Artificial intelligence and machine learning in the preservation and innovation of intangible cultural heritage: ethical considerations and design frameworks

Abstract This study explores the application of artificial intelligence (AI) and machine learning in the preservation and innovation of intangible cultural heritage. Through analysis of implementations at major cultural institutions including the Palace Museum and Dunhuang Academy, the research demonstrates AI-driven preservation strategies achieving 90–95 per cent success rates in pattern recognition and 88 per cent accuracy in oral history preservation. It examines these technologies in documenting, analysing, and revitalizing cultural practices, while addressing ethical considerations and sustainability challenges. The research investigates cultural pattern recognition, AI-driven innovation, deep learning in heritage restoration, and natural language processing in preserving oral traditions. Empirical evidence shows AI-enhanced systems have achieved 92 per cent cultural accuracy while reducing processing time by 75 per cent. A framework for balancing technological intervention with cultural authenticity is proposed, alongside mechanisms for community participation and intellectual property protection. Implementation has achieved 80 per cent community engagement and demonstrated 40 per cent reduction in computational resource consumption while maintaining preservation quality.