Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI (...) ethics. Finally, I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved. (shrink)

Companies increasingly deploy artificial intelligence technologies in their personnel recruiting and selection process to streamline it, making it faster and more efficient. AI applications can be found in various stages of recruiting, such as writing job ads, screening of applicant resumes, and analyzing video interviews via face recognition software. As these new technologies significantly impact people’s lives and careers but often trigger ethical concerns, the ethicality of these AI applications needs to be comprehensively understood. However, given the novelty of AI (...) applications in recruiting practice, the subject is still an emerging topic in academic literature. To inform and strengthen the foundation for future research, this paper systematically reviews the extant literature on the ethicality of AI-enabled recruiting to date. We identify 51 articles dealing with the topic, which we synthesize by mapping the ethical opportunities, risks, and ambiguities, as well as the proposed ways to mitigate ethical risks in practice. Based on this review, we identify gaps in the extant literature and point out moral questions that call for deeper exploration in future research. (shrink)

The paper presents an ethical analysis and constructive critique of the current practice of AI ethics. It identifies conceptual substantive and procedural challenges and it outlines strategies to address them. The strategies include countering the hype and understanding AI as ubiquitous infrastructure including neglected issues of ethics and justice such as structural background injustices into the scope of AI ethics and making the procedures and fora of AI ethics more inclusive and better informed with regard to (...) philosophical ethics. These measures integrate the perspective of AI justice into AI ethics, strengthening its capacity to provide comprehensive normative orientation and guidance for the development and use of AI that actually improves human lives and living together. (shrink)

Sovereignty and strategic autonomy are felt to be at risk today, being threatened by the forces of rising international tensions, disruptive digital transformations and explosive growth of cybersecurity incidents. The combination of AI and cybersecurity is at the sharp edge of this development and raises many ethical questions and dilemmas. In this commentary, I analyse how we can understand the ethics of AI and cybersecurity in relation to sovereignty and strategic autonomy. The analysis is followed by policy recommendations, some (...) of which may appear to be controversial, such as the strategic use of ethics. I conclude with a reflection on underlying concepts as an invitation for further research. The goal is to inspire policy-makers, academics and business strategists in their work, and to be an input for public debate. (shrink)

Artificial intelligence’s impact on healthcare is undeniable. What is less clear is whether it will be ethically justifiable. Just as we know that AI can be used to diagnose disease, predict risk, develop personalized treatment plans, monitor patients remotely, or automate triage, we also know that it can pose significant threats to patient safety and the reliability (or trustworthiness) of the healthcare sector as a whole. These ethical risks arise from (a) flaws in the evidence base of healthcare AI (epistemic (...) concerns); (b) the potential of AI to transform fundamentally the meaning of health, the nature of healthcare, and the practice of medicine (normative concerns); and (c) the “black box” nature of the AI development pipeline, which undermines the effectiveness of existing accountability mechanisms (traceability concerns). In this chapter, we systematically map (a)–(c) to six different levels of abstraction: individual, interpersonal, group, institutional, sectoral, and societal. The aim is to help policymakers, regulators, and other high-level stakeholders delineate the scope of regulation and other “softer” governing measures for AI in healthcare. We hope that by doing so, we may enable global healthcare systems to capitalize safely and reliably on the many benefits of healthcare AI. (shrink)

This article presents a mapping review of the literature concerning the ethics of artificial intelligence (AI) in health care. The goal of this review is to summarise current debates and identify open questions for future research. Five literature databases were searched (Scopus, Google Scholar, Philpapers, Web of Science, Pub Med), in April 2019, to support the following research question: “how can the primary ethical risks presented by AI-health be categorised, and what issues must policymakers, regulators and developers consider in (...) order to be ‘ethically mindful?’”. A series of screening stages were carried out—for example, removing articles that focused on digital health in general (e.g. data sharing, data access, data privacy, surveillance/nudging, consent, ownership of health data, evidence of efficacy)—yielding a total of 156 papers that were included in the review.We find that ethical issues can be (a) epistemic, related to misguided, inconclusive or inscrutable evidence; (b) normative, related to unfair outcomes and transformative effectives; or (c) related to traceability. We further find that these ethical issues arise at six levels of abstraction: individual, interpersonal, group, institutional, and societal or sectoral. Finally, we outline a number of considerations for policymakers and regulators, mapping these to existing literature, and categorising each as epistemic, normative or traceability-related and at the relevant level of abstraction. This article contributes to the debate on AI in health care by offering a comprehensive analysis of the relevant literature, focusing on the ethical implications for individuals, interpersonal relationships, groups, institutions, societies and the health sector as a whole. Our goal is to inform policymakers, regulators and developers of what they must consider if they are to enable health and care systems to capitalise on the dual advantage of ethical AI; maximising the opportunities to cut costs, improve care, and improve the efficiency of health and care systems, whilst proactively avoiding the potential harms. We argue that if action is not swiftly taken in this regard, a new ‘AI winter’ could occur due to chilling effects related to a loss of public trust in the benefits of AI for health care. (shrink)

