Copyrights Infringement Risks in AI-generated Cover Songs: An Analysis Based on Current Legislation

Jingwen Ji

doi:10.54254/2753-7048/20/20231467

Research Article

Open access

Published on 26 October 2023

Download pdf

Ji,J. (2023). Copyrights Infringement Risks in AI-generated Cover Songs: An Analysis Based on Current Legislation. Lecture Notes in Education Psychology and Public Media,20,19-25.

Export citation

Copyrights Infringement Risks in AI-generated Cover Songs: An Analysis Based on Current Legislation

Jingwen Ji *^,1,

¹ Beijing Foreign Studies University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2753-7048/20/20231467

Abstract

In the age of “Big Data”, the accelerated iteration of AI models characterized by ChatGPT has fueled both excitement and fear. With the diversified application of generative AI models, last year witnessed a surge in AI cover songs. Compared with the discussions around the content generated by AI, the prior training process receives less attention. This article aims at analyzing the copyright law issues related to AI cover songs. By examining current legislation in different countries, the author believes that the training of AI cover models risks violating both property rights and moral rights stipulated in copyrights laws. Moreover, it fails to fit in the fair-use defense in most states. Considering the emotional values preserved by AI cover songs as well as the spirit of copyright laws, this article argues that basically, the training of AI cover models should be solely for non-commercial use. An unregulated approach toward AI cover songs can otherwise hinder innovations and disproportionately harm the interest of minority groups.

Keywords

AI cover songs, copyright law, fair use, TDM

View pdf

References

[1]. Takyar, K. Data Center Infrastructure Built on the Intel Xeon Processor E5 v3 Family. Retrieved from http://www.intel.com/content/www/us/en/cloud-computing/xeon-e5-products-real-world-guide.html.

[2]. Eiseman, J., Ortiz, N. (2023) Generative AI & Machine Learning in Law Libraries: The Benefits, Risks, and Ethical Issues Surrounding These Potentially Transformative New Tools. AALL Spectrum. 27, 14-17.

[3]. Sunray, E. (2021) Sounds of Science: Copyright Infringement in AI Music Generator Outputs. Catholic University Journal of Law and Technology. 29, 185-218.

[4]. Ibrahim, S. (2023). AI-generated Drake song is an insult to the artistry of hip-hop. Retrieved from https://www.washingtonpost.com/music/2023/04/26/ai-drake-weeknd/

[5]. Yurkevich, V. (2023). Universal Music Group calls AI music a ‘fraud,’ wants it banned from streaming platforms. Experts say it’s not that easy. Retrieved from https://edition.cnn.com/2023/04/18/tech/universal-music-group-artificial-intelligence/index.html

[6]. Savage, M. (2023). Sting warns against AI songs as he wins prestigious music prize. Retrieved from https://www.bbc.com/news/entertainment-arts-65627089

[7]. Veltman, C. (2023). When you realize your favorite new song was written and performed by ... AI. Retrieved from https://www.npr.org/2023/04/21/1171032649/ai-music-heart-on-my-sleeve-drake-the-weeknd

[8]. Rallabhandi, K. (2023) The Copyright Authorship Conundrum for Works Generated by Artificial Intelligence: A Proposal for Standardized International Guidelines in the WIPO Copyright Treaty. George Washington International Law Review. 54, 311-348.

[9]. Lindberg, V. (2023) Building and Using Generative Models under US Copyright Law. Rutgers Business Law Review. 18, 1-65.

[10]. The Economist. (2023). Art made by artificial intelligence is developing a style of its own. Retrieved from https://www.economist.com/culture/2023/05/24/art-made-by-artificial-intelligence-is-developing-a-style-of-its-own

[11]. Sunray, E. (2021) Train in Vain: A Theoretical Assessment of Intermediate Copying and Fair Use in Machine AI Music Generator Training. American University Intellectual Property Brief. 13, 1-32.

[12]. Ruby, D. (2023). 30+ Detailed ChatGPT Statistics — Users & Facts (July 2023), Retrieved from https://www.demandsage.com/chatgpt-statistics/

[13]. Schreiner, M. (2023). GPT-4 architecture, datasets, costs and more leaked. Retrieved from https://the-decoder.com/gpt-4-architecture-datasets-costs-and-more-leaked/

[14]. Future Web Tools. (2023). AI cover Sovits 4.0 model (Colab teaching). Retrieved from https://futureweb.pro/tools/ai-web3-blog/ai-covers-so-vits-svc-tutorial

[15]. Gao, W., Xiaobin, H. (2021) Study on the Design of Fair Use Ｒules for Text and Data Mining in the Age of Artificial Intelligence. Library and Information Service. 65, 3-13.

