Research on the Dilemmas and Improvement Paths of Applying Copyright Law to Style Imitation in AI-Generated Music

DOI

10.2991/978-2-38476-611-6_77How to use a DOI?

Keywords

AI-generated music; Style imitation; Copyright law; Idea-expression dichotomy; Anti-unfair competition law

Abstract

The breakthrough in generative artificial intelligence technology has made music style imitation possible, posing new challenges to traditional copyright law. While a musical style itself is not protected, original expressions incorporating that style may constitute a work. The AI imitation process consists of two stages: training, which may infringe the reproduction right, and generation, which may infringe the adaptation right or invoke the application of anti-unfair competition law. Current copyright law faces dilemmas such as ambiguity in determining originality in human-computer collaboration and difficulties in proving the “access” requirement for infringement. Future regulation should prioritize interpretative approaches within the framework of copyright law, while simultaneously introducing anti-unfair competition law as a supplement, to balance technological innovation and rights protection.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 3.0 International License (http://creativecommons.org/licenses/by-nc/3.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shengjie Ding
PY  - 2026
DA  - 2026/09/07
TI  - Research on the Dilemmas and Improvement Paths of Applying Copyright Law to Style Imitation in AI-Generated Music
BT  - Proceedings of the 2026 12th International Conference on Digital Humanities and Frontiers in Social Sciences (DHFSS 2026)
PB  - Atlantis Press
SP  - 697
EP  - 703
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-611-6_77
DO  - 10.2991/978-2-38476-611-6_77
ID  - Ding2026
ER  -