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Negotiating Autonomy and Trust when Performing with an AI Musician
University of Nottingham Nottingham, United Kingdom.
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0009-0005-7428-4434
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0003-2549-6367
University of Nottingham Nottingham, UK.
2024 (English)In: TAS 2024 - Proceedings of the 2nd International Symposium on Trustworthy Autonomous Systems, Association for Computing Machinery (ACM) , 2024, article id 6Conference paper, Published paper (Refereed)
Abstract [en]

We report a practice-based exploration of developing and performing with an autonomous AI musician called LOERIC that improvises folk tunes in response to a human partner. We follow an artist-led methodology involving a subjective, first-person reflection on our own practice of iteratively developing LOERIC through a series of public performances. A key feature of LOERIC is the manner in which autonomy is negotiated. Prior to a performance, surrender and looseness of control are preconfigured as playing styles. During a performance, the human and LOERIC interact solely through the single parameter of musical intensity to enable the human musician to loose awareness of explicit control as part of a flowful musical experience. This separation also helps the human establish a baseline of trust in how the system might potentially behave beforehand, within which they can safely experiment and improvise when playing live.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2024. article id 6
Keywords [en]
artificial intelligence, autonomous systems, autonomy, control, mixed initiative, music, performance, practice-based research, trust, trustworthiness
National Category
Music
Identifiers
URN: urn:nbn:se:kth:diva-354658DOI: 10.1145/3686038.3686040ISI: 001324818900006Scopus ID: 2-s2.0-85205337023OAI: oai:DiVA.org:kth-354658DiVA, id: diva2:1904554
Conference
2nd International Symposium on Trustworthy Autonomous Systems, TAS 2024, Austin, United States of America, Sep 15 2024 - Sep 18 2024
Note

QC 20241010

Part of ISBN 9798400709890

Available from: 2024-10-09 Created: 2024-10-09 Last updated: 2025-02-21Bibliographically approved

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Amerotti, MarcoSturm, Bob

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CiteExportLink to record
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