How does AI-assisted diagnosis decision support systems influence doctors' coping styles and work outcomes? Bright and dark sides of AI in the workplace

Artificial intelligence (AI), specifically AI-assisted diagnosis decision support systems (DSSs), have been integrated into doctors' work in substituted or complementary ways. From the perspective of doctors, the impact of AI roles on work outcomes is a double-edged sword that may induce both positive and negative consequences and even create ethical issues related to work. However, little is known on why and how the dual effects take place. To address this knowledge gap, we draw on coping theory and explore the roles of AI-assisted diagnosis DSSs in doctors' work meaningfulness and core work capability through their coping style. We employ a sequential mixed-methods design to develop a theoretical framework and test the research model. Results indicate that perceived complementation and substitution for non-core tasks are positively associated with work specialization (bright side), promoting work meaningfulness and core work capability. By contrast, perceived substitution for core tasks is positively associated with a threat to human distinctiveness (dark side), which harms work meaningfulness and core work capability. Our findings contribute to the emerging literature on AI's impact in the doctors' workplace and provide ethical suggestions for practitioners.