Human detection of AI-generated faces and voices is not domain-general

Source record ivory-2026-faces-voices-domain · 2026 · Scientific Reports
Evidence tier: B (peer-reviewed-journal) · Verification: verified-fulltext
Bottom line: Faces were detected above chance (65.48%) but cloned voices barely (53.95%); face and voice skill were not significantly related, and confidence tracked accuracy for faces but not voices.

Citation

Matthew R. Ivory, Carolyn McGettigan, Helen E. Nuttall, Sophie J. Nightingale (2026). Human detection of AI-generated faces and voices is not domain-general. Scientific Reports, 16, 28639. https://doi.org/10.1038/s41598-026-59364-3

Verification entry (identifiers, resolvers, claims with source locations): /data/citations.json#ivory-2026-faces-voices-domain

Study design

Field	Value
Design	Preregistered within-participant study: real-vs-synthetic classification of faces and of voices, each followed by confidence ratings; signal detection (d', c) and type-II AUROC for metacognition
Modality	image-face, audio
Stimuli	20 FFHQ real faces + 20 Adobe Firefly (diffusion) faces; 40 VCTK real speakers and ElevenLabs Instant Voice Cloning clones (each listener heard 20 real + 20 clones of other speakers)
Participants (N)	172
N detail	200 recruited on Prolific, 172 analysed; ages 18-30
Topics	human-detection, voice, voice-clone, confidence, individual-differences

Results

Metric	Value	Note
Face accuracy (diffusion faces)	65.48% [95% CI 63.75, 67.21]	d' = .85
Voice-clone accuracy	53.95% [95% CI 52.64, 55.27]	d' = .20; 35.47% of participants at or below chance (faces 12.80%)
Face d' predicting voice d'	beta = .21, p = .053, R² = .02	not significant; no evidence of a domain-general ability
Response criterion c	faces -.24; voices -.07	both biased toward 'real'
Metacognitive AUROC	faces .59 (above chance); voices .48 (below chance)	confidence informative for faces only

Moderators

Skin smoothness was used as an AI cue for faces and predicted accuracy; breathing predicted voice accuracy

Limitations

Task difficulty not matched across modalities
Static faces and short clips only, single play
Participants warned that stimuli could be synthetic
Young sample (18-30)

Cited in

MR-0001: Human Detection of Deepfakes: Accuracy, Bias, Confidence, and Training
MR-0003: Voice Clones and Synthetic Speech: How Well Do People Detect Them?

Verification

Field	Value
Status	`verified-fulltext`
Compiler confidence	high
Checked on	2026-10-12
Via	nature.com full text, doi:10.1038/s41598-026-59364-3