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)

Prosocial crowdfunding was originally conceived as a financial mechanism to assist vulnerable unbanked populations, typically excluded from formal financial markets. It subsequently grew into a billion-dollar scheme (Kiva 2020a, https://www.kiva.org/blog/1-billion-in-life-changing-loans ) in the multi-billion-dollar crowdfunding industry. However, recent evidence claims prosocial crowdfunding may be shifting away from its goal to support the poor and underserved. Drawing on a composite social responsibility and framing theory framework, we examine the role that vulnerability plays in successfully raising funds in a prosocial crowdfunding context. (...) We conduct multilevel logistic regressions on a sample of microloans allocated to 105,727 ventures in 64 countries. Our results indicate that applying for funds through a field partner which caters to vulnerable populations may in fact have a negative effect on the entrepreneur’s request to be fully funded. Notwithstanding, framing the entrepreneur as being female or rural as key characteristics of individual vulnerability increases the project’s likelihood to be fully funded. This conflict offers noteworthy theoretical and practical implications for ethics in prosocial crowdfunding, an understudied field of research. (shrink)

Crowdfunding platforms have revolutionized entrepreneurial finance, with 200 billion dollars expected to be dispersed annually to entrepreneurs and small business owners by 2020. Despite the importance of this growing phenomenon, our knowledge of the dynamics of successful lending-based prosocial crowdfunding and its implications for the business ethics literature remain limited. We use a social responsibility lens to examine whether crowdfunders on a lending-based prosocial platform lend their money based on altruistic or strategic motives. Our results indicate that the dynamics of (...) prosocial lending-based crowdfunding are somewhat consistent with traditional forms of financing. Specifically, despite a prosocial setting in nature, crowdfunders tend to act strategically, positively responding to signals of quality and low risk. Notably, we also find that projects that are high on both financial and social appeal receive the highest average amount of funding. Furthermore, language on the lender’s profile indicating ability to pay is positively related to both funding success and funding amount. Our study contributes to filling the gap in the business ethics literature about the dynamics of lending-based prosocial crowdfunding, and the strategic and altruistic ethical motives that drive lenders in such endeavors. (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)