The effect of applying digital filters in photo processing on the evaluation of human attractiveness

Abstract

In the context of the rapid spread of digital technologies and visual media, the topic of human attractiveness perception is gaining particular relevance. The widespread use of filters and artificial intelligence (AI) algorithms for image processing is transforming notions of appearance, beauty standards, and self-identity. The present study focuses on examining the impact of AI-based digital filters on the perception of human attractiveness, naturalness, and trustworthiness, as well as on users’ self-esteem.

The research combines a theoretical review of current studies in visual psychology, digital aesthetics, and media effects with an empirical experiment conducted among Russian respondents. The study investigated the consequences of applying filters of varying intensity—from minimal correction to pronounced retouching—on the perception of portrait images. Participants viewed 60 images and completed a self-esteem questionnaire twice: before and after exposure to the visual stimuli. Evaluations were made along the dimensions of attractiveness, naturalness, and perceived trustworthiness.

The results demonstrate that digital retouching significantly affects the perception of appearance: moderate use of filters enhances subjective attractiveness ratings, while excessive correction evokes impressions of artificiality and reduces trust in the image. Gender-specific differences were also observed: moderate retouching was found to be optimal for female faces, whereas even strong alterations could enhance attractiveness ratings for male faces. However, the use of filters did not produce a statistically significant change in participants’ overall self-esteem, suggesting a complex and mediated psychological effect of visual modification.

The findings highlight the need for critical reflection on the role of digital filters in shaping media representations and social norms of beauty. The results can inform the development of media literacy programs, prevention strategies against negative psychological impacts, and responsible approaches to visual content creation, as well as guide future interdisciplinary research at the intersection of psychology, media, and technology.