In the style of… Appropriation, AI, and Unstable Authorship
This research examines how fine artists use cinematic genre tropes and visual motifs in moving image work and photography, how authorship is conceptualised when working with techniques including appropriation and pastiche, and how working with AI-generated content complicates these issues further.
While the deliberate appropriation of existing images, styles, or motifs from other works and cultural sources is a well documented creative method, this approach appears to be an increasing aspect of works which use prompt based and generative ai systems as a tool. Rather than a deliberate critique or contextualisation of the original materials, AI image tools often recreate the visual style of individuals and movements, potentially without the intention, or the understanding of the artist making a new work. In the context of a technologically engaged visual practice, I’m interested in how artists approach copying, pastiche, homage, remix, appropriation, ripping, quotation and recontextualisation, and where the differences between these practices lie.
This research spans appropriation theory, cinematic genre studies, AI aesthetics, theories of voice and style, and questions of dissemination and communal reception. It is grounded in a personal arts practice characterised by what might be called a magpie relationship with style, constitutively inconsistent, moving between registers without claiming (or necessarily desiring) mastery of any. This paper describes the early stages of a practice based PhD in Arts and Computational Technology at Goldsmiths UoL.
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Katie Tindle is a multidisciplinary artist, researcher and founder member of the collective, In-grid. Her recent research focuses on how re/use of tropes and genre conventions function in the context of a critically technologically engaged arts practice. She is a lecturer in Computational Arts at Goldsmiths, University of London, where she is also currently a Doctoral Candidate and member of the Process Iteration Network. More info: https://katietindle.co.uk/ https://in-grid.io/