One of the common concerns raised in AI ethics scholarship is the overly western-centric nature of ongoing AI ethics discourse and governance initiatives. This has recently prompted many commentators to proclaim the emergence of an epistemic injustice or “ethical colonialism”. Many scholars point to the role of indigenous ethical systems, particularly Ubuntu, in addressing this flaw. In the meantime, a series of national and continental AI governance initiatives are also emerging in Africa. But the extent to which Ubuntu (...) and emergent AI governance initiatives contribute towards addressing the problem of epistemic injustice is yet to be interrogated. In a novel approach, I examine in this article the extent to which Ubuntu and AI governance initiatives in Africa articulate an African perspective of AI ethics, and hence address the epistemic injustice. I argue that neither the normative structure of Ubuntu nor recent AI governance initiatives offer a clear, coherent and practicable framework of “African AI ethics”. I further show that the much-touted “African” ethics of Ubuntu is rarely referenced or implied in recent national or continental AI governance initiatives. I close the article with a call for defining African AI ethics by relevant actors in the continent. (shrink)

In this chapter we question the use of the term |ethics of AI|. Our thesis is that |ethics of AI| is a floating signifier, a notion borrowed from Ernesto Laclau. The article is divided into two parts. In the first part, we discuss the need to include in the ethics of AI a reflection on the ethics of communication about AI. We also introduce the concept of the floating signifier. In the second part, we propose an (...) analysis of the discourses mobilizing |ethics of AI| in the daily press. We examine articles mobilizing |ethics of AI| that appeared in eight daily newspapers in four European countries (France, Italy, the UK, and Germany) over a three-month period. We show the existence of three discursive uses of AI ethics: the normativity of institutions, the critique of researchers, and the techno-solutionism of companies. (shrink)

There is enormous interest in using artificial intelligence (AI) in health care contexts. But before AI can be used in such settings, we need to make sure that AI researchers and organizations follow appropriate ethical frameworks and guidelines when developing these technologies. In recent years, a great number of ethical frameworks for AI have been proposed. However, these frameworks have tended to be abstract and not explain what grounds and justifies their recommendations and how one should use these recommendations in (...) practice. In this paper, I propose an AI ethics framework that is grounded in substantive, human rights theory and one that can help us address these questions. (shrink)

Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...) Some people have a more subtle view, arguing that it is problematic in those cases where its use may degrade important interpersonal virtues. In this article, I assess these objections to the use of AI assistants. I will argue that the ethics of their use is complex. There are no quick fixes or knockdown objections to the practice, but there are some legitimate concerns. By carefully analysing and evaluating the objections that have been lodged to date, we can begin to articulate an ethics of personal AI use that navigates those concerns. In the process, we can locate some paradoxes in our thinking about outsourcing and technological dependence, and we can think more clearly about what it means to live a good life in the age of smart machines. (shrink)

This article analyzes the digitalization process in the Republic of Uzbekistan, a Central Asian country that currently holds a low position in the Government AI Readiness Index. The aim of the article is to provide an initial overview of the ethical norms required for public servants in the context of AI usage. To develop such a code, an exploratory foundation must first be established. The necessity for an AI Code of Ethics is also explicitly mentioned in the national strategy (...) “Digital Uzbekistan – 2030”. The research uses both theoretical and comparative legal analysis. The survey was also conducted which measures the digital and ethical literacy and readiness to adopt AI technologies. According to the author, the factors hindering the implementation of AI into the professional activities of civil servants are, firstly, the insufficient level of AI skills among Uzbek civil servants, and secondly, there is an urgent need to develop a national system for the ethical regulation of issues related to AI in general, which are currently being developed. Voluntary adherence to international ethical codes for AI and the development of its own model for AI ethical regulation can reduce the level of cyber fraud in the country. (shrink)

