Technological change often prompts calls for regulation. Yet formulating regulatory policy in relation to rapidly-changing technology is complex. It requires an understanding of the politics of technology, the complexity of the innovation process, and its general impact on society. Chapter 3 introduces a variety of academic literatures across the humanities, law and the social sciences that offer insights on understanding technological change that have direct relevance to the challenges of regulating new and emerging technology. The chapter discusses different strands of scholarship, ranging from the history of technology, innovation studies and the growing field of law and technology that have until now remained largely fragmented and siloed, focusing primarily on digital technologies.

This chapter explores the reasonable person’s encounter with entities that possess artificial intelligence (AI). A discussion of this encounter is particularly important, since it has been argued that the advent of AI will lead to the demise of the reasonable person. The first section focuses on the ability of the reasonable person standard to assess the behaviour of machines or algorithms that act on behalf of humans and lack autonomous decision-making capacities. The second section considers proposals to replace the reasonable person standard with a reasonable robot or reasonable AI standard. The section also asks to what extent the reasonable person standard can be used to assess the behaviour of autonomous digital agents that act autonomously. The third section discusses contemporary proposals to subjectivise law through big data, in a manner that would dispense with the need for a reasonable person standard, since everyone would be measured with reference to their own personal standard.

Chapter 1 ties together the problems of central elements of privacy law: the individual choice-based system, the fair information principles that originated it, the view that privacy is about secrecy, and dichotomies such as public versus private. We don’t have actual choices about our data beyond mechanically agreeing to privacy policies because we lack outside options and information such as what the choice means and what risk we’re taking on by agreeing. The choice-based approach creates a false binary of secret and open information when, in reality, privacy is a spectrum. The idea that someone, at any given time, has either total privacy or no privacy at all is unfounded. Additionally, data are bundled: you can’t reveal just one thing without letting companies infer other things. Reckoning with this reality defeats the popular “I have nothing to hide” argument, which traces back to Joseph Goebbels.

Artificial intelligence (AI) and automated decision-making (ADM) tools promise money and unmatched power to banks and governments alike. As the saying goes, they will know everything about their citizens and customers and will also be able to predict their behaviour, preferences, and opinions. Global consulting firm McKinsey estimates that AI technologies will unlock $1 trillion in additional value for the global banking industry every year.1 Governments around the world are getting on the AI bandwagon, expecting increased efficiency, reduced costs, and better insights into their populations.

In this set of reflections, Sir David Baragwanath, former Justice of the Court of Appeal of New Zealand, part-time President of the Court of Appeal of Samoa and Appellate Judge of the Special Tribunal for Lebanon in The Hague, considers some of the ways in which judges and lawyers situate themselves within the familiar and the foreign. He urges reflection on the challenge of the judicial oath to ‘do right to all manner of people after the laws and usages of this realm without fear, favour, affection or ill-will’, as enriched by the basic judicial precepts of modestie et audace – caution – and mains tremblantes – the need for care, sensitivity and humility – to control personal predilections and learn and comprehend the distinctive values that underlie what, to an outsider, is novel jurisprudence. Judges ought to strive for a ‘periscope’ approach, in order to penetrate the mists of their own education and experience and search for answers congruent with the values of the unfamiliar law or society illuminated by a vision of its highest standards.

Describing drone programs as a network of interacting and interdependent factors including the contemporary technological capacities of drones, law and military strategy is one of the main aspects of this study. All chapters identify where and how these factors converge or diverge and examine the result of this interaction. This description shows that combat drone technology facilitates anticipatory warfare – the scope of which is indefinite in time and space – and that the law is rearranged around anticipation. Further examining the socio-techno-legal phenomena produced by drone programs, the book explores the long-term effects produced by drone programs over populations living under drones as well as the international legal order. This book can be thought of as an act of compiling the textual, bureaucratic, and material traces of these programs in order to lay bare the infrastructure that is extending warfare in time and space and exacerbating state power.

Drone programs in the counterterrorism context rest on the use of force in self-defense not against an (imminent) act, but against individuals in the light of their personal or behavioral characteristics. Because drone programs are motivated by the objective of permanently addressing future threats before they materialize, technology and legal rhetoric are used as instruments to authorize action against individuals who are not presently perpetrating terrorist acts, nor even clearly preparing, such acts. Some states active in the transnational war on terror have proposed a legal framework for the continuous anticipation of armed attacks against individuals who show signs of hostile intent. These changes in military strategy and legal discourse are not merely the result of how states decide to use force in the counterterrorism context, but also of what technology allows them to do. As such, drones facilitate and arguably intensify the phenomena of the individualization and dematerialization of the use of force. Although the interpretation of self-defense proposed by some states active in the war on terror is still highly contested on some points, the chapter shows that even if some limitations remain, concessions to the extensive interpretation of some limitations appear to have a direct cascade effect on the remaining checks because these limitations are interconnected.

Compared to other highly skilled labour markets, the legal profession has been slow to adopt technological changes, but lawyers have been downright speedy compared to courts. Courts already generate voluminous amounts of data, but restrict access to it. The private sector, recognizing how legal data can help its clients, willingly incurs the costs to gather this data and develop proprietary tools to analyze it. As this trend continues, access to justice will worsen, further benefitting wealthier clients over opposing litigants as well as the courts, for no other reason than that courts will lag in their ability to efficaciously decide judicial matters. The judiciary—across all levels—could reverse this trend. The first step is to develop a more robust institutional framework for making court data publicly available. The second step is a willingness among courts to analyze this data when issuing decisions, both procedural and sustantive. Doing so requires courts to develop core competencies in existing and emerging legal technology. Democratizing access to judicial data will diminish the advantage currently enjoyed by affluent litigants, but accrue to the benefit of everyone else—including courts themselves.

It is difficult to come up with any events after World War II that have led our entire global society to recognise that before The Times They Are A‐Changin’1 as clearly as today’s global crisis has done. The COVID-19 pandemic and its aftermath have revealed that almost everything we once considered stable and sustainable is actually built on quite shaky ground. But the crisis has also brought out the best in our coexistence, seeing that societies in many countries have shown that they are capable of finding creative solutions to overcome the current challenges. Digital technologies have played a crucial role in the world’s response to the COVID-19 crisis. Just think of modern methods of telecommunication such as video conferencing, which have made an immense contribution to maintaining the economy and work processes, or the various corona tracking apps, which try to help stopping the spread of the virus. It can be assumed that the harmful consequences of the pandemic would have grown even greater if those digital solutions had not been available. Just as almost every area of life is affected by the pandemic, so are the law itself and legal practice.

By 2020 law firms will be faced with a “tipping point” for a new talent strategy. Now is the time for all law firms to commit to becoming AI-ready by embracing a growth mindset, set aside the fear of failure and begin to develop internal AI practices.1

Though worries about the impact of new technology have accompanied many inventions, AI is unusual in that some of the starkest recent warnings have come from those most knowledgeable about the field. Many of these concerns are linked to ‘general’ or ‘strong’ AI, meaning the creation of a system that is capable of performing any intellectual task that a human could – and raising complex questions about the nature of consciousness and self-awareness in a non-biological entity. The possibility that such an entity might put its own priorities above those of humans is non-trivial, but this book focuses on the more immediate challenges raised by ‘narrow’ AI – meaning systems that can apply cognitive functions to specific tasks typically undertaken by a human. The book is organized around the following sets of problems: How should we understand the challenges to regulation posed by the technologies loosely described here as ‘AI systems’? What regulatory tools exist to deal with those challenges and what are their limitations? And what more is needed – rules, institutions, actors – to enable us to reap the benefits offered by AI while minimizing avoidable harm?