{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T13:53:43Z","timestamp":1791208423957,"version":"4.1.0"},"reference-count":11,"publisher":"Darcy & Roy Press Co. Ltd.","license":[{"start":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T00:00:00Z","timestamp":1791158400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EHSS"],"abstract":"<jats:p>The deep integration of generative artificial intelligence and music education has demonstrated unprecedented instructional efficiency. However, beneath this technological empowerment lies a profound crisis. This paper focuses on two major issues emerging from AI-enhanced music teaching: the alienation of creativity and aesthetic homogenization. Creative alienation reduces students from artistic subjects to mere prompt-input operators, while artistic exploration and emotional experience are increasingly replaced by algorithms. Aesthetic homogenization, driven by the commercial bias embedded in model training, pushes outputs toward an \u201caverage aesthetic,\u201d thereby suppressing musical diversity and cultural individuality. Drawing upon educational ethics and theories of arts education, this study upholds the humanistic core of music education and seeks to redefine the relationship between artificial intelligence and learners, ensuring that technology genuinely serves artistic creation rather than replacing the creative subject. The paper aims to provide theoretical references for the human-centered restoration and sustainable development of music education in the age of artificial intelligence.<\/jats:p>","DOI":"10.54097\/defffv81","type":"journal-article","created":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T13:06:25Z","timestamp":1791205585000},"page":"193-199","source":"Crossref","is-referenced-by-count":0,"title":["The Alienation of Creativity, Aesthetic Homogenization, and Their Governance in AI-Driven Music Education"],"prefix":"10.54097","volume":"64","author":[{"given":"Yijing","family":"Yang","sequence":"first","affiliation":[{"name":"Sichuan Normal University, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"32412","published-online":{"date-parts":[[2026,10,5]]},"reference":[{"key":"628","unstructured":"[1] Yu, H., Zhang, L., & Zhao, M. (2023). Intelligent accompaniment and harmonic analysis tools for instrumental teaching. Journal of Digital Music Education, 5(2), 22\u201330."},{"key":"629","doi-asserted-by":"crossref","unstructured":"[2] Wei, J., Karuppiah, M., & Prathik, A. (2022). College music education and teaching based on AI techniques. Computers and electrical engineering, 100, 107851.","DOI":"10.1016\/j.compeleceng.2022.107851"},{"key":"630","unstructured":"[3] Mao, Q. S. (2022). Student satisfaction with AI-assisted music classroom teaching. Journal of Arts Education, 9(3), 78\u201385."},{"key":"631","doi-asserted-by":"crossref","unstructured":"[4] Chen, Y., & Sun, Y. (2024). The usage of artificial intelligence technology in music education system under deep learning. Ieee Access, 12, 130546\u2013130556.","DOI":"10.1109\/ACCESS.2024.3459791"},{"key":"632","doi-asserted-by":"crossref","unstructured":"[5] Faure-Carvallo, A., Gustems-Carnicer, J., & Guaus Termens, E. (2022). Music education in the digital age: Challenges associated with sound homogenization in music aimed at adolescents. International Journal of Music Education, 40(4), 598\u2013612.","DOI":"10.1177\/02557614221084315"},{"key":"633","unstructured":"[6] Jiao, J. L. (2023). ChatGPT: Friend or foe of school education? Modern Educational Technology, 33(4), 5\u201315."},{"key":"634","unstructured":"[7] G\u00fclcan, M. (2015). Educational ethics is a regulatory framework for instructional technology. Journal of Educational Philosophy, 18(2), 41\u201357."},{"key":"635","unstructured":"[8] Wang, P., & Li, X. B. (2026). Research on the integrated model of artificial intelligence and teachers\u2019 professional development for future education. Technology Wind, (12), 144\u2013146."},{"key":"636","doi-asserted-by":"crossref","unstructured":"[9] Li, Y., & Sun, R. (2023). Innovations of music and aesthetic education courses using intelligent technologies. Education and Information Technologies, 28(10), 13665\u201313688.","DOI":"10.1007\/s10639-023-11624-9"},{"key":"637","unstructured":"[10] Wang, X. X. (2026). Transformation paths and value retention of music education under generative artificial intelligence. Portrait Photography, (6), 138\u2013140."},{"key":"638","unstructured":"[11] Yuan Li. (2022). The Development and Application of Artificial Intelligence Technology in the Field of Music Education. (eds.) Proceedings of 2022 the 6th International Conference on Scientific and Technological Innovation and Educational Development (pp.855\u2013857). School of Music & Dancing, Lingnan Normal University;"}],"container-title":["Journal of Education, Humanities and Social Sciences"],"original-title":[],"link":[{"URL":"https:\/\/ehssdata.org\/index.php\/ojs\/article\/download\/48\/45","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ehssdata.org\/index.php\/ojs\/article\/download\/48\/45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T13:06:31Z","timestamp":1791205591000},"score":1,"resource":{"primary":{"URL":"https:\/\/ehssdata.org\/index.php\/ojs\/article\/view\/48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,5]]},"references-count":11,"URL":"https:\/\/doi.org\/10.54097\/defffv81","relation":{},"ISSN":["2771-2907"],"issn-type":[{"value":"2771-2907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,5]]}}}