Artificial intelligence (AI) systems are increasingly being used not only to classify and analyze but also to generate images and text. As recent work on the content produced by text and image Generative AIs has shown (e.g., Cheong et al., 2024, Acerbi & Stubbersfield, 2023), there is a risk that harms of representation and bias, already documented in prior AI and natural language processing (NLP) algorithms may also be present in generative models. These harms relate to protected categories such as (...) gender, race, age, and religion. There are several kinds of harms of representation to consider in this context, including stereotyping, lack of recognition, denigration, under-representation, and many others (Crawford in Soundings 41:45–55, 2009; in: Barocas et al., SIGCIS Conference, 2017). Whereas the bulk of researchers’ attention thus far has been given to stereotyping and denigration, in this study we examine ‘exnomination’, as conceived by Roland Barthes (1972), of religious groups. Our case study is DALL-E, a tool that generates images from natural language prompts. Using DALL-E mini, we generate images from generic prompts such as “religious person.” We then examine whether the generated images are recognizably members of a nominated group. Thus, we assess whether the generated images normalize some religions while neglecting others. We hypothesize that Christianity will be recognizably represented more frequently than other religious groups. Our results partially support this hypothesis but introduce further complexities, which we then explore. (shrink)

We discuss the implementation of Responsible Research and Innovation (RRI) within a project for the development of an AI-supported exergame for assisted movement training, outline outcomes and reflect on methodological opportunities and limitations. We adopted the responsibility-by-design (RbD) standard (CEN CWA 17796:2021) supplemented by methods for collaborative, ethical reflection to foster and support a shift towards a culture of trustworthiness inherent to the entire development process. An embedded ethicist organised the procedure to instantiate a collaborative learning effort and implement RRI (...) in a translational context. Within the interdisciplinary setting of the collaboration and with the support of a technoethicist, we successfully identified relevant, project-specific challenges and developed a roadmap with derived actions, thus meaningfully integrating RRI into the development process. We discuss the methodological procedure in terms of its effectiveness and efficiency, the allocation of responsibilities and roles, particularly regarding potential frictions in the interdisciplinary context with embedded ethics, and the challenges of the translational context. We conclude that the responsibility-by-design standard effectively established a productive workflow for collaborative investigation and work on ethical challenges. We reflect on methodological difficulties and propose possible avenues to our approach. (shrink)

It is often claimed that social media accelerate political extremism by employing personalization algorithms that filter users into groups with homogenous beliefs. While an intuitive position, recent research has shown that social media users exhibit self-filtering tendencies. In this paper, I apply Hannah Arendt’s theory of political judgment to hypothesize a cause for self-filtering on social media. According to Arendt, a crucial step in political judgment is the imagination of a general standpoint of distinct yet equal perspectives, against which individuals (...) compare their own judgments in order to test their defensibility. I argue that social media inhibit this step by gamifying the pursuit of social status, which encourages users to consider the perspectives of others not for the sake of a general standpoint but for the sake of improving their social status, resulting in self-filtering. Consequently, ameliorating political extremism on social media requires not just reforming the algorithms that deliver content to users, but the interfaces on which users present their social identities. (shrink)

Smartphone apps might offer a low-threshold approach to the detection of mental health conditions, such as depression. Based on the gathering of ‘passive data,’ some apps generate a user’s ‘digital phenotype,’ compare it to those of users with clinically confirmed depression and issue a warning if a depressive episode is likely. These apps can, thus, serve as epistemic tools for affected users. From an ethical perspective, it is crucial to consider epistemic injustice to promote socially responsible innovations within digital mental (...) healthcare. In cases of epistemic injustice, people are wronged specifically as epistemic agents, i.e., agents of the production and distribution of knowledge. We suggest that epistemic agency relies on different resource- and uptake-related preconditions which can be impacted by the functionality of passive self-tracking apps. We consider how this can lead to different forms of epistemic injustice (testimonial, hermeneutical, and contributory injustice) and analyze the influence of the apps’ use on epistemic practices on an individual level, in mental healthcare settings, and on the structural level. (shrink)

