<p>This paper examines the relationship between artificial intelligence, contemporary artistic production and content creation through an intersectional feminist framework, arguing that AI operates as a reflective system that reproduces and amplifies existing social, economic, and cultural biases. Beginning with examples of AI artistic collaborations such as 'What I Saw Before the Darkness', and 'Théâtre D'opéra Spatial' the research investigates how generative AI exposes underlying tensions surrounding creativity, authorship, labour, and representation. The study critically engages with the principle of “Garbage In, Garbage Out” as a governing logic of AI training. Through case studies of art competition controversies, interviews with industry professionals, and experimental comparisons between AI-generated and human-curated gallery representations, the thesis demonstrates that current AI models are limited in their ability to produce novel aesthetics, instead privileging the replication of established and commercially legible styles. Central to the analysis is AI’s entanglement with techno-patriarchal and capitalist structures. The research shows how AI art accelerates pre-existing inequities, including the appropriation of intellectual property from marginalised artists, the reinforcement of Eurocentric beauty standards, and the commodification of gendered and sexualised imagery. These dynamics are situated within broader discussions of platform economies, copyright ambiguity, environmental cost, and labour displacement. The thesis concludes by arguing that AI is not an autonomous creative agent but an extension of human decision-making, calling for ethically grounded development practices that prioritise accountability, artist participation, and social responsibility.</p>

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Garbage in, garbage out? How the monster of AI art reflects human fault, bias, and capitalism in contemporary culture

  • Amber Coen Collins

摘要

This paper examines the relationship between artificial intelligence, contemporary artistic production and content creation through an intersectional feminist framework, arguing that AI operates as a reflective system that reproduces and amplifies existing social, economic, and cultural biases. Beginning with examples of AI artistic collaborations such as 'What I Saw Before the Darkness', and 'Théâtre D'opéra Spatial' the research investigates how generative AI exposes underlying tensions surrounding creativity, authorship, labour, and representation. The study critically engages with the principle of “Garbage In, Garbage Out” as a governing logic of AI training. Through case studies of art competition controversies, interviews with industry professionals, and experimental comparisons between AI-generated and human-curated gallery representations, the thesis demonstrates that current AI models are limited in their ability to produce novel aesthetics, instead privileging the replication of established and commercially legible styles. Central to the analysis is AI’s entanglement with techno-patriarchal and capitalist structures. The research shows how AI art accelerates pre-existing inequities, including the appropriation of intellectual property from marginalised artists, the reinforcement of Eurocentric beauty standards, and the commodification of gendered and sexualised imagery. These dynamics are situated within broader discussions of platform economies, copyright ambiguity, environmental cost, and labour displacement. The thesis concludes by arguing that AI is not an autonomous creative agent but an extension of human decision-making, calling for ethically grounded development practices that prioritise accountability, artist participation, and social responsibility.