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Beyond Diverse Datasets: Responsible MIR, Interdisciplinarity, and the Fractured Worlds of Music
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.ORCID iD: 0000-0003-1679-6018
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-2549-6367
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.ORCID iD: 0000-0002-7605-0093
2023 (English)In: Transactions of the International Society for Music Information Retrieval, E-ISSN 2514-3298, Vol. 6, no 1, p. 43-59Article in journal (Refereed) Published
Abstract [en]

Musical worlds, not unlike our lived realities, are fundamentally fragmented and diverse, a fact often seen as a challenge or even a threat to the validity of research in Music Information Research (MIR). In this article, we propose to treat this characteristic of our musical universe(s) as an opportunity to fundamentally enrich and re-orient MIR. We propose that the time has arrived for MIR to reflect on its ethical and cultural turns (if they have been initiated at all) and take them a step further, with the goal of profoundly diversifying the discipline beyond the diversification of datasets. Such diversification, we argue, is likely to remain superficial if it is not accompanied by a simultaneous auto-critique of the discipline’s raison d’être. Indeed, this move to diversify touches on the philosophical underpinnings of what MIR is and should become as a field of research: What is music (ontology)? What are the nature and limits of knowledge concerning music (epistemology)? How do we obtain such knowledge (methodology)? And what about music and our own research endeavor do we consider “good” and “valuable” (axiology)? This path involves sincere inter- and intra-disciplinary struggles that underlie MIR, and we point to “agonistic interdisciplinarity” — that we have practiced ourselves via the writing of this article — as a future worth reaching for. The two featured case studies, about possible philosophical re-orientations in approaching ethics of music AI and about responsible engineering when AI meets traditional music, indicate a glimpse of what is possible.

Place, publisher, year, edition, pages
Ubiquity Press, Ltd. , 2023. Vol. 6, no 1, p. 43-59
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-326016DOI: 10.5334/tismir.141Scopus ID: 2-s2.0-85165911770OAI: oai:DiVA.org:kth-326016DiVA, id: diva2:1752389
Funder
EU, Horizon 2020, 864189Marianne and Marcus Wallenberg Foundation, 2020.0102Swedish Research Council, 2019-03694
Note

QC 20230425

Available from: 2023-04-21 Created: 2023-04-21 Last updated: 2024-02-13Bibliographically approved

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Huang, RujingHolzapfel, AndreSturm, BobKaila, Anna-Kaisa

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