"Reading the Mind through Aesthetics: AI-Powered Personality Profiling without Words"

Traditional psychometric models often rely on explicit questionnaires, which can be prone to biases. This paper introduces AESTHLYZER, a novel AI framework that pioneers the use of aesthetic preferences for deep psychological profiling. By analyzing user responses to a curated set of visual stimuli, the model infers personality traits, cognitive styles, and emotional tendencies without requiring direct self-report. The system leverages advanced computer vision and machine learning algorithms to map aesthetic choices to validated psychological constructs. Results from a study with N=200 participants show that AESTHLYZER can predict Big Five personality traits with up to 82% accuracy, demonstrating its potential as a subtle, engaging, and effective alternative to traditional assessment methods. This work opens new avenues for non-intrusive psychological profiling in domains such as personalized recommendations, user experience design, and digital mental health.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-12
DOI
https://doi.org/10.5281/zenodo.15649881
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.00
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article

"Reading the Mind through Aesthetics: AI-Powered Personality Profiling without Words"

Zenodo (CERN European Organization for Nuclear Research)
Personality Traits and Psychology
article

"Reading the Mind through Aesthetics: AI-Powered Personality Profiling without Words"

article en

Abstract

Traditional psychometric models often rely on explicit questionnaires, which can be prone to biases. This paper introduces AESTHLYZER, a novel AI framework that pioneers the use of aesthetic preferences for deep psychological profiling. By analyzing user responses to a curated set of visual stimuli, the model infers personality traits, cognitive styles, and emotional tendencies without requiring direct self-report. The system leverages advanced computer vision and machine learning algorithms to map aesthetic choices to validated psychological constructs. Results from a study with N=200 participants show that AESTHLYZER can predict Big Five personality traits with up to 82% accuracy, demonstrating its potential as a subtle, engaging, and effective alternative to traditional assessment methods. This work opens new avenues for non-intrusive psychological profiling in domains such as personalized recommendations, user experience design, and digital mental health.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 46%
Personality Traits and Psychology
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