Chapter 10 explores the evolving regulatory landscape surrounding Web3 technologies. It highlights the need for coordinated and adaptive regulations to foster innovation while managing potential risks. The chapter examines the impact of major crypto company collapses in 2022 on regulatory frameworks and emphasizes the importance of proactive measures to protect investors and mitigate risks. It delves into the regulatory landscapes in the United States, the European Union, China, and Web3-friendly countries such as the United Arab Emirates, Singapore, Germany, and Switzerland. The chapter covers key initiatives, including the Executive Order Ensuring Responsible Development of Digital Assets and the Responsible Financial Innovation Act in the United States, as well as stablecoin regulations and regulatory challenges related to decentralized autonomous organizations (DAOs). It also explores the intersection of the General Data Protection Regulation (GDPR) and Web3, emphasizing the challenges of privacy and compliance. Overall, the chapter provides a comprehensive overview of regulatory considerations in Web3, addressing innovation, consumer protection, financial stability, and privacy concerns. It emphasizes the importance of regulatory coordination and adaptation to promote innovation while safeguarding against potential risks.

This chapter discusses the use of AI ethics standardizations for robot governance. Specifically, the chapter considers challenges to the regulation of AI-enabled technology due to slow legislative processes that have not been able to keep pace with the rapid speed of technological advances. In addition to considering the regulation of critical AI technologies, the chapter also argues for a regulatory framework that relies on nonbinding and flexible AI ethics standards to ensure that stakeholders manage ethical, legal, and social implication (ELSI) risks that are inherent in daily human–robot interactions. By including AI ethics standards into the development process for humanoid and expressive robots, robot developers will be able to include principles of responsible innovation and research without conflicting with “hard laws” enacted for robot regulation. In this chapter, through two case studies, I explore the approach of ethical robot design, examine its potential and limitations, and demonstrate the utility of “ethically aligned design” and “social system design” frameworks in implementing legal human–robot interaction (L-HRI).

Chapter 2 leverages first principles thinking to reveal the seismic shift enabled by Web3’s self-sovereign Internet and decentralized economic architecture. Opportunities emerge in infrastructure, access, efficiency, accountability, and empowerment. On-chain data sharing and self-sovereign identity allow efficient bootstrapping in an open ecosystem. Decentralized finance increases financial access, while blockchain ID could facilitate inclusive programs such as universal basic income. By automating manual workflows, smart contracts and traceability boost efficiency. Immutable blockchain ledgers enhance transparency via innovations such as triple-entry accounting. The creator economy shifts power by enabling direct content monetization and ownership through NFT marketplaces, decentralized social platforms, and games. Despite adoption hurdles, Web3 fundamentally reshapes incentives around user control over identity, data, and value creation in a decentralized economy. Capturing the full potential requires reimagining economic systems, not just optimizing current models. This epochal shift promises to unlock tremendous value by aligning technology with empowerment in an open, user-centric Internet.

One of the ways in which artificial intelligence can be a useful tool in the scientific study of religion is in developing a computational model of how the human mind is deployed in spiritual practices. It is a helpful first step to develop a precise cognitive model using a well-specified cognitive architecture. So far, the most promising architecture for this purpose is the Interacting Cognitive Subsystems of Philip Barnard, which distinguishes between two modes of central cognition: intuitive and conceptual. Cognitive modelling of practices such as mindfulness and the Jesus Prayer involves a shift in central cognition from the latter to the former, though that is achieved in slightly different ways in different spiritual practices. The strategy here is to develop modelling at a purely cognitive level before attempting full computational implementation. There are also neuropsychological models of spiritual practices which could be developed into computational models.

This chapter comprehensively lays out all the possible ways that artificial intelligence (AI) might interact with Jewish sources as their relationship develops over the next many years. It divides the scope of the relationship into three parts. First, it engages with questions of moral agency and their potential interactions with Jewish law, and suggests that this path, while enticing, may not be particularly fruitful. Second, it suggests that Jewish historical sources generally distinguish human value from human uniqueness, and that there is therefore quite a bit of room to think of an AI as a person, if we so choose, without damaging the value of human beings. Finally, it considers how Jewish thought might respond to AI as a new height of human innovation, and how the human–AI relationship shares many characteristics with the God–human relationship as imagined in Jewish sources.

