mlsanityData to 14 Oct 2026

Supporting Creative Ownership through Deep Learning-Based Music Variation

arXiv 2509.25834 ↗First posted 30 Sep 2025cs.HC cs.AIcited by 1

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Abstract (arXiv)

This paper investigates the importance of personal ownership in musical AI design, examining how practising musicians can maintain creative control over the compositional process. Through a four-week ecological evaluation, we examined how a music variation tool, reliant on the skill of musicians, functioned within a composition setting. Our findings demonstrate that the dependence of the tool on the musician's ability, to provide a strong initial musical input and to turn moments into complete musical ideas, promoted ownership of both the process and artefact. Qualitative interviews further revealed the importance of this personal ownership, highlighting tensions between technological capability and artistic identity. These findings provide insight into how musical AI can support rather than replace human creativity, highlighting the importance of designing tools that preserve the humanness of musical expression.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 24 references that are in the map. First posted on arXiv 30 Sep 2025.

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8 of 24 references.

References · 8

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2023Generative artificial intelligence enhances creativity but reduces the diversity of novel contentcited by 167
  3. 2021MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Trainingcited by 89
  4. 2021Sequence-to-Sequence Piano Transcription with Transformerscited by 48
  5. 2024The Effects of Generative AI on Design Fixation and Divergent Thinkingcited by 37
  6. 2023Anticipatory Music Transformercited by 36
  7. 2025Evaluating Human-AI Interaction via Usability, User Experience and Acceptance Measures for MMM-C: A Creative AI System for Music Compositioncited by 4
  8. 2025Exploring the Needs of Practising Musicians in Co-Creative AI Through Co-Designcited by 3

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