AI, IP, and the Future of Creativity
Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Professor of Technology, Operations, and Statistics at New York University's Stern School of Business. He is also Director of NYU's Fubon Center for Technology, Business and Innovation. His research focuses on AI, intellectual property, and how digital technologies transform business and society, with an emphasis on the economics of digital goods, network effects, and the regulation of artificial intelligence and digital platforms (NYU, n.d.). He is widely known for his best-selling book, “The Sharing Economy.” His academic credentials include a bachelor's degree in electrical engineering from the Indian Institute of Technology Madras and a Ph.D. in business administration from the University of Rochester. Professor Sundararajan's profound expertise and insight into the digital economy of nations place him at the forefront of discussions on technology, innovation, and the future of work.
We asked Prof. Sundararajan about the concept of an AI “digital twins.” He explained both the potential benefits and problems with the development and use of digital twins.
Prof. Sundararajan explained the risks of the “monocultural” phenonenon, where AI systems trained on similar data produces homogenous outputs. He also highlighted how governments may need to change intellectual property laws to better protect creators in the AI age.
Intellectual Property (IP)
Intellectual property refers to original works, such as inventions, literary and artistic work, designs, symbols, names, and images used in commerce. Intellectual property law protects those work via legal rights, and enable creators to gain economically from their innovations by providing them with exclusive possession over the use, reproduction, and distribution of their work. Intellectual property consists of four broad categories:
Copyright: protects original works of authorship, including literature, music, and visual arts.
Patents: protect inventions and grant exclusive rights to the inventors.
Trademarks: protect distinctive symbols, names, and slogans associated with goods or services.
Trade Secrets: protect secret business data that gives a competitive edge.
Intellectual Property in the Music Industry
In the music industry, IP rights are significant for safeguarding the interests of artists, composers, and producers. Copyright provides creators with exclusive reproduction, distribution, and public performance rights of their musical compositions. Licensing enables artists to authorize others to use their songs, typically on a royalty basis. Performance rights enable artists to be remunerated if their work is publicly performed. These rights promote creativity and allow artists to benefit financially from their work (Recording Academy, 2025).
Challenges AI Presents in Music Production
Authorship and Ownership
One of the main legal challenges of AI music production is authorship. The U.S. Copyright Office has taken the stance that work produced solely by AI and without any human intervention is not eligible for copyright protection. But if a human creatively participates, by choosing inputs or refining outputs, the resulting work can qualify for protection (U.S. Copyright Office, 2023).
Training AI with Pre-existing Works
AI models are trained on existing music, which raises fear of unauthorized use of copyrighted music. If the AI-generated work is very much alike existing original work, it could be a copyright infringement of the creators' rights (RIAA, 2024). This has resulted in various court cases questioning whether such use is fair use or a copyright infringement (Harvard Law Today, 2023).
Legal and Ethical Issues
The intersection of AI and IP in music production calls for serious legal and ethical examination. Legislative action such as the NO FAKES Act has been suggested to prevent unauthorized AI-aided copies of artists' images and voices (New York Post, 2025). Additionally, AI producers are increasingly under pressure to disclose their training data sources to guarantee copyright respect. Keeping fair remuneration for creators whose works are employed to train artificial intelligence models remains an urgent matter (Recording Academy, 2025).
References
Harvard Law Today. (2023). AI created a song mimicking the work of Drake and The Weeknd. What does that mean for copyright law? https://hls.harvard.edu/today/ai-created-a-song-mimicking-the-work-of-drake-and-the-weeknd-what-does-that-mean-for-copyright-law/
New York Post. (2025). Paul McCartney warns proposed AI law will rip off the next generation of musicians. https://nypost.com/2025/01/25/entertainment/paul-mccartney-warns-proposed-ai-copyright-laws-will-rip-off-artists/
New York University (n.d.). Arun Sundararajan. https://www.stern.nyu.edu/faculty/bio/arun-sundararajan
Recording Industry Association of America (RIAA). (2024). Record companies bring landmark cases for responsible AI against Suno and Udio in Boston and New York federal courts respectively.https://www.riaa.com/record-companies-bring-landmark-cases-for-responsible-ai-againstsuno-and-udio-in-boston-and-new-york-federal-courts-respectively
Recording Academy. (2025). AI and copyright: How the Recording Academy is leading the charge. https://www.recordingacademy.com/advocacy/news/ai-copyright-protecting-music-creators-united-states-copyright-office
The Times. (2025). Labour’s AI copyright law short-sighted, says Emmy winner. https://www.thetimes.co.uk/article/labour-ai-copyright-law-short-sighted-says-emmy-winner-bgs7k6vxk
U.S. Copyright Office. (2023). Copyright registration guidance: Works containing material generated by artificial intelligence.https://www.copyright.gov/ai/