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)

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)

Understanding what makes governance 'good' or 'bad' has been impeded by construct ambiguity. Contemporary governance research has struggled to define 'governance' and related constructs such as 'ownership', 'agency', and 'management' in a way that clearly separates and distinguishes them. Often, the line between governance and management is so blurred that it is impossible to say what is good or bad 'governance' versus 'management'. Here we provide a systematic classification of key governance concepts in terms of their distinct economic functions. 'Governance', (...) for instance, is the economic function of behavioural constraint. This allows us to state what 'good' governance is and how it might be assessed. We conclude that goodness of governance is idiosyncratic to each organisation, or even to each owner. Thus, while objective measures of good governance are possible, broadly utilised criteria for measuring governance are unlikely to capture whether governance is actually good or bad. (shrink)

Biology, during the last decade in particular, is making substantial headway into our social theories of business and behavior. While the social sciences rush to keep up with the advancement of knowledge, we highlight the need for an ethics discussion to also keep pace. Although the implications to theory are important, our focus is on how new knowledge has the capacity to alter the formulation and practice of business policy, which we believe is potentially profound. Furthermore, the ethicality of a (...) set of issues can depend heavily on one’s perspective, and differing views may not always be compatible. With this in mind, we discuss the ways in which one area of emerging biological knowledge—behavioral genetics—invites a rethinking of the nuances of four long-standing topic areas of business ethics surrounding personnel selection; and we do so from two perspectives—that of the employer and of the job seeker. The four ethical topics are the static nature of genetic information that is out of an individual’s control, faking and lying during selection processes, privacy, and stigmatization of minority groups. (shrink)