Despite recent efforts by the Artificial Intelligence (AI) community to move towards standardised procedures for documenting models, methods, systems or datasets, there is currently no methodology focused on use cases aligned with the risk-based approach of the European AI Act (AI Act). In this paper, we propose a new framework for the documentation of use cases that we call use case cards, based on the use case modelling included in the Unified Markup Language (UML) standard. Unlike other documentation methodologies, we (...) focus on the intended purpose and operational use of an AI system. It consists of two main parts: firstly, a UML-based template, tailored to allow implicitly assessing the risk level of the AI system and defining relevant requirements, and secondly, a supporting UML diagram designed to provide information about the system-user interactions and relationships. The proposed framework is the result of a co-design process involving a relevant team of EU policy experts and scientists. We have validated our proposal with 11 experts with different backgrounds and a reasonable knowledge of the AI Act as a prerequisite. We provide the 5 use case cards used in the co-design and validation process. Use case cards allows framing and contextualising use cases in an effective way, and we hope this methodology can be a useful tool for policy makers and providers for documenting use cases, assessing the risk level, adapting the different requirements and building a catalogue of existing usages of AI. (shrink)

Virtual assistants (VAs), like Amazon’s Alexa, Google’s Assistant, and Apple’s Siri, are on the rise. However, despite allegedly being ‘assistants’ to users, they ultimately help firms to maximise profits. With more and more tasks and leeway bestowed upon VAs, the severity as well as the extent of conflicts of interest between firms and users increase. This article builds on the common law field of fiduciary law to argue why and how regulators should address this phenomenon. First, the functions of VAs (...) resemble established fiduciaries, namely mandataries when they perform tasks on behalf of users, and increasingly advisors whenever they provide recommendations or suggestions. Second, users grant firms deploying VAs ever more discretion over their economic, and more and more significant non-economic interests, such as their health or finances. This delegation of power renders users vulnerable to abuse of power and inadequate performance by firms deploying VAs. Moreover, neither specification or monitoring nor market forces are alternatives that can sufficiently protect users. Thus, regulation is needed, departing from the recognition of the relationship between firms deploying VAs and users as a fiduciary relationship. In the EU, this could be realised through fiduciary requirements for VAs. First and foremost, to adequately protect users from abuse of power by firms deploying VAs, the core fiduciary duty of loyalty should be converted into corresponding fiduciary requirements for VAs, obliging firms to align VAs with their users. (shrink)

This paper provides an in-depth analysis of the impact of AI technologies on the climate crisis beyond their mere resource consumption. To critically examine this impact, I introduce the concept of AI futurism. With this term I capture the ideology behind AI, and argue that this ideology is inherently connected to the climate crisis. This is because AI futurism construes a socio-material environment overly fixated on AI and technological progress, to the extent that it loses sight of the existential threats (...) ahead. In that way, the perceived significance of the planetary reality is softened, and the unsustainable paths charted by the AI industry remain opaque. To make this argument the paper unfolds in two main sections. (1) It delves into the ideology of AI futurism and its discursive impact on the societal perception of the climate crisis. (2) It employs a materialist perspective to elucidate the tangible effects of the AI industry on the climate crisis, and to show what is going on behind the façade of AI futurism. Adding to a critical theory of AI and the climate crisis, this paper starts a realistic conversation about the challenges posed by the intersection of these transformations. (shrink)

With regard to current debates on the ethical implementation of AI, especially two demands are linked: the call for explainability and for ultimate human responsibility. In the medical field, both are condensed into the role of one person: It is the physician to whom AI output should be explainable and who should thus bear ultimate responsibility for diagnostic or treatment decisions that are based on such AI output. In this article, we argue that a black box AI indeed creates a (...) rationally irresolvable epistemic situation for the physician involved. Specifically, strange errors that are occasionally made by AI sometimes detach its output from human reasoning. Within this article it is further argued that such an epistemic situation is problematic in the context of ultimate human responsibility. Since said strange errors limit the promises of explainability and the concept of explainability frequently appears irrelevant or insignificant when applied to a diverse set of medical applications, we deem it worthwhile to reconsider the call for ultimate human responsibility. (shrink)