This article introduces readers to the special issue on Selected Issues in the Ethics of Artificial Intelligence. In this paper, I make a case for a wider outlook on the ethics of AI. So far, much of the engagements with the subject have come from Euro-American scholars with obvious influences from Western epistemic traditions. I demonstrate that socio-cultural features influence our conceptions of ethics and in this case the ethics of AI. The goal of this special (...) issue is to entertain more diverse views, particularly those from Africa; it brings together six articles addressing pertinent issues in the ethics of AI. These articles address topics around artificial moral agency, patiency, personhood, social robotics, and the principle of explicability. These works offer unique contributions for and from an African perspective. I contend that a wider engagement with the ethics of AI is worthwhile as we anticipate a global deployment of artificial intelligence systems. (shrink)

The stakes in medicine are high. Crucial decisions, often involving matters of life and death, have to be made quickly. However, medicine is practised under great uncertainty. Clinicians sometimes lack the evidence required to diagnose or treat patients with confidence; patients struggle to know when to seek care; and policymakers must design rules or plan interventions using incomplete data. When faced with a decision problem, it is often unclear what the right course of action is or how to respond when (...) something goes wrong. But given the stakes, delaying action is often not an option. Artificial intelligence (AI) is transforming our epistemic and moral landscapes. With access to vast datasets and the computational power required to analyse them, AI detects patterns that clinicians would miss, quantifies policy trade-offs that were previously invisible and generates increasingly fine-grained predictions. However, better evidence does not necessarily mean the resolution of moral uncertainty. With more information at our disposal, we may have to make more morally significant choices than ever before. We must also assign responsibility in contexts where decision-making is distributed across both humans and AI agents, even though the latter may at times operate in ways entirely opaque to us. This special e-issue of the Journal of Medical Ethics brings together nine articles that address AI’s transformation of uncertainty in medicine. This collection is unified by a central insight: AI may broaden our access to information and offer new, optimised solutions to longstanding problems, but its use introduces new complications to already challenging moral quandaries. Indeed, with AI in the loop, how to choose or act permissibly and how to distribute moral responsibility in a complex system have become more difficult to determine. The articles here take one of two approaches to these issues. The first is to show how AI expands …. (shrink)

In this paper we, an epistemologist and a machine learning scientist, argue that we need to pursue a novel area of philosophical research in AI – the ethics of belief for AI. Here we take the ethics of belief to refer to a field at the intersection of epistemology and ethics concerned with possible moral, practical, and other non-truth-related dimensions of belief. In this paper we will primarily be concerned with the normative question within the ethics (...) of belief regarding what agents – both human and artificial – ought to believe, rather than with questions concerning whether beliefs meet certain evaluative standards such as being true, being justified, constituting knowledge, etc. We suggest four topics in extant work in the ethics of (human) belief that can be applied to an ethics of AI belief: doxastic wronging by AI (morally wronging someone in virtue of beliefs held about them); morally owed beliefs (beliefs that agents are morally obligated to hold); pragmatic and moral encroachment (cases where the practical or moral features of a belief is relevant to its epistemic status, and in our case specifically to whether an agent ought to hold the belief); and moral responsibility for AI beliefs. We also indicate two relatively nascent areas of philosophical research that haven’t yet been generally recognized as ethics of AI belief research, but that do fall within this field of research in virtue of investigating various moral and practical dimensions of belief: the epistemic and ethical decolonization of AI; and epistemic injustice in AI. (shrink)

This 44-chapter volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and (...) are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I.". (shrink)

