Sven Nyholm

_The Ethics of Artificial Intelligence_ explores, analyzes, and investigates some of the most basic concepts, values, moral principles, and ethical dilemmas shaping contemporary human life. Old philosophical questions—such as puzzles about meaning in life, moral responsibility, or the nature and importance of consciousness—get new life and are given new twists in the contemporary age of artificial intelligence. From questions about the impact of AI on moral responsibility and meaning in life, to puzzles about generative AI and authorship, the possibility of artificial consciousness, control and value alignment problems, AI imitations of living or dead people, and on to the ethics of gambling with the future of humanity—this book tackles some of the most pressing issues of our time head on.

Recently, several large tech companies have pushed the notion of AI assistants into the public debate. These envisioned agents are intended to far outshine current systems, as they are intended to be able to manage our affairs as if they are personal assistants. In turn, this ought to give users a leg up, as one prominent tech exec has put it. However, it remains to be seen how these Personal AI Assistants (PAIAs) are implemented, and critical reflection on how and whether they can be implemented in a responsible way is needed. Currently, such agents are undertheorized and this may cause us to misunderstand their value and capacity. In this paper, we explore and critique the potential for responsible implementation by considering some design requirements based on the notion of meaningful human control. If we desire to have control over such assistants, then we need to be able to do so meaningfully and effectively. In looking at the design requirements, we run into the issue that their broad and differing capacities make any kind of design requirements hard because there are simply no standards to which we can measure PAIAs. Furthermore, it seems that the implementation of these assistants will be a matter of trade-offs both in capacities and in values, which will likely lead to enhancement for some rather than an improvement for all.

_A cutting-edge selection of current issues and explorations of the ethics of artificial intelligence_ As artificial intelligence continues to influence virtually every facet of modern life, _Contemporary Debates in the Ethics of Artificial Intelligence_ offers a timely and rigorous examination of the field's most pressing questions. Equally useful in the classroom or as a reference for interdisciplinary research, this volume fosters informed and critical engagement with the ethical dimensions of artificial intelligence in today's world. Curated by renowned scholars Sven Nyholm, Atoosa Kasirzadeh, and John Zerilli, _Contemporary Debates in the Ethics of Artificial Intelligence_ brings together a dynamic mix of established leaders and emerging voices from both philosophy and computer science. The result is a uniquely structured collection of debates that not only introduces key concepts—such as agency, moral status, and value alignment—but also challenges readers to engage deeply with controversies around bias, transparency, and the societal risks posed by AI technologies. Providing frameworks for engaging responsibly with current and future AI technologies, _Contemporary Debates in the Ethics of Artificial Intelligence:_ Presents a dual-perspective debate format that fosters critical thinking and comparative analysis Includes both foundational conceptual discussions and cutting-edge applied ethical issues Features original contributions from interdisciplinary experts in philosophy, law, cognitive science, and computer science Addresses timely topics such as algorithmic bias, opacity, value alignment, and the moral status of AI Explores forward-looking concerns, including the future of AI governance and long-term existential risks _Contemporary Debates in the Ethics of Artificial Intelligence_ is ideal for undergraduate, advanced undergraduate, and graduate-level courses in philosophy, computer science, public policy, and related disciplines. It is well-suited for courses such as Ethics of Artificial Intelligence, Technology and Society, and Digital Ethics in philosophy, computer science, political science, international relations, and data science programs.

Self‐driving cars hold out the promise of being much safer than regular cars. Yet they cannot be 100% safe. Accordingly, they need to be programmed for how to deal with crash scenarios. Should cars be programmed to always prioritize their owners, to minimize harm, or to respond to crashes on the basis of some other type of principle? The article first discusses whether everyone should have the same “ethics settings.” Next, the oft‐made analogy with the trolley problem is examined. Then follows an assessment of recent empirical work on lay‐people's attitudes about crash algorithms relevant to the ethical issue of crash optimization. Finally, the article discusses what traditional ethical theories such as utilitarianism, Kantianism, virtue ethics, and contractualism imply about how cars should handle crash scenarios. The aim of the article is to provide an overview of the existing literature on these topics and to assess how far the discussion has gotten so far.

