Organizations increasingly rely on algorithm-based HR decision-making to monitor their employees. This trend is reinforced by the technology industry claiming that its decision-making tools are efficient and objective, downplaying their potential biases. In our manuscript, we identify an important challenge arising from the efficiency-driven logic of algorithm-based HR decision-making, namely that it may shift the delicate balance between employees’ personal integrity and compliance more in the direction of compliance. We suggest that critical data literacy, ethical awareness, the use of participatory (...) design methods, and private regulatory regimes within civil society can help overcome these challenges. Our paper contributes to literature on workplace monitoring, critical data studies, personal integrity, and literature at the intersection between HR management and corporate responsibility. (shrink)

People are often involuntarily laid off from their jobs through no fault of their own. Employees who are dismissed in this manner cannot always legitimately hold employers accountable for these miserable situations because the decision to implement layoffs is often the best possible outcome given the context—that is, layoffs in and of themselves may be “necessary evils.” Yet, even in circumstances in which layoffs qualify as “necessary evils,” morality demands that employers respect the dignity of those whose employment is involuntarily (...) terminated. In this paper I argue that to preserve the dignity of employees who are involuntarily terminated, in most cases employers have a substantial reason to offer a special kind of unemployment benefit, “severance pay.” To support my claim I draw and expand upon Bernard Williams’s analysis of “agent-regret,” which I believe greatly helps to address and articulate employers’ obligations in the context of involuntary termination. (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)