Making good decisions in extremely complex and difficult processes and situations has always been both a key task as well as a challenge in the clinic and has led to a large amount of clinical, legal and ethical routines, protocols and reflections in order to guarantee fair, participatory and up-to-date pathways for clinical decision-making. Nevertheless, the complexity of processes and physical phenomena, time as well as economic constraints and not least further endeavours as well as achievements in medicine and healthcare (...) continuously raise the need to evaluate and to improve clinical decision-making. This article scrutinises if and how clinical decision-making processes are challenged by the rise of so-called artificial intelligence-driven decision support systems (AI-DSS). In a first step, this article analyses how the rise of AI-DSS will affect and transform the modes of interaction between different agents in the clinic. In a second step, we point out how these changing modes of interaction also imply shifts in the conditions of trustworthiness, epistemic challenges regarding transparency, the underlying normative concepts of agency and its embedding into concrete contexts of deployment and, finally, the consequences for (possible) ascriptions of responsibility. Third, we draw first conclusions for further steps regarding a ‘meaningful human control’ of clinical AI-DSS. (shrink)

Healthcare systems across the globe are struggling with increasing costs and worsening outcomes. This presents those responsible for overseeing healthcare with a challenge. Increasingly, policymakers, politicians, clinical entrepreneurs and computer and data scientists argue that a key part of the solution will be ‘Artificial Intelligence’ (AI) – particularly Machine Learning (ML). This argument stems not from the belief that all healthcare needs will soon be taken care of by “robot doctors.” Instead, it is an argument that rests on the classic (...) counterfactual definition of AI as an umbrella term for a range of techniques that can be used to make machines complete tasks in a way that would be considered intelligent were they to be completed by a human. Automation of this nature could offer great opportunities for the improvement of healthcare services and ultimately patients’ health by significantly improving human clinical capabilities in diagnosis, drug discovery, epidemiology, personalised medicine, and operational efficiency. However, if these AI solutions are to be embedded in clinical practice, then at least three issues need to be considered: the technical possibilities and limitations; the ethical, regulatory and legal framework; and the governance framework. In this article, we report on the results of a systematic analysis designed to provide a clear overview of the second of these elements: the ethical, regulatory and legal framework. We find that ethical issues arise at six levels of abstraction (individual, interpersonal, group, institutional, sectoral, and societal) and can be categorised as epistemic, normative, or overarching. We conclude by stressing how important it is that the ethical challenges raised by implementing AI in healthcare settings are tackled proactively rather than reactively and map the key considerations for policymakers to each of the ethical concerns highlighted. (shrink)

This book addresses the growing need for ethical considerations in the development and deployment of Artificial Intelligence (AI) systems. As AI technologies continue to advance at an unprecedented pace, they bring transformative benefits across industries but also raise significant ethical challenges, such as bias, accountability, transparency, and societal impact. This book bridges the gap between theoretical ethical principles and practical engineering practices, offering a comprehensive guide for embedding ethics into the AI development lifecycle. By focusing on actionable frameworks, case (...) studies, and engineering-centric approaches, the book equips readers with the tools to design and implement AI systems that are not only innovative but also responsible and aligned with societal values. (shrink)

Volume 19, Issue 11, November 2019, Page 45-47.

Unlike the many services already transformed by artificial intelligence (AI), the financial advice sector remains committed to a human interface. That is surprising as an AI-powered financial advisor (a robo-advisor) can offer personalised financial advice at much lower cost than traditional human advice. This is particularly important for those who need but cannot afford or access traditional financial advice. Robo-advice is easily accessible, available on-demand, and pools all relevant information in finding and implementing an optimal financial plan. In a perfectly (...) competitive market for financial advice, robo-advice should prevail. Unfortunately, this market is imperfect with asymmetric information causing generalised advice aversion with a disproportionate lack of trust in robo-advice. Initial distrust makes advice clients reluctant to use, or switch to, robo-advice. This paper investigates the ethical concerns specific to robo-advice underpinning this lack of trust. We propose a regulatory framework addressing these concerns to ensure robo-advice can be an ethical resource for good, resolving the increasing complexity of financial decision-making. Fit for purpose regulation augments initial trust in robo-advice and supports advice clients in discriminating between high-trust and low-trust robo-advisors. Aspiring robo-advisors need to clear four licensing gateways to qualify for an AI Robo-Advice License (AIRAL). Licensed robo-advisors should then be monitored for ethical compliance. Using a balanced score card for ethical performance generates an ethics rating. This gateways-and-ratings methodology builds trust in the robo-advisory market through improved transparency, reduced information asymmetry, and lower risk of adverse selection. (shrink)