When generative AI technologies generate novel texts, images, or music in response to prompts from users of these technologies, are the resulting outputs meaningful in all the ways that human‐created texts, images, or music can be meaningful? Moreover, who exactly should be considered as the author of these AI outputs? Are texts created by generative AI perhaps best considered as authorless texts? In my paper, I will relate the above‐mentioned questions to the topic of who (if anyone) can take credit for, or potentially be blameworthy for, outputs created with the help of large language models and other generative AI technologies. I will argue that there is an important asymmetry with respect to how easily people can be praiseworthy or blameworthy for outputs they create with the help of generative AI technologies: in general, it is much harder to be praiseworthy for impressive outputs of generative AI than it is to be blameworthy for harmful outputs that we may produce with generative AI. This has implications for the issues of meaning and authorship. Generative AI technologies are in important ways “gappy”: they create gaps with respect to meaning and authorship, as well as with respect to responsibility for their outputs.

Imagine that you are given access to an AI chatbot that compellingly mimics the personality and speech of a deceased loved one. If you start having regular interactions with this “thanabot,” could this new relationship be a continuation of the relationship you had with your loved one? And could a relationship with a thanabot preserve or replicate the value of a close human relationship? To the first question, we argue that a relationship with a thanabot cannot be a true continuation of your relationship with a deceased loved one, though it might support one’s continuing bonds with the dead. To the second question, we argue that, in and of themselves, relationships with thanabots cannot benefit us as much as rewarding and healthy intimate relationships with other humans, though we explain why it is difficult to make reliable comparative generalizations about the instrumental value of these relationships.

In her 1993 book Freedom within Reason, Susan Wolf discusses what she identifies as an asymmetry between the good and the bad: to qualify as doing good in a praiseworthy way, it is not necessary that one should have the ability to do otherwise, but in order to qualify as doing something bad in a blameworthy way, it is necessary that one has the ability to do otherwise. In this chapter, I relate this asymmetry between the good and the bad that Wolf discusses to a range of other asymmetries between the good and the bad that various philosophers – both historical figures and contemporary philosophers – have identified. I discuss different ways of thinking about the relations among these supposed asymmetries between the good and the bad, identify different ways in which one can relate to these ideas in one’s philosophical thinking, and lastly also argue that the long history of philosophical reflections on asymmetries between the good and the bad is interesting to contemporary discussions within applied ethics. In particular, I relate these ideas about asymmetries between the good and the bad to contemporary discussions about moral responsibility – and possible gaps in responsibility – within the ethics of artificial intelligence.

In my contribution to this book symposium on Emma Gordon’s book Human Enhancement and Well-Being, I discuss and respond to Gordon’s extensive discussion and criticisms of a skeptical argument regarding the desirability of love enhancements that I presented in a 2015 paper. I start by first explaining the overall project of Gordon’s book, make a general comment about her overall approach (which I am broadly sympathetic with), and then proceed to a detailed discussion of Gordon’s critical engagement with my 2015 argument. I defend my argument against Gordon’s interesting criticisms and argue that Gordon has not defused my skeptical challenge to the desirability of love enhancements, but I also end by identifying key points of agreement between me and Gordon. Specific topics discussed include the distinction between ways of loving and causes of loving, the value of ways of loving and the value of the causes of loving, and whether or not the ideal of robust love attachments can be seen as compatible attachments causally dependent on love enhancements.

Recent developments in AI and robotics enable people to create _personalised digital duplicates_ – these are artificial, at least partial, recreations or simulations of real people. The advent of such duplicates enables people to overcome their individual scarcity. But this comes at a cost. There is a common view among ethicists and value theorists suggesting that individual scarcity contributes to or heightens the value of a life or parts of a life. In this paper, we address this topic. We make five main points. First, that there is a plausible _prima facie_ case for the scarcity threat: AI may undermine the value of an individual human life by making us less scarce. Second, notwithstanding this prima facie threat, the role of scarcity in individual value is disputable and always exists in tension with the contrasting view that scarcity is a tragedy that limits our value. Third, there are two distinct forms of scarcity – instrumental and intrinsic – and they contribute to value in different ways. Fourth, digital duplication technology may undermine instrumental scarcity, to at least some extent, but the axiological consequences of this are highly variable. Fifth, digital duplication technology does not affect intrinsic scarcity, and may actually heighten it.

