According to virtue epistemology, the main aim of education is the development of the cognitive character of students (Pritchard, 2014, 2016). Given the proliferation of technological tools such as ChatGPT and other LLMs for solving cognitive tasks, how should educational practices incorporate the use of such tools without undermining the cognitive character of students? Pritchard (2014, 2016) argues that it is possible to properly solve this ‘technology-education tension’ (TET) by combining the virtue epistemology framework with the theory of extended cognition (...) (EXT) (Clark and Chalmers, 1998). He argues that EXT enables us to consider tools as constitutive parts of the students’ cognitive system, thus preserving their cognitive character from technologically induced cognitive diminishment. The first aim of this paper is to show that this solution is not sufficient to solve the TET. Second, I aim to offer a complementary and more encompassing framework of tool-use to address the TET. Then, I apply it to the educational uses of ChatGPT as the most notable example of LLM, although my arguments can be extended to other generative AI systems. To do so, in Sect. 1.1, I present Pritchard’s framework of cognitive character and virtue epistemology applied in education, to which I am committed in this treatment. In Sects. 2 and 3, I respectively illustrate Pritchard’s (2014) solution to the TET, and I highlight the general limitations of his proposal. Thus, in Sect. 4.1 I characterize ChatGPT as a computational cognitive artifact using Fasoli’s (2017, 2018) taxonomy of cognitive artifacts. In Sect. 4.2, I introduce my proposal, which combines Pritchard’s account of virtue epistemology with Fasoli’s (2017, 2018) taxonomy of cognitive artifacts to address the TET. Finally, in Sect. 5.1, I present some epistemically virtuous uses of ChatGPT in educational contexts. To conclude, I argue in favor of a multidisciplinary approach for analyzing educational activities involving AI technologies such as ChatGPT. (shrink)

In the popular and academic literature on the problems of the so-called attention economy, the cost of attention grabbing, sustaining, and immersing digital medias has been addressed as if it touched all people equally. In this paper I ask whether everyone has the same resources to respond to the recent changes in their stimulus environments caused by the attention economy. I argue that there are not only differences but disparities between people in their responses to the recent, significant increase in (...) the degree and persuasiveness of digital distraction. I point toward individual variance in an agent’s top-down and bottom-up attention regulation, and to further inequality-exacerbating variance in active participation on the internet and in regulating reward-seeking behaviors on the internet. Individual differences in these areas amount to disparities because they have been found to be connected to socioeconomic background factors. I argue that disparities in responding to digital distraction threaten fair equality of opportunity when it comes to digital distraction in the classroom and that they may lead to an unequal contribution of achievements that require complex cognition by people from lower socioeconomic backgrounds. (shrink)

Deepfakes pose a multi-faceted threat to the acquisition of knowledge. It is widely hoped that technological solutions—in the form of artificially intelligent systems for detecting deepfakes—will help to address this threat. I argue that the prospects for purely technological solutions to the problem of deepfakes are dim. Especially given the evolving nature of the threat, technological solutions cannot be expected to prevent deception at the hands of deepfakes, or to preserve the authority of video footage. Moreover, the success of such (...) technologies depends on institutional trust that is in short supply. Finally, outsourcing the discrimination between the real and the fake to automated, largely opaque systems runs the risk of undermining epistemic autonomy. (shrink)

Machine learning, and more broadly artificial intelligence (AI), is a fascinating technology and can be considered as the closest approximation to the Cartesian “thinking thing” that humans have ever created. Just as the industrial revolution required a new ethos, the age of intelligent machines will create its own, challenging the established moral, economic, and political presuppositions. This paper discusses the relationship between AI and society; it presents several thought experiments to explore the complexity of the relationship and highlights the insufficiency (...) of the current normative paradigm in addressing technological expansion. I argue that many of the externalities, such as security risks, loss of privacy, and economic instability will result from trying to fit the emerging technologies into the existing frame of efficiency and utility, by redefining the notions of human value, identity, autonomy, purity, and truth, among others. The age of the intelligent machine is elevating alienation to new levels, treating the individual as mere patterns in data—its primary commodity. I further argue that while the possibility of unintended consequences, due to the potential misuse of AI is ever present, the intelligent machine per se is unlikely to engage in a zero-sum game for power on its own initiative. I question whether singularity is at all attainable and argue that technology will forever remain a proxy for human interests. I conclude by posing questions for charting the path forward. Through this analysis, I aim to provide a more nuanced understanding of the complex relationship between the AI and humans. (shrink)

