Fabio Tollon

The use of AI in school settings has received widespread attention in recent years. However, there are many unresolved practical and ethical issues surrounding educational AI. In this paper, we contribute to this ongoing debate by examining how AI affects the role and responsibilities of educators. We argue that educational AI will decrease moral entanglement, and consequently teachers’ sense of responsibility. On the one hand, this makes it questionable whether teachers will willingly assume new duties introduced by AI or whether others are justified in expecting them to do so. On the other, it raises concerns about broader shifts to teachers’ professional and personal values and commitments. Moral entanglement is the idea that one can become entangled with other entities based on relational features of our personal identity and commitments. Applied to teachers and students, this entanglement results in the emergence of certain responsibilities and a willingness to take responsibility, the strength of which will be mediated by the introduction of AI in the classroom. We argue that current mainstream AI tools will reduce the number and depth of teacher-student interactions, increase the distance between teachers and students, and alienate teachers by transforming their role in the classroom. Thus, these technologies will reduce moral entanglement between students, change teachers’ professional roles and teachers and decrease teachers’ sense of responsibility. On this basis, we discuss how the idea of moral entanglement can be used for the evaluation of the impact that instrumentally-minded interventions have on the relational work undertaken in care-centric professions.

Responsibility gaps arise when harm is caused by autonomous systems and we are unable to appropriately assign moral responsibility for that harm. This occurs because (i) no human being can be held accountable given the autonomous nature of the system that created the harm; and (ii) the system itself lacks the relevant features to be considered a responsible agent. Neither the humans who developed and deployed the system nor the machines themselves are responsible. Hence, the gap arises: there is no one to be held responsible for the harm, yet (unlike cases of natural disasters) we have the intuition that someone should be responsible. In this paper, we tap into the literature on conceptual engineering to explore two strategies regarding this issue. On the one hand, we can identify the risks of gaps and attempt to ameliorate the concept of moral responsibility in the hope of removing them. On the other hand, we can highlight the risks of conceptual revision and aim to preserve our current concept as it is. In this paper we explore the underutilized strategy of preservation with respect to RESPONSIBILITY and highlight the upsides of such an approach.

In this paper, we empirically and conceptually examine how distributed human–machine networks of labour comprise a form of underlying intelligence within Artificial Intelligence (AI), considering the implications of this for Responsible Artificial Intelligence (R-AI) innovation. R-AI aims to guide AI research, development and deployment in line with certain normative principles, for example fairness, privacy, and explainability; notions implicitly shaped by comparisons of AI with individualised notions of human intelligence. However, as critical scholarship on AI demonstrates, this is a limited framing of the nature of intelligence, both of humans and AI. Furthermore, it dismisses the skills and labour central to developing AI systems, involving a distributed network of human-directed practices and reasoning. We argue that inequities in the agency and recognition of different types of practitioners across these networks of AI development have implications beyond RAI, with narrow framings concealing considerations which are important within broader discussions of AI intelligence. Drawing from interactive workshops conducted with AI practitioners, we explore practices of data acquisition, cleaning, and annotation, as the point where practitioners interface with domain experts and data annotators. Despite forming a crucial part of AI design and development, this type of data work is frequently framed as a tedious, unskilled, and low-value process. In exploring these practices, we examine the political role of the epistemic framings that underpin AI development and how these framings can shape understandings of distributed intelligence, labour practices, and annotators’ agency within data structures. Finally, we reflect on the implications of our findings for developing more participatory and equitable approaches to machine learning applications in the service of R-AI.

Recent work in philosophy of technology has come to bear on the question of responsibility gaps. Some authors argue that the increase in the autonomous capabilities of decision-making systems makes it impossible to properly attribute responsibility for AI-based outcomes. In this article we argue that one important, and often neglected, feature of recent debates on responsibility gaps is how this debate maps on to old debates in responsibility theory. More specifically, we suggest that one of the key questions that is still at issue is the significance of the reactive attitudes, and how these ought to feature in our theorizing about responsibility. We will therefore provide a new descriptive categorization of different perspectives with respect to responsibility gaps. Such reflection can provide analytical clarity about what is at stake between the various interlocutors in this debate. The main upshot of our account is the articulation of a way to frame this ‘new’ debate by drawing on the rich intellectual history of ‘old’ concepts. By regarding the question of responsibility gaps as being concerned with questions of metaphysical priority, we see that the problem of these gaps lies not in any advanced technology, but rather in how we think about responsibility.

