We argue that explainable artificial intelligence (XAI), specifically reason-giving XAI, often constitutes the most suitable way of ensuring that someone can properly be held responsible for decisions that are based on the outputs of artificial intelligent (AI) systems. We first show that, to close moral responsibility gaps (Matthias 2004), often a human in the loop is needed who is directly responsible for particular AI-supported decisions. Second, we appeal to the epistemic condition on moral responsibility to argue that, in order to (...) be responsible for her decision, the human in the loop has to have an explanation available of the system’s recommendation. Reason explanations are especially well-suited to this end and we examine whether – and how – it might be possible to make such explanations fit with AI systems. We support our claims by focusing on a case of disagreement between human in the loop and AI system. (shrink)

Our ability to locate moral responsibility is often thought to be a necessary condition for conducting morally permissible medical practice, engaging in a just war, and other high-stakes endeavors. Yet, with increasing reliance upon artificially intelligent systems, we may be facing a wideningresponsibility gap, which, some argue, cannot be bridged by traditional concepts of responsibility. How then, if at all, can we make use of crucial emerging technologies? According to Colin Allen and Wendell Wallach, the advent of so-called ‘artificial moral (...) agents’ (AMAs) is inevitable. Still, this notion may seem to push back the problem, leaving those who have an interest in developing autonomous technology with a dilemma. We may need to scale-back our efforts at deploying AMAs (or at least maintain human oversight); otherwise, we must rapidly and drastically update our moral and legal norms in a way that ensures responsibility for potentially avoidable harms. This paper invokes contemporary accounts of responsibility in order to show how artificially intelligent systems might be held responsible. Although many theorists are concerned enough to develop artificial conceptions ofagencyor to exploit our present inability to regulate valuable innovations, the proposal here highlights the importance of—and outlines a plausible foundation for—a workable notion ofartificial moral responsibility. (shrink)

Artificial intelligence increasingly executes tasks that previously only humans could do, such as drive a car, fight in war, or perform a medical operation. However, as the very best AI systems tend to be the least controllable and the least transparent, some scholars argued that humans can no longer be morally responsible for some of the AI-caused outcomes, which would then result in a responsibility gap. In this paper, I assume, for the sake of argument, that at least some of (...) the most sophisticated AI systems do indeed create responsibility gaps, and I ask whether we can bridge these gaps at will, viz. whether certain people could take responsibility for AI-caused harm simply by performing a certain speech act, just as people can give permission for something simply by performing the act of consent. So understood, taking responsibility would be a genuine normative power. I first discuss and reject the view of Champagne and Tonkens, who advocate a view of taking liability. According to this view, a military commander can and must, ahead of time, accept liability to blame and punishment for any harm caused by autonomous weapon systems under her command. I then defend my own proposal of taking answerability, viz. the view that people can makes themselves morally answerable for the harm caused by AI systems, not only ahead of time but also when harm has already been caused. (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)

This article proposes a conceptual mapping to outline salient properties and relations that allow for a knowledge transfer from the well-established greenwashing phenomenon to the more recent machinewashing. We account for relevant dissimilarities, indicating where conceptual boundaries may be drawn. Guided by a “reasoning by analogy” approach, the article addresses the structural analogy and machinewashing idiosyncrasies leading to a novel and theoretically informed model of machinewashing. Consequently, machinewashing is defined as a strategy that organizations adopt to engage in misleading behavior (...) about ethical Artificial Intelligence /algorithmic systems. Machinewashing involves misleading information about ethical AI communicated or omitted via words, visuals, or the underlying algorithm of AI itself. Furthermore, and going beyond greenwashing, machinewashing may be used for symbolic actions such as lobbying and prevention of stricter regulation. By outlining diverse theoretical foundations of the established greenwashing domain and their relation to specific research questions, the article proposes a machinewashing model and a set of theory-related research questions on the macro, meso, and micro-level for future machinewashing research. We conclude by stressing limitations and by outlining practical implications for organizations and policymakers. (shrink)

