Scholarlink

<p>This paper examines how generative artificial intelligence (GenAI) mediates authorship, voice, and cultural representation in Vietnamese community-based tourism storytelling. Using a three-phase Participatory Analytical Synthesis (PAS) that combines netnography, GenAI prototyping, and community dialogue through a cross-layer integration index, it analyses convergence and divergence across human, algorithmic, and participant narratives. Findings reveal ambient authorship, the algorithmic reproduction of local aesthetics that displaces lived voice, and show that storytellers adopt GenAI conditionally as a drafting aid rather than as authors. The integration index (Ī = 0.46) indicates partial resonance, strongest for authenticity and representation, and weakest for affect and identity. From these results, the paper advances cultural explainability, reframing explainable AI as a social process in which meaning, emotion, and authorship are co-produced and contestable. The study provides conceptual and methodological guidance for participatory and culturally accountable GenAI design in tourism and related creative sectors.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

What happens when AI tells our stories? Ambient authorship, cultural explainability, and digital voice

  • 期刊论文

  • 发表日期：

    2026年2月5日

查看全文
  • Huu Nghia Le

摘要

This paper examines how generative artificial intelligence (GenAI) mediates authorship, voice, and cultural representation in Vietnamese community-based tourism storytelling. Using a three-phase Participatory Analytical Synthesis (PAS) that combines netnography, GenAI prototyping, and community dialogue through a cross-layer integration index, it analyses convergence and divergence across human, algorithmic, and participant narratives. Findings reveal ambient authorship, the algorithmic reproduction of local aesthetics that displaces lived voice, and show that storytellers adopt GenAI conditionally as a drafting aid rather than as authors. The integration index (Ī = 0.46) indicates partial resonance, strongest for authenticity and representation, and weakest for affect and identity. From these results, the paper advances cultural explainability, reframing explainable AI as a social process in which meaning, emotion, and authorship are co-produced and contestable. The study provides conceptual and methodological guidance for participatory and culturally accountable GenAI design in tourism and related creative sectors.