AI Generated Music & Copyright Liability

By Poorvi J & Harsh Raj

I. Introduction

India’s Copyright Act, 1957, does not explicitly address the issue of AI authorship. Section 2(d)(v) of the Act defines the author of a computer-generated work as “the person by whom the arrangements necessary for the creation of the work are undertaken”. This suggests that the person who initiates the AI process or the AI developer could be considered the author. However, there is no clear consensus on this issue, and courts may need to interpret the law in the context of AI-generated music.

II. The History of Copyright’s Relationship to AI-Generated Works 

Currently, under the U.S. Copyright Office provision, AI-generated art cannot be protected under copyright because of the human authorship clause, which states that a human must be deemed the author of a creative work for copyright to apply. More specifically, the human authorship clause originated from the third of three requirements outlined by the original 1909 Copyright Act that a work of art must meet to qualify for copyright protection. The first requirement for copyright protection states that “the work must be fixed in a tangible form of expression”, the second is that it must be an “original work”, and the third is that it must be “created by an author”.  In its 2021 Edition of the Compendium, the U.S. Copyright Office updated by specifying that for a work of art the “work must be created by a human being”, and “works that do not satisfy this requirement are not copyrightable”. Under the UK laws the, Music generated by AI can be protected as work “generated by computer in circumstances that there is no Human involvement” (s. 178, Copyright, Designs and Patents Act 1988 (CDPA)). But it does not imply on AI generated music. Whereas the U.S. Copyright Office has stated that it “does not recognise AI as an author” under current law, and that the terms ‘author’, used in both the Constitution and the Copyright Act, excludes non-humans”.  

India’s Copyright Act, 1957, does not explicitly address the issue of AI authorship. Section 2(d)(v) of the Act defines the author of a computer-generated work as “the person by whom the arrangements necessary for the creation of the work are undertaken”. This suggests that the person who initiates the AI process or the AI developer could be considered the author. However, there is no clear consensus on this issue, and courts may need to interpret the law in the context of AI-generated music.

III. How Does AI music work?

It uses algorithms, machine learning and other computational methods to analyse musical data, understand musical patterns and come up with original tunes. So instead of having a human composer or tuner, we have got a computer doing the job. With the growth of Large language Models (LLMs) have made it more enhanced and more perfect and perform most of the human tasks that traditionally require human cognitive abilities. One of the key components of AI music is machine learning, a subset of AI that focuses on enabling computers to learn from data, these algorithms are trained on large datasheets, where they iteratively adjust their parameters to improve performances on a specific task. In 2019, OpenAI introduced Muse Net, a transformer-based model generating multi-instrument, multi genre compositions. In 2022, Riffusion applied image to spectrogram diffusion models, generating “Other worldly” music via Stable Diffusion Fine-Tuning. In 2023, Google DeepMind announced Lyria, capable of generating high quality music with vocals and instruments, powering experiments like Dream Track with major artists. In present, AI powered tools for composition, sound design, mixing and real time performances continue to evolve with integrating deep learning to assist musicians across the creative process. 

IV. Copyright Law & AI‑Created Music

 In Thaler v. Perlmutter, the court concluded that copyright protection is reserved for works of human creation. After Stephen Thaler attempted to apply for copyright protection on an AI-generated visual work created by an AI algorithm known as the “Creativity Machine,” the Court conducted an in-depth analysis of current definitions of authorship in legal texts such as the Constitution. To protect the basis of artistic creativity as stemming from human creations, the Court upheld authorship as requiring human origins. However, in an attempt to protect creativity itself, the Court allowed AI-generated programs to remain unregulated, thereby enabling them to copy and infringe upon the creative works of human artists. The verdict in Thaler has also been applied to the world of music. As of March 15, 2024, the Copyright Office issued its latest formal guidance after a TikTok user named Ghostwriter977’s AI software produced a hit song from superstar musicians Drake and The Weeknd’s music. In the Copyright Office’s statement, the Office continued to affirm that works created by “AI without human intervention or human involvement cannot be copyrighted”. AI-generated music introduces a new dimension of creativity. On April 2023, A Drake Song was released featuring Weekend on all streaming platforms (including Spotify, YouTube, etc). It quickly went viral across various streaming platforms, including Spotify and YouTube. But here the problem was that this track was not created by either of these artists. A TikTok user Ghostwriter977 had created the song “Heart on My Sleeve” using AI. 