AI has become the poster child for a certain kind of thinking which holds that some technologies can become objective, independent and emergent entities which can evolve beyond the control of their creators. This thinking is not new however. It is a product of certain philosophical ideas such as materialism, a common-sense world of objective and independent objects, a correspondence theory of truth, and so forth, which are centered around the pre-eminence of science, epistemology, and logical reasoning, among others, as (...) the supremely valid modes of engaging experience. This paper aims to critically examine the synthesis of the development program for AI to be found in the writings of computer scientist John McCarthy (1927–2011). McCarthy has been called one of the founding fathers of AI. First, some of the main themes which recur in his writings from as early as the mid nineteen fifties in the Dartmouth proposal, up to his late writings, are considered. A discussion of the goals that such a program implies, follows, in terms of society’s relation with AI based technology and the nature and purpose of AI itself. These implications are arguably related to social control and are also moral. Ultimately, McCarthy’s idea that AI is and can be built upon a paradigm of reasoning and logic so as to simulate a perfectly rational abstraction of human thinking is shown to be motivated by his view that AI systems should be controlled, as servants. This understanding of human thinking is questionable, however, given current research on human irrationality, as well as on the argumentative role of reasoning. And yet, the process of development toward the unachievable goal of controllable, rational, logical AI systems, has handily come to serve as a blind for increasing techno-corporate control of society, with techno-corporate interests displacing blame for devaluations and harms caused by their push to develop the technology to AI systems which they can conveniently ‘lose control of.’. (shrink)

Franke, in Philosophy & Technology, 37(1), 1–6, (2024), connects the recent debate about manipulative algorithmic transparency with the concerns about problematic pursuits of positive liberty. I argue that the indifference view of manipulative transparency is not aligned with positive liberty, contrary to Franke’s claim, and even if it is, it is not aligned with the risk that many have attributed to pursuits of positive liberty. Moreover, I suggest that Franke’s worry may generalise beyond the manipulative transparency debate to AI ethics (...) in general. (shrink)

In this paper, we argue that boredom can be an important experience that contributes to personal autonomous agency by providing authentic motivation, and that strategies of social media providers to bind users’ attention to their platforms undermine this authenticity. As discussed in social epistemology and media ethics for a while now, such strategies can lead to so-called epistemic or filter bubbles. Our analysis of the relation between boredom and social media use focuses on a similarly impairing effect of social media (...) on users’ autonomy, which we call authenticity bubbles. (shrink)

With robots increasingly integrated into various areas of life, the question of relationships with them is gaining prominence. Are friendship and partnership with robots possible? While there is already extensive research on relationships with robots, this article critically examines whether the relationship with non-human entities is sufficiently explored on a deeper level, especially in terms of ethical concepts such as autonomy, agency, and responsibility. In robot ethics, ethical concepts and considerations often presuppose properties such as consciousness, sentience, and intelligence, which (...) are exclusively aligned with humans. I will challenge the understanding of these properties by anchoring them in contexts, bodies, and actions. This approach allows to consider the specific ways of being of various human and non-human entities and to identify these properties in non-human entities as well. My “eco-relational” approach posits that it is crucial to consider the relationality with non-human entities such as animals and technology in central ethical concepts from the beginning. This approach reflects the “eco”, the entire house in which we live including animals and robots. To support this, I examine two dominant approaches in robot ethics within the contemporary Western tradition: the “properties approach” and modestly relational approaches. I will develop an eco-relational approach as an alternative. Employing a phenomenological method, I will demonstrate through various examples that our properties and actions are inherently connected with non-human entities. I will show that robots play a central role in our properties and actions, leading to concepts such as hybrid actions and non-human agency. It becomes clear that technology and our relationships with it disrupt traditional ethical concepts. (shrink)

