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Chapter Interpreting musical artificial intelligence
W. White, Christopher

Chapter Interpreting musical artificial intelligence

Author / Organization:
Humanities & Social Sciences Published 2026 Verification Pending

Overview & Synopsis

Music poses unique and complex challenges for artificial intelligence, even as 21st-century AI grows ever more adept at generating compelling content. The AI Music Problem: Why Machine Learning Conflicts With Musical Creativity probes the challenges behind AI-generated music, with an investigation that straddles the technical, the musical, and the aesthetic. Bringing together the perspectives of the humanities and computer science, the author shows how the difficulties that music poses for AI connect to larger questions about music, artistic expression, and the increasing ubiquity of artificial intelligence. Taking a wide view of the current landscape of machine learning and Large Language Models, The AI Music Problem offers a resource for students, researchers, and the public to understand the broader issues surrounding musical AI on both technical and artistic levels. The author breaks down music theory and computer science concepts with clear and accessible explanations, synthesizing the technical with more holistic and human-centric analyses. Enabling readers of all backgrounds to understand how contemporary AI models work and why music is often a mismatch for those processes, this book is relevant to all those engaging with the intersection between AI and musical creativity today.

Indexed from repository: OAPEN Library (www.oapen.org)

Document Information

Document Title Chapter Interpreting musical artificial intelligence
Author / Organization W. White, Christopher
Subject & Discipline AI
Categories Humanities & Social Sciences
Publication Year 2026
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website OAPEN Library (www.oapen.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-129521
Original Source Link Visit Source Page on www.oapen.org »