queer艺术家挑战AI模型的刻板规范，探索其在酷儿文化中的创造性使用
Un-Straightening Generative AI: How Queer Artists Surface and Challenge the Normativity of Generative AI Models
- 13位酷儿艺术家使用GPT-4和DALL-E 3开展工作坊，发现模型存在泛化正向与反性倾向的规范
- 参与者发展出绕过限制的策略，仍从高度规范化的技术中获得价值
- 呼吁以酷儿理论重构“前沿”模型认知，支持酷儿替代方案
酷儿群体常被研究视为生成式AI偏见与伤害的受害者，但其如何具体使用生成式AI，以及可能带来的赋能用途，尚待探索。本研究对13位酷儿艺术家开展工作坊，提供GPT-4与DALL-E 3访问，并组织集体意义建构活动。发现参与者因模型设计中嵌入的规范性价值（如过度积极、反性倾向）而难以使用。研究描述了参与者发展出的应对策略，尽管如此，他们仍从高度规范化的技术中找到价值。基于酷儿女性主义理论，讨论了对“前沿模型”的概念化影响，并思考FAccT研究者如何支持酷儿替代路径。
原文摘要 · Abstract (English)
Queer people are often discussed as targets of bias, harm, or discrimination in research on generative AI. However, the specific ways that queer people engage with generative AI, and thus possible uses that support queer people, have yet to be explored. We conducted a workshop study with 13 queer artists, during which we gave participants access to GPT-4 and DALL-E 3 and facilitated group sensemaking activities. We found our participants struggled to use these models due to various normative values embedded in their designs, such as hyper-positivity and anti-sexuality. We describe various strategies our participants developed to overcome these models' limitations and how, nevertheless, our participants found value in these highly-normative technologies. Drawing on queer feminist theory, we discuss implications for the conceptualization of "state-of-the-art" models and consider how FAccT researchers might support queer alternatives.
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