在线标记人工智能生成的媒体
Chloe Wittenberg1, Ziv Epstein2,3, Gabrielle Péloquin-Skulski4
1Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
PNAS nexus
|June 16, 2025
概括
标记人工智能生成的图像可以减少对错误信息的信念. 然而,简单地说内容是人工智能生成的,对用户参与潜在的误导性帖子的影响很小.
科学领域:
- 人工智能的人工智能
- 媒体研究 媒体研究
- 心理学 心理学 心理学
背景情况:
- 生成性人工智能的进步引发了对视听错误信息的担忧.
- 政策制定者和科技公司正在推动对人工智能产生的媒体进行标签.
- 不同的标签策略的有效性仍然不清楚.
研究的目的:
- 评估基于人工智能生成的内容的基于过程的与基于危害的标签.
- 评估标签对观众信仰和行为意图的影响.
- 确定在线人工智能媒体最有效的标签策略.
主要方法:
- 两项预先注册的调查实验,共有7,579名美国参与者.
- 专注于误导性,人工智能生成的图像.
- 不同的标签策略的比较:基于过程和基于危害的.
主要成果:
- 所有测试的标签都显著降低了参与者对所提出的索赔的信念.
- 基于过程的标签 (识别人工智能生成) 对参与度的影响很小.
- 基于危害的标签显示了对影响信仰和意图的更大潜力.
结论:
- 标记人工智能产生的媒体可以减轻对错误信息的信念.
- 基于过程的标签本身不足以制与误导性内容的接触.
- 标签策略的组合可能是必要的,以有效控制错误信息.
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