Deepfake Research Index
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As good as a coin toss: Human detection of AI-generated images, videos, audio, and audiovisual stimuli

Source record cooke-2024-coin-toss · 2025 · Communications of the ACM
Evidence tier: B (peer-reviewed-journal) · Verification: verified-abstract (compiler confidence: high)
Bottom line: Mean detection was close to 50% chance; accuracy dropped for any synthetic content, foreign-language content, single-modality stimuli and synthetic images of faces; prior knowledge of synthetic media did not help; older participants did worse.

Citation

Di Cooke, Abigail Edwards, Sophia Barkoff, Kathryn Kelly (2025). As good as a coin toss: Human detection of AI-generated images, videos, audio, and audiovisual stimuli. Communications of the ACM, 68, 100-109. https://doi.org/10.1145/3729417

Verification entry (identifiers, resolvers, claims with source locations): /data/citations.json#cooke-2024-coin-toss

Study design

Field Value
Design Online US survey; mixed-modality stimuli (images, audio, video, audiovisual)
Modality image-face, video, audio, audiovisual
Stimuli Mixed 2023-era generators
Participants (N) 1276
N detail preprint first posted March 2024 (arXiv 2403.16760)
Topics human-detection, modality

Results

Metric Value Note
Mean detection close to chance (50%) abstract gives no exact figure
Lower accuracy when stimulus contains synthetic content, foreign language, single modality, or a synthetic human face
Mixed-authenticity audiovisual harder
Prior knowledge of synthetic media no significant effect
Age older participants performed worse

Limitations

Cited in

Verification

Field Value
Status verified-abstract
Compiler confidence high
Checked on 2026-10-07
Via arXiv 2403.16760 abstract page (journal ref CACM 68, 2025)

Values on this page have not all been checked against the full text. Confirm them against the primary source before high-stakes use.