A study on musicians’ interaction with computer-generated and automated music systems
Music generated using artificial intelligence (AI) technology has received considerable public attention in recent years. The convergence of massive data and computational resources, funding from private circles, and considerable efforts from academic engineering environments have made machine learning (ML) techniques commercially exploitable. Today, these technologies are moving into mainstream and commercial music ecosystems and can be used for the creation, production, and distribution of musical content. However, the public response to AI music is indecisive. While some claim that these technologies will democratize music production and composition, others claim that they will, on the contrary, be detrimental to it.
This project arose from an open question: What is musical expertise when significant parts of artistic processes can be generated and automated through computer-based systems? Can we understand the commercial breakthrough of AI music as a “critical moment” (Boltanski and Thévenot), where tacit knowledge and values become explicit? In that case, what defines a “talented” musician and composer in digitalized musical ecosystems? And what forms of musical knowledge are distributed in the new digital technologies?
While some public debates on AI music have explored subjects such as intellectual property (such as legal ownership), the aim of this project is to investigate how AI music technologies are shaping and are in turn shaped by artistic practices and expertise. Throughout the history of modern music, artists have used technological innovations in creative and unexpected ways. An urgent question seems to be, therefore, how musicians make use of AI technologies and constitute this human-machine interaction as an artistic and aesthetic interaction. How do they negotiate their expertise, creativity, and agency in collaboration with computer-generated automated music systems?
Following musical knowledge production inside both public and private Norwegian music academies, I aim to study socio-material processes leading to new musical expertise. I will focus on the use of AI technologies, but first and foremost, I will understand musical knowledge as something produced and distributed in material assemblages of instruments, speakers, notation systems, codes, publics, and bodies. Finally, this project highlights fundamental questions regarding the interaction between music, science, and technology. Artistic, scientific, and technological innovations are interrelated, but also simultaneously subject to ongoing negotiations between human and non-human actors.
Supervisor: Associate professor Lars E. F. Johannessen, OsloMet
Co-supervisor: Professor Yngvar Kjus, University of Oslo
