这是真的吗? 机器和人类对深度假冒的易感性
Didem Pehlivanoglu1,2, Mengdi Zhu3,4, Jialong Zhen5
1Department of Psychology, University of Florida, 945 Center Dr, Gainesville, FL, 32603, USA. dpehlivanoglu@ufl.edu.
Cognitive research: principles and implications
|January 7, 2026
概括
这项研究比较了人类和机器的深度假冒检测. 机器在静态图像方面表现出色,但人类在动态视频方面表现出色,在分析思维和互联网技能的帮助下.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 人与计算机的交互
- 心理学 心理学 心理学
背景情况:
- 深度假冒技术,使用深度生成方法,创建现实的合成媒体,对算法和人类的检测提出了挑战.
- 深度假冒日益复杂,需要对不同模式 (静态图像与动态视频) 的检测能力和局限性进行彻底了解.
研究的目的:
- 为了调查深度假冒检测中的机器错误分类错误.
- 确定影响人类深度假冒检测性能的心理机制.
- 为了比较人类和机器在分类真实与深度假冒媒体方面的准确性和信心.
主要方法:
- 研究1:使用真实和深度假的静态面部图像来评估机器和人类分类的准确性,信心和偏见.
- 研究2:使用动态视频刺激来比较机器和人类的性能,分析分析思维,影响和互联网技能等因素.
主要成果:
- 机器在静态图像深度假冒检测方面表现出色,而人类则扎,表现出机会级准确性和真相偏差.
- 对于动态视频,机器性能下降到接近偶然的水平,功能分类差,谎言偏差.
- 人类在视频深度假冒检测方面表现优于机器,与分析思维相关的准确性更高,积极影响较低,互联网技能更强.
结论:
- 人类和机器的深度假冒检测能力在媒体类型之间存在显著差异,人类在动态视频分析中表现出优势.
- 了解心理因素对于增强人类深度假冒检测至关重要,补充机器学习方法.
- 调查结果为人类-人工智能合作策略提供了信息,以打击日益严重的深度假冒威胁,优化检测系统.
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