Effect of Anthropomorphic Design and Hierarchical Status on Balancing Self-Serving Bias: Accounting for Education, Ethnicity, and Experience

To address the issue of self-serving attributional bias linked to automation technology and artificial intelligence (AI), this study recruited a gender-balanced sample to investigate the positive effects of perceived anthropomorphism and hierarchical status of computer systems on users' self-accountability and use intention. The specific research context was intelligent vehicles, a common form of automation and AI. Findings showed that anthropomorphism can significantly boost user self-accountability for both successes and failures, while hierarchical status primarily affected accountability for failures. Besides, the positive effects of anthropomorphism on self-accountability and use intention were mediated by cognitive empowerment and social rewards, respectively. This study also found that educational background amplified the impact of anthropomorphism, whereas ethnic differences moderated the effects of hierarchical status on self-accountability. Furthermore, incident experiences were found to positively moderate the relationship between hierarchical status and use intention, which indicates the need for more safety-focused strategies for human-computer interaction (HCI). In general, this study presented a promising strategy for academia and industry in designing human-like interactions to balance self-serving bias and foster self-accountability, which can potentially result in more inclusive and effective HCI experiences.