Toward a New Ethics of Artificial Intelligence Generated Music: Husserl’s Intentionality and Levinas’s Ethics of the Other

Abstract

Objectives: This study aims to explore the ethical dimensions of listening to AI-generated music by introducing the concept of ethical intentionality. The goal is to investigate how emotional and moral responses are integrated within the listener’s experience, and how AI challenges traditional notions of authorship, agency, and aesthetic reception. Methods: A qualitative philosophical methodology was employed, grounded in conceptual analysis and interpretive phenomenology. The study draws on Edmund Husserl’s theory of affective intentionality and Emmanuel Levinas’s ethics of the Other to construct a theoretical framework. This framework is used to analyze how AI-generated music functions as both a medium of emotional resonance and a site of ethical encounter. Results: The analysis shows that ethical intentionality operates as a dual structure in which the listener simultaneously constructs emotional meaning and responds to the music as a moral presence. Listening is thereby reconceptualized as a complex act involving both affective interpretation and ethical responsiveness. Conclusions: The study concludes that AI-generated music can serve as a catalyst for ethical reflection and offers a posthuman perspective on creativity and musical subjectivity. Future research is encouraged to empirically explore how ethical intentionality manifests in actual listening contexts.