测试10种AI生成内容警示标签，发现设计影响可信度但不改变用户互动行为。
Labeling Synthetic Content: User Perceptions of Warning Label Designs for AI-generated Content on Social Media
- 设计10种不同颜色、图标、位置和细节的警示标签进行对比实验
- 有标签时用户更相信内容是AI生成，但信任度因设计而异
- 政治与娱乐类内容互动差异大，标签未显著影响点赞评论分享
本研究探讨了社交媒体上针对AI生成内容（如深度伪造）的警示标签设计的有效性。我们设计并评估了十种在情感倾向、色彩/图标、位置和细节程度上不同的标签样本。通过包含911名参与者和一个对照组的实验，考察了用户对内容真实性判断、对标签的信任度以及社交互动感知。结果显示，标签显著提升了用户对内容为AI生成的信念，但对标签的信任度随设计不同而有明显差异。尽管如此，标签并未显著改变用户的互动行为（如点赞、评论、分享）。不过，内容类型存在显著差异：政治类和娱乐类内容的互动行为受标签影响更大。该研究为人机交互领域定义了标签设计空间，并提供了实证支持，以战略性使用标签降低合成媒体风险。
原文摘要 · Abstract (English)
In this research, we explored the efficacy of various warning label designs for AI-generated content on social media platforms e.g., deepfakes. We devised and assessed ten distinct label design samples that varied across the dimensions of sentiment, color/iconography, positioning, and level of detail. Our experimental study involved 911 participants randomly assigned to these ten label designs and a control group evaluating social media content. We explored their perceptions relating to 1. Belief in the content being AI-generated, 2. Trust in the labels and 3. Social Media engagement perceptions of the content. The results demonstrate that the presence of labels had a significant effect on the users belief that the content is AI generated, deepfake, or edited by AI. However their trust in the label significantly varied based on the label design. Notably, having labels did not significantly change their engagement behaviors, such as like, comment, and sharing. However, there were significant differences in engagement based on content type: political and entertainment. This investigation contributes to the field of human computer interaction by defining a design space for label implementation and providing empirical support for the strategic use of labels to mitigate the risks associated with synthetically generated media.
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