Piyush Senapati
Class of 2026 | NLU Jodhpur
Image by Khanchit Khirisutchalual from iStock
INTRODUCTION
One of the songs to go viral recently was a trap number titled ‘Heart on My Sleeve’ featuring Canadian rapper Drake and pop icon the Weekend. However, what is peculiar about this song is that neither of the abovementioned artists contributed a single note or lyric to it. The songwriter, singer, and producer for the song were all an Artificial Intelligence (AI) based application. The immediate takedown of this song from all streaming platforms on behest of UMG, the record label of both Drake and the Weekend on grounds of copyright infringement exemplifies how AI generated content has been a matter of contention in the art world due to its copyright implications.
Far from being an isolated incident, this follows after a host of copyright infringement claims and concerns voiced by musicians due to AI generated music, both abroad and in India.
Through the lens of Indian and American jurisprudence, this article seeks to analyse in what circumstances can AI generated music infringe copyright, including instances where the style of an artist is replicated by the system and whether such music can qualify for the fair dealing defence.
HOW AI CREATES MUSIC TESTING
The prospect of computers generating music is nothing new, with Lady Ada Lovelace herself predicting that they “might compose elaborate and scientific pieces of music of any degree of complexity or extent.” Understanding the exact mechanism by which AI creates music is necessary as the process itself raises copyright concerns- AI generated music is based on nothing but using already copyright music as ‘training material’ for the system. AI applications use databases of pre-existing songs, and use inferences from them to generate new content. Once a user feeds a musician’s existing music into the AI system, the machine learns to detect their stylistic patterns and then produces new music in that artist’s voice and style; but with lyrics, compositions, and other specifications of our choice. Thus, only at the effort of a few clicks, one can create an endless array of new music.
AI-GENERATED MUSIC ON THE TOUCHSTONE OF THE AVERAGE LISTENER’S TEST
The case of R.G Anand v. Delux Films (hereinafter, R.G Anand) and subsequent judgements established that the test to determine copyright infringement is to see whether an average listener having heard both the works gets an unmistakable impression that the subsequent work is a copy of the original. Therefore, the question of copyright infringement in cases of music generated through AI applications would ultimately boil down to whether an average listener would be under the impression that it is a copy of the music that’s used to generate it.
Before we test AI generated music based on the average listener’s test, it is important to note that music involves two copyrights– copyright over the musical works (rhythm, composition, and lyrics) and secondly copyright over the sound recording itself, also known as the master recording. Thus, our analysis of this question will have to be undertaken for both the copyrights.
Where copyright infringement of the musical works is concerned, it is unlikely that an average listener would recognise a meaningful percentage of the original works in the AI song. The reason for this boils down to the mechanism by which AI applications create music. Substantial portions of the musical works, do not manifest expressly in the final output as AI creates music by using the sound recording and mining the performative nuances therein, rather than using the musical works themselves. However, AI generated songs will nonetheless have to be analysed on a case-to-case basis, as certain musical works portions could appear in the final output, leading to copyright infringement if recognisable to the average listener.
Coming to copyright violations of the sound recording, there are two broad ways by which AI uses sound recordings to create music. The first is through independent fixation, i.e., recording an independent version of the song. The second is by manipulation of the actual copyrighted sound recording through encoding and decoding, wherein a portion of the same manifests in the final output.
The American case of Bridgeport Music, Inc. v. Dimension Films held that independent fixation would not amount to copyright infringement, no matter how similar the new version is to the original recording, as one cannot violate sound recording copyright by creating an independent version of the recording.
Similarly, the High Court of Delhi in Gramophone Company of India v. Super Cassette Industries (hereinafter, Gramophone Company) held that creation of a different version of the sound recording does not amount to copyright infringement. However, in the second instance where the AI generated music involves a reproduction of the original copyrighted sound recording, there can be a case of infringement if a substantial portion of the same manifests in the output and is recognisable to the audience.
Therefore, whether or not an AI generated song would violate copyright would depend on a number of factors ranging from the type of musical copyright involved, the method used by the AI to generate the song and recognisability of the original music manifesting in it.
AI RECREATING THE STYLE OF AN ARTIST- INSPIRATION OR INFRINGEMENT?