While the ethics of technology is analyzed across disciplines from science and technology studies, engineering, computer science, critical management studies, and law, less attention is paid to the role that firms and managers play in the design, development, and dissemination of technology across communities and within their firm. Although firms play an important role in the development of technology, and make associated value judgments around its use, it remains open how we should understand the contours of what firms owe society (...) as the rate of technological development accelerates. We focus here on digital technologies: devices that rely on rapidly accelerating digital sensing, storage, and transmission capabilities to intervene in human processes. This symposium focuses on how firms should engage ethical choices in developing and deploying these technologies. In this introduction, we, first, identify themes the symposium articles share and discuss how the set of articles illuminate diverse facets of the intersection of technology and business ethics. Second, we use these themes to explore what business ethics offers to the study of technology and, third, what technology studies offers to the field of business ethics. Each field brings expertise that, together, improves our understanding of the ethical implications of technology. Finally we introduce each of the five papers, suggest future research directions, and interpret their implications for business ethics. (shrink)

Business, management, and business ethics literature pay little attention to the topic of AI robots. The broad spectrum of potential ethical issues pertains to using driverless cars, AI robots in care homes, and in the military, such as Lethal Autonomous Weapon Systems. However, there is a scarcity of in-depth theoretical, methodological, or empirical studies that address these ethical issues, for instance, the impact of morality and where accountability resides in AI robots’ use. To address this dearth, this study offers a (...) conceptual framework that interpretively develops the ethical implications of AI robot applications, drawing on descriptive and normative ethical theory. The new framework elaborates on how the locus of morality and moral intensity combine within context-specific AI robot applications, and how this might influence accountability thinking. Our theorization indicates that in situations of escalating AI agency and situational moral intensity, accountability is widely dispersed between actors and institutions. ‘Accountability clusters’ are outlined to illustrate interrelationships between the locus of morality, moral intensity, and accountability and how these invoke different categorical responses: illegal, immoral, permissible, and supererogatory pertaining to using AI robots. These enable discussion of the ethical implications of using AI robots, and associated accountability challenges for a constellation of actors—from designer, individual/organizational users to the normative and regulative approaches of industrial/governmental bodies and intergovernmental regimes. (shrink)

Most accounts of responsibility focus on one type of responsibility, moral responsibility, or address one particular aspect of moral responsibility such as agency. This article outlines a broader framework to think about responsibility that includes causal responsibility, relational responsibility, and what I call “narrative responsibility” as a form of “hermeneutic responsibility”, connects these notions of responsibility with different kinds of knowledge, disciplines, and perspectives on human being, and shows how this framework is helpful for mapping and analysing how artificial intelligence (...) (AI) challenges human responsibility and sense-making in various ways. Mobilizing recent hermeneutic approaches to technology, the article argues that next to, and interwoven with, other types of responsibility such as moral responsibility, we also have narrative and hermeneutic responsibility—in general and for technology. For example, it is our task as humans to make sense of, with and, if necessary, against AI. While from a posthumanist point of view, technologies also contribute to sense-making, humans are the experiencers and bearers of responsibility and always remain in charge when it comes to this hermeneutic responsibility. Facing and working with a world of data, correlations, and probabilities, we are nevertheless condemned to make sense. Moreover, this also has a normative, sometimes even political aspect: acknowledging and embracing our hermeneutic responsibility is important if we want to avoid that our stories are written elsewhere—through technology. (shrink)

