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The Well Trained Algorithm: An exploration of the use of AI as a tool for musical expression
Kungl. Musikhögskolan, Institutionen för komposition, dirigering och musikteori.
2023 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave [Kunstnerisk arbeiden]
Abstract [en]

The Well Trained Algorithm is a composition that challenges prevailing conceptions of the use of AI tools in music through the reconceptualising of JukeBox, a generative AI model for music, as an instrument in its own right. Here, I am coining the term ‘instrumentisation’ to describe a methodology for applying the qualities and associations of a musical instrument to a traditionally non-musical object. To showcase this conceptual approach, this model of thinking is applied to aid in the composition of the AI-generated musical piece, The Well Trained Algorithm. Through this process of ‘instrumentisation’, musical terms such as tuning and timbre are redefined to better relate to the specific affordances of an artificially intelligent system. The composition is informed, then, by an exploration of a system's instrumental possibilities, leading to a more effective and artistic use of the technology in the creative process. The seminal works of J. S. Bach and La Monte Young, The Well Tempered Clavier and The Well Tuned Piano, respectively, provide a historical, musical, and theoretical context for the piece as well as the datasets used to fine-tune the JukeBox model. With this thesis, I ask if, through a process of ‘instrumentisation’ AI technology can be successfully reconceptualised as a musical instrument as a means to promote artistic expression.

sted, utgiver, år, opplag, sider
2023.
Emneord [en]
Artificial Intelligence, AI, Machine Learning, ML, Generative Music, J. S. Bach, LaMonte Young, The Well Tempered Clavier, The Well Tuned Piano, Tuning System, Instrumentisation
HSV kategori
Identifikatorer
URN: urn:nbn:se:kmh:diva-4998OAI: oai:DiVA.org:kmh-4998DiVA, id: diva2:1768052
Presentation
2023-05-03, 1E207, Valhallavägen 105, 115 51 Stockholm, Stockholm, 09:00 (engelsk)
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Examiner
Tilgjengelig fra: 2023-06-15 Laget: 2023-06-14 Sist oppdatert: 2023-06-15bibliografisk kontrollert

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