miscellaneous-5
Human Detection of Deepfakes
3260 papers • 126 benchmarks • 313 datasets
The task of detecting deepfake stimuli, as given to human participants in a statistical study. Methodologies should ideally include a-priori power analysis (e.g. using the GPower software) to calculate the sample size of human participants that would be sufficient to detect the presence of a main effect of a specified effect size.
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Testing Human Ability To Detect Deepfake Images of Human Faces
Bennett Kleinberg, Sergi D. Bray, Shane D. Johnson•Tue Dec 06 2022
Assessment of human ability to identify image deepfakes of human faces from a pool of non-deepfake images and the effectiveness of some simple interventions intended to improve detection accuracy is interpreted as suggesting that there is a need for an urgent call to action to address this threat.
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