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Commercial Generative Music: A Practice-Based Study of AI Music Production

Oliver Bown, Associate Professor in Computational Creativity and Generative Music & Art, University of New South Wales, Sydney

This project investigates the dramatic rise of commercial AI music enterprises, particularly AI music startups. It looks at the multiple value propositions being put forward by these enterprises, and the technological strategies and problems being encountered by companies that must manage the dual tasks of technological innovation and building and maintaining a viable product. The project asks: how is innovation and transformation of musical practices driven in these complex sociotechnical systems?

To address this question I examine the myriad interplays between technological and social elements within a number of AI music commercial enterprises. In each case, the company must navigate between the development of a product and the development of a user base, where both are relatively underexplored: we don’t know how well the software will do its intended job, what architectures and interface designs will be successful, what patterns of use will emerge amongst users, and what types of role AI will play in the resulting products. 

In such cases companies must balance the need to engage in an exploratory search for solutions with the need to support and maintain an existing product. Following theories of innovation and creativity, the role of blind, exploratory search for new designs and use cases in these companies’ search for product-market-fit is a particular point of interest. I look at how companies take risks and respond in agile ways to user trends and new technology discoveries, but above all, at the extent to which they simply explore hunches and unformed ideas. In relation to this I look at how the technology itself pushes and pulls its developers through its own internal logic, and consider how these companies’ product innovations take an emergent form. I consider whose or what agency is involved in driving this emergence. How do companies’ narratives of value around AI’s potential to transform music combine the elements of clear product vision and space to allow blind search?

A consequent and more speculative question is the extent to which such efforts may be driving an intensifying industrialisation of music creation, one that is taking entirely new forms, and how this might be seen as part of longer term processes of technology and change.