Abstract“Gamification” refers to adding game-like elements to non-game activities so as to encourage participation. Gamification is used in various contexts: apps on phones motivating people to exercise, employers trying to encourage their employees to work harder, social media companies trying to stimulate user engagement, and so on and so forth. Here, I focus on gamification with this property: the game-designer (a company or other organization) creates a “game” in order to encourage the players (the users) to bring about certain outcomes as a side effect of playing the game. The side effect might be good for the user (e.g., improving her health) and/or good for the company or organization behind the game (e.g., advertising their products, increasing their profits, etc.). The “players” of the game may or may not be aware of creating these side effects; and they may or may not approve of/endorse the creation of those side effects. The organizations behind the games, in contrast, are typically directly aiming to create games that have the side effects in question. These aspects of gamification are puzzling and interesting from the point of view of philosophical analyses of agency and responsibility for outcomes. In this paper, I relate these just-mentioned aspects of gamification to some philosophical discussions of responsibility gaps, the ethics of side effects (including the Knobe effect and the doctrine of double effect), and ideas about the relations among different parties’ agency.

As sophisticated artificial intelligence software becomes more ubiquitously and more intimately integrated within domains of traditionally human endeavor, many are raising questions over how responsibility (be it moral, legal, or causal) can be understood for an AI’s actions or influence on an outcome. So called “responsibility gaps” occur whenever there exists an apparent chasm in the ordinary attribution of moral blame or responsibility when an AI automates physical or cognitive labor otherwise performed by human beings and commits an error. Healthcare administration is an industry ripe for responsibility gaps produced by these kinds of AI. The moral stakes of healthcare are often life and death, and the demand for reducing clinical uncertainty while standardizing care incentivizes the development and integration of AI diagnosticians and prognosticators. In this paper, we argue that (1) responsibility gaps are generated by “black box” healthcare AI, (2) the presence of responsibility gaps (if unaddressed) creates serious moral problems, (3) a suitable solution is for relevant stakeholders to voluntarily responsibilize the gaps, taking on some moral responsibility for things they are not, strictly speaking, blameworthy for, and (4) should this solution be taken, black box healthcare AI will be permissible in the provision of healthcare.

Artificial intelligence-driven technology increasingly shapes work practices and, accordingly, employees’ opportunities for meaningful work (MW). In our paper, we identify five dimensions of MW: pursuing a purpose, social relationships, exercising skills and self-development, autonomy, self-esteem and recognition. Because MW is an important good, lacking opportunities for MW is a serious disadvantage. Therefore, we need to know to what extent employers have a duty to provide this good to their employees. We hold that employers have a duty of beneficence to design for opportunities for MW when implementing AI-technology in the workplace. We argue that this duty of beneficence is supported by the three major ethical theories, namely, Kantian ethics, consequentialism, and virtue ethics. We defend this duty against two objections, including the view that it is incompatible with the shareholder theory of the firm. We then employ the five dimensions of MW as our analytical lens to investigate how AI-based technological innovation in logistic warehouses has an impact, both positively and negatively, on MW, and illustrate that design for MW is feasible. We further support this practical feasibility with the help of insights from organizational psychology. We end by discussing how AI-based technology has an impact both on meaningful work (often seen as an aspirational goal) and decent work (generally seen as a matter of justice). Accordingly, ethical reflection on meaningful and decent work should become more integrated to do justice to how AI-technology inevitably shapes both simultaneously.

Advancements in artificial intelligence and (social) robotics raise pertinent questions as to how these technologies may help shape the society of the future. The main aim of the chapter is to consider the social and conceptual disruptions that might be associated with social robots, and humanoid social robots in particular. This chapter starts by comparing the concepts of robots and artificial intelligence and briefly explores the origins of these expressions. It then explains the definition of a social robot, as well as the definition of humanoid robots. A key notion in this context is the idea of anthropomorphism: the human tendency to attribute human qualities, not only to our fellow human beings, but also to parts of nature and to technologies. This tendency to anthropomorphize technologies by responding to and interacting with them as if they have human qualities is one of the reasons why social robots (in particular social robots designed to look and behave like human beings) can be socially disruptive. As is explained in the chapter, while some ethics researchers believe that anthropomorphization is a mistake that can lead to various forms of deception, others — including both ethics researchers and social roboticists — believe it can be useful or fitting to treat robots in anthropomorphizing ways. The chapter explores that disagreement by, among other things, considering recent philosophical debates about whether social robots can be moral patients, that is, whether it can make sense to treat them with moral consideration. Where one stands on this issue will depend either on one’s views about whether social robots can have, imitate, or represent morally relevant properties, or on how people relate to social robots in their interactions with them. Lastly, the chapter urges that the ethics of social robots should explore intercultural perspectives, and highlights some recent research on Ubuntu ethics and social robots.

