This chapter discusses how AI bots help negotiate some of the intense emotions and sense of vulnerability that come with grief. It considers both the promise and peril of AI-powered grief work, as well as how this technology is already sculpting our emotional life more generally. The chapter argues that AI ‘griefbots’ may, for some, be a useful resource for negotiating their grief. First, emotions and absence experiences in everyday life are discussed. Then the chapter examines how AI bots are increasingly used to address these experiences, before turning to a consideration of AI in prolonged grief disorder. The chapter offers a possible application of AI griefbots in narrative-based interventions to prolonged grief disorder, and concludes by raising some worries in need of further consideration.

I argue that that the “current era” involves a revolutionary transformation in group mind phenomena as we add AI superintelligent machines to the things that (when they cooperate with humans) very likely generate group minds. The AI–human hybrid cooperatives are also facilitating what I argue (along with many other scholars) is a major evolutionary transition into a global group mind that encompasses the entire globe. I consider the impact that developments in superintelligent AI will have on group mind phenomena. I discuss, in particular, multi-agent AI systems that are capable of cooperating with other AI agents and with humans. AI–human hybrids will produce new forms of group mind phenomena characterized in part by techno-biotic forms of cognition.

Painful as it is for a Remain campaigner like me to admit, the EU has always been dire when it comes to policies for supporting innovation and technology. Even more painfully, things have worsened over the past ten years. Longstanding structural weaknesses in EU innovation policy date from well before the Brexit referendum in 2016. The European Union had dismally failed to create a regulatory environment conducive to technological innovation. As I found whenever I visited to Brussels as a No. 10 adviser under David Cameron, the policy instincts of European Commission officials were overwhelmingly rooted in market stability and risk avoidance – values that, while defensible in themselves, often produced unintended consequences for fast-moving sectors such as digital technology and life sciences. Take the EU’s data privacy rules, which were debated and developed for years before being finally implemented in 2018. As Cameron’s team repeatedly warned at the time, the compliance costs fell disproportionately on small and early-stage firms. Even before fines or litigation, the administrative burden for smaller organisations typically ran into tens of thousands of pounds.

Machines are becoming more autonomous and intelligent, capable of making decisions and interacting with their environment. As they become more ubiquitous in our daily lives, it becomes increasingly important to understand and model their behaviour. This chapter will discuss the concept of machine behaviour and its importance in various fields, including artificial intelligence, robotics and human–computer interaction. The chapter starts by defining machine behaviour and providing an overview of its key characteristics. It will then explore the different approaches to modelling and understanding machine behaviour, including rule-based systems, statistical models and deep learning techniques. The chapter also covers the challenges and limitations of modelling machine behaviour, including the black box problem, interpretability and ethics. It also focuses on the applications of machine behaviour in various domains, such as autonomous vehicles, robotics and cybersecurity. The chapter will highlight how machine behaviour models can help in improving the performance, safety and security of these systems. The chapter discusses the future of machine behaviour and its potential impact on society. The chapter will explore the ethical implications of autonomous machines, including issues of responsibility, accountability and transparency. It will also discuss the need for interdisciplinary research in machine behaviour.

Welfare economic theory seeks the justification for government intervention in markets, in market failure, and in distributional issues. An analysis of the market failures that exist in a specific industry or market can not only provide justification for government regulation or other kinds of intervention in general, but it can also suggest which type of intervention or regulation is optimal from a welfare economic perspective. This chapter addresses the question of how the emergence of news aggregator platforms and the introduction of generative AI in news production have affected the market failures that constitute the core problem underlying private investment in news production. The focus of the analysis is on the public good character of news and the positive externalities of news production. The question addressed is: Have the consequences of these existing market failures become more prominent or have they been resolved by these developments? Based on this analysis, the chapter discusses how this informs policy concerning these developments.

Narcissism in America is a maladaptive posture that infects individuals, organizations, social movements, and even the entire country. A comprehensive strategy to address narcissism in the future should include primary, secondary, and tertiary prevention. Young people can learn to not exploit or retaliate. Organizations should weed out narcissistic leaders who can corrupt the entire organization. Those eligible to vote should support candidates and issues that advance cooperation, reciprocity, and altruism. Future research should include countries like the Russian Federation to better understand how a democracy can take a dark turn toward autocracy. AI could express itself narcissistically, and this warrants thoughtful study.

This introduction offers an overview of the evolving role of artificial intelligence in civil dispute resolution, discussing current developments against the background of broader technological, regulatory and institutional contexts. It examines the dual forces of genuine innovation and persistent hype, clarifies the book’s open and technology-neutral definition of AI, and articulates an equally broad conception of civil dispute resolution encompassing adjudicative but also consensual, formal but also informal mechanisms. The introduction also outlines the book’s comparative ambition and structural organisation, ultimately framing AI as a transformative yet contested actor whose integration into justice systems demands careful, context-sensitive governance.

This chapter explores the interplay of playfulness and precarity in AI-mediated languaging. Drawing on examples from social media users experimenting with generative AI, the chapter illustrates how AI reshapes communication, linguistic practices, and social interaction. These playful engagements demonstrate AI’s capacity to expand linguistic creativity and produce novel forms of meaning, while simultaneously revealing its fragility and the ethical tensions inherent in its use. By exposing the cultural assumptions, power relations, and value judgments embedded in AI systems, such moments highlight the non-neutral and unpredictable nature of AI technologies. The chapter argues that while AI opens up new possibilities for expression, it also demands critical reflection on issues of power, identity, and social norms. Ultimately, these examples highlight the ‘dis’engagement with AI’s potentiality while recognising and addressing the risks it poses to language and society.

Though coverage denials and delays impose on physicians and patients (especially marginalized patients) substantial administrative burden, the persistence of this practice is inevitable. Drawing on interviews with patients and former health insurance executives, this chapter reflects on harms caused by prior authorization and offers a menu of state and federal solutions to expand access to care, while also reflecting on how the 2024 election results impact their likelihood. A growing complication is major insurers’ increasing reliance on AI tools to process prior authorizations and claims in seconds. Though many states have sought to lessen prior authorization burden in targeted ways, this reach is limited because the Employee Retirement Income Security Act preempts state policies that “relate to” much of employer-sponsored health insurance. Despite some appetite for reform in Congress, legislative efforts have stalled. The 2024 election results signal a likely acceleration of America’s reliance on privatization (especially Medicare Advantage), so it is especially important to understand the impact of these managed care practices and ways to mitigate their burdens.

The adoption of Artificial Intelligence (AI) in the maritime sector marks a significant technological advancement with broad implications for operational efficiency, crewing, and regulatory frameworks. While these innovations are expected to enhance safety, reduce operating costs, and promote environmental sustainability, they are also likely to introduce challenges related to workforce displacement, cybersecurity, and evolving labor regulations at sea. This chapter examines the impact of AI on the maritime workforce, more specifically seafarers. It explores how AI may affect crew size, the emergence of new roles, and new skills in the future. It also offers an analysis of the significant impact of AI on working conditions and labor rights at sea under international maritime regulations, particularly the Maritime Labour Convention (MLC), 2006, and the Standards of Training, Certification and Watchkeeping for Seafarers Convention (1978, STCW Convention), as amended. This chapter explores the intersection areas of AI and maritime law, focusing on the emerging regulatory frameworks, including the EU AI Act and the International Maritime Organization’s Maritime Autonomous Surface Ships (MASS) Code. The findings point out that while AI presents opportunities for improving the working conditions of seafarers, its use must adhere to acceptable labor standards, legal clarity, and robust cybersecurity measures.