Perception of AI-Generated Music -- The Role of Composer Identity, Personality Traits, Music Preferences, and Perceived Humanness
David Stammer, Hannah Strauss, Peter Knees

TL;DR
This study explores how composer identity, personality traits, music preferences, and perceived humanness influence audience perceptions of AI-generated music, highlighting the importance of attitudes toward AI and ethical considerations.
Contribution
It provides a comprehensive analysis of listener perceptions of AI music, emphasizing the roles of perceived authorship, personality, and attitudes, with both quantitative and qualitative insights.
Findings
Attitudes toward AI strongly predict liking and emotional response.
Perceived humanness influences listener evaluations.
Ethical and cultural considerations are key criteria in judgments.
Abstract
The rapid rise of AI-generated art has sparked debate about potential biases in how audiences perceive and evaluate such works. This study investigates how composer information and listener characteristics shape the perception of AI-generated music, adopting a mixed-method approach. Using a diverse set of stimuli across various genres from two AI music models, we examine effects of perceived authorship on liking and emotional responses, and explore how attitudes toward AI, personality traits, and music-related variables influence evaluations. We further assess the influence of perceived humanness and analyze open-ended responses to uncover listener criteria for judging AI-generated music. Attitudes toward AI proved to be the best predictor of both liking and emotional intensity of AI-generated music. This quantitative finding was complemented by qualitative themes from our thematic…
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Taxonomy
TopicsNeuroscience and Music Perception · Aesthetic Perception and Analysis · Creativity in Education and Neuroscience
