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<p>Generative AI in music (GAIM) technologies are rapidly transforming music production, yet little is known about how working musicians perceive and respond to these changes. This study presents findings from in-depth interviews with 43 musicians, spanning diverse genres, professional roles and experience with music technology. Our analysis, informed by a reflexive thematic analysis approach, suggests complex tensions between perceived benefits and risks of GAIM adoption. Key themes were generated around tensions between (i) fear of reduced job opportunities for professional musicians and appreciation of the potential of AI to make individual musicians more independent and productive; (ii) fear about the exploitation of artists’ work and benefits of open music exchanges; (iii) fear that AI will exacerbate inequities and recognition of AI’s potential to increase access to music production. Our findings highlight the need for careful consideration of justice and fairness in GAIM development and deployment, suggesting that different types of GAIM use (from assistant to replacement) carry distinct ethical implications. This work provides a foundation for understanding how GAIMs can be integrated into music production while respecting artists’ rights and creative agency.</p>

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Musicians’ ethical concerns about AI: an interview study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月14日

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  • Jonathan Herington,
  • Raffaella Borasi,
  • Benjamin J. Guerrero,
  • David E. Miller,
  • Blaire Koerner,
  • Yu Jung Han,
  • Zenon Borys,
  • Rachel Roberts

摘要

Generative AI in music (GAIM) technologies are rapidly transforming music production, yet little is known about how working musicians perceive and respond to these changes. This study presents findings from in-depth interviews with 43 musicians, spanning diverse genres, professional roles and experience with music technology. Our analysis, informed by a reflexive thematic analysis approach, suggests complex tensions between perceived benefits and risks of GAIM adoption. Key themes were generated around tensions between (i) fear of reduced job opportunities for professional musicians and appreciation of the potential of AI to make individual musicians more independent and productive; (ii) fear about the exploitation of artists’ work and benefits of open music exchanges; (iii) fear that AI will exacerbate inequities and recognition of AI’s potential to increase access to music production. Our findings highlight the need for careful consideration of justice and fairness in GAIM development and deployment, suggesting that different types of GAIM use (from assistant to replacement) carry distinct ethical implications. This work provides a foundation for understanding how GAIMs can be integrated into music production while respecting artists’ rights and creative agency.