Several technological developments, such as self-service technologies and artificial intelligence, are disrupting the retailing industry by changing consumption and purchase habits and the overall retail experience. Although AI represents extraordinary opportunities for businesses, companies must avoid the dangers and risks associated with the adoption of such systems. Integrating perspectives from emerging research on AI, morality of machines, and norm activation, we examine how individuals morally behave toward AI agents and self-service machines. Across three studies, we demonstrate that consumers’ moral concerns (...) and behaviors differ when interacting with technologies versus humans. We show that moral intention is less likely to emerge for AI checkout and self-checkout machines compared with human checkout. In addition, moral intention decreases as people consider the machine less humanlike. We further document that the decline in morality is caused by less guilt displayed toward new technologies. The non-human nature of the interaction evokes a decreased feeling of guilt and ultimately reduces moral behavior. These findings offer insights into how technological developments influence consumer behaviors and provide guidance for businesses and retailers in understanding moral intentions related to the different types of interactions in a shopping environment. (shrink)

Vicarious responsibility is sometimes analysed by considering the different kinds of agents involved—who is vicariously responsible for the actions of whom? In this paper, I discuss vicarious responsibility from a different angle: in what sense is the vicarious agent responsible? I do this by considering the ways in which one may take responsibility for events caused by another agent or process. I discuss three senses of taking responsibility—accepting fault, assuming obligations, and fulfilling obligations—and the forms of vicarious responsibility that correspond (...) to these. I end by explaining how to judge which sense applies in a given case, based on the degree of (what I call) moral entanglement between the agent and what they should take responsibility for. (shrink)

In the debate on whether to ban LAWS, moral arguments are mainly used. One of these arguments, proposed by Sparrow, is that the use of LAWS goes hand in hand with the responsibility gap. Together with the premise that the ability to hold someone responsible is a necessary condition for the admissibility of an act, Sparrow believes that this leads to the conclusion that LAWS should be prohibited. In this article, it will be shown that Sparrow’s argumentation for both premises (...) is not convincing. If one interprets the thesis that responsibility (first premise) is necessary in a descriptive sense, this assertion clashes with military theory and practice. And even if you focus on the normative interpretation, that claim does not stand. The second premise for Sparrow’s conclusion, namely that you cannot hold anyone responsible for LAWS’ (mis)deeds, is based on the idea that control is a necessary condition for responsibility. It will be shown that this idea too is not correct, which means that Sparrow’s control argument does not do the work it should do. From this, we can conclude that Sparrow’s justification for his claim that LAWS should be banned is insufficient, and neither can we conclude that the thesis of a responsibility gap has in any case been undermined. However, it will also be argued that someone may be responsible for the actions of LAWS, or that it cannot be excluded that one can be held responsible. (shrink)

Most accounts of responsibility focus on one type of responsibility, moral responsibility, or address one particular aspect of moral responsibility such as agency. This article outlines a broader framework to think about responsibility that includes causal responsibility, relational responsibility, and what I call “narrative responsibility” as a form of “hermeneutic responsibility”, connects these notions of responsibility with different kinds of knowledge, disciplines, and perspectives on human being, and shows how this framework is helpful for mapping and analysing how artificial intelligence (...) (AI) challenges human responsibility and sense-making in various ways. Mobilizing recent hermeneutic approaches to technology, the article argues that next to, and interwoven with, other types of responsibility such as moral responsibility, we also have narrative and hermeneutic responsibility—in general and for technology. For example, it is our task as humans to make sense of, with and, if necessary, against AI. While from a posthumanist point of view, technologies also contribute to sense-making, humans are the experiencers and bearers of responsibility and always remain in charge when it comes to this hermeneutic responsibility. Facing and working with a world of data, correlations, and probabilities, we are nevertheless condemned to make sense. Moreover, this also has a normative, sometimes even political aspect: acknowledging and embracing our hermeneutic responsibility is important if we want to avoid that our stories are written elsewhere—through technology. (shrink)