Debates about the moral status of social robots (SRs) currently face a second-order, or metatheoretical impasse. On the one hand, moral individualists argue that the moral status of SRs depends on their possession of morally relevant properties. On the other hand, moral relationalists deny that we ought to attribute moral status on the basis of the properties that SRs instantiate, opting instead for other modes of reflection and critique. This paper develops and defends a pragmatic approach which aims to reconcile (...) these two positions. The core of this proposal is that moral individualism and moral relationalism are best understood as distinct deliberative strategies for attributing moral status to SRs, and that both are worth preserving insofar as they answer to different kinds of practical problems that we face as moral agents. (shrink)

The world is witnessing a rise in speech-enabled devices serving as epistemic informants to their users. Some philosophers take the view that because the utterances produced by such machines can be phenomenologically similar to an equivalent human speech, and they may deliver the same function in terms of delivering content to their audience, such machine utterances should be conceptualized as “assertions”. This paper argues against this view and highlights the theoretical and pragmatic challenges faced by such a conceptualization which seems (...) to be based on a “functionalist” account of assertion. Instead, the paper argues that the view that some such machine utterances can be “proxy assertions”, made on behalf of the designers and/or deployers of such machines is more tenable. Existing accounts of such a view, however, need further refinement, which is provided here. The paper then discusses implications of this view for design of such machines, particularly those enabled and equipped with machine learning capabilities. (shrink)

Much of the excitement about virtual reality and its potential for things like entertainment, art, education, and activism is its ability to generate experiences that are powerfully immersive. However, discussions of VR tend to invoke the notion of immersive experience without subjecting it to closer scrutiny; and discussions often take it for granted that immersive experience is a single unified phenomenon. Against this, we argue that there are four distinct types or aspects of immersive experience that should be distinguished: representational (...) immersion, which corresponds roughly to what is sometimes called “psychological presence”; participatory immersion, which is related to the interactive aspects of VR experience; affective immersion, which has to do with the subject’s emotional relation to the experience; and narrative immersion, which captures the phenomenon of being caught up in the flow of events experienced. We argue that this four-way distinction helps us understand the powerfully immersive character of VR, while also recognizing its continuity with the immersion we experience with media such as novels, films, and music. We also argue that the account of immersion we offer here lets us better understand the connection between VR and empathy, charting a middle course between extreme enthusiasts who view VR as the ultimate “empathy machine” and extreme skeptics who argue that this attitude is misguided. (shrink)

Ethical discussions about Artificial Intelligence (AI) often overlook its potentially large impact on nonhuman animals. In a recent commentary on our paper about AI’s possible harms, Leonie Bossert argues for a focus not just on the possible negative impacts but also the possible beneficial outcomes of AI for animals. We welcome this call to increase awareness of AI that helps animals: developing and using AI to improve animal wellbeing and promote positive dimensions in animal lives should be a vital ethical (...) goal. Nonetheless, we argue that there is some value in focusing on technology-based harms in the context of AI ethics and policy discourses. A harms framework for AI can inform some of our strongest duties to animals and inform regulation and risk assessment impacts designed to prevent serious harms to humans, the environment, and animals. (shrink)

In a bid to boost fertility levels, Iran and Japan have recently launched their own dating apps, with more countries likely to follow. The aim of this article is to consider whether state-run dating apps are morally desirable, which is a question that has not received any scholarly attention. It finds that such apps have at least two benefits that collectively, if not individually, render their introduction to be welcomed provided certain conditions are met. These benefits are that they are (...) better placed than commercial dating apps such as Tinder, Bumble, and Badoo to (i) help people find lasting love and to (ii) protect individuals from spending too much money and/or time on online dating. Several objections are discussed and shown to be unconvincing as arguments against state-run dating apps tout court, including the objection that for states to offer their own dating apps is unduly expensive; the objection that it gives them too much power; and the objection that they should invest in creating offline opportunities for meeting potential partners instead. (shrink)

