Synthetic authenticity and audience trust in AI-generated intangible cultural heritage: a qualitative multimodal study - Chuyao, Wang; Adzharuddin, Nor Azura (Faculty of Communication & Media Studies, 2025)
In the digital era, generative AI is increasingly leveraged to craft cultural content, prompting considerations of authenticity and trust in intangible cultural heritage (ICH) dissemination. This study explores how AI-generated cultural depictions impact audience trust, introducing "synthetic authenticity" to denote algorithmically created content mimicking traditional heritage. Using a qualitative multi-method approach, it analyzes two notable Chinese AI-ICH cases—Baidu Baike’s AI Museum and Guangming Online’s Intangible Heritage Revived series—via multimodal content analysis and open coding of semi-structured interviews. Results identify four thematic aspects shaping audience perceptions: perceived authenticity, emotional resonance, platform credibility, and participatory co-creation. Audiences tend to trust content with traditional aesthetic cues, expert voiceovers, and clear AI labeling, while overly refined or culturally alien visuals diminish credibility. The study highlights that trust in AI-generated heritage is context-dependent, influenced by cultural familiarity, emotional connection, and platform reputation. It proposes a new framework for understanding trust in AI-mediated cultural communication and offers practical suggestions for platform designers, cultural institutions, and policymakers, including transparent AI marking, heritage stakeholder involvement, and digital literacy education to foster more authentic and reliable cultural experiences in the algorithmic media age.