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.

本研究针对生成AI模型中对酷儿艺术家参与的忽视进行了探讨，揭示了酷儿群体在使用这些技术时面临的嵌入性常规价值，例如超积极和反性。研究显示，参与者开发了多种策略克服模型的局限性，并在该过程中发现了这些高度常规化技术的价值，为生成AI的未来应用提供了有益的启示。

非直线化生成AI：酷儿艺术家如何浮现和挑战生成AI模型的常规性