Supporting Creative Ownership through Deep Learning-Based Music Variation

TL;DR

The paper addresses the risk that AI-generated music can erode personal artistic ownership. It assesses a musician-driven variation tool, Rhapsody Refiner, over four weeks in real-world creative settings, combining qualitative and usage data. Findings show that preserving the musician’s initial input and requiring active refinement fosters ownership of both process and artefact, while AI serves as a source of inspiration rather than a replacement for creativity. The study offers design guidance for human-centered musical AI that supports, co-creates, and maintains the humanity of musical expression.

Abstract

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.

Figures (1)

• Figure 1: Interface for Rhapsody Refiner.