This is a commentary on Andrea Lavazza and Murilo Vilaça's article "Human Extinction and AI: What We Can Learn from the Ultimate Threat" (Lavazza & Vilaça, 2024). I discuss the potential concern that their proposal to create artificial successors to "insure" against the tragedy of human extinction might mean being too quick to accept that catastrophic prospect as inevitable, rather than single-mindedly focusing on avoiding it. I also consider the question of the value that we might reasonably assign to such (...) a future of artificial successors under the assumption that they do not enjoy phenomenal consciousness. (shrink)

As more decisions are made by automated algorithmic systems, the transparency of these systems has come under scrutiny. While such transparency is typically seen as beneficial, there is a also a critical, Foucauldian account of it. From this perspective, worries have recently been articulated that algorithmic transparency can be used for manipulation, as part of a disciplinary power structure. Klenk (Philosophy & Technology 36, 79, 2023) recently argued that such manipulation should not be understood as exploitation of vulnerable victims, but (...) rather as indifference to whether the information provided enhances decision-making by revealing reasons. This short commentary on Klenk uses Berlin’s (1958) two concepts of liberty to further illuminate the concept of transparency as manipulation, finding alignment between positive liberty and the critical account. (shrink)

In this response, I express sympathy for Buhr's proposal to expand our typology into an ethical framework of eco-normative profiling of (sustainable) technologies. I reflect on crucial issues that this framework should include, offering some words of caution against taking concepts such as Anthropocene and sustainability too lightly. I end with an invitation to include multiple and diverse perspectives about what sustainable futures could look like.

Bioconservative bioethicists (e.g., Kass, 2002, Human Dignity and Bioethics, 297–331, 2008; Sandel, 2007; Fukuyama, 2003) offer various kinds of philosophical arguments against cognitive enhancement—i.e., the use of medicine and technology to make ourselves “better than well” as opposed to merely treating pathologies. Two notable such bioconservative arguments appeal to ideas about (1) the value of achievement, and (2) authenticity. It is shown here that even if these arguments from achievement and authenticity cut ice against specifically pharmacologically driven cognitive enhancement, they (...) do not extend over to an increasingly viable form of technological cognitive enhancement – namely, cognitive enhancement via augmented reality. An important result is that AR-driven cognitive enhancement aimed at boosting performance in certain cognitive tasks might offer an interesting kind of “sweet spot” for proponents of cognitive enhancement, allowing us to pursue many of the goals of enhancement advocates without running into some of the most prominent objections from bioconservative philosophers. (shrink)

This article sets in with the question whether current or foreseeable transformer-based large language models (LLMs), such as the ones powering OpenAI’s ChatGPT, could be language users in a way comparable to humans. It answers the question negatively, presenting the following argument. Apart from niche uses, to use language means to act. But LLMs are unable to act because they lack intentions. This, in turn, is because they are the wrong kind of being: agents with intentions need to be autonomous (...) organisms while LLMs are heteronomous mechanisms. To conclude, the article argues, based on structural aspects of transformer-based LLMs, that these LLMs have taken a first step away from mechanistic artificiality to autonomous self-constitution, which means that these models are (slowly) moving into a direction that someday might result in non-human, but equally non-artificial agents, thus subverting the time-honored Kantian distinction between organism and mechanism. (shrink)

In an important and widely cited paper, Zerilli, Knott, Maclaurin, and Gavaghan (2019) argue that opaque AI decision makers are at least as transparent as human decision makers and therefore the concern that opaque AI is not sufficiently transparent is mistaken. I argue that the concern about opaque AI should not be understood as the concern that such AI fails to be transparent in a way that humans are transparent. Rather, the concern is that the way in which opaque AI (...) is opaque is very different than the way in which humans are opaque. What matters is the degree to which the opaque processes of a class of decision makers are stable, uniform, and safe. The degree to which such processes have these features in humans is higher than the degree to which such processes have these features in opaque AI. And therefore we should require AI to be more transparent than humans. (shrink)