In the music world, infringement claims are often based not on direct copying of the musical works or sound recordings, but creating songs with a similar ‘vibe’ or ‘feel’ of another artist, i.e., music in another artists’ style. The discussion above demonstrates that there is ample scope for AI music creators to evade copyright infringement by using independent fixation. However, if a particular musicians’ work has been fed into the system, the output could definitely contain substantial stylistic similarities, even if it doesn’t copy any musical works or sound recordings. Therefore, it must be examined whether replication of another artists’ style by AI could amount to infringement.
The general consensus is that it is the unique expression of an idea that is capable of protection, and not the idea itself, as held in R.G Anand. Therefore, aspects of an artwork such as the theme, feel, style, and the ‘vibe’ are considered incapable of copyright protection. In light of this traditionally upheld idea-expression dichotomy, the Court in Gramophone Company held that the Copyright Act does not vest copyright in the style of performance of an artist. However, this dichotomy has been slightly deviated from of recent, such as in Anil Kumar v. Kunal Dasgupta. In this case, the Court held that when people create an idea, concept, or theme which is original, the law must ensure that they are rewarded for their labour. Although the Court did reiterate that ideas per se are not capable of copyright, it went on to hold that when an idea is developed into a concept fledged with adequate details, it can be copyrighted and hence granted copyright protection to the theme of a show.
Similarly, the Bombay High Court in Shamoil Khan v. Falguni Shah granted copyright protection to the central theme and concept of the literary work in question. Thus, since Courts have not displayed a doctrinaire adherence to the idea-expression dichotomy, copyright protection might be extended to musical style in some instances, such as in the American case of Williams v. Gaye wherein a claim for copyright infringement was allowed due to similarity of the ‘feel’ and ‘vibe’ of the two songs. This was in contrast to the American Courts’ usual approach of rejecting infringement claims based on a similarity in the ‘feel’ and theme of the song, as was done in Black v. Gosdin. Therefore, while the question of whether AI creating music in another artists’ style could amount to copyright violation erstwhile had a straightforward answer, it has now become hazy in light of the shifting jurisprudence.
AI GENERATED MUSIC AND THE DEFENCE OF FAIR USE
The ‘Fair dealing’ exception to copyright infringement covers bona fide use of copyrighted works without any prior permission or remuneration to the copyright owner, as opposed to blatant copying with an ulterior motives. Some examples include using copyrighted works for research or review purposes. Supposing that an AI generated song fails the average listener’s test, it is pertinent to analyse whether it could fall under this exception.
The Court in Civic Chandran v. Ammini Amma (hereinafter, Civic Chandran) laid down the factors for determining whether a case falls under the fair dealing exception as- the quantum of the matter taken from another work, the purpose for which it is taken, and the likelihood of competition between the two works. More importantly, the allegedly infringing work must be transformative, i.e., different from the original work in character, expression, and meaning to fall under this exception. It is to be noted that these factors for the fair dealing defence laid down by the Indian judiciary were adopted from American jurisprudence.
Where AI generated music is concerned, depending on the facts and circumstances of the case, the factors mentioned in Civic Chandran could have either allowed or disallowed the same to qualify for the fair dealing exception. However, what is concerning is that the Indian Judiciary has allowed the transformative factor to override the other factors as outlined in Civic Chandran– it has been held that if the work is transformative, it would be considered as fair dealing and the quantum of copying and potential commercial competition between the works would be immaterial. American Courts have also followed a similar approach by allowing the transformative factor to eclipse the other factors in the fair dealing enquiry.
Given that AI generated work can easily be classified as transformative, this heightened emphasis on the transformative factor could provide leeway for AI based musicians to evade infringement claims even if they heavily copy and compete with original music they trained their systems with.
CONCLUSION
While there is ample scope for AI music producers to evade copyright infringement, artists viewing AI generated music with suspicion, even hostility is natural, particularly in a country like India having a poor track record of musical copyright protection. While one side of the camp would hail AI for opening the floodgates for musical creativity, the other side would understandably fear its impact on musicians’ rights and livelihoods. To arrive at a balance between these two competing aspects, numerous solutions have been suggested, such as new licensing and royalty splitting arrangements, wherein AI based music creators would have to obtain licenses from musicians to use their work to train their systems, and share a portion of the profit they earn from the AI generated songs. While the feasibility of these solutions is to be tested, if global trends indicate anything, sooner or later the Indian judiciary too will be grappled with infringement claims against AI generated music. In adjudicating the same, Courts must similarly endeavour to arrive at a balance between fostering creativity and protecting musicians.
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