Security and privacy protection in developing ethical AI: a mixed-methods study from a marketing employee perspective - Wang, Xuequn (Journal of business ethics, 2025)
Despite chatbots' increasing popularity, firms often fail to fully achieve their benefits because of their underutilization. We argue that ethical concerns dealing with chatbot-related privacy and security may prevent firms from developing a culture of embracing chatbot use and fully integrating chatbots into their workflows. Our research draws upon the stimulus-organism-response theory (SOR) and a study by Floridi et al. (Minds and Machines, 28:689-707, 2018) on the ethical artificial intelligence framework to investigate how chatbot affordances can foster employees' positive perceptions of privacy protection and security, which may increase perceived ethics in beneficence and ultimately support recommendation intentions. To validate our proposed research model and provide a robust understanding of chatbot-related ethics, we conducted two studies following a mixed-methods design. We used Study 1 as the quantitative phase to collect survey data from full-time marketing employees, and the results provided strong support for our research model based on the relevant theory and literature. We used Study 2 as the qualitative phase to collect interview data to further validate our research model, and the results confirmed Study 1's quantitative findings and provided complementary insights into the phenomenon of interest. Our studies contribute to the literature by providing initial insights into chatbot-related ethics through the exploration of chatbot affordances, security, and privacy protection as the antecedents and through depictions of how these variables foster employees' perceived ethics in beneficence and recommendation intention. Our results can inform practitioners how to develop ethics involving chatbots and promote a chatbot-friendly culture such that firms can fully achieve chatbots' benefits and can thus increase their competitive advantages in emerging chatbot marketing.