In this paper, I explore Derrida’s concept of exteriorization in relation to texts generated by machine learning. I first discuss Heidegger’s view of machine creation and then present Derrida’s criticism of Heidegger. I explain the concept of iterability, which is the central notion on which Derrida’s criticism is based. The thesis defended in the paper is that Derrida’s account of iterability provides a helpful framework for understanding the phenomenon of machine learning–generated literature. His account of textuality highlights the incalculability and (...) mechanical elements characteristic of all texts, including machine-generated texts. By applying Derrida’s concept to the phenomenon of machine creation, we can deconstruct the distinction between human and non-human creation. As I propose in the conclusion to this paper, this provides a basis on which to consider potential positive uses of machine learning. (shrink)

Human extinction is something generally deemed as undesirable, although some scholars view it as a potential solution to the problems of the Earth since it would reduce the moral evil and the suffering that are brought about by humans. We contend that humans collectively have absolute intrinsic value as sentient, conscious and rational entities, and we should preserve them from extinction. However, severe threats, such as climate change and incurable viruses, might push humanity to the brink of extinction. Should that (...) occur, it might be useful to envision a successor to humans able to preserve and hand down its value. One option would be to resort to humanoid robots that reproduce our salient characteristics by imitation, thanks to AI powered by machine learning. However, the question would arise of how to select the characteristics needed for our successors to thrive. This could prove to be particularly challenging. A way out might come from an algorithm entrusted with this choice. In fact, an algorithmic selection both at the social and at the individual level could be a preferred choice than other traditional ways of making decisions. In this sense, reflecting on human extinction helps us to identify solutions that are also suitable for the problems we face today. (shrink)

Novel technological devices, applications, and algorithms can provide us with a vast amount of personal information about ourselves. Given that we have ethical and practical reasons to pursue self-knowledge, should we use technology to increase our self-knowledge? And which ethical issues arise from the pursuit of technologically sourced self-knowledge? In this paper, I explore these questions in relation to bioinformation technologies (health and activity trackers, DTC genetic testing, and DTC neurotechnologies) and algorithmic profiling used for recommender systems, targeted advertising, and (...) technologically supported decision-making. First, I distinguish between impersonal, critical, and relational self-knowledge. Relational self-knowledge is a so far neglected dimension of self-knowledge which is introduced in this paper. Next, I investigate the contribution of these technologies to the three types of self-knowledge and uncover the connected ethical concerns. Technology can provide a lot of impersonal self-knowledge, but we should focus on the quality of the information which tends to be particularly insufficient for marginalized groups. In terms of critical self-knowledge, the nature of technologically sourced personal information typically impedes critical engagement. The value of relational self-knowledge speaks in favour of transparency of information technology, notably for algorithms that are involved in decision-making about individuals. Moreover, bioinformation technologies and digital profiling shape the concepts and norms that define us. We should ensure they not only serve commercial interests but our identity and self-knowledge interests. (shrink)

This commentary on Daniel Stader's recent article, “Algorithms Don't Have a Future: On the Relation of Judgement and Calculation” develops and complicates his argument by suggesting that algorithms ossify multiple kinds of prejudices, namely, the structural prejudices of the programmer and the exemplary prejudices of the dataset. This typology at once suggests that the goal of transparency may be impossible, but this impossibility enriches the possibilities for developing Stader's concept of reflected prejudiced use.

