Methodological Considerations of Digital Ethnographic Studies in the AI Music Field

As music generation systems driven by artificial intelligence (AI) gain popularity, understanding how users engage with these platforms is essential for examining the emerging practices surrounding AI music. This paper reflects on our ongoing digital ethnographic research conducted on the AI music platforms Suno and Boomy and their corresponding Discord discussion forums. We propose an AI music landscape that illustrates the interaction between users, platforms, and music-related activities, and examine two user groups: Boomy users who create tracks, and Suno users who create AI metal music. We critically analyse the challenges we encounter throughout the process regarding accessing and gatekeeping, trust-building, and the blurred positionality of researchers. We reflect on our experiences and propose methods for immersion and adaptation in AI music research. This study contributes to the refinement of digital ethnographic methodologies for the diverse field of AI music and encourages ongoing reflection on research strategies in AI music studies.