The increasing workplace use of artificially intelligent (AI) technologies has implications for the experience of meaningful human work. Meaningful work refers to the perception that one’s work has worth, significance, or a higher purpose. The development and organisational deployment of AI is accelerating, but the ways in which this will support or diminish opportunities for meaningful work and the ethical implications of these changes remain under-explored. This conceptual paper is positioned at the intersection of the meaningful work and ethical AI (...) literatures and offers a detailed assessment of the ways in which the deployment of AI can enhance or diminish employees’ experiences of meaningful work. We first outline the nature of meaningful work and draw on philosophical and business ethics accounts to establish its ethical importance. We then explore the impacts of three paths of AI deployment (replacing some tasks, ‘tending the machine’, and amplifying human skills) across five dimensions constituting a holistic account of meaningful work, and finally assess the ethical implications. In doing so we help to contextualise the meaningful work literature for the era of AI, extend the ethical AI literature into the workplace, and conclude with a range of practical implications and future research directions. (shrink)

While autonomous vehicles (AVs) are not designed to harm people, harming people is an inevitable by-product of their operation. How are AVs to deal ethically with situations where harming people is inevitable? Rather than focus on the much-discussed question of what choices AVs should make, we can also ask the much less discussed question of who gets to decide what AVs should do in such cases. Here there are two key options: AVs with a personal ethics setting (PES) or an (...) “ethical knob” that end users can control or AVs with a mandatory ethics setting (MES) that end users cannot control. Which option, a PES or an MES, is best and why? This chapter argues, by drawing on the choice architecture literature, in favor of a hybrid view that requires mandated default choice settings while allowing for limited end user control. (shrink)

People give surprising weight to others’ expectations about their behaviour. I argue the practice of conforming to others’ expectations is ethically well-grounded. A special class of ‘reasonable expectations’ can create prima facie obligations even in cases where the expectations arise from contingent pre-existing practices, and the duty-bearer has not created them, or directly benefited from them. The obligation arises because of the substantial goods that follow from such conformity—goods capable of being endorsed from many different ethical perspectives and implicating key (...) moral factors such as consent, fairness, respect, autonomy, and reciprocity. Given the innumerable situations where such expectations can arise, their ethical significance is critical both practically and philosophically. (shrink)

“Meta-argument allegations” consist of protestations that an interlocutor’s speech is wrongfully offensive or will trigger undesirable social consequences. Such protestations are meta-argument in the sense that they do not interrogate the soundness of an opponent’s argumentation, but instead focus on external features of that argument. They are allegations because they imply moral wrongdoing. There is a legitimate place for meta-argument allegations, and the moral and epistemic goods that can come from them will be front of mind for those levelling such (...) allegations. But I argue there is a dark side to such allegations, and their epistemic and moral costs must be seriously weighed. Meta-argument allegations have a concerning capacity to derail discussions about important topics, stymieing argumentational interactions and the goods they provide. Such allegations can license efforts to silence, punish and deter—even as they provoke the original speaker to retaliate in kind. Used liberally, such allegations can escalate conflicts, block open-mindedness, and discourage constructive dialogues. In response, I defend “argumentational tolerance”—a principled wariness in employing meta-argument allegations—as a virtue of ethical argument. (shrink)

How social media impacts the autonomy of its users is a topic of increasing focus. However, much of the literature that explores these impacts fails to engage in depth with the philosophical literature on autonomy. This has resulted in a failure to consider the full range of impacts that social media might have on autonomy. A deeper consideration of these impacts is thus needed, given the importance of both autonomy as a moral concept and social media as a feature of (...) contemporary life. By drawing on this philosophical literature, we argue that autonomy is broadly a matter of developing autonomy competencies, having authentic ends and control over key aspects of your own life, and not being manipulated, coerced, and controlled by others. We show how the autonomy of users of social media can be disrespected and harmed through the control that social media can have over its users’ data, attention, and behaviour. We conclude by discussing various recommendations to better regulate social media. (shrink)

Kant begins his Lectures on Pedagogy by stating, “[t]he human being is the only creature that must be educated” (Kant, 2007, 9:441), and he argues that it is through education that we can transform our initial “animal nature into human nature” (ibid. 2007, 9:441). Kant understands education as involving an ordered process of care, discipline, instruction and formation through enculturating, civilizing and moralizing (Formosa 2011). Further, Kant envisages that we should pursue as a species the “moral perfection” that is the (...) “final destiny of the human race” through education (Collins, 1997, 27:470; see Dean, 2014). However, to engage in this pursuit Kant believes that, through education and social change, we have to regulate our “animal nature” and counter the moral corruption of our species, which he calls the “radical innate evil in human nature (not any the less brought upon us by ourselves)” (Kant, 1998, 6:32). If humanity is to pursue its final destiny of moral perfection, then education will need to respond responsibly to the propensity to evil that is deeply rooted in us as finite and imperfect rational beings living in imperfect and at times even in morally corrupted social conditions. This paper outlines some of the relevant issues. (shrink)

As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive analysis (...) of the relevant arguments for and against creating AMAs, and we argue that all things considered we have strong reasons to continue to responsibly develop AMAs. The key contributions of this paper are threefold. First, to provide the first comprehensive response to the important arguments made against AMAs by Wynsberghe and Robbins (in “Critiquing the Reasons for Making Artificial Moral Agents”, Science and Engineering Ethics 25, 2019) and to introduce several novel lines of argument in the process. Second, to collate and thematise for the first time the key arguments for and against AMAs in a single paper. Third, to recast the debate away from blanket arguments for or against AMAs in general, to a more nuanced discussion about the use of what sort of AMAs, in what sort of contexts, and for what sort of purposes is morally appropriate. (shrink)

For Kant, we cannot understand how to approach moral education without confronting the radical evil of humanity. But if we start out, as Kant thinks we do, from a morally corrupt state, how...

Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions of being (...) treated in a dignified and respectful way in various healthcare decision contexts. Participants were subject to a 2 (human or AI decision maker) x 2 (positive or negative decision outcome) x 2 (diagnostic or resource allocation healthcare scenario) factorial design. We found evidence of a “human bias” (i.e., a preference for human over AI decision makers) and an “outcome bias” (i.e., a preference for positive over negative outcomes). However, we found that for perceptions of respectful and dignified interpersonal treatment, it matters more who makes the decisions in diagnostic cases and it matters more what the outcomes are for resource allocation cases. We also found that humans were consistently viewed as appropriate decision makers and AI was viewed as dehumanizing, and that participants perceived they were treated better when subject to diagnostic as opposed to resource allocation decisions. Thematic coding of open-ended text responses supported these results. We also outline the theoretical and practical implications of these findings. (shrink)