Sven Nyholm

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.

The absence of meaningfulness in life is meaninglessness. But what is the polar opposite of meaningfulness? In recent and ongoing work together with Stephen Campbell and Marcello di Paola respectively, I have explored what we dub ‘anti-meaning’: the negative counterpart of positive meaning in life. Here, I relate this idea of ‘anti-meaningful’ actions, activities, and projects to the topic of death, and in particular the deaths or suffering of those who will live after our own deaths. Connecting this idea of anti-meaning and what happens after our own deaths to recent work by Samuel Scheffler on what he calls ‘the collective afterlife’ and his four reasons to care about future generations, I argue that if we today make choices or have lifestyles that later lead to unnecessarily early deaths and otherwise avoidable suffering of people who will live after we have died, this robs our current choices and lifestyles of some of their meaning, perhaps even making them the opposite of meaningful in the long run.

The concept of a digital twin comes from engineering.1 It refers to a digital model of an artefact in the real world, which takes data about the artefact itself, data about other such artefacts, among other things, as inputs. The idea is that the maintenance of artefacts—such as jet engines—can be vastly improved if we work with digital twins that simulate actual objects. Similarly, personalised medicine might benefit from the digital modelling of body parts or even whole human bodies. A medical digital twin could use data about the patient, more general population data, and other inputs to generate predictions about the patient. This could lead to highly personalised interventions and nuanced judgments about the patient’s health. Matthias Braun2 discusses this intriguing prospect, asking how we should think about the way in which a digital twin could represent a patient. I will respond to Braun’s striking suggestion that we can regard a digital twin as an extension of the patient’s body. Notably, Braun does not compare his just-mentioned idea with the extended mind thesis popularised by Andy Clark and David Chalmers.3 But I am sure many readers will be reminded of the extended mind thesis. Accordingly, I will consider this comparison. I cannot discuss this comparison in detail, nor fully evaluate Braun’s suggestion. But I can say something about how we might approach this comparison, and provide some …

In fascinating recent work, Julian Savulescu and his various co‐authors argue that human love is one of the things we can improve upon using biomedical enhancements. Is that so? This article first notes that Savulescu and his co‐authors mainly treat love as a means to various other goods. Love, however, is widely regarded as an intrinsic good. To investigate whether enhancements can produce the distinctive intrinsic good of love, this article does three things. Drawing on Philip Pettit's recent discussion of ‘robustly demanding goods’, it asks what exactly we intrinsically desire in seeking love; it considers four possible outcomes involving attachment‐enhancements and attachments; and it considers two different pieces of news we might receive about our lovers' attachment to us (that it is, or that it is not, sustained with the help of enhancement‐technologies). Enhancement‐sustained attachment, it is concluded, is less desirable than the intrinsic good of love.

Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit people’s ability to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem.

The literature on ethics and user attitudes towards AVs discusses user concerns in relation to automation; however, we show that there are additional relevant issues at stake. To assess adolescents’ attitudes regarding the ‘car of the future’ as presented by car manufacturers, we conducted two studies with over 400 participants altogether. We used a mixed methods approach in which we combined qualitative and quantitative methods. In the first study, our respondents appeared to be more concerned about other aspects of AVs than automation. Instead, their most commonly raised concerns were the extensive use of AI, recommender systems, and related issues of autonomy, invasiveness and personal privacy. The second study confirmed that several AV impacts were negatively perceived. The responses were, however, ambivalent. This confirms previous research on AV attitudes. On one hand, the AV features were perceived as useful, while on the other hand, their impacts were negatively assessed. We followed theoretical insights form futures studies and responsible research and innovation, which helped to identify that there are additional user concerns than what has been previously discussed in the literature on public attitudes and ethics of AVs, as well what has been envisioned by car manufactures.

This paper discusses the robotization of the workplace, and particularly the question of whether robots can be good colleagues. This might appear to be a strange question at first glance, but it is worth asking for two reasons. Firstly, some people already treat robots they work alongside as if the robots are valuable colleagues. It is worth reflecting on whether such people are making a mistake. Secondly, having good colleagues is widely regarded as a key aspect of what can make work meaningful. In discussing whether robots can be good colleagues, the paper compares that question to the more widely discussed questions of whether robots can be our friends or romantic partners. The paper argues that the ideal of being a good colleague has many different parts, and that on a behavioral level, robots can live up to many of the criteria typically associated with being a good colleague. Moreover, the paper also argues that in comparison with the more demanding ideals of being a good friend or a good romantic partner, it is comparatively easier for a robot to live up to the ideal of being a good colleague. The reason for this is that the “inner lives” of our friends and lovers are more important to us than the inner lives of our colleagues.

The concept of meaningful work has recently received increased attention in philosophy and other disciplines. However, the impact of the increasing robotization of the workplace on meaningful work has received very little attention so far. Doing work that is meaningful leads to higher job satisfaction and increased worker well-being, and some argue for a right to access to meaningful work. In this paper, we therefore address the impact of robotization on meaningful work. We do so by identifying five key aspects of meaningful work: pursuing a purpose, social relationships, exercising skills and self-development, self-esteem and recognition, and autonomy. For each aspect, we analyze how the introduction of robots into the workplace may diminish or enhance the meaningfulness of work. We also identify a few ethical issues that emerge from our analysis. We conclude that robotization of the workplace can have both significant negative and positive effects on meaningful work. Our findings about ways in which robotization of the workplace can be a threat or opportunity for meaningful work can serve as the basis for ethical arguments for how to—and how not to—implement robots into workplaces.