Trust Study on Artificial Intelligence Generated Artistic Images

CHEN Li; LIU Yidong; WANG Kang; CHEN Xinxing

doi:10.19554/j.cnki.1001-3563.2025.18.032

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (18) : 359-367. DOI: 10.19554/j.cnki.1001-3563.2025.18.032

Design Discussion

Trust Study on Artificial Intelligence Generated Artistic Images

CHEN Li¹, LIU Yidong^2,*, WANG Kang³, CHEN Xinxing⁴

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Abstract

There have been numerous practical cases of AI-generated art images in the field of packaging design, but not all AI-generated images are accepted by users. The work aims to explore how the properties of art images influence people's judgment about whether art images are generated by AI, with focus on whether the user can "trust" the way the image is drawn, rather than whether the user can distinguish the AI-generated art image, so as to provide empirical reference and advice for designers to screen the AI-generated art image and AI-generated image technology. AI generated art images and real-life art images in the art image database were classified based on the three attributes of art image complexity, sample entropy and art style; 160 art images with different complexity and art style were screened. Each art image was scored by the subjects based on their level of trust in whether it was generated by AI. A questionnaire test was conducted on the artistic knowledge level of the subjects. The attributes of art images and the users' degree of trust on the ways of image drawing were analyzed. The results showed that entropy had no significant effect on user trust, and complexity and individual artistic knowledge had a significant effect on the way users trust images. The results have practical implications for understanding user trust building in artistic images, and deepen the understanding of how image properties affect human perception.

Key words

trust / art image design / artificial intelligence generation / complexity / visual recognition

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CHEN Li, LIU Yidong, WANG Kang, CHEN Xinxing. Trust Study on Artificial Intelligence Generated Artistic Images[J]. Packaging Engineering. 2025, 46(18): 359-367 https://doi.org/10.19554/j.cnki.1001-3563.2025.18.032

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