Abstract
AbstractRecent advances in technology for hyper-realistic visual and audio effects provoke the concern that deepfake videos of political speeches will soon be indistinguishable from authentic video. We conduct 5 pre-registered randomized experiments with N = 2215 participants to evaluate how accurately humans distinguish real political speeches from fabrications across base rates of misinformation, audio sources, question framings with and without priming, and media modalities. We do not find base rates of misinformation have statistically significant effects on discernment. We find deepfakes with audio produced by the state-of-the-art text-to-speech algorithms are harder to discern than the same deepfakes with voice actor audio. Moreover across all experiments and question framings, we find audio and visual information enables more accurate discernment than text alone: human discernment relies more on how something is said, the audio-visual cues, than what is said, the speech content.
Funder
TruePic Research Grant, Kellogg School of Management, MIT Media Lab
Publisher
Springer Science and Business Media LLC
Reference107 articles.
1. Hancock, J. T. & Bailenson, J. N. The social impact of deepfakes. Cyberpsychol. Behav. Soc. Netw. 24, 149–152 (2021).
2. Chesney, B. & Citron, D. Deep fakes: A looming challenge for privacy, democracy, and national security. Calif. L. Rev. 107, 1753 (2019).
3. Paris, B. & Donovan, J. Deepfakes and Cheap Fakes. United States of America: Data & Society (2019).
4. Leibowicz, C., McGregor, S. & Ovadya, A. The Deepfake Detection Dilemma: A Multistakeholder Exploration of Adversarial Dynamics in Synthetic Media (2021).
5. Agarwal, S. et al. Protecting World Leaders Against Deep Fakes. In CVPR workshops, vol. 1 (2019).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献