AI Music Problem

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A01=Christopher W. White
aesthetic evaluation in AI
AI
algorithmic composition
Artificial intelligence
Author_Christopher W. White
Category=AVA
Category=AVLA
Category=AVP
Category=UYQ
Category=UYU
challenges of machine learning in music
Composition
computational musicology
Computer engineering
Computer science
Creativity
data-driven music analysis
Digital humanities
eq_art-fashion-photography
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_music
eq_nobargain
eq_non-fiction
Generative AI
interdisciplinary research methods
Large Language Model
Large Language Modeling
LLM
Machine learning
Music
Music composition
Music technology
Music theory
Musical AI
Musicology
symbolic music representation

Product details

  • ISBN 9781032959764
  • Weight: 530g
  • Dimensions: 152 x 229mm
  • Publication Date: 15 Jun 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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.

Christopher W. White is Associate Professor of Music Theory at the University of Massachusetts Amherst.

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