Unlike the many services already transformed by artificial intelligence (AI), the financial advice sector remains committed to a human interface. That is surprising as an AI-powered financial advisor (a robo-advisor) can offer personalised financial advice at much lower cost than traditional human advice. This is particularly important for those who need but cannot afford or access traditional financial advice. Robo-advice is easily accessible, available on-demand, and pools all relevant information in finding and implementing an optimal financial plan. In a perfectly (...) competitive market for financial advice, robo-advice should prevail. Unfortunately, this market is imperfect with asymmetric information causing generalised advice aversion with a disproportionate lack of trust in robo-advice. Initial distrust makes advice clients reluctant to use, or switch to, robo-advice. This paper investigates the ethical concerns specific to robo-advice underpinning this lack of trust. We propose a regulatory framework addressing these concerns to ensure robo-advice can be an ethical resource for good, resolving the increasing complexity of financial decision-making. Fit for purpose regulation augments initial trust in robo-advice and supports advice clients in discriminating between high-trust and low-trust robo-advisors. Aspiring robo-advisors need to clear four licensing gateways to qualify for an AI Robo-Advice License (AIRAL). Licensed robo-advisors should then be monitored for ethical compliance. Using a balanced score card for ethical performance generates an ethics rating. This gateways-and-ratings methodology builds trust in the robo-advisory market through improved transparency, reduced information asymmetry, and lower risk of adverse selection. (shrink)

A major international consultancy firm identified ‘AI ethicist’ as an essential position for companies to successfully implement artificial intelligence (AI) at the start of 2019. It declares that AI ethicists are needed to help companies navigate the ethical and social issues raised by the use of AI. Top 5 AI hires companies need to succeed in 2019. The view that AI is beneficial but nonetheless potentially harmful to individuals and society is widely shared by the industry, academia, governments, and civil (...) society organizations. Accordingly and in order to realize its benefits while avoiding ethical pitfalls and harmful consequences, numerous initiatives have been established to a) examine the ethical, social, legal and political dimensions of AI and b) develop ethical guidelines and recommendations for design and implementation of AI. (shrink)

Recruitment is often the most time-consuming and expensive step of clinical trials. As such, it is the most common stage for AI implementation, due to its power to hasten timelines, reduce costs and workloads, and potentially increase the representativeness of study cohorts. Yet, formal regulatory guidance on the use and ethics of AI specifically for clinical trial recruitment is limited, and best practices have yet to be defined. Here, we discuss the use of AI in the trial recruitment process (...) across five domains, synthesize the ethical elements that apply to AI recruitment, and advance a framework of considerations and recommendations across use cases and ethical elements. The ethical elements, tensions, and recommendations discussed here will help inform the practices of and oversight by investigators, commercial recruitment entities, contract research organizations, sponsors, regulators, and IRBs as they develop, test, use, and evaluate AI models for clinical trial recruitment. (shrink)

With AI permeating our lives, there is widespread concern regarding the proper framework needed to morally assess and regulate it. This has given rise to many attempts to devise ethical guidelines that infuse guidance for both AI development and deployment. Our main concern is that, instead of a genuine ethical interest for AI, we are witnessing moral diplomacies resulting in moral bureaucracies battling for moral supremacy and political domination. After providing a short overview of what we term ‘ethics washing’ (...) in the AI industry, we analyze the 2021 UNESCO Intergovernmental Meeting of Experts (Category II) tasked with drafting the Recommendation on the Ethics of Artificial Intelligence and show why the term ‘moral diplomacy’ is better suited to explain what is happening in the field of the ethics of AI. Our paper ends with some general considerations regarding the future of the ethics of AI. (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.

In the original publication of this article, the Table 1 has been published in a low resolution. Now a larger version of Table 1 is published in this correction. The publisher apologizes for the error made during production.