In this paper, I introduce a “promises and perils” framework for understanding the “soft” impacts of emerging technology, and argue for a eudaimonic conception of well-being. This eudaimonic conception of well-being, however, presupposes that we have something like stable character traits. I therefore defend this view from the “situationist challenge” and show that instead of viewing this challenge as a threat to well-being, we can incorporate it into how we think about living well with technology. Human beings are susceptible to situational influences and are often unaware of the ways that their social and technological environment influence not only their ability to do well, but even their ability to know whether they are doing well. Any theory that attempts to describe what it means for us to be doing well, then, needs to take these contextual features into account and bake them into a theory of human flourishing. By paying careful attention to these contextual factors, we can design systems that promote human flourishing.

In this paper I aim to establish that our belief in free will is epistemically innocent. Many contemporary accounts that deal with the potential “illusion” of freedom seek to describe the pragmatic benefits of belief in free will, such as how it facilitates or grounds our notions of moral responsibility or basic desert. While these proposals have their place (and use), I will not explicitly engage with them. I aim to establish that our false belief in free will is an epistemically innocent belief. I will endeavour to show that if we carefully consider the circumstances in which particular beliefs (such as our belief in free will) are adopted, we can come to better appreciate not just their psychological but also their epistemic benefits. The implications, therefore, for future investigations into the philosophy of free will are that we should consider whether we have been too narrow in our pragmatic defences of free will, and that we should also be sensitive to epistemic considerations.

Artificial Intelligence (AI) systems are ubiquitous. From social media timelines, video recommendations on YouTube, and the kinds of adverts we see online, AI, in a very real sense, filters the world we see. More than that, AI is being embedded in agent-like systems, which might prompt certain reactions from users. Specifically, we might find ourselves feeling frustrated if these systems do not meet our expectations. In normal situations, this might be fine, but with the ever increasing sophistication of AI-systems, this might become a problem. While it seems unproblematic to realize that being angry at your car for breaking down is unfitting, can the same be said for AI-systems? In this paper, therefore, I will investigate the so-called “reactive attitudes”, and their important link to our responsibility practices. I then show how within this framework there exist exemption and excuse conditions, and test whether our adopting the “objective attitude” toward agential AI is justified. I argue that such an attitude is appropriate in the context of three distinct senses of responsibility (answerability, attributability, and accountability), and that, therefore, AI-systems do not undermine our responsibility ascriptions.

In this paper I critically evaluate the value neutrality thesis regarding technology, and find it wanting. I then introduce the various ways in which artifacts can come to influence moral value, and our evaluation of moral situations and actions. Here, following van de Poel and Kroes, I introduce the idea of value sensitive design. Specifically, I show how by virtue of their designed properties, artifacts may come to embody values. Such accounts, however, have several shortcomings. In agreement with Michael Klenk, I raise epistemic and metaphysical issues with respect to designed properties embodying value. The concept of an affordance, borrowed from ecological psychology, provides a more philosophically fruitful grounding to the potential way in which artifacts might embody values. This is due to the way in which it incorporates key insights from perception more generally, and how we go about determining possibilities for action in our environment specifically. The affordance account as it is presented by Klenk, however, is insufficient. I therefore argue that we understand affordances based on whether they are meaningful, and, secondly, that we grade them based on their force.

