BRIDGING THE AI ACCOUNTABILITY GAP: THE ROLE OF COLLABORATION PARADIGMS AND REASON RESPONSIVENESS

Artificial intelligence (AI) is transforming organisational operations, yet it also poses challenges in attributing accountability in human-AI interaction (HAII) scenarios. This study aims to bridge this accountability gap by examining how different collaboration paradigms and types of reason responsiveness influence users’ perceptions and subsequent intentions. Drawing on Psychological Ownership Theory and Construal Level Theory, we propose that users’ involvement levels and psychological distances can shape their perceptions of accountability attribution, intention to use AI systems, and retention intentions. To test our hypotheses empirically, we design a 2×2 between-subject experiment with scenarios where joint human-AI judgement errors occur. This study will contribute to the theoretical landscape of AI accountability and provide practical guidance for AI system and collaboration mode designs.