The use of artificial intelligence (AI) in hiring entails vast ethical challenges. As such, using an ethical lens to study this phenomenon is to better understand whether and how AI matters in hiring. In this paper, we examine whether ethical perceptions of using AI in the hiring process influence individuals’ trust in the organizations that use it. Building on the organizational trust model and the unified theory of acceptance and use of technology, we explore whether ethical perceptions are shaped by (...) individual differences in performance expectancy and social influence and how they, in turn, impact organizational trust. We collected primary data from over 300 individuals who were either active job seekers or who had recent hiring experience to capture perceptions across the full range of hiring methods. Our findings indicate that performance expectancy, but not social influence, impacts the ethical perceptions of AI in hiring, which in turn influence organizational trust. Additional analyses indicate that these findings vary depending on the type of hiring methods AI is used for, as well as on whether participants are job seekers or individuals with hiring experience. Our study offers theoretical and practical implications for ethics in HRM and informs policy implementation about when and how to use AI in hiring methods, especially as it pertains to acting ethically and trustworthily. (shrink)

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

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

I argue that the right to sexual satisfaction of severely physically and mentally disabled people and elderly people who suffer from neurodegenerative diseases can be fulfilled by deploying sex robots; this would enable us to satisfy the sexual needs of many who cannot provide for their own sexual satisfaction; without at the same time violating anybody’s right to sexual self-determination. I don’t offer a full-blown moral justification of deploying sex robots in such cases, as not all morally relevant concerns can (...) be addressed here; rather, I put forward a plausible way of fulfilling acute sexual needs without thereby violating anybody’s sexual rights. (shrink)

Artificial intelligence has dramatically changed the way organizations communicate, understand, and interact with their potential consumers. In the context of this trend, the ethical considerations of advertising when applying AI should be the core question for marketers. This paper discusses six dominant algorithmic purchase decision pathways that align with ethical philosophies for online customers when buying a product/goods. The six ethical positions include: ethical egoism, deontology, relativist, utilitarianism, virtue ethics, and ethics of care. Furthermore, this paper launches an “intelligent advertising” (...) AI theme by examining its present and future as well as identifying the key phases of intelligent advertising. Several research questions are offered to guide future research on intelligent advertising to benefit ethical AI decision-making. Finally, several areas that can be widely applied to ethical intelligent advertising are suggested for future research. (shrink)

Background The use of Artificial Intelligence (AI) has the potential to provide relief in the challenging and often stressful clinical setting for physicians. So far, however, the actual changes in work for physicians remain a prediction for the future, including new demands on the social level of medical practice. Thus, the question of how the requirements for physicians will change due to the implementation of AI is addressed. Methods The question is approached through conceptual considerations based on the potentials that (...) AI already offer and the focus on central normative concepts of trust, explainability, and responsibility which play an important role when implementing AI in everyday clinical practice. Conclusion Interpersonal communication will not disappear upon implementation of AI. Instead, it is much more likely that the exchange between various actors in medical practice will become increasingly important. This adds another level of complexity to practical concepts such as Shared-Decision-Making, which must be addressed in empirical research, including the involvement of AI systems as actors in communication. (shrink)

Despite the rapid adoption of technology in human resource departments, there is little empirical work that examines the potential challenges of algorithmic decision-making in the recruitment process. In this paper, we take the perspective of job applicants and examine how they perceive the use of algorithms in selection and recruitment. Across four studies on Amazon Mechanical Turk, we show that people in the role of a job applicant perceive algorithm-driven recruitment processes as less fair compared to human only or algorithm-assisted (...) human processes. This effect persists regardless of whether the outcome is favorable to the applicant or not. A potential mechanism underlying algorithm resistance is the belief that algorithms will not be able to recognize their uniqueness as a candidate. Although the use of algorithms has several benefits for organizations such as improved efficiency and bias reduction, our results highlight a potential cost of using them to screen potential employees during recruitment. (shrink)

