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        Chapter Interpreting musical artificial intelligence

        IN Book: The AI Music Problem

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        Author(s)
        W. White, Christopher
        Language
        English
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        Abstract
        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.
        URI
        https://oapen-dev.siscern.org/handle/20.500.12657/108846
        Keywords
        AI; Artificial intelligence; Music; Composition; Music composition; Creativity; Music technology; Music theory; Musicology; Computer science; Digital humanities; LLM; Large Language Modeling; Large Language Model; Machine learning; Generative AI; Musical AI; Computer engineering
        DOI
        10.4324/9781003587415-6
        ISBN
        9781003587415, 9781003587415, 9781032959764, 9781032959757
        Publisher
        Taylor & Francis
        Publisher website
        https://taylorandfrancis.com/
        Publication date and place
        New York, 2025
        Imprint
        Routledge
        Classification
        Information technology: general topics
        Digital music: professional
        Machine learning
        Music
        Theory of music and musicology
        Pages
        148 - 180
        Rights
        https://creativecommons.org/licenses/by-nc-nd/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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