AI-Enabled Sustainable Indigenous Heritage

Integrating Language Revitalization, Cultural Memory, and Digital Humanities in Taiwan

Abstract

The rapid decline of indigenous languages poses a significant challenge to cultural
heritage preservation worldwide. This study argues that indigenous language
preservation should be understood as a process of cultural revitalization rather than
merely linguistic documentation.
Using Taiwan’s indigenous languages as a representative case, the study explores how
artificial intelligence (AI) can support indigenous cultural sustainability. Drawing
from Indigenous Studies, Cultural Sustainability, Digital Humanities, and AI research,
it develops an interdisciplinary framework linking language revitalization, knowledge
transmission, community participation, and technological innovation.
The paper proposes the AI-Supported Indigenous Cultural Revitalization Framework
(AICRF) and further develops the AI-Enabled Sustainable Indigenous Heritage Model (AI-SIHM). These models illustrate how AI technologies—including speech
recognition, natural language processing, machine translation, large language models,
and digital storytelling—can facilitate language preservation, cultural transmission,
and indigenous heritage sustainability.
The findings suggest that AI should serve as a supportive tool rather than a
replacement for indigenous knowledge holders. Effective AI-assisted cultural
revitalization requires Indigenous Data Sovereignty, ethical governance, and
community participation. The study contributes to the literature by integrating cultural
sustainability theory with indigenous knowledge systems and proposing AI-SIHM as
a multidisciplinary framework for future research and practice. It concludes that AI,
when guided by indigenous self-determination, can become a catalyst for
safeguarding indigenous heritage and promoting sustainable cultural futures.