"I Just Don't Want My Work Being Fed Into The AI Blender": Queer Artists on Refusing and Resisting Generative AI
Jordan Taylor, Joel Mire, Alicia DeVrio, Maarten Sap, Haiyi Zhu + 1 more
TLDR
This paper explores how queer artists perceive and resist generative AI, highlighting tensions between their relational art practices and GenAI's anti-relational nature.
Key contributions
- Interviews with 15 queer artists reveal their perspectives on generative AI's impact.
- Identifies tensions between relational queer art practices and GenAI's anti-relational development.
- Details queer artists' strategies for refusing and resisting GenAI use and development.
- Discusses how CSCW researchers can support queer artists by challenging dominant AI imaginaries.
Why it matters
This paper is crucial for understanding the social and ethical implications of generative AI on marginalized artistic communities. It highlights the need for AI developers and researchers to consider diverse perspectives and support world-building that resists dominant AI narratives.
Original Abstract
Art-making is a collective social activity through which queer people engage in political resistance, develop identities, archive queer memory, and form community. However, in recent years, generative AI has disrupted queer artistic communities. Through 15 semi-structured interviews, we examine how queer artists are making sense of the encroachment of GenAI into their art worlds. Our findings surface significant tensions between the relationality of our participants' queer art practices and the perceived anti-relationality of GenAI development and use. We detail how our participants refuse and resist GenAI use and development in response and highlight the limited role our participants saw for GenAI within art-making, such as the queer aesthetic potential of surreal image models. Drawing on queer theory, we discuss how CSCW researchers might support queer artists by refusing dominant AI imaginaries and supporting queer world-building.
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