Measuring Digital Aesthetic Fatigue: An Empirical Exploration of Visual Overload Caused by AI in Sichuan’s Art and Design Educational Context

Abstract

Introduction: The proliferation of Generative AI (AIGC) tools in art education presents a dual challenge: while offering new creative possibilities, their intensive use risks causing digital aesthetic fatigue. This study investigates this phenomenon among fine arts and design students, examining its causes and impacts to develop effective mitigation strategies.

Objective: This study aimed to investigate the usage of Generative Artificial Intelligence (AIGC) tools among undergraduate fine arts and design students in Mianyang City, Sichuan Province, and to explore the phenomenon, causes, impacts, and coping strategies of digital aesthetic fatigue.

Methods: A quantitative survey was conducted with 329 students. Four research hypotheses were tested using statistical analysis to examine the relationships between variables.

Results: The use of AIGC tools significantly enhanced students' aesthetic perception, while a positive aesthetic attitude strengthened their evaluation skills. Acceptance of AIGC tools was closely linked to adaptive aesthetic skills. However, prolonged exposure led to visual saturation and creative burnout, gradually reducing interest and engagement with AI-generated art.

Conclusions: To address digital aesthetic fatigue, cognitive-behavioral and psychosocial interventions are recommended. The study emphasizes the critical importance of integrating critical thinking and aesthetic restoration into art education, providing a reference for balancing traditional and digital tools in the AI era.