It is a truism that, due to human weaknesses, human soldiers have yet to have sufficiently ethical warfare. It is arguable that the likelihood of human soldiers to breach the Principle of Non-Combatant Immunity, for example, is higher in contrast tosmart soldierswho are emotionally inept. Hence, this paper examines the possibility that the integration of ethics into smart soldiers will help address moral challenges in modern warfare. The approach is to develop and employ smart soldiers that are enhanced with ethical (...) capabilities. Advocates of this approach think that it is more realistic to make competent entities (i.e., smart soldiers) become morally responsible than to enforce moral responsibility on human soldiers with inherent (moral) limitations. This view somewhat seeks a radical transition from the usual anthropocentric warfare to arobocentricwarfare with the belief that the transition has moral advantages. However, the paper defends the claim that despite human limitations, the capacity ofethically enhanced smart soldiersfor moral sensitivity is artificial and unauthentic. There are significant problems with the three models of programming ethics into smart soldiers. Also, there are further challenges from the absence of emotion as a moral gauge, and the problems of apportioning responsibility in case of mishap from the actions or omissions of smart soldiers. Among other reasons, the paper takes the replacement of human soldiers as an extreme approach towards an ethical warfare. This replacement predicates ethical complications that outweigh the benefits from the exclusive use of smart soldiers. (shrink)

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use (...) AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers. (shrink)

The ethical issues introduced by excessive uses of ubiquitous information technology at work have received little attention, from either practitioners or ethics scholars. This article suggests the concept of technological ill-being and explores the ethical issues arising from such ill-being, according to the individual and collective responsibilities associated with their negative effects. This article turns to the philosopher Michel Foucault and proposes a renewed approach of the relationship among IT, ethics, and responsibility, based on the concepts of practical rationality, awareness, (...) and self-engagement. This article reports a case study of an international automotive company actively engaged in both corporate social responsibility and ubiquitous IT deployment. Technological ill-being is an expression of the tension between an individual’s social attributes and aspirations when using modern IT and a system of norms, rules, and values imposing constraints on him or her. We identify the reasons for the lack of consideration of technological ill-being in CSR through identification of the inclusion–exclusion principle. The resulting critical, comprehensive approach to corporate responsibilities and IT uses incorporates the ethical implications of the latter, highlights the practical rationality of their relationship, and demands both individual and collective responses, through a call for collective ethical awareness and self-engagement. The findings prompt a Foucauldian ethics of IT use in organizations, which emerges in a mutually constitutive relationship between the self, as a moral subject of own actions, and broader organizational principles, in which CSR appears as a techne. (shrink)

Why do organizations conduct job interviews? The traditional view of interviewing holds that interviews are conducted, despite their steep costs, to predict a candidate’s future performance and fit. This view faces a twofold threat: the behavioral and algorithmic threats. Specifically, an overwhelming body of behavioral research suggests that we are bad at predicting performance and fit; furthermore, algorithms are already better than us at making these predictions in various domains. If the traditional view captures the whole story, then interviews seem (...) to be a costly, archaic human resources procedure sustained by managerial overconfidence. However, building on T. M. Scanlon’s work, we offer the value of choice theory of interviewing and argue that interviews can be vindicated once we recognize that they generate commonly overlooked kinds of noninstrumental value. On our view, interviews should thus not be entirely replaced by algorithms, however sophisticated algorithms ultimately become at predicting performance and fit. (shrink)

Theories of action tend to require agents to have mental representations. A common trope in discussions of artificial intelligence (AI) is that they do not, and so cannot be agents. Properly understood there may be something to the requirement, but the trope is badly misguided. Here we provide an account of representation for AI that is sufficient to underwrite attributions to these systems of ownership, action, and responsibility. Existing accounts of mental representation tend to be too demanding and unparsimonious. We (...) offer instead a minimalist account of representation that ascribes only those features necessary for explaining action, trimming the “extra” features in existing accounts (e.g., representation as a “mental” phenomenon). Our account makes ‘representation’ whatever it is that, for example, the thermostat is doing with the thermometer. The thermostat is disposed to act as long as the thermometer is outside a given range of parameters.. Our account allows us to offer a new perspective on the ‘responsibility gap’, a problem raised by the actions of sophisticated machines: because nobody has enough control over the machine’s actions to be able to assume responsibility, conventional approaches to responsibility ascription are inappropriate. We argue that there is a distinction between finding responsible and holding responsible and, in order to resolve the responsibility gap, we must first clarify the conceptual terrain on which agent is in fact responsible. (shrink)

