mlsanityData to 14 Oct 2026

Opening Musical Creativity? Embedded Ideologies in Generative-AI Music Systems

arXiv 2508.08805 ↗First posted 12 Aug 2025cs.SD cs.AI cs.HCcited by 4

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Abstract (arXiv)

AI systems for music generation are increasingly common and easy to use, granting people without any musical background the ability to create music. Because of this, generative-AI has been marketed and celebrated as a means of democratizing music making. However, inclusivity often functions as marketable rhetoric rather than a genuine guiding principle in these industry settings. In this paper, we look at four generative-AI music making systems available to the public as of mid-2025 (AIVA, Stable Audio, Suno, and Udio) and track how they are rhetoricized by their developers, and received by users. Our aim is to investigate ideologies that are driving the early-stage development and adoption of generative-AI in music making, with a particular focus on democratization. A combination of autoethnography and digital ethnography is used to examine patterns and incongruities in rhetoric when positioned against product functionality. The results are then collated to develop a nuanced, contextual discussion. The shared ideology we map between producers and consumers is individualist, globalist, techno-liberal, and ethically evasive. It is a 'total ideology' which obfuscates individual responsibility, and through which the nature of music and musical practice is transfigured to suit generative outcomes.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 5 of its 71 references that are in the map. First posted on arXiv 12 Aug 2025.

Builds on

5 of 71 references.

References · 5

  1. 2023Generative AIcited by 120
  2. 2023Exploring how a Generative AI interprets musiccited by 4
  3. 2025Music for All: Representational Bias and Cross-Cultural Adaptability of Music Generation Modelscited by 4
  4. 2025Exploring the Needs of Practising Musicians in Co-Creative AI Through Co-Designcited by 3
  5. 2023AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learningcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.