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Who Owns the Rights to AI-Generated Music?

The emergence of artificial intelligence in music creation raises significant debates about copyright, and the question of “who owns the rights to a musical work created by AI?” lies at the heart of this complex legal and artistic debate. Current laws, designed to protect human creations, do not account for works generated by "machines", and such a misalignment presents significant economic and artistic challenges – questioning established business models, as well as threatening cultural and artistic diversity.


To explore the topic, dive into this blog to assess the legal implications and current debates surrounding the ownership of musical works created by AI, while examining potential solutions for the future.


A Music Studio

AI-Generated Music: The Analysis

AI systems used to compose music, such as AIVA, OpenAI's MuseNet, and Amper Music, often analyze thousands of existing pieces to generate new compositions. From this analysis, these systems can imitate specific styles or create entirely original pieces, posing unique challenges to the current legal framework. For instance, AIVA can compose classical music by imitating the styles of famous composers, while MuseNet can generate music across various genres by blending different styles and instruments.


Suno.ai is another innovative platform in this field, utilizing AI to generate complete musical compositions based on natural language descriptions such as the musical style, desired emotion, or song theme. Recently, Suno raised $125 million in a Series B funding round, reaching a valuation of $500 million. Since its launch, 10 million users, including Grammy-winning artists, have used Suno, and it has been integrated into Microsoft’s Copilot AI app, making music creation accessible to everyone, regardless of musical skills.


There is constant and frequent debate around the training practices for a tool such as Suno. The majority of industry players question the integrity – ethically AND legally speaking – of training on past compositions without compensation for the creators of such music. As the dust settles, legislation & technology will continue to emerge which puts pressure on AI companies to be more transparent in their training practices.


The Current Legal Framework

In the United States, copyright law stipulates that works must be created by a human author, excluding works generated by machines – for example, the U.S. Copyright Office has previously refused to recognize the copyright of an image created by AI without human intervention.


Similarly, in the European Union, copyright directives require human involvement for copyright recognition. Although the EU's Digital Single Market Copyright Directive adopted in 2019 does not explicitly mention AI-generated works, current interpretations generally exclude works without direct human contribution.


In the United Kingdom, while the law allows computer-generated works to be protected by copyright, the rights are attributed to the person who made the necessary arrangements for creating the work. This means that the AI developer or the user who configures the AI to create the work could be considered the copyright holder.


Things are moving in the right direction with regards to legislation, and we have already seen the implementation of certain legislation, such as the Elvis Act in Tennesse earlier this year. This law, for example, has strengthened the protection of artists' voices and their heirs in response to the challenges posed by new technologies. Such legislative initiatives show that regulators are beginning to adapt to the realities of AI-assisted creation. However, much remains to be done to clarify and harmonize rules at the international level to effectively protect artistic works, both those created by artists and those created by AI, in order to find a balance. If you're looking to learn more about international regulations surrounding AI, check out this blog.


Solutions and Future Perspectives

To address these challenges, initiatives are underway to find equitable solutions. Some suggest creating a new category of copyright specifically for AI-generated works, recognizing the contributions of both human designers and AI systems. Others advocate for a more flexible approach, promoting collaboration between humans and AI in the creative process. For example, musician Taryn Southern used AI to compose one of her albums but actively participated in the creative process by guiding the AI and collaborating with human producers to refine arrangements, lyrics, and vocal performances. This hybrid approach showcased the combined potential of AI technology with artistic expertise and human expression.


On the technological side, there are a number of tools available to rights holders, and an innovative example of this is exemplified by CoverNet, an AI tool designed by MatchTune to protect copyright in the modern era. CoverNet helps ensure that artists' rights are safeguarded by monitoring the use of their works across various digital platforms, allowing for the detection of unlicensed covers, modified audio and, most relevantly, deepfakes – all in real time, and across all key music streaming & sharing platforms.


Conclusion

The question of who owns the copyright of AI-generated music highlights significant gaps in current legal frameworks, which are not designed to address non-human authorship. As AI advances, it is essential to update copyright laws to accommodate the prevailing changes. Addressing these issues requires a balanced approach that recognizes both human and AI contributions, fostering an environment where both can thrive.


Learn more about CoverNet here: https://www.covernet.ai/

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