This paper discusses two opposing views about the relation between artificial intelligence (AI) and human intelligence: on the one hand, a worry that heavy reliance on AI technologies might make people less intelligent and, on the other, a hope that AI technologies might serve as a form of cognitive enhancement. The worry relates to the notion that if we hand over too many intelligence-requiring tasks to AI technologies, we might end up with fewer opportunities to train our own intelligence. Concerning AI as a potential form of cognitive enhancement, the paper explores two possibilities: (1) AI as extending—and thereby enhancing—people’s minds, and (2) AI as enabling people to behave in artificially intelligent ways. That is, using AI technologies might enable people to behave as if they have been cognitively enhanced. The paper considers such enhancements both on the level of individuals and on the level of groups.

In this chapter, I use the expression “robotic animism” to refer to the tendency that many people have to interact with robots as if the robots have minds or a personality. I compare the idea of robotic animism with what philosophers and psychologists sometimes refer to as “mind-reading”, as it relates to human interaction with robots. The chapter offers various examples of robotic animism and mind-reading within different forms of human-robot interaction, and it also considers ethical and prudential arguments for and against attributing minds and a personality to robots. In the last section of the chapter, I also consider the intriguing question of whether any robots that exist today could be said to have some sort of minds in some non-trivial sense.

In this paper, we discuss the relation between recent philosophical discussions about meaning in life (from authors like Susan Wolf, Thaddeus Metz, and others) and the ethics of artificial intelligence (AI). Our goal is twofold, namely, to argue that considering the axiological category of meaningfulness can enrich AI ethics, on the one hand, and to portray and evaluate the small, but growing literature that already exists on the relation between meaning in life and AI ethics, on the other hand. We start out our review by clarifying the basic assumptions of the meaning in life discourse and how it understands the term ‘meaningfulness’. After that, we offer five general arguments for relating philosophical questions about meaning in life to questions about the role of AI in human life. For example, we formulate a worry about a possible meaningfulness gap related to AI on analogy with the idea of responsibility gaps created by AI, a prominent topic within the AI ethics literature. We then consider three specific types of contributions that have been made in the AI ethics literature so far: contributions related to self-development, the future of work, and relationships. As we discuss those three topics, we highlight what has already been done, but we also point out gaps in the existing literature. We end with an outlook regarding where we think the discussion of this topic should go next.

In this paper, we propose meaningfulness as one important evaluative criterion in individual climate ethics and suggest that most of our greenhouse gas emitting actions, behaviours, and lives are the opposite of meaningful: anti-meaningful. We explain why such actions etc. score negatively on three important dimensions of the meaningfulness scale, which we call the agential, narrative, and generative dimensions. We suggest that thinking about individual climate ethics also in terms of (anti-) meaningfulness illuminates important aspects of our troubled ethical involvement with CC and can make a fresh and fruitful contribution to existing discussions, which tend to focus on moral responsibility and obligations.

In the Technology Age, innovations in medical, communications, and weapons technologies have given rise to many new ethical questions: Are technologies always value-neutral tools? Are human values and human prejudices sometimes embedded in technologies? Should we merge with the technologies we use? Is it ethical to use autonomous weapons systems in warfare? What should a self-driving car do if it detects an unavoidable crash? Can robots have morally relevant properties? This is Technology Ethics: An Introduction provides an accessible overview of the sub-field of philosophy that focuses on the ethical implications of new technologies. Requiring no previous background in the subject, this reader-friendly volume explores ethical questions concerning artificial intelligence, robots, self-driving cars, brain implants, social media and communication technologies, and more. Throughout the book, clear and engaging chapters describe and discuss key discussions, issues, and themes while inviting readers to develop their own perspectives on a wide range of moral and ethical questions. * Discusses how various technologies influence and shape individuals and society both positively and negatively * Illustrates how emerging technologies affect traditional ideas about ethics and human self-understanding * Addresses the ethical complications of creating technologies that may lead to morally problematic consequences * Considers if the benefits of new technologies outweigh potential drawbacks, such as how people interact online through social media * Explores how established moral and ethical theories relate to new questions concerning advanced technologies Part of the popular This is Philosophy series published by Wiley-Blackwell, This is Technology Ethics: An Introduction is a must-read for undergraduate students taking a Technology Ethics course, researchers in the field, engineers, technology professionals, and general readers looking to learn more about the topic.