Tanner Mirlees

The Labour of AI Music Generation Platforms: Subjugation, Contestation, Augmentation

The idea that new technology will totally deskill and automate the labour of creating music is a longstanding dystopian trope in science fiction. Backed by global venture capital and used by millions, AI music generation platforms such as SUNO and Udio now appear to bring that trope to life. These platforms allow users to swiftly prompt, remix, and share songs across every genre, while reshaping the industrial conditions under which music has traditionally been conceived, composed, recorded, produced and released. With millions of AI-generated songs now flooding Spotify and Apple, the line between human music creation and machine music generation is blurred. Against this backdrop, salient questions come to mind: which occupational roles in the music industry risk being deskilled, displaced, or devalued by AI music generation platforms? How are music industry workers being subjugated by AI platforms, and, contesting and adapting them in their labour processes? What new forms of human–machine-labour (HML) are emerging as workers integrate AI into music creation? To address these questions, I contextualize AI music platforms within the longer history of technological development in the music industry and then share a critical case study of SUNO. I advance three claims: first, generative AI firms subjugate music workers; second, workers actively contest AI firms; and third, workers also adopt AI to augment their labour. I conclude the presentation by theorizing “generative labour” and human–machine labour (HML) in the music industry. Overall, the impact of AI platforms on the music workers’ labour is neither singular nor totalizing, but multi-faceted and contested.

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