🤖 AI Summary
This study addresses the lack of systematic understanding of AI’s artistic roles and practical manifestations in music creation. Methodologically, it conducts a multidimensional classification analysis of 337 AI-assisted musical works—including singles, albums, live performances, sound installations, ballet/opera scores, and film/TV soundtracks—drawn from empirical case collection. The research reconceptualizes AI not merely as a technical aid but as a dual-function entity: a *co-creative tool* and an *artistic medium*. It identifies core application paradigms—AI composition, human–AI co-creation, dynamic sound design, and multilingual lyric generation/translation—and documents emergent trends such as the uncanny aesthetic, cross-genre and multilingual synthesis, and real-time interactive online installations. The study yields the most comprehensive empirically grounded cartography of AI music practice to date, providing foundational evidence and methodological frameworks for theoretical development, artistic evaluation, and interdisciplinary advancement in music AI research.
📝 Abstract
We study how musicians use artificial intelligence (AI) across formats like singles, albums, performances, installations, voices, ballets, operas, or soundtracks. We collect 337 music artworks and categorize them based on AI usage: AI composition, co-composition, sound design, lyrics generation, and translation. We find that AI is employed as a co-creative tool, as an artistic medium, and in live performances and installations. Innovative uses of AI include exploring uncanny aesthetics, multilingual and multigenre song releases, and new formats such as online installations. This research provides a comprehensive overview of current AI music practices, offering insights into emerging artistic trends and the challenges faced by AI musicians.