Algorithms are now routinely used in decision-making; they are potent components in decisions that affect the lives of individuals and the activities of public and private institutions. Although use of algorithms has many benefits, a number of problems have been identified with their use in certain domains, most notably in domains where safety and fairness are important. Awareness of these problems has generated public discourse calling for algorithmic accountability. However, the current discourse focuses largely on algorithms and their opacity. I (...) argue that this reflects a narrow and inadequate understanding of accountability. I sketch an account of accountability that takes accountability to be a social practice constituted by actors, forums, shared beliefs and norms, performativity, and sanctions, and aimed at putting constraints on the exercise of power. On this account, algorithmic accountability is not yet constituted; it is in the making. The account brings to light a set of questions that must be addressed to establish it. (shrink)

This article addresses a dilemma about autonomous vehicles: how to respond to trade-off scenarios in which all possible responses involve the loss of life but there is a choice about whose life or lives are lost. I consider four options: kill fewer people, protect passengers, equal concern for survival, and recognize everyone’s interests. I solve this dilemma via what I call the new trolley problem, which seeks a rationale for the intuition that it is unethical to kill a smaller number (...) of people to avoid killing a greater number of people based on numbers alone. I argue that killing a smaller number of people to avoid killing a greater number of people based on numbers alone is unethical because it disrespects the humanity of the individuals in the smaller-numbered group. I defend the recognize-everyone’s-interests algorithm, which will probably kill fewer people but will not do so based on numbers alone. (shrink)

Empathy is a specific moral aspect of human behavior. The global workplace, and thereby a consideration of employee stakeholders, includes unique behavioral and ethical considerations, including a consideration of human empathy. Further, the human aspects of workplaces are within the domain of human resources and managerial oversight in business organizations. As such, human emotions and interactions are complicated by daily work related expectations, employee/employer interactions and work practices, and the outcomes of employees’ work routines. Business ethics, human resources, and risk (...) management practices are endemic aspects within workplaces. Increasingly, the understanding of models of AI-reliant business practices underscores the need for the consideration of the ethical aspects of AI impacts on employees in the workplace. This paper explores a systematic ethical lens of the opportunities and the risks of AI ideation, development, and deployment in business-employee relations practices beyond a compliance mindset, and that introduces a further set of workplace considerations. Empathy is concerned with human intentions. As such, attributive ethical indications of the role of AI in the workplace and its impacts on employees is necessary. Moreover, this paper uses a cognitive lens of empathy and focuses on artificial morality related to the ethical concerns, implications, and practices of AI development, deployment, and workplace practices that may impact employees in a variety of business aspects. (shrink)

Artificial intelligence (AI) has long been recognised as a challenge to responsibility. Much of this discourse has been framed around robots, such as autonomous weapons or self-driving cars, where we arguably lack control over a machine’s behaviour and therefore struggle to identify an agent that can be held accountable. However, most of today’s AI is based on machine-learning technology that does not act on its own, but rather serves as a decision-support tool, automatically analysing data to help human agents make (...) better decisions. I argue that decision-support tools pose a challenge to responsibility that goes beyond the familiar problem of finding someone to blame or punish for the behaviour of agent-like systems. Namely, they pose a problem for what we might call “decision ownership”: they make it difficult to identify human agents to whom we can attribute value-judgements that are reflected in decisions. Drawing on recent philosophical literature on responsibility and its various facets, I argue that this is primarily a problem of attributability rather than of accountability. This particular responsibility problem comes in different forms and degrees, most obviously when an AI provides direct recommendations for actions, but also, less obviously, when it provides mere descriptive information on the basis of which a decision is made. (shrink)