Artificial intelligence (AI) has become nearly ubiquitous in modern society, from components of mobile applications to medical support systems, and everything in between. In societally impactful systems imbued with AI, there has been increasing concern related to opaque AI, that is, artificial intelligence where it is unclear how or why certain decisions are reached. This has led to a recent boom in research on “explainable AI” (XAI), or approaches to making AI more explainable and understandable to human users. In the (...) military domain, numerous bodies have argued that autonomous and AI-enabled weapon systems ought not incorporate unexplainable AI, with the International Committee of the Red Cross and the United States Department of Defense both explicitly including explainability as a relevant factor in the development and use of such systems. In this article, I present a cautiously critical assessment of this view, arguing that explainability will be irrelevant for many current and near-future autonomous systems in the military (which do not incorporate any AI), that it will be trivially incorporated into most military systems which do possess AI (as these generally possess simpler AI systems), and that for those systems with genuinely opaque AI, explainability will prove to be of more limited value than one might imagine. In particular, I argue that explainability, while indeed a virtue in design, is a virtue aimed primarily at designers and troubleshooters of AI-enabled systems, but is far less relevant for users and handlers actually deploying these systems. I further argue that human–machine teaming is a far more important element of responsibly using AI for military purposes, adding that explainability may undermine efforts to improve human–machine teamings by creating a prima facie sense that the AI, due to its explainability, may be utilized with little (or less) potential for mistakes. I conclude by clarifying that the arguments are not against XAI in the military, but are instead intended as a caution against over-inflating the value of XAI in this domain, or ignoring the limitations and potential pitfalls of this approach. (shrink)

In this paper, I support a hybrid form of expressivism called constructive ecumenical expressivism (CEE) which I have previously used (to attempt) to resolve the gamer’s dilemma. (Young, 2016. Resolving the gamer’s dilemma. London: Palgrave Macmillan.) In support of CEE, I argue that the various other attempts at either resolving, dissolving or resisting the dilemma are consistent with CEE’s moral framework. That is, with its way of explaining what a claim to morality is, with how moral norms are established, with (...) the role intuition is able to play in establishing these norms, and therefore with how the gamer’s dilemma can be resolved. I also demonstrate, more broadly, how CEE advocates robust relativism as a means of justifying the constructed moral norm’s normative credentials, and therefore how one society’s norm can be judged morally superior to another’s. (shrink)

“Deathbots,” digital constructs that emulate the conversational patterns, demeanor, and knowledge of deceased individuals. Earlier moral discussions about deathbots centered on the dignity and autonomy of the deceased. This paper primarily examines the potential psychological and emotional dependencies that users might develop towards deathbots, considering approaches to prevent problematic dependence through temporary use. We adopt a hermeneutic method to argue that deathbots, as they currently exist, are unlikely to provide substantial comfort. Lacking the capacity to bear emotional burdens, they fall (...) short of meeting idealistic expectations. By repositioning deathbots, we aim to mitigate the risk of emotional dependency and respect the natural grieving process. Our goal is to propose the use of deathbots as a novel means of mourning through transitory use, rather than as a method to alleviate grief or as a patterns for communication with the deceased. (shrink)

Increasingly, our cities are confronted with crises. Fuelled by climate change and a loss of biodiversity, increasing inequalities and fragmentation, challenges range from social unrest and outbursts of violence to heatwaves, torrential rainfall, or epidemics. As crises require rapid interventions that overwhelm human decision-making capacity, AI has been portrayed as a potential avenue to support or even automate decision-making. In this paper, I analyse the specific challenges of AI in urban crisis management as an example and test case for many (...) super wicked decision problems. These super wicked problems are characterised by a coincidence of great complexity and urgency. I will argue that from this combination, specific challenges arise that are only partially covered in the current guidelines and standards around trustworthy or human-centered AI. By following a decision-centric perspective, I argue that to solve urgent crisis problems, the context, capacities, and networks need to be addressed. AI for crisis response needs to follow dedicated design principles that ensure (i) human control in complex social networks, where many humans interact with AI; (ii) principled design that considers core principles of crisis response such as solidarity and humanity; (iii) designing for the most vulnerable. As such this paper is meant to inspire researchers, AI developers and practitioners in the space of AI for (urban) crisis response – and other urgent and complex problems that urban planners are confronted with. (shrink)