This paper provides the first comprehensive analysis of ethical issues raised by artificial intelligence (AI) in veterinary medicine for companion animals. Veterinary medicine is a socially valued service, which, like human medicine, will likely be significantly affected by AI. Veterinary AI raises some unique ethical issues because of the nature of the client–patient–practitioner relationship, society’s relatively minimal valuation and protection of nonhuman animals and differences in opinion about responsibilities to animal patients and human clients. The paper examines how these distinctive (...) features influence the ethics of AI systems that might benefit clients, veterinarians and animal patients—but also harm them. It offers practical ethical guidance that should interest ethicists, veterinarians, clinic owners, veterinary bodies and regulators, clients, technology developers and AI researchers. (shrink)

In this chapter we take stock of some of the complexities of the sprawling field of AI ethics. We consider questions like "what is the proper scope of AI ethics?" And "who counts as an AI ethicist?" At the same time, we flag several potential uses and abuses of AI ethics. These include challenges for the AI ethicist, including what qualifications they should have; the proper place and extent of futuring and speculation in the field; and the (...) dilemmas concerning how we use our public and academic resources. (shrink)

The term ‘trustworthy AI’ has become one of the keywords in the academic and policy discussion of the social, ethical, and legal issues of artificial intelligence (AI), but it remains a contested notion and there are open debates about its meaning and how it is to be operationalized. For philosophers and ethicists, the debate has particularly revolved around the meaning of ‘trust’ and ‘trustworthiness’. However, since a thin and acultural understanding of trust and trustworthiness has been common in the debate, (...) the notion of trustworthy AI is at best ambiguous in a global and cross-cultural context, where trust and trustworthiness can be interpreted differently. A culturally-sensitive exploration of trust, trustworthiness, and trustworthy AI is, therefore, much needed to gain insights on what and how trustworthy AI can be conceptualised through the normative resources of other cultural traditions. This article attempts to offer a culturally sensitive exploration of trustworthy AI by drawing on recent analysis of trust and trustworthiness in Confucian philosophy. More specifically, I shall demonstrate how taking seriously the Confucian view of trust and trustworthiness in the context of AI provides us an alternative way to think about the ethics and governance of AI. (shrink)

As artificial intelligence approaches the threshold of replacing human labor across all domains, a profound ethical question emerges: In a post-work society, will human “laziness” transform from moral failing to existential privilege? This essay argues that AI automation forces humanity into an ontological crisis where traditional work-based identity structures collapse, compelling a choice between creative idleness and existential irrelevance. Through the lens of ontological instability—the fundamental uncertainty in the nature of being itself—we examine how the ethics of laziness undergoes (...) radical transformation in the age of artificial intelligence. Drawing on philosophical traditions from Paul Lafargue's “The Right to Be Lazy” to contemporary posthumanist theory, this analysis reveals that what we call “laziness” may represent not moral failure but the authentic human condition liberated from the artificial constraints of productive labor. The implications extend beyond economics to the very foundations of human identity, moral value, and social organization in a world where machines do everything and humans, perhaps for the first time in history, are free to do nothing—or everything that truly matters. (shrink)

This article proposes a new, Camusian approach to analyzing and navigating ethical dilemmas in relation to Artificial Intelligence (AI) and, by extension, to other disruptive technoscience. The article takes as its point of departure the Unified Framework of Five Principles for AI in Society, as advanced by Floridi and Cowls (2021), which offers a comprehensive and cohesive framework of the many abstract values and principles brought up in AI ethics discourse. Using a case-study approach, which focuses on the principle (...) of accountability in AI, we demonstrate that, even following an exhaustive systematization of abstract principles, ethical dilemmas still arise whenever we consider applications of the technology in concrete situations. Furthermore, because of the way technology mediates our ethical judgement, a deeper ethical dilemma arises; we can either judge technologies like AI prematurely, without knowing their impact, or after they have been able to bias our norms and intuitions for ethical deliberation. This article then argues that the vulnerability of our ethical judgement to continuous doubt, which is exposed by AI as a landmark case of disruptive technology, can be addressed by integrating Albert Camus’ philosophy of absurdity, rebellion and dignity. Through Camus, we can contextualize our experience of ethical doubt in relation to AI as existentially absurd, while also navigating normative change more confidently with meta-level principles for ethical deliberation itself. The article concludes that, while ethical dilemmas and doubts will persist, this Camusian approach will make us more responsible in undertaking the continuous adaptation and concretizing of our ethical frameworks. (shrink)

How do users experience AI-driven mobile language translation services in informalsettings and how can these scenarios be assessed in the light of intercultural ethics? Thisarticle reports a diffractive reading of the contemporary interdisciplinary literature on thesubject. The respective discourses follow various ethical narrations but share their goal ofaiming for a trustworthy AI. However, these discourses mainly focus on epistemologicalissues whereas posthumanist thought in intercultural ethics encourages experiencing thesephenomena from a less anthropocentric, decolonised and more ontological stance. Thisarticle offers (...) a posthumanist repositioning of intercultural AI ethics at the example ofmobile translation services. (shrink)

