, self-execute transactions and policies without and beyond the law. One of the main challenges here thus concerns the regulatory effects of these novel technologies and the potential incompatibility of legal protection with techno-regulation (defined as the regulatory effects of a technology, whether or not intended). This challenge will be discussed in terms of automated compliance (‘legal by design’) and technological articulation of fundamental rights (‘legal protection by design’).

This introductory chapter briefly situates the rise of modern positive law as an affordance of a specific information and communication technology (ICT)—namely the printing press, which is better described as an information and communication infrastructure (ICI). One of the challenges that modern positive law faces is the transformation of the ICI from books and mass media to a digital and computational ICI. Cyberspace here refers to cyber (steering) and connects with cybernetics (remote control of one's environment by means of feedback loops). This highlights that the new ICI is fundamentally different from speech, writing, printing, and mass media. Cyberspace is not merely a digitized version of physical space, but refers to an architecture with two novel characteristics: its hyperconnectivity and its computational pre-emptions.

This chapter considers instances where ICT applications cause physical, material, economic, or emotional harm, with a focus on third party liability or tort law. The chapter should be read as an important example of how private law liability may step in to deter the development, sale, or usage of faulty ICT. It discusses the relevant legal conditions of damage, causation, fault liability, and strict liability, ending with questions around compensation and deterrence as the overarching goals of tort law.

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Multimedia research has long moved beyond laboratory experiments and is being rapidly deployed in real-life applications including advertisements, search, security, automated driving, and healthcare. Hence, the developed algorithms now have a direct impact on the individuals using the abovementioned services and the society as a whole. While there is a huge potential to benefit the society using such technologies, there is also an urgent need to identify the checks and balances to ensure that the impact of such technologies is ethical and positive. For instance, if the multimedia technologies are being used to detect and protect pedestrians from accidents by autonomous vehicles, then the pedestrian detection performance needs to be equitable across demographic descriptors, such as gender and race of the pedestrians. Similarly, while logs of driving behaviors are important in many applications, making such information available to corporate entities and third parties could raise important privacy challenges. This position article aims to: first, increase the awareness of such concepts and existing legal constraints in the multimedia research community, second, initiate a discussion on community guidelines on how to conduct multimedia research in a lawful and ethical manner, and third, identify some important research directions to support a vision of lawful and ethical multimedia research.

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This Article takes the perspective of law and philosophy, integrating insights from computer science. First, I will argue that in the era of big data analytics we need an understanding of privacy that is capable of protecting what is uncountable, incalculable or incomputable about individual persons. To instigate this new dimension of the right to privacy, I expand previous work on the relational nature of privacy, and the productive indeterminacy of human identity it implies, into an ecological understanding of privacy, taking into account the technological environment that mediates the constitution of human identity. Second, I will investigate how machine learning actually works, detecting a series of design choices that inform the accuracy of the outcome, each entailing trade-offs that determine the relevance, validity and reliability of the algorithm’s accuracy for real life problems. I argue that incomputability does not call for a rejection of machine learning per se but calls for a research design that enables those who will be affected by the algorithms to become involved and to learn how machines learn — resulting in a better understanding of their potential and limitations. A better understanding of the limitations that are inherent in machine learning will deflate some of the eschatological expectations, and provide for better decision-making about whether and if so how to implement machine learning in specific domains or contexts. I will highlight how a reliable research design aligns with purpose limitation as core to its methodological integrity. This Article, then, advocates a practice of “agonistic machine learning” that will contribute to responsible decisions about the integration of data-driven applications into our environments while simultaneously bringing them under the Rule of Law. This should also provide the best means to achieve effective protection against overdetermination of individuals by machine inferences.