The inquiry into the moral status of artificial intelligence (AI) is leading to prolific theoretical discussions. A new entity that does not share the material substrate of human beings begins to show signs of a number of properties that are nuclear to the understanding of moral agency. It makes us wonder whether the properties we associate with moral status need to be revised or whether the new artificial entities deserve to enter within the circle of moral consideration. This raises the (...) foreboding that we are at the gates of an anthropological crisis: the properties bound to moral agency have been exclusively possessed in the past by human beings and have shaped the very definition of being human. In this article, I will argue that AI does not lead us to an anthropological crisis and that, if we adhere to the history and philosophy of technology, we will notice that the debate on the moral status of AI uncritically starts from an anthropology of properties and loses sight of the relational dimension of technology. First, I will articulate three criteria for analyzing different anthropological views in philosophy of technology. Second, I will propose six anthropological models: traditional, industrial, phenomenological, postphenomenological, symmetrical, and cyborg. Third, I will show how the emergence of AI breaks with the dynamics of increased relationality in the history and philosophy of technology. I will argue that this aspect is central to debates about the moral status of AI, since it sheds light on an aspect of moral consideration that has been obscured. Finally, I will reject entirely relational approaches to moral status and propose two hybrid possibilities for rethinking it. (shrink)

Fairness in machine learning (ML) is an ever-growing field of research due to the manifold potential for harm from algorithmic discrimination. To prevent such harm, a large body of literature develops new approaches to quantify fairness. Here, we investigate how one can divert the quantification of fairness by describing a practice we call “fairness hacking” for the purpose of shrouding unfairness in algorithms. This impacts end-users who rely on learning algorithms, as well as the broader community interested in fair AI (...) practices. We introduce two different categories of fairness hacking in reference to the established concept of p-hacking. The first category, intra-metric fairness hacking, describes the misuse of a particular metric by adding or removing sensitive attributes from the analysis. In this context, countermeasures that have been developed to prevent or reduce p-hacking can be applied to similarly prevent or reduce fairness hacking. The second category of fairness hacking is inter-metric fairness hacking. Inter-metric fairness hacking is the search for a specific fair metric with given attributes. We argue that countermeasures to prevent or reduce inter-metric fairness hacking are still in their infancy. Finally, we demonstrate both types of fairness hacking using real datasets. Our paper intends to serve as a guidance for discussions within the fair ML community to prevent or reduce the misuse of fairness metrics, and thus reduce overall harm from ML applications. (shrink)

Democratic innovations have been widely presented by both academics and practitioners as a potential remedy to the crisis of representative democracy. Many argue that deliberation should play a pivotal role in these innovations, fostering greater citizen participation and political influence. However, it remains unclear how digitalization affects the quality of deliberation—whether digital democratic innovations (DDIs) undermine or enhance deliberation. This paper takes an inductive approach in political theory to critically examine three features of online deliberation that matter for deliberative democracy: (...) scale, transparency, and the facilitation of equality. It argues that the enhancement of equality should be given special attention when designing and implementing deliberative DDIs. Equality is a basic democratic value that is crucial for the intrinsic quality of deliberation. One way of enhancing equality through digital deliberative practices is via AI facilitation, which can assist human facilitators and help mitigate power dynamics, often present in non-digital settings. (shrink)

In this article, we argue that rational persuasion can be a _pro tanto_ wrong and that online platforms possess features that are especially conducive to this wrong. We begin by setting out an account of rational persuasion. This consists of four jointly sufficient conditions for rational persuasion and is intended to capture the core, uncontroversial cases of such persuasion. We then discuss a series of wrong-making features which are present in methods of influence commonly thought of as _pro tanto_ wrong, (...) such as manipulation and paternalism. It is next shown that these wrong-making features are also present in a range of cases that are, by the jointly sufficient conditions already established, rational persuasion, and so some forms of rational persuasion are _pro tanto_ wrong, including in some ways that have not previously been remarked upon. Finally, we demonstrate that online settings possess a number of features that are especially conducive to wrongful rational persuasion. (shrink)

The article _Anthropological crisis or crisis in moral __status: a philosophy of technology approach to the moral consideration of artificial intelligence_ questions the anthropology of properties commonly assumed in philosophical discussions about the relationship between humans and technologies and the attribution of moral status. By beginning to develop the possible link between the ontology of properties and the anthropological question aptly outlined by that contribution, this short commentary suggests that the adoption of a truly relational or non-proprietary approach in the (...) philosophy of technology seems at once necessary and challenging. For, on the one hand, it represents a response to the demands posed by information technologies; on the other it seems to call into question some of our deeply ingrained habits of thought. (shrink)

