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Generative Artificial Intelligence (GenAI) has the potential to change the landscape of music creativity through new working practices and tools to assist in all aspects of music making. However, acceleration of this technology has also prompted concerns relating to a variety of ethical issues. Discourse surrounding Artificial Intelligence (AI) has been limited to conversations pertaining to Artificial General Intelligence (AGI) with limited consultation with creative practitioners surrounding the myriad ethical concerns and disruption to current working practices. Adoption of a human-centered approach to AI development has the potential to create a meaningful musical collaborator which may assist in idea generation and provide creative inspiration. This study centres the concept of musicking to identify participants to gather data pertaining to views of Generative AI as a creative collaborator for music composition. Findings indicate musicians are already incorporating AI within their practice as a creative tool, aiding with composition and production tasks. However, concerns abound relating to economic impact, devaluing musicianship and authenticity. Harnessing the positive potential of the technology outlined in this paper will require greater co-creation with musicians to fulfil a human-centered musical collaborator.
Author (s): Allen, Becky; Mo, Ronald
Affiliation:
University of Sunderland; University of Sunderland
(See document for exact affiliation information.)
Publication Date:
2025-09-02
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Session subject:
Artificial Intelligence and Machine Learning for Audio
Permalink: https://aes2.org/publications/elibrary-page/?id=22998
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Allen, Becky; Mo, Ronald; 2025; Perceptions of an Artificial Intelligence Musical Collaborator [PDF]; University of Sunderland; University of Sunderland; Paper 9; Available from: https://aes2.org/publications/elibrary-page/?id=22998
Allen, Becky; Mo, Ronald; Perceptions of an Artificial Intelligence Musical Collaborator [PDF]; University of Sunderland; University of Sunderland; Paper 9; 2025 Available: https://aes2.org/publications/elibrary-page/?id=22998