EarlyMuse COST action
Published June 11, 2026 | Version v1
Publication Open

Musicology and artificial intelligence

Authors/Creators

  • 1. ROR icon Centre National de la Recherche Scientifique
  • 2. ROR icon Utrecht University

Contributors

Researcher (46):

  • 1. ROR icon Utrecht University
  • 2. ROR icon Centre National de la Recherche Scientifique
  • 3. ROR icon Université de Tours
  • 4. ROR icon National Research Council
  • 5. CNRS UMR 7323
  • 6. ROR icon University of the Aegean
  • 7. ROR icon Centre d'Etudes Supérieures de la Renaissance
  • 8. EDMO icon Katholieke Universiteit Leuven
  • 9. CNRS Délégation Paris B
  • 10. ROR icon Universitat de València
  • 11. Charles University
  • 12. ROR icon Ministry of the Interior and Kingdom Relations
  • 13. ROR icon Fryderyk Chopin Institute
  • 14. ROR icon University of Wrocław
  • 15. ROR icon Karol Lipiński Academy of Music in Wrocław
  • 16. Schola Cantorum Basiliensis / FHNW
  • 17. University of Oslo
  • 18. ROR icon University of Oxford
  • 19. ROR icon Université Libre de Bruxelles
  • 20. ROR icon Harvard University
  • 21. Universidad de Alicante
  • 22. ROR icon Aalborg University
  • 23. ROR icon Academy of Sciences and Literature
  • 24. ROR icon Paderborn University
  • 25. ROR icon Johannes Gutenberg University Mainz
  • 26. ROR icon University of Bern
  • 27. RISM Digital Center
  • 28. Instituto Superior de Enseñanzas Artísticas de la Comunidad Valenciana - ISEA.CV (Generalitat Valenciana)
  • 29. University of Alicante
  • 30. ROR icon Université de Lorraine
  • 31. ROR icon Centre de Recherche Universitaire Lorrain d'Histoire
  • 32. Consejo Superior de Investigaciones Científicas (CSIC), Institución Milá y Fontanals de Investigación en Humanidades
  • 33. ROR icon Hacettepe University
  • 34. ESMAE – Escola Superior de Música, Artes e Espetáculo / CESEM
  • 35. ROR icon Universidade Nova de Lisboa
  • 36. ROR icon Universidad de Málaga
  • 37. Sveučilište u Zagrebu Muzička akademija Zagreb
  • 38. Royal Birmingham Conservatoire
  • 39. ROR icon Birmingham City University
  • 40. Staatliches Institut für Musikforschung Preussischer Kulturbesitz

Description

This report provides an overview of Artificial Intelligence in European musicological research, addressed to musicologists, librarians, archivists, curators, educators, research-policy officers, infrastructure coordinators, and tool developers. Moving from conceptual foundations to institutional implications, it maps the affordances and limitations of AI-based models and tools for the discipline, while situating them within the European normative landscape defined by the ALLEA European Code of Conduct for Research Integrity, the EU Artificial Intelligence Act, and the UNESCO Recommendation on the Ethics of Artificial Intelligence.

The six complementary sections successively address: (1) methodological foundations, clarifying notions of model, tool, and critical posture, and surveying audio-, image-, encoding-, and language-model-based applications such as automatic music transcription, optical music recognition, score-audio alignment, automated analysis, reconstruction, and LLM prompt­ing; (2) data infrastructure, covering FAIR/CARE governance, ontologies and persistent identifiers, European federated infra­structures, auditory digital twins, and risks of fragmentation, representational bias, quality variability, and copyright; (3) a continuation of the disciplinary stakes involved in source and corpus processing; (4) musicological education in the age of AI, including curricular redesign, AI literacy, and design models such as the Two-Lane Approach; (5) professional practices and responsibilities, examining scholarly credibility, intellectual property, academic integrity frameworks, cultural and creative industry collaborations, institutional and legal risks, gender equality, and lessons from organised labour; and (6) best practic­es, articulating methodological pluralism against technological determinism and formalising principles of ethical reflexivity, human oversight, explainability, reproducibility, and accountability.

Files

Early-Muse_3-Vendrix-Ahrendt_260616.pdf

Files (22.9 MB)

Name Size Download all
md5:51d38b686dcb2b2baa07412952da21a7
22.9 MB Preview Download

Additional details

Funding

European Cooperation in Science and Technology
EarlyMuse CA21161

Dates

Copyrighted
2026-06-16