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Language in AI Art: Encoding, Folding and Transforming

Year: 2025
Type: article
Abstract: This article discusses four artworks that employ artificial intelligence (AI) as practice as research (PaR) by artist Garrett Lynch IRL. These are: I’m not Garrett Lynch IRL – DoppelGANger Portraits (2021), a series of Generative Adversarial Network (GAN) portraits; TheLastStraw (2021–23), a performative generative artwork for social media; Flag for States of Damage (2018), a performative mixed-reality artwork for the web and The Traveller (2024), a four-channel video installation with artefacts.The objective of the works is two-fold. Firstly, each artwork’s use of AI is distinct yet is intended to form part of a broad ongoing exploration of how networks can be transformative to art practice. The works maintain that AI is a form of network that enables emergence. Not the emergence of intelligence as defined in the field of AI, but instead in the context of art theory a manner in which artworks are expanded, extended or activated beyond their artist/author defined forms. AI as a network is therefore defined as both the generative adversarial network, the input, employed in the formation of the work and the resulting network of artist, artwork and audience that emerges when a work is expanded, extended or activated. Secondly, instrumental in facilitating AI as a network is the use of language as a combined form of encoding and performative utterance (Austin, 2018). Building on a fundamental basis of computing that all digital media is reducible to language, code, and numbers as well as a basis of communication theory that language is a social construct, the works explore language as both form of representation and communication between human and machine. Language enables a process of folding (O’Sullivan, 2005) or flipping (Sloan, 2012) of concepts, media and artefacts between ‘virtual’ and ‘real’ spaces, between digital and materialised forms. keywords: AI art, language, practice as research, networks, folding, encoding, transforming
DOI: 10.22501/hub.3012435
Language: English
Open Access status: hybrid
OpenAlex ID: W4411256121
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