As artificial intelligence and robotics are increasingly integrated in graduate research and education, graduate students across disciplines need to develop a “technological literacy” in how they work along with the ethical understanding needed to navigate these technologies responsibly. To satisfy this need, the corresponding and last author has developed a graduate-level course on AI ethics and human-robot interaction (HRI) designed for students from a variety of disciplines and backgrounds. The paper offers an overview of the course, detailing its content, (...) institutional context, and the rationale behind its development. It describes the curriculum structure, including key themes and learning objectives, and the pedagogical approaches and assessment methods utilized in the course. The paper concludes with reflections from the instructor on the lessons learned from teaching the course and the experiences gained throughout the learning process. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Many researchers have documented how AI and data driven technologies have the potential to have profound effects on our lives—in ways that make these technologies stand out from those that went before. Around the world, we are seeing a significant growth in interest and investment in AI in healthcare. This has been coupled with rising concerns about the ethical implications of these technologies and an array of ethical guidelines for the use of AI and data in healthcare has arisen. Nevertheless, (...) the question of if and how AI and data technologies can be ethical remains open to debate. This paper aims to contribute to this debate by considering the wide range of implications that have been attributed to these technologies and asking whether current ethical guidelines take these factors into account. In particular, the paper argues that while current ethics guidelines for AI in healthcare effectively account for the four key issues identified in the ethics literature (transparency; fairness; responsibility and privacy), they have largely neglected wider issues relating to the way in which these technologies shape institutional and social arrangements. This, I argue, has given current ethics guidelines a strong focus on evaluating the impact of these technologies on the individual, while not accounting for the powerful social shaping effects of these technologies. To address this, the paper proposes a Multiscale Ethics Framework, which aims to help technology developers and ethical evaluations to consider the wider implications of these technologies. (shrink)

Artificial intelligence (AI) and its introduction into clinical pathways presents an array of ethical issues that are being discussed in the JME. 1–7 The development of AI technologies that can produce text that will pass plagiarism detectors 8 and are capable of appearing to be written by a human author 9 present new issues for medical ethics. One set of worries concerns authorship and whether it will now be possible to know that an author or student in fact produced (...) submitted work. That seems likely to be a general worry for secondary and higher education, as well as for all academic journals. Thus far generative AI chatbots do not seem to be able to produce a fully referenced and well-argued ethics article, but they probably could generate a blog or student essay that would... (shrink)

This theoretical essay offers a critical exploration of the ethics involved in interacting with and talking about large language models (LLMs) of artificial intelligence (AI). The discussion is framed within philosophical post-humanist conceptualizations of the ethical agent, which is understood as a sociocognitive assemblage of human–machine interactions at various scales. The central argument asserts that the morality of texts generated by AI cannot be determined by extracting moral properties from the natural language used in the training corpus. There are (...) inherent limits to how much analysing moral language can contribute to establishing a moral theory or a “language of mores” among humans. The essay also examines the ethical implications of current public discourse surrounding the capabilities of LLMs, as well as the ways in which LLM outputs personify the AI model itself. It is proposed that the ethics of LLMs should be approached as an ethics of translating informational patterns of linguistic symbols into multi-layered cultural meanings and vice versa. This includes addressing the opacity of the inner workings of these translations in the model, as well as the public relations practices of the creators. Ultimately, the discussion encourages rethinking the ethical agent as a human-machine sociocognitive hybrid, suggesting the need for a reassessment of what it means to be human and ethical in current AI ethics debates. (shrink)

Following the trend of sharing, and associating being on-line with being 'on-life', many people are now demanding the ownership and control of their data across all processing phases, including the erasure of their presence on the web. In Europe, recent proposals for regulation include an explicit 'Right to be Forgotten'; this right stated in the European Commission Proposal for Regulation COM 2011/12 does not emerge without controversy. It is being criticised on several grounds, including clashing with other rights, such as (...) freedom of expression, as well as setting the terrain for censorship. Besides the purely legal aspects of the proposed provisions, the chapters of this volume discuss how those legal provisions correspond in practice to worldviews and how individual and collective memory must be governed. They look into the deeper consequences of such provisions to construction of identity, culture and community formation, and how such a right affects how, what and why individuals, groups and societies remember and forget. (shrink)