Recent work in AI ethics has come to bear on questions of responsibility. Specifically, questions of whether the nature of AI-based systems render various notions of responsibility inappropriate. While substantial attention has been given to backward-looking senses of responsibility, there has been little consideration of forward-looking senses of responsibility. This paper aims to plug this gap, and will concern itself with responsibility as moral obligation, a particular kind of forward-looking sense of responsibility. Responsibility as moral obligation is predicated on the idea that agents have at least some degree of control over the kinds of systems they create and deploy. AI systems, by virtue of their ability to learn from experience once deployed, and their often experimental nature, may therefore pose a significant challenge to forward-looking responsibility. Such systems might not be able to have their course altered, and so even if their initial programming determines their goals, the means by which they achieve these goals may be outside the control of human operators. In cases such as this, we might say that there is a gap in moral obligation. However, in this paper, I argue that there are no “gaps” in responsibility as moral obligation, as this question comes to bear on AI systems. I support this conclusion by focusing on the nature of risks when developing technology, and by showing that technological assessment is not only about the consequences that a specific technology might have. Technological assessment is more than merely consequentialist, and should also include a hermeneutic component, which looks at the societal meaning of the system. Therefore, while it may be true that the creators of AI systems might not be able to fully appreciate what the consequences of their systems might be, this does not undermine or render improper their responsibility as moral obligation.

The ubiquity of technology in our lives and its culmination in artificial intelligence raises questions about its role in our moral considerations. In this paper, we address a moral concern in relation to technological systems given their deep integration in our lives. Coeckelbergh develops a social-relational account, suggesting that it can point us toward a dynamic, historicised evaluation of moral concern. While agreeing with Coeckelbergh’s move away from grounding moral concern in the ontological properties of entities, we suggest that it problematically upholds moral relativism. We suggest that the role of power, as described by Arendt and Foucault, is significant in social relations and as curating moral possibilities. This produces a clearer picture of the relations at hand and opens up the possibility that relations may be deemed violent. Violence as such gives us some way of evaluating the morality of a social relation, moving away from Coeckelbergh’s seeming relativism while retaining his emphasis on social–historical moral precedent.

As technology advances and artificial agents (AAs) become increasingly autonomous, start to embody morally relevant values and act on those values, there arises the issue of whether these entities should be considered artificial moral agents (AMAs). There are two main ways in which one could argue for AMA: using intentional criteria or using functional criteria. In this article, I provide an exposition and critique of “intentional” accounts of AMA. These accounts claim that moral agency should only be accorded to entities that have internal mental states. Against this thesis I argue that the requirement of internal states is philosophically unsound as it runs up against the problem of other minds. In place of intentional accounts, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with moral situations in which no human being is responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not

Up to 70% of all watch time on YouTube is due to the suggested content of its recommender system. This system has been found, by virtue of its design, to be promoting conspiratorial content. In this paper, I first critique the value neutrality thesis regarding technology, showing it to be philosophically untenable. This means that technological artefacts can influence what people come to value (or perhaps even embody values themselves) and change the moral evaluation of an action. Second, I introduces the concept of an affordance, borrowed from the literature on ecological psychology. This concept allows me to make salient how technologies come to solicit certain kinds of actions from users, making such actions more or less likely, and in this way influencing the kinds of things one comes to value. Third, I critically assesses the results of a study by Alfano et al. I make use of the literature on affordances, introduced earlier, to shed light on how these technological systems come to mediate our perception of the world and influence action.

In this paper I critically evaluate the value neutrality thesis regarding technology, and find it wanting. I then introduce the various ways in which artifacts can come to influence moral value, and our evaluation of moral situations and actions. Here, following van de Poel and Kroes, I introduce the idea of value sensitive design. Specifically, I show how by virtue of their designed properties, artifacts may come to embody values. Such accounts, however, have several shortcomings. In agreement with Michael Klenk, I raise epistemic and metaphysical issues with respect to designed properties embodying value. The concept of an affordance, borrowed from ecological psychology, provides a more philosophically fruitful grounding to the potential way(s) in which artifacts might embody values. This is due to the way in which it incorporates key insights from perception more generally, and how we go about determining possibilities for action in our environment specifically. The affordance account as it is presented by Klenk, however, is insufficient. I therefore argue that we understand affordances based on whether they are meaningful, and, secondly, that we grade them based on their force.

