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)

Interactions between human beings and chatbots are gradually becoming part of our everyday social lives. It is still unclear how human–chatbot interactions, compared to human–human interactions, influence individual morality. Building on the dual-process theory of moral judgment, a secondary data analysis, and two scenario-based experiments provide sufficient evidence that HCIs support utilitarian judgments, which reduce participants' donation amount. Study 3 further demonstrates that the negative effects of HCIs can be attenuated by inducing a social-oriented communication style in chatbots’ verbal language (...) designs. These findings highlight the negative impacts of HCIs on relationships among human beings and suggest a practical intervention for nonprofit organization managers. (shrink)

Firms use algorithms to make important business decisions. To date, the algorithmic accountability literature has elided a fundamentally empirical question important to business ethics and management: Under what circumstances, if any, are algorithmic decision-making systems considered legitimate? The present study begins to answer this question. Using factorial vignette survey methodology, we explore the impact of decision importance, governance, outcomes, and data inputs on perceptions of the legitimacy of algorithmic decisions made by firms. We find that many of the procedural governance (...) mechanisms in practice today, such as notices and impact statements, do not lead to algorithmic decisions being perceived as more legitimate in general, and, consistent with legitimacy theory, that algorithmic decisions with good outcomes are perceived as more legitimate than bad outcomes. Yet, robust governance, such as offering an appeal process, can create a legitimacy dividend for decisions with bad outcomes. However, when arbitrary or morally dubious factors are used to make decisions, most legitimacy dividends are erased. In other words, companies cannot overcome the legitimacy penalty of using arbitrary or morally dubious factors, such as race or the day of the week, with a good outcome or an appeal process for individuals. These findings add new perspectives to both the literature on legitimacy and policy discussions on algorithmic decision-making in firms. (shrink)

Clients may feel trapped into sharing their private digital data with insurance companies to get a desired insurance product or premium. However, private insurance must collect some data to offer products and premiums appropriate to the client’s level of risk. This situation creates tension between the value of privacy and common insurance business practice. We argue for three main claims: first, coercion to share private data with insurers is pro tanto wrong because it violates the autonomous choice of a privacy-valuing (...) client. Second, we maintain that irrespective of being coerced, the choice of accepting digital surveillance by insurers makes it harder for the client to protect his or her autonomy. The violation of autonomy also makes coercing customers into digital surveillance pro tanto morally wrong. Third, having identified an economically plausible process involving no direct coercion by insurers, leading to the adoption of digital surveillance, we argue that such an outcome generates further threats against autonomy. This threat provides individuals with a pro tanto reason to prevent this process. We highlight the freedom dilemma faced by regulators who aim to prevent this outcome by constraining market freedoms and argue for the need for further moral and empirical research on this question. (shrink)

EM Forster’s short story “The Machine Stops” from 1909 is widely reread and discussed again for some ten years as it portrays a science-fiction world resting on similar technological advancements as today in the digital era. Also management literature reviewed the short story with regard to centralized decision making, rationality and totalitarianism. I argue instead, that the main theme of the short story is – in Forster’s own words – the closing of a civilization in times of transition and facing (...) major challenges. I built the argument by original quotes from Forster and by portraying the years 1906–9, when Forster developed the short story. This era before the Great War starting in 1914 was characterized by euphoric ‘futurism’ based on groundbreaking innovations like ‘long distance messaging’, ‘penny post’, ‘animated films’, Ford’s assembly line, ‘Olivetti typewriter’, ‘feature film’, ‘large ships’ and ‘air transportation’ – the ingredients of the short story as I argue. At the same time these acquitted years were characterized by increasing disintegration, instability, rebellions and a financial crisis with bailout programs. Based on the analogy and as part of speculative philosophy I reconstruct the current great challenges with Forster’ shadow of fatalism and arrive at the urgency to put more effort in addressing and researching pathways out of the crisis and towards stabilization of business and society. (shrink)

Online retailers are using advances in data collection and computing technologies to “personalize” prices, i.e., offer goods for sale to shoppers at their reservation prices, or the highest price they are willing to pay. In this paper, I offer a criticism of this practice. I begin by putting online personalized pricing in context. It is not something entirely new, but rather a kind of price discrimination, a familiar pricing practice. I then offer a fairness-based argument against it. When an online (...) retailer personalizes prices, it competes unfairly for the social surplus created by a transaction. I defend this argument against objections, and offer a simple remedy: online retailers should either disclose that they are personalizing prices, or stop doing so. (shrink)