Discussions on the Anthropocene as the geology of mankind imply the question whether globalized technology such as energy technologies or A.I. ought to be first and foremost conceptualized as a strategy of the human in relation to nature or as a strategy of some humans over others. I argue that both positions are mirrored in the philosophy and sociology of technology through the concepts of technology as an extension and as a fetish. The extension concept understands technology as an extension (...) of the human body and its capabilities, resulting in a local ‘inward’ perspective. The fetish concept offers a contrary ‘outward’ perspective by drawing attention to the global socio-material context of modern technology. Despite their differences, I argue that both concepts share an underlying operation principle of technology as functional simplification. Technology always involves a functional simplification of physical as well as social causality. Sociologists and philosophers of technology would do well not to give primacy to the former as it leads to the belief in technology as a universal tool that neglects how technology is not embedded in but consists of (unequal) social arrangements. (shrink)

The focus of AI ethics has recently shifted towards the question of whether and how the use of AI technologies can promote sustainability. This new research question involves discerning the sustainability of AI itself and evaluating AI as a tool to achieve sustainable objectives. This article aims to examine the justifications that one might employ to advocate for promoting sustainable AI. Specifically, it concentrates on a dimension of often disregarded reasons — reasons of “meaning” or “meaningfulness” — as discussed more (...) recently in the “meaning in life” literature of analytic ethics. To proceed, the article first elucidates the working definitions of “sustainable AI” and “meaning in life”, while also setting the criteria for evaluating the plausibility of these reasons. Subsequently, it presents and scrutinises three arguments for the claim that one has reasons to care about sustainable AI from a perspective of meaning: the Meaning-conferring-action Argument, the Afterlife Argument, and the Harm Argument. In conclusion, this article asserts that only the Harm Argument presents a viable line of reasoning. However, it also outlines the presuppositions of this argument and the additional steps necessary to make it compelling. (shrink)

Artificial intelligence is increasingly permeating many types of high-stake societal decision-making such as the work at the criminal courts. Various types of algorithmic tools have already been introduced into sentencing. This article concerns the use of algorithms designed to deliver sentence recommendations. More precisely, it is considered how one should determine whether one type of sentencing algorithm (e.g., a model based on machine learning) would be ethically preferable to another type of sentencing algorithm (e.g., a model based on old-fashioned programming). (...) Whether the implementation of sentencing algorithms is ethically desirable obviously depends upon various questions. For instance, some of the traditional issues that have received considerable attention are algorithmic biases and lack of transparency. However, the purpose of this article is to direct attention to a further challenge that has not yet been considered in the discussion of sentencing algorithms. That is, even if is assumed that the traditional challenges concerning biases, transparency, and cost-efficiency have all been solved or proven insubstantial, there will be a further serious challenge associated with the comparison of sentencing algorithms; namely, that we do not yet possess an ethically plausible and applicable criterion for assessing how well sentencing algorithms are performing. (shrink)

This paper is about the opposite of judgement and calculation. This opposition has been a traditional anchor of critiques concerned with the rise of AI decision making over human judgement. Contrary to these approaches, it is argued that human judgement is not and cannot be replaced by calculation, but that it is human judgement that contextualises computational structures and gives them meaning and purpose. The article focuses on the epistemic structure of algorithms and artificial neural networks to find that they (...) always depend on human judgement to be related to real life objects or purposes. By introducing the philosophical concept of judgement, it becomes clear that the property of judgement to provide meaning and purposiveness is based on the temporality of human life and the ambiguity of language, which quantitative processes lack. A juxtaposition shows that calculations and clustering can be used and referred to in more or less prejudiced and reflecting as well as opaque and transparent ways, but thereby always depend on human judgement. The paper clearly asserts that the transparency of AI is necessary for their autonomous use. This transparency requires the explicitness of the judgements that constitute these computational structures, thereby creating an awareness of the conditionality of such epistemic entities. (shrink)