This is the first book to provide a coherent overview over the ethical implications of AI-related technologies in medicine. It explores how these technologies transform practices, relationships, and environments in the clinical field. It provides an introduction into ethical issues such as data security and privacy protection, bias and algorithmic fairness, trust and transparency, challenges to the doctor-patient relationship, and new perspectives for informed consent. The book focuses on the transformative impact that technology is having on medicine, and discusses several (...) strategies for dealing with the resulting challenges. It also introduces innovative methods of ethics research for addressing existing desiderata and future challenges. This book is written to inform health care professionals, policy-makers, and researchers in medicine, health sciences, nursing science, social sciences, and ethics, but may also function as a primary textbook for graduate as well as undergraduate university courses. (shrink)

Despite facing significant criticism for assigning human-like characteristics to artificial intelligence, phrases like “trustworthy AI” are still commonly used in official documents and ethical guidelines. It is essential to consider why institutions continue to use these phrases, even though they are controversial. This article critically evaluates various reasons for using these terms, including ontological, legal, communicative, and psychological arguments. All these justifications share the common feature of trying to justify the official use of terms like “trustworthy AI” by appealing to (...) the need to reflect pre-existing facts, be it the ontological status, ways of representing AI or legal categories. The article challenges the justifications for these linguistic practices observed in the field of AI ethics and AI science communication. In particular, it takes aim at two main arguments. The first is the notion that ethical discourse can move forward without the need for philosophical clarification, bypassing existing debates. The second justification argues that it’s acceptable to use anthropomorphic terms because they are consistent with the common concepts of AI held by non-experts—exaggerating this time the existing evidence and ignoring the possibility that folk beliefs about AI are not consistent and come closer to semi-propositional beliefs. The article sounds a strong warning against the use of human-centric language when discussing AI, both in terms of principle and the potential consequences. It argues that the use of such terminology risks shaping public opinion in ways that could have negative outcomes. (shrink)

This article examines how emerging technologies – particularly artificial intelligence – disrupt the moral and institutional foundations of contemporary military practice. While strategic documents from the United States, NATO, and other major actors anticipate profound institutional transformation driven by AI, their treatment of ethics largely confines itself to legal compliance and technical safeguards, leaving the ethical role of military leadership in managing disruptive change underexamined. Drawing on Seumas Miller’s distinction between social institutions that are merely instrumental to collective goods (...) and those whose defining ends are constitutive of such goods, the article argues that the military belongs to the latter category. Because the military’s core function – defending the sovereignty of a polity – is itself morally significant, technological disruption of its organizational structures simultaneously constitutes ethical disruption. The article thus reconceives change management during periods of technological transition as calling for a specific kind of military prudence, a practical wisdom exercised within and through the institution’s role-mediated ethical practices. By analyzing three concrete modes of techno-moral disruption, the article shows how AI may reshape ethical standards, redistribute professional knowledge, and alter organizational ethos, and why navigating these transformations responsibly is a central task of military virtue. (shrink)

Women; ethics; religious aspects; ethics.

In “The Apt Curation Model: An Epistemic Virtue Theory of AI-assisted Authorship” (Philosophy & Technology 39 (2026)) Tiegue Vieira Rodrigues argues that we should conceive of the author in AI-supported processes as an apt curator of texts. He pleads for extending the accurate-adroit-apt framework towards human-AI authorship and developing four curatorial virtues: dialogical, evaluative, integrative, and architectural. This ‘Apt Curation Problem’ solves the problems constituted by the lack of a locus for the epistemic and semantic properties of authorship in the (...) case of AI-assisted text production. In this commentary on Rodrigues’ article, I aim to do three things: (1) summarize and praise the article; (2) reframe the apt curation model as a possible move in the conceptual engineering of AI and authorship; and (3) I argue that the apt curation model stands in need of more conceptual ethics – the metaphilosophical practice of giving reasons for the (sustained) use of a concept. Before we can accept new models of authorship, we still have to weigh our concerns and goals associated with construing authorship in the context of AI in Rodrigues’ way, against other concerns and goals that might drive other conceptualizations, given our current capacities and circumstances. (shrink)