In this paper, we adopt a survivor-centered approach to locate and dissect the role of sociotechnical AI governance in preventing AI-Generated Non-Consensual Intimate Images (AIG-NCII) of adults, colloquially known as "deep fake pornography." We identify a "malicious technical ecosystem" or "MTE," comprising of open-source face-swapping models and nearly 200 "nudifying" software programs that allow non-technical users to create AIG-NCII within minutes. Then, using the National Institute of Standards and Technology (NIST) AI 100-4 report as a reflection of current synthetic content governance methods, we show how the current landscape of practices fails to effectively regulate the MTE for adult AIG-NCII, as well as flawed assumptions explaining these gaps.

本研究关注如何通过以生存者为中心的方法来应对AI生成的非自愿亲密影像（AIG-NCII），即“深度伪造色情”的治理问题。通过识别和分析包括开源人脸交换模型及近200种“裸体化”软件的“恶意技术生态系统”，本研究揭示了当前技术治理方法在有效监管该生态系统方面的失败及其根本假设的缺陷。

恶意技术生态系统：揭示AI生成的非自愿亲密影像技术治理的局限性