Detecting Midjourney-Generated Images: An Eye-Tracking Study

This study investigated human performance in identifying AI-generated images. In a speeded forced-choice task, 255 participants viewed paired images (one real, one AI-generated by Midjourney) of standard or futuristic cars and buildings and had to identify the AI-generated one, while eye movements were recorded using an eye-tracker. Results revealed a powerful “futurism-as-artificiality” heuristic. Specifically, participants performed poorly (55% correct) when an AI-generated standard image was paired with a real futuristic image. Conversely, accuracy was high (91% correct) when the AI-generated futuristic image was paired with a real standard image. Participants’ gaze landed first on the AI-generated image more often when it depicted a futuristic design than when it depicted a standard one. The demonstrated heuristic presents a double-edged sword for information veracity: it may lead to the uncritical acceptance of AI-generated misinformation that appears conventional, while simultaneously causing real forward-thinking designs to be dismissed as fake.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2025-08-25
DOI
https://doi.org/10.1177/10711813251363209
Citations
1
Primary Topic
Aesthetic Perception and Analysis
Type
article
Field-Weighted Citation Impact
1.43
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article

Detecting Midjourney-Generated Images: An Eye-Tracking Study

Dimitra Dodou, Joost de Winter, Jochen Pfeifer, Yke Bauke Eisma
1 citations
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Aesthetic Perception and Analysis
1.43
article

Detecting Midjourney-Generated Images: An Eye-Tracking Study

Dimitra Dodou, Joost de Winter, Jochen Pfeifer, Yke Bauke Eisma
article en
1 citations

Abstract

This study investigated human performance in identifying AI-generated images. In a speeded forced-choice task, 255 participants viewed paired images (one real, one AI-generated by Midjourney) of standard or futuristic cars and buildings and had to identify the AI-generated one, while eye movements were recorded using an eye-tracker. Results revealed a powerful “futurism-as-artificiality” heuristic. Specifically, participants performed poorly (55% correct) when an AI-generated standard image was paired with a real futuristic image. Conversely, accuracy was high (91% correct) when the AI-generated futuristic image was paired with a real standard image. Participants’ gaze landed first on the AI-generated image more often when it depicted a futuristic design than when it depicted a standard one. The demonstrated heuristic presents a double-edged sword for information veracity: it may lead to the uncritical acceptance of AI-generated misinformation that appears conventional, while simultaneously causing real forward-thinking designs to be dismissed as fake.

Proceedings of the Human Factors and Ergonomics Society Annual MeetingVol. 69(1)
Delft University of Technology (NL)
Openalex Percentile: Top 16%
Aesthetic Perception and Analysis
1.43
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Detecting Midjourney-Generated Images: An Eye-Tracking Study — Dimitra Dodou, Joost de Winter, et al. · Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2025) | TGRS Research Map | TGRS