This chapter introduces issues of law, policy, and regulations for human interaction with robots that are AI enabled, expressive, humanoid in appearance, and that are anthropomorphized by users. These features are leading to a class of robots that are beginning to pose unique challenges to courts, legislators, and the robotics industry as they consider how the behavior of robots operating with sophisticated social skills and increasing levels of intelligence should be regulated. In this chapter we introduce basic terms, definitions, and concepts which relate to human interaction with AI-enabled and social robots and we review some of the regulations, statutes, and case law which apply to such robots and we do so specifically in the context of human–robot interaction. Our goal in this chapter is to provide a conceptual framework for the chapters which follow focusing on human interaction with robots that are becoming more like us in form and behavior.

This chapter on Human–Robot Interaction (HRI) focuses on the ways humans respond to and interact with social robots. It begins by delineating recent research into HRI and the factors influencing user interaction with social robots. The main interest of the chapter is on anthropomorphism, that is, the observed human tendency to assign human traits and characteristics to technology, and the implications this has for robot design. After critically analyzing anthropomorphic robot design and its implications for HRI, the chapter discusses the role of ethics in shaping the development of technology in general and social robots in particular. From the European Ethics Guidelines for Trustworthy AI – human agency, transparency, communication, and individual and societal well-being are presented here as concepts and principles of importance for the design of present and future social robots.

Chapter 6 addresses the problem of error estimation and resampling in both a theoretical and practical manner. The holdout method is reviewed and cast into the bias/variance framework. Simple resampling approaches such as cross-validation are also reviewed and important variations such as stratified cross-validation and leave-one-out are introduced. Multiple resampling approaches such as bootstrapping, randomization, and multiple trials of simple resampling approaches are then introduced and discussed.

Based primarily on the law of the Russian Federation, this chapter reviews the current state of intersectoral relations between different legal schemes that apply to the regulation of robots. To do so, the chapter discusses the complementarity and consistent attempt of legal scholars to integrate legal processes occurring within civil, administrative, and criminal law into a single comprehensive framework for robot regulation. As discussed in this chapter, the connection between the civil law principles of indemnification, liability insurance, and the consideration of criminal law provisions is essential for the establishment of an effective regulatory system for robotic devices, as well as for the construction of norms for the regulation of robots. The chapter argues that there are currently no well-accepted mechanisms in civil law to hold the developers for robots’ software accountable for resulting harm, which is a serious omission given the growing autonomy of robotic devices. Further, the chapter argues that it is essential to recognize controlled and semicontrolled robots as sources of increased danger to individuals and that the responsibility for the damage caused by controlled and semicontrolled robots should be assigned to the robot owners. The chapter concludes that the main criteria distinguishing civil law torts from criminal law offenses when considering harms to individuals resulting from interaction with robots are the degree of public danger and the extent of damage caused by the robotic technology.

Technology has been an integral part of biological life since the inception of terrestrial life. Evolution is the process by which biological life seeks to transcend itself in pursuit of more robust life. This chapter examines transhumanism as the use of technological means to enhance human biological function. Transhumanists see human nature as a work in progress and suggest that by responsible use of science, technology and other rational means, we shall become beings with vastly greater capacities and unlimited potential. Transhumanism has religious implications.

Chapter 2 reviews the principles of statistics that are necessary for the discussion of machine learning evaluation methods, especially the statical analysis discussion of Chapter 7. In particular, it reviews the notions of random variables, distributions, confidence intervals, and hypothesis testing.

This chapter briefly reviews various ways in which ethics have been implemented in AI-enabled devices such as humanoid and expressive robots, and how care for other forms of embedded AI is an important part of creating trustable and ethical AI systems. We look at nudging in particular, how robots experienced in social contexts could implement nudging, and the implications of nudging for four fundamental ethical values that underpin trust. We discuss this topic using examples and by presenting important questions that creators of AI-based nudging systems should ask themselves, before and after creating such systems.

This chapter explores issues for Islam in relation to religious themes arising from developments in artificial intelligence (AI), conceived both as a philosophical and scientific quest to understand human intelligence and as a technological enterprise to instrumentalise it for commercial or political purposes. The monotheistic teachings of Islam are outlined to identify themes in AI that relate to central questions in the Islamic context and to addresses nuances of Islamic belief that differentiate it from the other Abrahamic traditions in consideration of AI. This chapter draws together the existing sparse literature on the subject, including notable applications of AI in Islamic contexts, and draws attention to the role of the Muslim world as a channel and expositor of knowledge between the ancient and modern world in the pre-history of AI. The chapter provides foundations for future scholarship on Islam and AI and a resource for wider scholarship on the religious, societal and cultural significance of AI.