Date of Award

12-2025

Degree Name

MS in Computer Science

Department/Program

Computer Science

College

College of Engineering

Advisor

Javier Gonzalez-Sanchez

Advisor Department

Computer Science

Advisor College

College of Engineering

Abstract

The use of artificial intelligence (AI) has significantly advanced efficient decision-making, with trust in algorithmic decisions shown to vary by cultural upbringing [1]. As AI becomes increasingly embedded in everyday life, it is essential to examine how cultural values affect trust in AI in subjective contexts that extend beyond purely quantitative analysis, like the personal interpretation of art. This work utilizes Hofstede’s cultural dimensions to investigate potential patterns in receptiveness towards AI predictions during art interpretation, providing insight into individual susceptibility to bias in AI-assisted affective analysis.

The study leveraged a cultural dimension survey and a custom Java program connected to an electroencephalography (EEG) headset, collecting Pleasure-Arousal- Dominance (PAD) estimates of participants’ emotional subconscious with self-reported quantifiable data. This was conducted as participants viewed artwork before and after receiving predictions from a machine-learning model, allowing us to analyze changes triggered by the presence of AI. Through regression modeling, it was found that none of the cultural dimensions had a statistically significant relationship with the number of changed answers. However, 26 out of the 35 participants acknowledged experiencing self-reflection or persuasion when exposed to such recommendations. While the quantitative data did not reveal a measurable influence from espoused cultural dimensions, the qualitative insights affirm that AI presence can still exert affective influence by promoting introspection, regardless of one’s cultural dimensions. The exploration of how these findings align or expand upon prior research reveals opportunities for further investigation within the psychological elements of AI adoption.

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