揭露AI换脸技术如何被滥用生成成人非自愿裸照，揭示治理漏洞。
The Malicious Technical Ecosystem: Exposing Limitations in Technical Governance of AI-Generated Non-Consensual Intimate Images of Adults
- 从受害者视角分析技术治理失效，识别出恶意技术生态
- 发现近200款一键生成工具与开源换脸模型构成威胁体系
- 指出当前监管框架存在根本性缺陷，适合关注AI伦理与安全的研究者
本文采用以幸存者为中心的方法，剖析社会技术治理在防范成人非自愿生成亲密图像（AIG-NCII，俗称‘深度伪造色情’）中的作用。研究识别出一个‘恶意技术生态系统’（MTE），包含开源人脸替换模型及近200款‘裸化’软件，使非技术人员可在数分钟内生成AIG-NCII。基于美国国家标准与技术研究院（NIST AI 100-4）报告所反映的当前合成内容治理方法，本文揭示现有实践对成人AIG-NCII的MTE缺乏有效规制，并指出其中存在的错误假设。
原文摘要 · Abstract (English)
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.
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