Agency and authorship in AI art: Transformational practices for epistemic troubles

Abstract

The integration of Generative AI into artistic practices is not only expanding the possibilities for creative expression but also challenging foundational concepts such as agency and authorship. Combining Agential Realism and Speech Act Theory, this paper presents a case study involving three internationally recognised artists with extensive experience using text and image-based models. It combines in-depth interviews with critical readings of selected artworks to explore how generative AI Art emerges from the intra-actions between artists, data, and algorithms. Our contribution unfolds along two complementary directions. Firstly, we engage with epistemological debates by conceptualising agency and authorship as relational and distributed phenomena. Secondly, we challenge the notion of AI as a mere tool and advocate for design approaches that foreground shared authorship. By focusing on studio-level practices, this paper offers situated insights into artist–AI interaction, expands our understanding of de-individualised knowledge production, and points toward systems that support responsible co-creation.