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Are We All Musicians Now? Authenticity, Musicianship, and AI Music Generator Suno
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This paper examines the authenticity of music and the musicianship related to Suno, an artificial intelligence (AI) music generator. Suno was introduced in late 2023, and its latest version (v5.5) was released on March 26, 2026. The platform was developed by AI experts and musicians based in Cambridge, MA. Suno does not engage in conventional practices of composing, songwriting, performing, or recording. Instead, it generates music from user prompts via a text/audio/image/video-to-music interface. Suno is often presented as democratizing music production by enabling anyone to become a “musician.” However, the absence of a conventional “real” artist or author (auteur) responsible for these music productions raises questions about how different actors perceive their authenticity. Based on online observation, a qualitative interpretive approach, and a “partial insider” position, this paper explores the possibilities of authenticating AI-generated music, its implications for the changing nature of musicianship and music scenes. Finally, it argues that AI-generated music can achieve authenticity without conventional musicianship, allowing for the emergence of a new, albeit contested, form of musicianship.
Title: Are We All Musicians Now? Authenticity, Musicianship, and AI Music Generator Suno
Description:
This paper examines the authenticity of music and the musicianship related to Suno, an artificial intelligence (AI) music generator.
Suno was introduced in late 2023, and its latest version (v5.
5) was released on March 26, 2026.
The platform was developed by AI experts and musicians based in Cambridge, MA.
Suno does not engage in conventional practices of composing, songwriting, performing, or recording.
Instead, it generates music from user prompts via a text/audio/image/video-to-music interface.
Suno is often presented as democratizing music production by enabling anyone to become a “musician.
” However, the absence of a conventional “real” artist or author (auteur) responsible for these music productions raises questions about how different actors perceive their authenticity.
Based on online observation, a qualitative interpretive approach, and a “partial insider” position, this paper explores the possibilities of authenticating AI-generated music, its implications for the changing nature of musicianship and music scenes.
Finally, it argues that AI-generated music can achieve authenticity without conventional musicianship, allowing for the emergence of a new, albeit contested, form of musicianship.
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