When Labels Matter More: Behavioral and Eye-Tracking Evidence on Aesthetic Judgment of AI-Generated and Human-Created Paintings by Lay Viewers

Abstract

Although Artificial Intelligence (AI) can now produce exquisite artworks, evidence suggests that people hold biases against AI-generated art. Previous studies have primarily relied on self-report measures to examine the effects of creator labels and the actual source of artworks, with limited attention to viewers’ visual processing (e.g., fixation duration, pupil size, etc.) during art perception. Through three studies, the present study extends this literature by integrating eye-tracking with self-reports to investigate how top-down processing and bottom-up processing influence aesthetic judgments among lay participants. The results showed that a preference for paintings labeled as human-created under conditions in which participants could not reliably distinguish the artworks’ actual sources. Although the eye-tracking data indicated that artworks labeled as AI led to more dispersed gaze patterns, the overall results were mixed. These findings highlight the role of contextual and labeling information in aesthetic evaluations. Future research should promote transparency to reduce AI-label bias.