# Composers' Evaluations of an AI Music Tool: Insights for Human-Centred Design

arXiv: https://arxiv.org/abs/2412.10968 · HTML: https://mlsanity.com/paper/2412.10968/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 26 references that are in the map.
- First posted on arXiv 14 Dec 2024.

## Builds on (most cited first, 4 of 4)

- [The Challenge of Crafting Intelligible Intelligence](https://mlsanity.com/paper/1803.04263/) (2018)
- [The Machine Learning Algorithm as Creative Musical Tool](https://mlsanity.com/paper/1611.00379/) (2016)
- [Adoption of AI Technology in the Music Mixing Workflow: An Investigation](https://mlsanity.com/paper/2304.03407/) (2023)
- [JAZZVAR: A Dataset of Variations found within Solo Piano Performances of Jazz Standards for Music Overpainting](https://mlsanity.com/paper/2307.09670/) (2023)

## Abstract (arXiv)

We present a study that explores the role of user-centred design in developing Generative AI (GenAI) tools for music composition. Through semi-structured interviews with professional composers, we gathered insights on a novel generative model for creating variations, highlighting concerns around trust, transparency, and ethical design. The findings helped form a feedback loop, guiding improvements to the model that emphasised traceability, transparency and explainability. They also revealed new areas for innovation, including novel features for controllability and research questions on the ethical and practical implementation of GenAI models.