"Reading the Mind through Aesthetics: AI-Powered Personality Profiling without Words"
Year: 2025
Type: article
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.
Author: saraeian, nima
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6893342419
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