Artificial intelligence and machine learning in the preservation and innovation of intangible cultural heritage: ethical considerations and design frameworks.
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...
| Publicado en: | Digital Scholarship in the Humanities Vol. 40; no. 2; pp. 487 - 509 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Oxford University Press / USA
Jun2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=186085075&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 186085075 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Jun2025 vid: 40 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 186085075 10.1093/llc/fqaf034 ppf: 487 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.1MB tig: atl: Artificial intelligence and machine learning in the preservation and innovation of intangible cultural heritage: ethical considerations and design frameworks. aug: au: Fu, Yanan Shi, Ke Xi, Le affil: School of Art and Design, Henan University of Science and Technology, LuoYang, Henan, 471023, China su: Natural language processing Pattern recognition systems Artificial intelligence Intellectual property Machine learning Deep learning sug: subj: Natural language processing Pattern recognition systems Artificial intelligence Intellectual property Machine learning Deep learning keyword: artificial intelligence community participation cultural preservation deep learning digital innovation ethics intangible cultural heritage machine learning natural language processing sustainability ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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