Artificial intelligence and normative ethics: Who is responsible for the crime of LAWS? In his text “Killer Robots”, Robert Sparrow holds that killer robots should be forbidden. This conclusion is based on two premises. The first is that attributive responsibility is a necessary condition for admitting an action; the second premise is that the use of killer robots is accompanied by a responsibility gap. Although there are good reasons to conclude that killer robots should be banned, the article shows that (...) Sparrow's argument for the ban is not correct. (shrink)

The abundance of literature on ethical concerns regarding artificial intelligence (AI) highlights the need to systematize, integrate, and categorize existing efforts through a systematic literature review. The article aims to investigate prevalent concerns, proposed solutions, and prominent ethical approaches within the field. Considering 309 articles from the beginning of the publications in this field up until December 2021, this systematic literature review clarifies what the ethical concerns regarding AI are, and it charts them into two groups: (i) ethical concerns that (...) arise from the design of AI and (ii) ethical concerns that arise from human–AI interactions. The analysis of the obtained sample highlights the most recurrent ethical concerns. Finally, it exposes the main proposals of the literature to handle the ethical concerns according to the main ethical approaches. It interprets the findings to lay the foundations for future research on the ethics of AI. (shrink)

Despite the widespread use of automated decision-making (ADM) systems, they are often developed without involving the public or those directly affected, leading to concerns about systematic biases that may perpetuate structural injustices. Existing formal fairness approaches primarily focus on statistical outcomes across demographic groups or individual fairness, yet these methods reveal ambiguities and limitations in addressing fairness comprehensively. This paper argues for a holistic approach to algorithmic fairness that integrates procedural fairness, considering both decision-making processes and their outcomes. Procedural fairness (...) emphasizes the importance of fair decision-making procedures, which aligns with theories of relational justice that stress the quality of social relations and power dynamics. We highlight the need for substantive procedural fairness to ensure better outcomes and address forward-looking responsibilities. Additionally, we propose leveraging Public Engagement, a core dimension within the well-established Responsible Research and Innovation framework, to enhance procedural fairness in ADM systems. Our contribution underscores the value of Public Engagement in fostering fairer ADM processes, thereby expanding the current focus beyond technical outcome-based approaches to encompass broader procedural considerations. (shrink)

Purpose The purpose of this paper is to present the conceptual model of an innovative methodology (SAT) to assess the social acceptance of technology, especially focusing on artificial intelligence (AI)-based technology. -/- Design/methodology/approach After a review of the literature, this paper presents the main lines by which SAT stands out from current methods, namely, a four-bubble approach and a mix of qualitative and quantitative techniques that offer assessments that look at technology as a socio-technical system. Each bubble determines the social (...) variability of a cluster of values: User-Experience Acceptance, Social Disruptiveness, Value Impact and Trust. -/- Findings The methodology is still in development, requiring further developments, specifications and validation. Accordingly, the findings of this paper refer to the realm of the research discussion, that is, highlighting the importance of preventively assessing and forecasting the acceptance of technology and building the best design strategies to boost sustainable and ethical technology adoption. -/- Social implications Once SAT method will be validated, it could constitute a useful tool, with societal implications, for helping users, markets and institutions to appraise and determine the co-implications of technology and socio-cultural contexts. -/- Originality/value New AI applications flood today’s users and markets, often without a clear understanding of risks and impacts. In the European context, regulations (EU AI Act) and rules (EU Ethics Guidelines for Trustworthy) try to fill this normative gap. The SAT method seeks to integrate the risk-based assessment of AI with an assessment of the perceptive-psychological and socio-behavioural aspects of its social acceptability. (shrink)

