AI models as cultural beings: investigating AI cultural biases and the impact of cultural alignment on human-AI creative collaboration

Speaker: Roy Chua

Venue: Room A1001, School of Management, Zijingang Campus

Abstract: Existing research on AI cultural biases predominantly focuses on Western models, overlooking critical gaps in non-Western models. We conduct a comparative analysis of AI models – ChatGPT (U.S. developed) and ErnieBot (China developed) – from different cultures to investigate how corresponding cultural biases manifest in their outputs. Additionally, we examine how cultural alignment between human users and AI models impacts their collaborative creative performance and the underlying psychological mechanisms. Through a series of experiments and field research, our findings show that AI models developed in different cultural contexts exhibit distinct cultural perspectives and worldviews. Furthermore, when human users' and AI models' cultural backgrounds align, human users demonstrate increased usefulness – but not novelty – in creative solutions for local (but not global) tasks, driven by an enhanced psychological state of flow. This finding highlights the importance of cultural alignment between human users and AI models, particularly during creative collaborations. We discuss the implications of cultural biases in AI, emphasizing the need for cross-cultural AI literacy to improve user interactions and support more effective global AI integration.