深度假冒检测有和没有内容警告
Andrew Lewis1, Patrick Vu2, Raymond M Duch1
1University of Oxford, Oxford, UK.
Royal Society open science
|November 29, 2023
概括
深度假冒的检测是具有挑战性的,即使有警告. 人们很难识别人工智能生成的假视频,这表明需要更好的适度策略来处理不真实的内容.
科学领域:
- 计算机科学 计算机科学
- 媒体研究 媒体研究
- 心理学 心理学 心理学
背景情况:
- 深度假冒技术,利用深度学习人工智能,创建现实的假视频,给内容调节带来挑战.
- 不真实的内容的扩散需要了解公众的感知和检测能力.
研究的目的:
- 通过实验测量个体在检测高质量的Deepfake视频方面的警觉性和准确性.
- 评估内容警告对深度假冒识别的影响.
主要方法:
- 进行了一项实验,让参与者看到真实视频和深度假视频.
- 测试了两种条件:没有警告的自然暴露和关于深度假冒存在的警告的暴露.
主要成果:
- 在没有警告的情况下,接触深度假冒的参与者在检测异常 (32.9%) 与对照组 (34.1%) 相比没有显著差异.
- 有一个警告,只有21.6%正确识别了单个深度假冒,其他人错误地将真实的视频归类为假冒.
结论:
- 个人在自然环境中对深度假冒的基本意识较低.
- 内容警告不能可靠地改善深度假冒的检测,甚至可能导致对真实的内容的错误识别.
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