Modern society makes extensive use of automated algorithmic decisions, fueled by advances in artificial intelligence. However, since these systems are not perfect, questions about fairness are increasingly investigated in the literature. In particular, many authors take a Rawlsian approach to algorithmic fairness. Based on complications with this approach identified in the literature, this article discusses how Rawls’s theory in general, and especially the difference principle, should reasonably be applied to algorithmic fairness decisions. It is observed that proposals to achieve Rawlsian (...) algorithmic fairness often aim to uphold the difference principle in the individual situations where automated decision-making occurs. However, the Rawlsian difference principle applies to society at large and does not aggregate in such a way that upholding it in constituent situations also upholds it in the aggregate. But such aggregation is a hidden premise of many proposals in the literature and its falsity explains many complications encountered. (shrink)

More organizations use AI in the hiring process than ever before, yet the perceived ethicality of such processes seems to be mixed. With such variation in our views of AI in hiring, we need to understand how these perceptions impact the organizations that use it. In two studies, we investigate how ethical perceptions of using AI in hiring are related to perceptions of organizational attractiveness and innovativeness. Our findings indicate that ethical perceptions of using AI in hiring are positively related (...) to perceptions of organizational attractiveness, both directly and indirectly via perceptions of organizational innovativeness, with variations depending on the type of hiring method used. For instance, we find that individuals who consider it ethical for organizations to use AI in ways often considered to be intrusive to privacy, such as analyzing social media content for traits and characteristics, view such organizations as both more innovative and attractive. Our findings trigger a timely discussion about the critical role of ethical perceptions of AI in hiring on organizational attractiveness and innovativeness. (shrink)

Firms increasingly deploy algorithmic pricing approaches to determine what to charge for their goods and services. Algorithmic pricing can discriminate prices both dynamically over time and personally depending on individual consumer information. Although legal, the ethicality of such approaches needs to be examined as often they trigger moral concerns and sometimes outrage. In this research paper, we provide an overview and discussion of the ethical challenges germane to algorithmic pricing. As a basis for our discussion, we perform a systematic interpretative (...) review of 315 related articles on dynamic and personalized pricing as well as pricing algorithms in general. We then use this review to define the term algorithmic pricing and map its key elements at the micro-, meso-, and macro levels from a business and marketing ethics perspective. Thus, we can identify morally ambivalent topics that call for deeper exploration by future research. (shrink)

In recent decades, huge technological changes have opened up possibilities and potentials for new socio-technological forms of violence, violation and abuse, themselves intersectionally gendered, that form part of and extend offline intimate partner violence (IPV). Digital IPV (DIPV)—the use of digital technologies in and for IPV—takes many forms, including: cyberstalking, internet-based abuse, non-consensual intimate imagery, and reputation abuse. IPV is thus now in part digital, and digital and non-digital violence may merge and reinforce each other. At the same time, technological (...) and other developments have wrought significant changes in the nature of work, such as the blurring of work/life boundaries and routine use of digital technologies. Building on feminist theory and research on violence, and previous research on the ethics of digitalisation, this paper examines the ethical challenges raised for business, workplaces, employers and management by digital IPV. This includes the ethical challenges arising from the complexity and variability of DIPV across work contexts, its harmful impacts on employees, productivity, and security, and the prospects for proactive ethical responses in workplace policy and practice for victim/survivors, perpetrators, colleagues, managers, and stakeholders. The paper concludes with contributions made and key issues for the future research agenda. (shrink)

The development of “smart stadia”, i.e. the use of “smart technologies” in the way sports stadia are designed and managed, promises to enhance the experience of attending a live match through innovative and improved services for the audience, as well as for the players, vendors and other stadium stakeholders. These developments offer us a timely opportunity to reflect on the ethical implications of the use of smart technologies and the emerging Internet of Things. The IoT has the potential to radically (...) transform society and is representative of the ways that novel technologies will alter human life. We use Dublin’s Croke Park stadium smart project as a case study for examining the development of smart stadia. (shrink)