Sound Ethics
AI Research Lab Serving Artists
Transparency First
Champion Artists
Safeguarding Creative Rights in the Age of AI
Sound Ethics is an independent research organization dedicated to serving artists, rights holders, and safeguarding creative rights in the age of AI.
Composers, songwriters, producers, musicians, and rights holders have been heavily disrupted by AI. We face serious challenges around copyright, fraud, deepfakes, and transparency when our songs are used to train and advance AI and machine learning models.
Grounded in university partnerships, our research advances responsible Gen-AI music systems.
Embrace AI. Champion Artists.
Sound Ethics
Sound Ethics (Side A)
Transparency First
Champion Artists
Safeguarding Creative Rights in the Age of AI
Sound Ethics is an independent research organization dedicated to serving artists, rights holders, and safeguarding creative rights in the age of AI.
Composers, songwriters, producers, musicians, and rights holders have been heavily disrupted by AI. We face serious challenges around copyright, fraud, deepfakes, and transparency when our songs are used to train and advance AI and machine learning models.
Grounded in university partnerships, our research advances responsible Gen-AI music systems.
Research
Sound Ethics leads the 2026 University AI Music Research Initiative, a multi-institutional project spanning 12 teams across eight university AI labs. Researchers at UC Berkeley, UCLA, NYU, UCSB, UCI, and other institutions work with Sound Ethics on music and AI projects involving data science, computer science, and machine learning.
This is a critical moment: landmark litigation, rapidly evolving legislation, and the commercial expansion of generative AI are shaping precedents that may govern music and technology for decades.
Ethical AI in Academia
Sound Ethics
From Labs
To Legends
University AI researchers and engineers are building the systems that will shape the future of music.
Sound Ethics leads university teams and researchers working on Gen-AI music models, attribution systems, uncovering songs used in training models, AI detection models, and music intelligence that can identify when copyrighted material is used in AI-generated works.
In collaboration with universities and industry leaders, we're establishing responsible AI research practices for the next generation of engineers that respect artists. We also provide opportunities for developing engineers who want to work in the music industry.
Standardizing AI Rights
Sound Ethics
TRAINING AI?
We believe artists, songwriters, and rights holders deserve to know when their work trains AI. Our researchers study foundational AI music and audio machine learning models including which songs have been used in their development. Sound Ethics is carefully releasing its findings and preparing a public lookup tool that will make this history more visible and searchable.
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