[16]. Fan, D. (2019) On the Construction of Copyright Exception Rules for the Application of Text and Mining Technology. Hebei Law Science. 37, 148-160.

[17]. Chunlin, L., Liwei, Z. (2008) Research on Conflict between Temporary Copying and Fair Use. Modern Business Trade Industry.273-274.

[18]. Daniel Schönberger, D. (2018) Deep Copyright: Up - and Downstream Questions Related to Artificial Intelligence (AI) and Machine Learning (ML).1, 1-19.

[19]. Yang, G. (2022) Research on the Dilemma and Improvement of the Copyright Fair Use Doctrine Related to Machine Learning in China. UIC Review of Intellectual Property Law. 22, 1-22.

[20]. Chiou, T. (2019) Copyright Lessons on Machine Learning: What Impact on Algorithmic Art. Journal of Intellectual Property, Information Technology and Electronic Commerce Law. 10, 398-412.

[21]. Xiangjun, P. (2023) Research on the Copyright Risk Resolution Mechanism of Machine Learning Training Set. Shanghai Legal Studies. 6, 158-169.

[22]. KaiXin, Z., Yiqun, Z. (2023). “Your AI infringes my copyright”: Talking about the copyright protection behind AIGC. Retrieved from https://www.tisi.org/25255

[23]. Moral Rights in U.S. Copyright Law. (2023). Retrieved from https://www.copyrightlaws.com/moral-rights-in-u-s-copyright-law/

[24]. Matulionyte, R. (2023) Can AI Infringe Moral Rights of Authors and Should We Do Anything About it: An Australian Perspective. Law, Innovation and Technology. 15, 124-147.

[25]. svc-develop-team/so-vits-svc. Retrieved from https://github.com/svc-develop-team/so-vits-svc

[26]. IP Experts Focus On 3-Step Test In Copyright, Discuss Way Forward. Retrieved from https://www.ip-watch.org/2011/12/21/ip-experts-focus-on-3-step-test-in-copyright-debate-way-forward/

[27]. Hermann, RM. (2013). The Three-Step Test. Retrieved from https://www.eff.org/files/filenode/three-step_test_fnl.pdf

[28]. Kenneth D. Fair Use. Retrieved from https://copyright.columbia.edu/basics/fair-use.html

[29]. Authors Guild, Inc. v. HathiTrust, 755 F.3d 87 (2d Cir. 2014).

[30]. Campbell v. Acuff-Rose Music, Inc., 510 U.S. 569 (1994).

[31]. Dickens, R. (2023). UK re-considers proposed exception for text and data mining. Retrieved from https://www.allenovery.com/en-gb/global/blogs/digital-hub/uk-re-considers-proposed-exception-for-text-and-data-mining

[32]. Dermawan, A. (2023) Text and data mining exceptions in the development of generative AI models: What the EU member states could learn from the Japanese “nonenjoyment” purposes? The Journal of World Intellectual Property. 1-25.

[33]. Prime, D. (2023). Japan Goes All In: Copyright Doesn’t Apply To AI Training. Retrieved from https://technomancers.ai/japan-goes-all-in-copyright-doesnt-apply-to-ai-training/

[34]. Ormonde, I. (2023). Harry, sing Lana Del Rey! How AI is making pop fans’ fantasies come true. Retrieved from https://www.theguardian.com/music/2023/may/04/harry-sing-lana-del-rey-how-ai-is-making-pop-fans-fantasies-come-true

Cite this article

Ji,J. (2023). Copyrights Infringement Risks in AI-generated Cover Songs: An Analysis Based on Current Legislation. Lecture Notes in Education Psychology and Public Media,20,19-25.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 4th International Conference on Educational Innovation and Philosophical Inquiries

Conference website: https://www.iceipi.org/

ISBN：978-1-83558-065-3(Print) / 978-1-83558-066-0(Online)

Conference date: 7 August 2023

Editor：Javier Cifuentes-Faura, Enrique Mallen

Series: Lecture Notes in Education Psychology and Public Media

Volume number: Vol.20

ISSN：2753-7048(Print) / 2753-7056(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).