Authorship cues and aesthetic judgement in the age of AI: Evaluating AI-composed music and human-composed music among higher education music students

Abstract

The present study investigates how the type of composer and the disclosure of authorship jointly influence aesthetic evaluations of music, with perceived authorship attribution examined as a mediating cognitive mechanism. Using an explanatory sequential mixed-methods design, the study involved music undergraduates in two experiments and follow-up interviews. Experiment 1 tested blind-listening evaluations and found no significant differences between AI-composed and human-composed music in perceived creativity and expressiveness. When authorship was disclosed in Experiment 2, AI-composed music was evaluated as significantly less creative and expressive, whereas evaluations of human-composed music were largely unchanged. Mediation analyses further showed that these effects were mediated by perceived authorship attribution. Notably, this mediating mechanism emerged only in the AI-composed music condition, indicating an asymmetric attribution process. The interview findings supported and contextualized the quantitative results by showing how listeners reinterpreted authorship meaning when evaluating AI-composed music. Together, these findings suggest that aesthetic judgements of AI-composed music are shaped less by perceptual qualities than by identity-driven cognitive attribution, thereby extending current understanding of authorship effects in musical aesthetics.