Image Quality, Not Disclosure Labels, Shapes the Credibility of Artificial Intelligence–Generated He

Generative artificial intelligence (AI) can produce photorealistic health-campaign images, and regulators ask for labels. This study tested how disclosure labels and image fidelity affect credibility and gaze. In a 2 × 3 mixed design, 155 adults viewed 12 vaccination advertisements during webcam eye tracking. Each appeared as the original photograph or a high- or low-quality AI-generated image, with or without a “Human-Made”/“AI-Generated” label (between subjects). Fidelity affected credibility (sr2 = .107). Low-quality AI images were rated less credible than original photographs (d = 0.82) and high-quality AI images (d = 0.63), whereas originals and high-quality AI images did not differ reliably. The label had no main effect and interacted with fidelity, but no simple effect survived correction. Positive attitudes towards AI predicted higher credibility only for low-quality AI images. Neither factor detectably changed gaze, and the label was looked at on 36% of trials. Image quality, not disclosure, shaped credibility.

Authors

Publication Details

Journal
Open Science Framework
Published
2026-11-08
DOI
https://doi.org/10.17605/osf.io/mbtpr
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Image Quality, Not Disclosure Labels, Shapes the Credibility of Artificial Intelligence–Generated He

Chrysanthi Nega, Panagiotis Kourtesis, Elli Rizouli, Alkistis Kotsafti-Apergi4
2 links
Open Science Framework
Misinformation and Its Impacts
article

Image Quality, Not Disclosure Labels, Shapes the Credibility of Artificial Intelligence–Generated He

Chrysanthi Nega, Panagiotis Kourtesis, Elli Rizouli, Alkistis Kotsafti-Apergi4
article en

Abstract

Generative artificial intelligence (AI) can produce photorealistic health-campaign images, and regulators ask for labels. This study tested how disclosure labels and image fidelity affect credibility and gaze. In a 2 × 3 mixed design, 155 adults viewed 12 vaccination advertisements during webcam eye tracking. Each appeared as the original photograph or a high- or low-quality AI-generated image, with or without a “Human-Made”/“AI-Generated” label (between subjects). Fidelity affected credibility (sr2 = .107). Low-quality AI images were rated less credible than original photographs (d = 0.82) and high-quality AI images (d = 0.63), whereas originals and high-quality AI images did not differ reliably. The label had no main effect and interacted with fidelity, but no simple effect survived correction. Positive attitudes towards AI predicted higher credibility only for low-quality AI images. Neither factor detectably changed gaze, and the label was looked at on 36% of trials. Image quality, not disclosure, shaped credibility.

Open Science Framework
Misinformation and Its Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon