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Título:

AI and music at a crossroads : The role of the music information retrieval (MIR) community in shaping trustworthy, open, and culturally inclusive music-AI

Otros títulos:

Coordinador:

Director:

Compilador:

Autor:

Serra, Xavier
Alluri, Vinoo
Balke, Stefan

Tutor:

Tipo de documento:

Artículo

Editor:

Palabras clave:

Music information retrieval
Music-AI
Trustworthy AI
AI ethics and governance
Evaluation and reproducibility
Open science

Descriptores:

Año de publicación:

2026

Contenido:

Resumen:

Artificial intelligence (AI) has become central to debates about the future of music, particularly with the rise of generative systems and their societal, economic, cultural, and legal implications. Public and policy discourse, however, often follows commercial narratives that narrow music-AI to automated generation and treat music primarily as data or commodified output. This obscures both the broader range of AI applications in music and the long-standing contributions and responsibilities of the music information retrieval (MIR) community. Addressed primarily to this community, the article argues that MIR is well positioned to contribute to current debates on trustworthy music-AI but must also critically examine the limitations of its own research practices and incentives. We briefly situate MIR’s methodological development, applications, and shared infrastructures, emphasizing the culturally and socially situated character of music data. We then examine ethical, legal, and governance challenges in music-AI and propose transparency, accountability, provenance, and sustainability as criteria for assessing current practice and guiding future work. Finally, we identify six interconnected priorities: mission-oriented collaboration; sustainable open infrastructures; rigorous and context-sensitive evaluation; cultural diversity and responsibility; engagement across research, industry, policy, and society; and interdisciplinary education and mutual capacity-building. We conclude by identifying ways in which the MIR community can translate these priorities into practice through its research, infrastructures, evaluation and publication processes, educational activities, and engagement with musical, industry, policy, and civil society communities.

Descripción:

Listado completo de autores : Xavier Serra, Vinoo Alluri, Stefan Balke, Juan Pablo Bello, Emmanouil Benetos, Dmitry Bogdanov, Johanna Devaney, Simon Dixon, Zhiyao Duan, George Fazekas, Arthur Flexer, Frederic Font, Magdalena Fuentes, Ichiro Fujinaga, Emilia Gomez, Masataka Goto, Romain Hennequin, Dorien Herremans, Xiao Hu, Dasaem Jeong, Peter Knees, Filip Korzeniowski, Stefan Lattner, Jin Ha Lee, Alexander Lerch, Cynthia Liem, Brian McFee, Emilio Molina, Meinard Müller, Tomoyasu Nakano, Juhan Nam, Oriol Nieto, Sergio Oramas, Bryan Pardo, Geoffroy Peeters, Preeti Rao, Gaël Richard, Martín Rocamora, Ajay Srinivasamurthy, Li Su, Bob L. T. Sturm, George Tzanetakis, Anja Volk, Ye Wang, Gerhard Widmer, Frans Wiering, Christof Weiß, Yi-Hsuan Yang, Eva Zangerle.

metadata.articulos.dc.description.uri:

Editorial:

International Society for Music Information Retrieval (ISMIR)

EN:

Transactions of the International Society for Music Information Retrieval, vol. 9, no 1, 2026, pp. 510-525, DOI: 10.5334/tismir.372.

Financiadores:

Citación:

Serra, X., Alluri, V., Balke, S. y otros. "AI and music at a crossroads : The role of the music information retrieval (MIR) community in shaping trustworthy, open, and culturally inclusive music-AI". Transactions of the International Society for Music Information Retrieval [en línea]. 2026, vol, 9, no 1, pp. 510-525. DOI: 10.5334/tismir.372.

Citación:

metadata.articulos.cc.license.name:

ISBN:

e-ISBN:

ISSN:

2514-3298

ISMN:

Otros identificadores:

Cobertura geográfica:

Cobertura temporal:

Departamento académico:

Procesamiento de Señales

Grupo de investigación:

Procesamiento de Audio

Licencia:

Attribution-NonCommercial-NoDerivatives 4.0 International
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