In his engaging book, James MacFarlane details the emergence of Technological Human Enhancement Advocacy (THEA) and provides a detailed ethnographic account of this phenomenon. Specifically, he aims to outline how transhumanism, as a specific offshoot of THEA, has “come to represent an enduring set of techno-optimistic ideas surrounding the future of humanity, with its advocates seeking to transcend limits of the body and mind according to an unwavering Enlightenment-derived faith in science, reason and individual freedom” (pg. 3).

In this paper I provide an exposition and critique of Johnson and Noorman’s (2014) three conceptualizations of the agential roles artificial systems can play. I argue that two of these conceptions are unproblematic: that of causally efficacious agency and “acting for” or surrogate agency. Their third conception, that of “autonomous agency,” however, is one I have reservations about. The authors point out that there are two ways in which the term “autonomy” can be used: there is, firstly, the engineering sense of the term, which simply refers to the ability of some system to act independently of substantive human control. Secondly, there is the moral sense of the term, which has traditionally grounded many notions of human mor-al responsibility. I argue that the continued usage of “autonomy” in discussions of artificial agency complicates matters unnecessarily. This occurs in two ways: firstly, the condition of autonomy, even in its engineering sense, fails to accurately describe the way “autonomous” systems are developed in practice. Secondly, the continued usage of autonomy in the moral sense introduces unnecessary meta-physical baggage form the free will debate into discussions about moral agency. In order to understand the debate surrounding autonomy, we would therefore first need to settle many seemingly intractable metaphysical questions regarding the existence of free will in human beings.

In this paper I provide an exposition and critique of the Organic View of Ethical Status, as outlined by Torrance (2008). A key presupposition of this view is that only moral patients can be moral agents. It is claimed that because artificial agents lack sentience, they cannot be proper subjects of moral concern (i.e. moral patients). This account of moral standing in principle excludes machines from participating in our moral universe. I will argue that the Organic View operationalises anthropocentric intuitions regarding sentience ascription, and by extension how we identify moral patients. The main difference between the argument I provide here and traditional arguments surrounding moral attributability is that I do not necessarily defend the view that internal states ground our ascriptions of moral patiency. This is in contrast to views such as those defended by Singer (1975, 2011) and Torrance (2008), where concepts such as sentience play starring roles. I will raise both conceptual and epistemic issues with regards to this sense of sentience. While this does not preclude the usage of sentience outright, it suggests that we should be more careful in our usage of internal mental states to ground our moral ascriptions. Following from this I suggest other avenues for further exploration into machine moral patiency which may not have the same shortcomings as the Organic View.

The aim of this thesis is to advance a philosophically justifiable account of Artificial Moral Agency (AMA). Concerns about the moral status of Artificial Intelligence (AI) traditionally turn on questions of whether these systems are deserving of moral concern (i.e. if they are moral patients) or whether they can be sources of moral action (i.e. if they are moral agents). On the Organic View of Ethical Status, being a moral patient is a necessary condition for an entity to qualify as a moral agent. This view claims that because artificial agents (AAs) lack sentience, they cannot be proper subjects of moral concern and hence cannot be considered to be moral agents. I raise conceptual and epistemic issues with regards to the sense of sentience employed on this view, and I argue that the Organic View does not succeed in showing that machines cannot be moral patients. Nevertheless, irrespective of this failure, I also argue that the entire project is misdirected in that moral patiency need not be a necessary condition for moral agency. Moreover, I claim that whereas machines may conceivably be moral patients in the future, there is a strong case to be made that they are (or will very soon be) moral agents. Whereas it is often argued that machines cannot be agents simpliciter, let alone moral agents, I claim that this argument is predicated on a conception of agency that makes unwarranted metaphysical assumptions even in the case of human agents. Once I have established the shortcomings of this “standard account”, I move to elaborate on other, more plausible, conceptions of agency, on which some machines clearly qualify as agents. Nevertheless, the argument is still often made that while some machines may be agents, they cannot be moral agents, given their ostensible lack of the requisite phenomenal states. Against this thesis, I argue that the requirement of internal states for moral agency is philosophically unsound, as it runs up against the problem of other minds. In place of such intentional accounts of moral agency, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with situations for which no human being is morally responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not.