Ikigai is a Japanese concept, which, in brief, refers to the “reason or purpose to live”. I-risks have been identified as a category of risks complementing x- risks, i.e., existential risks, and s-risks, i.e., suffering risks, which describes undesirable future scenarios in which humans are deprived of the pursuit of their individual ikigai. While some developments in AI increase i-risks, there are also AI-driven virtual opportunities, which reduce i-risks by increasing the space of potential ikigais, largely due to developments in (...) generative AI, virtual worlds as well as AI-driven hyper-personalization. The purpose of this paper is to present a first attempt to map the potential AI-driven virtual hyper-personalised ikigai universe. Moreover, challenges and further ideas are presented. (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)

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)

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)

Merchants often use personalized pricing: they charge different consumers different prices for the same product. We assess the ethicality of personalized pricing by generalizing and extending an earlier model by Coker and Izaret (Journal of Business Ethics 173:387–398, 2021) who found that price personalization ethically outperforms unitary pricing. Using a simulation analysis, we show that these results crucially depend on the choice of parameters and do not hold universally. We further incorporate additional sources of marginal cost into the utility function (...) that will likely arise from personalized pricing. These include the expectation that personalized pricing is widely considered unfair by consumers who prefer that all consumers are charged the same price (unitary pricing), and that firms often approximate the consumers’ willingness-to-pay in ways that may raise negative sentiments among consumers who feel that their privacy is breached. By extending our model with disutility from unfairness perception and disutility from surveillance aversion, we demonstrate that personalized pricing is quickly outperformed by unitary pricing under social welfare functions that tend to prioritize total utility (utilitarianism and prioritarianism), whereas personalized pricing can ethically outperform unitary pricing under social welfare functions that tend to prioritize equality (egalitarianism and leximin). Our findings illustrate various intricacies and dynamics regarding the circumstances under which personalized pricing can be considered ethical. (shrink)