In November 2023, the new Beatles song “Now and Then” was released after 45 years, debuting on BBC radio at 2 p.m. of the 3rd of November and on the main streaming platforms, including Spotify and Apple Music. This was one of the most tangible signs that the music and the more general entertainment industry is undergoing a new transformation due to the integration of Artificial Intelligence (AI) algorithms.
The release of “Now and Then” represents a concrete example of how AI is changing the way music is composed, produced, and mixed. In fact, this song comes from the application of AI to an unreleased demo, recorded by John Lennon with piano and vocals before he was murdered in 1980, which isolated Lennon’s voice and removed background noise and improved sound quality to make it able to be normally mixed with the music track. This project led to a better understand how the spread of this technology is deeply transforming the entire society and almost all socio-economic processes. AI is also changing the music industry into a real technology-driven ecosystem, characterized by complex and networked interactions between different actors (e.g., musicians/performers, customers, producers, majors, etc.).
The growing use AI technologies is also changing the value creation processes that traditionally characterized this sector, making them more collaborative, and open integrating and intertwining in a value network primary (operations, logistics, marketing, sales, and services) and supportive (human resource management, technology, and procurement) activities often performed and managed digitally. In the technology-based music ecosystem, consumers (or people) play an active role, which has been further enhanced not only by AI, but also by different digital technologies such as the distributed computing accessible via well-known platforms like Amazon Web Services, Google Cloud, and Microsoft Azure, which have further democratized data storage and processing. This “generative” approach is changing music industry not only in terms of productivity reducing the gap between the ideation and the creation, but also blurring the boundaries between the different socio-economic factors, such as consumers, producers, and performers.
Together with other advanced technologies, AI is impacting almost all the actors and the processes of the music ecosystem, which go from music creation and production to the way it is consumed and experienced. The use of AI for creating music, comparable to the one created by humans, is now a concrete reality. In fact, music can be created from different data sources such as texts (e.g. MusicGen1) or images (e.g. BGT-G2G2), going beyond the traditional music generation from MIDI files or audio databases. It follows that in recent times AI development community has taken important step forward the development of assessment methods in line with the seven requirements for Trustworthy AI, defined by the High-Level Expert Group on Artificial Intelligence3 in 2019, which delve on 1) traditional evaluation criteria: accuracy and robustness, and 2) socially relevant evaluation criteria: fairness and diversity, transparency, accountability, and social well-being.
In these days most of the music majors are shifting to AI technologies for creating, mixing, or arranging music. The algorithms that are mostly used at professional level have been created and distributed by Sony, Google, and the Chinese Baidu; thus, their application contribute to reduce costs, improve process efficiency but also to stimulate the music industry.
However, if the positive effects of AI application to music industry are easy to understand, it does not come with no threats. In fact, important and challenging issues related to music ownership and distribution are affecting the industry and globally attracting the interest of practitioners and policymakers. In fact, a lively debate is currently ongoing about plagiarism or copyright infringement due to the generative music creation and the subsequent consequences for the whole industry. At this moment in time, no clear and shared solutions have been implemented to better regulate the creative process and the related intellectual property rights. In fact, even though the generative AI is quickly changing the way to approach digital art creation, together with plagiarism and copyright infringement other concerns are emerging and are interesting the ethical, social, and economic sphere of the music industry.
A question remains, can AI really replace human creative tasks, or it is something that complements and boosts it?
References
Batlle-Roca, R., Gómez, E., Liao, W., Serra, X., & Mitsufuji, Y. (2023). Transparency in music-generative AI: A systematic literature review.
Daniele, A., & Song, Y. Z. (2019, January). Ai+ art= human. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 155-161).
Oğul, S. (2024). In Tune with Ethics: Responsible Artificial Intelligence and Music Industry. REFLEKTİF Sosyal Bilimler Dergisi, 5(1), 139-149.
Shang, M., & Sun, H. (2020, October). Study on the New Models of Music Industry in the Era of AI and Blockchain. In 2020 3rd International Conference on Smart BlockChain (SmartBlock) (pp. 63-68). IEEE.
Shroff, L. (2024). AI & Copyright: A Case Study of the Music Industry. GRACE: Global Review of AI Community Ethics, 2(1).
Daniele and Song, 2019; Chung, 2021).
