EXPERIMENTAL INTELLIGENCE FOR ARTIFICIAL IMAGINATION

Abstract:

In contemporary sound and music production and composition, many techniques incorporate automatic generation tools. A key feature of these systems is their unpredictability in terms of the sounds produced when people interact with them. The randomness inherent in machine learning tools means users must partially relinquish control to the machine during the creative process. This significantly transforms the role of composers and performers, challenging traditional methods and reformulating established knowledge in music education with new media, particularly at secondary and higher education levels. While academia has started to incorporate automation-related content into art curricula, technical teaching focused solely on tool control remains prevalent in most educational environments. However, using automatic generation software in artistic production, including artificial intelligence, requires new methodological strategies that treat contingency as an integral part of the creative process. To achieve this, a specific approach to the unpredictable must be developed.

Keywords: experimental education, machine learning, randomness, contingency.

THIRD EDITION OF THE INTERNATIONAL SOUND ART SYMPOSIUM

Sound Worlds: Intersections, Circulations, Experiences

2024 Edition: (Un)Heard-of Futures

Wednesday, September 11, University Rectorate, Juncal 1319, Buenos Aires City.

Thursday, September 12 and Friday, September 13, San Martín Cultural Center, Sarmiento 1551, Buenos Aires City

Master's Degree in Art and Sound Studies - Specialization in Sound Art

Dr. Norberto Griffa Research Institute in Art and Culture (IIAC)

National University of Tres de Febrero

City of Buenos Aires, Argentina