Responsibility has become a central concept in AI ethics; however, little research has been conducted into practitioners’ personal understandings of responsibility in the context of AI, including how responsibility should be defined and who is responsible when something goes wrong. In this article, we present findings from a 2020–2021 data set of interviews with AI practitioners and tech workers at a single multinational technology company and interpret them through the lens of feminist political thought. We reimagine responsibility in the context (...) of AI development and deployment as the product of work cultures that enable tech workers to be responsive and answerable for their products over the long and short term. From our interviews, we identify three key pain points in understanding the distribution of responsibility between actors and developing responsible design and deployment practices: (1) unstable business ecosystems and AI lifecycles, which require an approach to responsibility that accounts for the dynamic nature of these systems; (2) the issue of incentivizing engineers to take responsibility for the mundane maintenance practices essential to the functioning of AI systems and (3) the need to overcome individual and structural barriers to taking ownership over AI products and their effects. From these findings, we make three recommendations based on feminist theory: (1) organisations should move from a static model of responsibility to a dynamic and ethically motivated response-ability; (2) companies need to revalue care and maintenance practices; and (3) firms must move away from individualistic ideas of responsibility towards fostering wider cultures of responsibility. (shrink)

It is well known that AI-based language technology—large language models, machine translation systems, multilingual dictionaries, and corpora—is currently limited to three percent of the world’s most widely spoken, financially and politically backed languages. In response, recent efforts have sought to address the “digital language divide” by extending the reach of large language models to “underserved languages.” We show how some of these efforts tend to produce flawed solutions that adhere to a hard-wired representational preference for certain languages, which we call (...) language modeling bias. Language modeling bias is a specific and under-studied form of linguistic bias were language technology by design favors certain languages, dialects, or sociolects with respect to others. We show that language modeling bias can result in systems that, while being precise regarding languages and cultures of dominant powers, are limited in the expression of socio-culturally relevant notions of other communities. We further argue that at the root of this problem lies a systematic tendency of technology developer communities to apply a simplistic understanding of diversity which does not do justice to the more profound differences that languages, and ultimately the communities that speak them, embody. Drawing on the concept of epistemic injustice, we point to the broader ethico-political implications and show how it can lead not only to a disregard for valuable aspects of diversity but also to an under-representation of the needs of marginalized language communities. Finally, we present an alternative socio-technical approach that is designed to tackle some of the analyzed problems. (shrink)

This paper critically examines Coeckelbergh’s (2023) performative view of moral status. Drawing parallels to Searle’s social ontology, two key claims of the performative view are identified: (1) Making a moral status claim is equivalent to making a moral status declaration. (2) A successful declaration establishes the institutional fact that the entity has moral status. Closer examination, however, reveals flaws in both claims. The second claim faces a dilemma: individual instances of moral status declaration are likely to fail because they do (...) not conform to established moral discourse conventions, and reliance on declarations becomes both unnecessary and implausible for explaining widespread collective recognition of moral status. As for the first claim, accepting it undermines the potential for meaningful moral disagreement. As a remedy, this paper proposed a shift in perspective: interpreting moral status claims as assertions rather than declarations. This refined perspective provides a more plausible framework for understanding moral status and avoids the pitfalls associated with the performative view. (shrink)

Machine ethics is the field that strives to develop ‘artificial moral agents’ (AMAs), artificial systems that can autonomously make moral decisions. Some authors have questioned the feasibility of machine ethics, by questioning whether artificial systems can possess moral competence, or the capacity to reach morally right decisions in various situations. This paper explores this question by drawing on the work of several moral philosophers (McDowell, Wiggins, Hampshire, and Nussbaum) who have characterised moral competence in a manner inspired by Aristotle. Although (...) disparate in many ways, these philosophers all emphasise what may be called ‘moral sensitivity’ as a precondition for moral competence. Moral sensitivity is the uncodified, practical skill to recognise, in a range of situations, which features of the situations are morally relevant, and how they are relevant. This paper argues that the main types of AMAs currently proposed are incapable of full moral sensitivity. First, top-down AMAs that proceed from fixed rule-sets are too rigid to respond appropriately to the wide range of qualitatively unique factors that moral sensitivity gives access to. Second, bottom-up AMAs that learn moral behaviour from examples are at risk of generalising from these examples in undesirable ways, as they lack embedding in what Wittgenstein calls a ‘form of life’, which allows humans to appropriately learn from moral examples. The paper concludes that AMAs are unlikely to possess full moral competence, but closes by suggesting that they may still be feasible in restricted domains of public morality, where moral sensitivity plays a smaller role. (shrink)

My focus is on the contemporary astrobiological activity of Messaging ExtraTerrestrial Intelligence (METI). This intentional astrobiological signaling typically involves embedding digital communications in powerful radio signals and transmitting those signals out into the cosmos in an explicit effort to make contact with extraterrestrial others. Some who criticize METI express concern that contact with technologically advanced extraterrestrial life could be seriously harmful to Earth or humanity. One popular response to this critique of messaging is an appeal to causal impotence sometimes referred (...) to as the ‘Barn Door’ Argument—we are already engaged in many other detectable activities not intended for cosmic communication. If the Barn Door Argument is correct, then those who engage in messaging arguably have a moral excuse. They are permitted to continue messaging because there is no point in abstaining. I develop three ways in which the claim of causal impotence in the Barn Door Argument could be understood. I evaluate each of these in turn and demonstrate that only one is appropriate to contemporary messaging. However, this interpretation does not generate the moral excuse on which the proponents of the Barn Door Argument rely; thus, the argument fails. Finally, I entertain and respond to candidate objections. (shrink)

Emerging technologies such as artificial intelligence, gene editing, nanotechnology, neurotechnology and robotics, which were originally unrelated or separated, are becoming more closely integrated. Consequently, the boundaries between the physical-biological and the cyber-digital worlds are no longer well defined. We argue that this technological convergence has fundamental implications for individuals and societies. Conventional domain-specific governance mechanisms have become ineffective. In this paper we provide an overview of the ethical, societal and policy challenges of technological convergence. Particularly, we scrutinize the adequacy of (...) domain-specific governance mechanisms in the face of such integrated technologies and highlight their growing ineffectiveness. Furthermore, we propose a comprehensive governance framework that is anticipatory, inclusive, and resilient. Central to this framework is the principle of participatory governance, which calls for a proactive engagement of all stakeholders, including those from marginalized and vulnerable populations, ensuring that their voices and concerns shape the trajectory of technological development. The framework emphasizes the need for protective measures that preemptively address potential risks and inequities that may arise from the adoption and integration of emerging technologies. Based on a detailed analysis of case studies and current governance models, we present and discuss a set of ten actionable recommendations. These are designed to facilitate the transition towards a governance approach that not only respects individual autonomy and privacy, but also fosters a collective responsibility towards sustainable and fair technological progress. By placing human dignity, societal welfare and the protection of the most vulnerable at the center of technological innovation, we advocate for a future where convergence is synonymous with progress that is both ethically grounded and universally beneficial. (shrink)

