深伪视频侵犯了个人对自身形象使用权限的控制权，即使未造成实际伤害。
Deepfakes at Face Value: Image and Authority
- 从身份治理权角度解释深伪内容为何错误，非仅因危害或利益侵害。
- 提出算法征用身份是侵权核心，滥用生物特征生成影像属越界行为。
- 区分艺术创作与算法模拟，明确合法与非法使用的界限。
深伪技术通过深度学习方法将某人的形象叠加或生成于已有音视频之上。现有研究多聚焦于深伪造成的损害或对非规范性权益的侵犯，但无法解释其在无实际伤害或未损害其他权益时为何仍属错误。本文指出被忽视的关键理由：深伪会削弱我们对自身形象合理使用及身份治理的正当权利。当深伪利用我们的生物特征作为生成资源，僭越了我们对自身行动来源的控制权时，即构成不正当行为。我们拥有反对算法征用身份的特定权利。论文进一步区分可接受的形象借用（如艺术描绘）与不当的算法仿真，明确该权利的适用边界。
原文摘要 · Abstract (English)
Deepfakes are synthetic media that superimpose or generate someone's likeness on to pre-existing sound, images, or videos using deep learning methods. Existing accounts of the wrongs involved in creating and distributing deepfakes focus on the harms they cause or the non-normative interests they violate. However, these approaches do not explain how deepfakes can be wrongful even when they cause no harm or set back any other non-normative interest. To address this issue, this paper identifies a neglected reason why deepfakes are wrong: they can subvert our legitimate interests in having authority over the permissible uses of our image and the governance of our identity. We argue that deepfakes are wrong when they usurp our authority to determine the provenance of our own agency by exploiting our biometric features as a generative resource. In particular, we have a specific right against the algorithmic conscription of our identity. We refine the scope of this interest by distinguishing between permissible forms of appropriation, such as artistic depiction, from wrongful algorithmic simulation.
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