Ghostwriter977 said in an interview that he had written, produced and he used his own voice to record the song. Then he used a tool which converted his vocals into Drake and Weeknd’s vocals. This tool used an algorithm that replicated Drake and The Weeknd’s vocals, an audio version of a deep faked image. They aren’t the only two artists whose voices were mimicked - artists like Bad Bunny, Rihanna and many others also have been mimicked.

The Song “Heart on My Sleeve” had gained more than 6 million views on YouTube. But later on, this song was taken down from all streaming platforms by Universal Music Group (UMG). They labelled the AI generated songs as “Fraud”. The CEO of Recording Academy Harvey Mason Jr. said this song is eligible for winning a Grammy award as this was written by a human. Three days later, The CEO stepped back from the decision because the song used voice of Drake and Weeknd. The problem that arises with the release of AI-generated songs like “Heart in My Heart” is that the artist’s voice is used without his consent and then not given proper royalties. While Ghostwriter977’s creative efforts showcase the potential of the artist, they ignore the ethical principle of recognizing and rewarding artists who play a role in the development of intellectual skills.

V. New copyright law for AI generated songs                                                                                   

Establishing a new legal framework specifically addressing AI generated music is crucial. This could involve - 

a. Defining authorship: recognising both the human programmer and the AI as coauthors. This acknowledges the programmer’s role in defining the parameters and training the AI, while also acknowledging the AI’s independent creative contributions. Copyright percentages: A system for determining the percentage of copyright ownership for each party based on pre defined criteria, such as the complexity of the AI algorithm, the amount of human input, and the originality of the generated music.

b. Open data and transparency: Requiring AI developers to disclose the training data and algorithms used to create their AI music tools. This transparency promotes ethical use, protects against potential plagiarism, and allows for informed discussions about originality and copyright ownership. 

c. Public Domain access and innovation: Establishing provisions for public domain access to certain AI - generated music after a defined period, fostering remix culture, experimentation, and further innovation in music creation. This could involve specific criteria for public domain access, such as a combination of time elapsed, minimal human input, and demonstrably significant contribution by the AI.

VI. Conclusion

AI - generated music raises complex questions about copyright and authorship. But the current copyright law struggles to do so. By combining voice biometrics, spectral analysis, and deep learning algorithms, we can develop tools to detect AI - generated music and ensure proper attribution or compensation for human artists whose voices or styles are mimicked. Additionally, a new copyright law specifically addressing AI - generated music is necessary, recognising the dual nature of authorship, promoting transparency in data and algorithms, and establishing safeguards for originality and ethical use.  

AI music has a bright future and a lot of creative expression possibilities. However, musicians, AI developers, lawyers, and legislators must work together to navigate the complex issues of copyright in this field. We can guarantee that AI - generated music flourishes inside a system that promotes creativity, justice, and respect for intellectual property by embracing innovation while defending the rights of human creators.

References:

1. Caitlin Van Orden, Musical Minds and Machine Learning: Copyright in the Age of AI‑Generated Music, 123 W. Va. L. Rev. 835 (2021). 

2. Joshua P. Friedlander, Year-End 2019 RIAA Music Revenues Report 1 (Recording Indus. Ass’n of Am. 2019). 

3. JESSICA LITMAN, DIGITAL COPYRIGHT (2001).

4. Michael W. Carroll, The Struggle for Music Copyright, 57 Fla. L. Rev. 907 (2005).

5. Edward Lee, Fair Use Avoidance in Music Cases, 59 B.C. L. Rev. 1874, 1890 (2018).

6. Shaad D’Souza, An AI‑Generated Band Got 1m Plays on Spotify. Now Music Insiders Say Listeners Should Be Warned, The Guardian (July 14, 2025).

7. Priya Raghavan, Copyright and Authorship in AI‑Generated Music, ResearchGate (Mar. 2024). 

8. Atreya Mathur, Case Review: Thaler v. Perlmutter (2023), Ctr. for Art L. (Dec. 11, 2023). 

9. Rachel Reed, AI Created a Song Mimicking the Work of Drake and The Weeknd. What Does That Mean for Copyright Law?, Harv. L. Today (May 2, 2023).

10. U.S. Copyright Office, Compendium of U.S. Copyright Office Practices § 313.2 (3d ed. 2017), ch. 300.

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