Towards a Model: Examining the Positive Associations of Warmth, Competence, and Familiarity with Musicians' Attitudes Towards AI

This study investigates attitudes towards AI musicians through a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. Data analysis focuses on the interplay between Anthropomorphism Degree (AD), Listening Type (LT), Warmth (W), Competence (C), Attitude (A), and Familiarity (F). The sample comprises 211 valid responses from college students, exploring perceptions via a questionnaire. Results indicate significant positive associations between attitudes towards AI and Competence, Familiarity, and Warmth. However, predictive validity analysis suggests caution in relying solely on the PLS-SEM model. Importance-Performance Analysis (IPMA) highlights competence as the primary influencer of attitudes towards AI, emphasizing its critical role over Warmth and Familiarity. This study contributes to understanding the nuanced dimensions of human interactions with AI musicians.