Cultural Tightness Increases Individuals’ Preference for Control in Human–AI Collaboration
Jiarui Sui, Yiwen Zhang, Yujie Zhao · International Journal of Human-Computer Interaction · 2025
Recent advances in artificial intelligence (AI) have highlighted the growing importance of human–AI collaboration, a critical framework for leveraging the complementary strengths of humans and AI in various domains. However, research on human–AI collaboration (HAIC) has largely overlooked the influence of cultural factors. This study investigates the role of cultural tightness—a measure of the strictness of societal norms and tolerance for deviance—in shaping consumer willingness to collaborate with AI. Across three experimental studies, we demonstrate a cultural moderation effect: in tight cultures, high decision control increased willingness to collaborate with AI by reducing identity threat, whereas in loose cultures, the effect of decision control on both identity threat and willingness was attenuated. Theoretically and practically, this research identifies cultural tightness as a key factor shaping preferences for decision control and identity threat in human–AI interaction, offering guidance for designing culturally sensitive AI systems.