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AI Images vs. Real Photographs: Investigating Visual Recognition and Perception
Veslava Osińska1, Weronika Kortas1, Adam Szalach2
1Institute of Information and Communication Research, Nicolaus Copernicus University, 87-100 Toruń, Poland.
Journal of Eye Movement Research
|November 24, 2025
Summary
AI-generated images are increasingly realistic, yet human perception varies. This study found significant differences in identifying AI vs. real images based on gender and digital graphics knowledge.
Area of Science:
- Computer Vision
- Human-Computer Interaction
- Cognitive Psychology
Background:
- Advancements in Artificial Intelligence (AI) algorithms have led to highly photorealistic generated images.
- These AI-generated images are often indistinguishable from authentic photographs to the untrained eye.
- Understanding human perception of AI-generated content is crucial for development and application.
Purpose of the Study:
- To assess human perception of AI-generated images versus real photographs.
- To investigate visual perception differences across various image categories (architecture, art, faces, cars, landscapes, pets).
- To analyze the influence of respondent demographics (gender) and AI graphics knowledge on image identification.
Main Methods:
- Comparative analysis of 12 AI-generated images and 12 real photographs.
- Utilized eye-tracking technology to record gaze patterns and visual attention.
- Collected subjective feedback from participants on their identification reasoning post-experiment.
Main Results:
- AI-generated pet images and real architecture photographs were most easily identified.
- Significant differences in visual perception were observed between genders.
- Individuals with digital graphics experience, including AI image knowledge, showed distinct perception patterns.
Conclusions:
- Human perception of AI-generated images is influenced by image category, gender, and prior AI graphics expertise.
- AI developers should consider these perceptual differences for improved AI image generation and user experience.
- End-users benefit from understanding these nuances in distinguishing AI-generated content.
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