Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine Learning

In the mid-2010s, media artists began developing practices using machine learning (ML) as an artistic medium. Since 2022, the rise of large generative models, the mainstreaming of AI as consumer products, and intensifying ethical disputes have reconfigured the conditions of their artistic practice. This paper aims to understand how artists working with ML over the past decade respond to these shifts, shedding light on how practices, tools, and culture co-evolve. We address this question through thematic analysis of semi-structured interviews with 30 artists active before 2020. Our findings show how artists experience narrowing aesthetics and reduced malleability of post-2020 ML systems, have diverging views on where to locate moral responsibility with large AI models, and face shifting cultural reception that challenges the legibility of their work. We map how artists envision their practice going forward and discuss those orientations with respect to HCI conversations on design and creativity.

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Published
2026-04-13
DOI
https://doi.org/10.1145/3772318.3790398
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine Learning

Téo Sanchez, Sarah Fdili Alaoui, Vaynee Sungeelee, Baptiste Caramiaux et al.
1 citations
Ethics and Social Impacts of AI
article

Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine Learning

Téo Sanchez, Sarah Fdili Alaoui, Vaynee Sungeelee, Baptiste Caramiaux, Mariya Dzhimova, Stacy Hsueh, Sarah Fdili Alaoui
article en
1 citations

Abstract

In the mid-2010s, media artists began developing practices using machine learning (ML) as an artistic medium. Since 2022, the rise of large generative models, the mainstreaming of AI as consumer products, and intensifying ethical disputes have reconfigured the conditions of their artistic practice. This paper aims to understand how artists working with ML over the past decade respond to these shifts, shedding light on how practices, tools, and culture co-evolve. We address this question through thematic analysis of semi-structured interviews with 30 artists active before 2020. Our findings show how artists experience narrowing aesthetics and reduced malleability of post-2020 ML systems, have diverging views on where to locate moral responsibility with large AI models, and face shifting cultural reception that challenges the legibility of their work. We map how artists envision their practice going forward and discuss those orientations with respect to HCI conversations on design and creativity.

Centre National de la Recherche Scientifique (FR), University of Nottingham (GB), Munich University of Applied Sciences (DE), Sorbonne Université (FR), Hochschule für Musik und Theater München (DE), Institut Systèmes Intelligents et de Robotique (FR), Ludwig-Maximilians-Universität München (DE), University of the Arts London (GB)
Microsoft Research, Agence Nationale de la Recherche
Openalex Percentile: Top 61%
Ethics and Social Impacts of AI
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