The use of artificial intelligence (AI) to make high-stakes decisions is sometimes thought to create a troubling responsibility gap – that is, a situation where nobody can be held morally responsible for the outcomes that are brought about. However, philosophers and practitioners have recently claimed that, even though no individual can be held morally responsible, groups of individuals might be. Consequently, they think, we have less to fear from the use of AI than might appear to be the case. This (...) paper assesses this claim. Drawing on existing philosophical models of collective responsibility, I consider whether changing focus from the individual to the collective level can help us identify a locus of responsibility in a greater range of cases of AI deployment. I find that appeal to collective responsibility will be of limited use in filling the responsibility gap: the models considered either do not apply to the case at hand or else the relevant sort of collective responsibility, even if present, will not be sufficient to remove the costs that are often associated with an absence of responsibility. (shrink)

This article provides a methodology for the interpretation of AI ethics principles to specify ethical criteria for the development and deployment of AI systems in high-risk domains. The methodology consists of a three-step process deployed by an independent, multi-stakeholder ethics board to: (1) identify the appropriate level of abstraction for modelling the AI lifecycle; (2) interpret prescribed principles to extract specific requirements to be met at each step of the AI lifecycle; and (3) define the criteria to inform purpose- and (...) context-specific balancing of the principles. The methodology presented in this article is designed to be agile, adaptable, and replicable, and when used as part of a pro-ethical institutional culture, will help to foster the ethical design, development, and deployment of AI systems. The application of the methodology is illustrated through reference to the UK Ministry of Defence AI ethics principles. (shrink)

Is ChatGPT an author? Given its capacity to generate something that reads like human-written text in response to prompts, it might seem natural to ascribe authorship to ChatGPT. However, we argue that ChatGPT is not an author. ChatGPT fails to meet the criteria of authorship because it lacks the ability to perform illocutionary speech acts such as promising or asserting, lacks the fitting mental states like knowledge, belief, or intention, and cannot take responsibility for the texts it produces. Three perspectives (...) are compared: liberalism (which ascribes authorship to ChatGPT), conservatism (which denies ChatGPT's authorship for normative and metaphysical reasons), and moderatism (which treats ChatGPT as if it possesses authorship without committing to the existence of mental states like knowledge, belief, or intention). We conclude that conservatism provides a more nuanced understanding of authorship in AI than liberalism and moderatism, without denying the significant potential, influence, or utility of AI technologies such as ChatGPT. (shrink)

In this paper, I discuss the formation of habits with the help of self-tracking technologies. Although devices like Fitbit smart bands come with promises of empowerment through the means of increased control over users’ habits, existing literature does not provide conclusive findings about the validity of such claims. I contribute to the ongoing debate by relying on John Dewey’s pragmatist philosophy and its notion of intelligent habit. I demonstrate that from a pragmatist standpoint, habits that are the most likely to (...) accomplish users’ goals contribute to their flourishing need to be reflective (accompanied by adequate deliberation) and flexible (adaptable to the changing circumstances). On this basis I highlight some ethical-epistemic issues surrounding self-tracking technologies that inhibit the formation of habits desirable from a Deweyan standpoint. These include a lack of reflection on the part of the developers, difficulties for users to deliberate and consciously shape the habits developed by their devices, and dependence upon self-tracking tools that makes it difficult to adapt habits to individual needs and circumstances. I conclude the paper by discussing self-tracking’s general impact on flourishing, as well as placing my arguments in the context of the diversity of self-tracking practices and identifying how users attempt to alleviate the shortcomings of the technology and make it more suitable to their goals and needs. (shrink)

In her paper “Human Flourishing and Technology Affordances”, Avigail Ferdman argues that our descriptions and analyses of the relationship between digital technology, and the capacities approach to human flourishing, can be enriched by building ‘affordances’ into those descriptions and analyses. This commentary article serves as a supplement to Ferdman’s paper. Here I argue that, in building affordances into the capacities approach, Ferdman has developed the foundations of a method by which perfectionist ethics can be built into action-theoretic accounts of technical (...) function. However, this is possible only if she is willing to expand the ambit of her theory beyond digital technologies and into technology more generally. (shrink)