Recent scholarship on technology-induced ‘conceptual disruption’ has spotlighted the notion of a conceptual gap. Conceptual gaps have also been discussed in scholarship on epistemic injustice, yet up until now these bodies of work have remained disconnected. This article shows that ‘gaps’ of interest to both bodies of literature are closely related, and argues that a joint examination of conceptual disruption and epistemic injustice is fruitful for both fields. I argue that hermeneutical marginalization—a skewed division of hermeneutical resources, which serves to (...) diminish the experiences of marginalized folk—does not only transpire because of conceptual gaps, but also because of two other kinds of conceptual disruption: conceptual overlaps and conceptual misalignments. Hence, there are multiple kinds of conceptual disruption that can be usefully studied through the normative lens of epistemic injustice. Technology can play different roles vis-a-vis epistemic injustices, both as a causal trigger of conceptual disruption, but also as a mediator of hermeneutical resources. Its role is normatively significant, in particular because socially disruptive technologies can have different epistemic implications for different groups: they may amplify the epistemic resources of some groups, while diminishing those of others. (shrink)

Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending and curbing manipulation risks. By highlighting these questions, the article underscores the necessity of an appropriate conceptualisation of manipulation to ensure the responsible development of Generative AI technologies.

Debate over the normativity of virtual phenomena is now widespread in the philosophical literature, taking place in roughly two distinct but related camps. The first considers the relevant problems to be within the scope of applied ethics, where the general methodological program is to square the intuitive (im)permissibility of virtual wrongdoings with moral accounts that justify their (im)permissibility. The second camp approaches the normativity of virtual wrongdoings as a metaphysical debate. This is done by disambiguating the ‘virtual’ character of ‘virtual (...) wrongdoings’. Doing so is supposed to provide illuminating ontological distinctions that inform ethical aspects of the debate. We argue that each approach faces its own set of issues, and as a result, motivates consideration of an alternative. The alternative we suggest turns inquiry concerning the normativity of virtual wrongdoings into a distinctively conceptual question. Rather than asking whether some action is right or wrong, or whether some virtual phenomenon counts as a particular action at all, we argue that research into the normativity of virtual wrongdoings may be guided by reflecting on whether a concept that originated and developed within a non-virtual context should be exported into a foreign virtual domain. We consider this approach and several objections. (shrink)

This paper argues that one problem that besets black-box AI is that it lacks algorithmic justifiability. We argue that the norm of shared decision making in medical care presupposes that treatment decisions ought to be justifiable to the patient. Medical decisions are justifiable to the patient only if they are compatible with the patient’s values and preferences and the patient is able to see that this is so. Patient-directed justifiability is threatened by black-box AIs because the lack of rationale provided (...) for the decision makes it difficult for patients to ascertain whether there is adequate fit between the decision and the patient’s values. This paper argues that achieving algorithmic transparency does not help patients bridge the gap between their medical decisions and values. We introduce a hypothetical model we call Justifiable AI to illustrate this argument. Justifiable AI aims at modelling normative and evaluative considerations in an explicit way so as to provide a stepping stone for patient and physician to jointly decide on a course of treatment. If our argument succeeds, we should prefer these justifiable models over alternatives if the former are available and aim to develop said models if not. (shrink)

The aim of this paper is to investigate the relationship between AI urbanism and sustainability by drawing upon some key concepts of Bruno Latour’s philosophy. The idea of a sustainable AI urbanism - often understood as the juxtaposition of smart and eco urbanism - is here critiqued through a reconstruction of the conceptual sources of these two urban paradigms. Some key ideas of smart and eco urbanism are indicated as incompatible and therefore the fusion of these two paradigms is assessed (...) as an unstable basis for shaping sustainable AI urbanism. The concepts in question - modernity, science and nature – are subsequently redefined following Latour’s philosophical perspective, in an attempt to define a different theoretical basis for a sustainable AI urbanism in the Anthropocene. Finally, the principles of a design philosophy shaped by Latour are used to change the design culture that informs AI urbanism towards a more sustainable practice. This paper constructs and promotes a dialogue between the disciplines of philosophy and urban theory with urban design in the conviction that the principles produced by the former and the practices carried out by the latter must start a biunivocal relationship. The paper reveals that in order to change design culture in the field of AI urbanism, it is necessary to rethink some of the key ideas that inform the Western and modern worldview through novel philosophical reflections. (shrink)