Workshop: Machine learning for sound-makers (part 2)
Published
BEK follows up the success of the first Machine learning for sound-makers workshop, with Luke Fischbecq (ph.d USC), this time as an online week-long workshop. Old and new participants will investigate the latest AI technologies on working with art and machine learning. Main focus is still audio, but also visual projects will be investigated to broaden the scope of the workshop. The perspective will still be critical, both in terms of who “owns” the technology and the datasets, and also their potential harmful use in surveillance and surveillance-capitalism etc.
Some of the resulting works and sketches of the workshop will be published at bek.no at the end of the week!
Participants: Elise Macmillan, Toril Johannessen, Magnus Bugge, Niklas Adam, Roel Heremans, Øyvind Torvund, Sindre Sørensen, HC Gilje, Bálint Laczkó, and Jørgen Skjulstad.
The workshopen is organised by Luke Fischbeck (USC) and Espen Sommer Eide (BEK).
The focus of this workshop will be on identifying the poetic possibilities inherent to this set of approaches, with the goal of initiating our own creative projects. Additionally, attention will be paid to philosophical and political questions embedded in the idea of ‘creative machine intelligence.’ What does it mean to work collaboratively with computers? Moreover, considering the resources required to develop this technology, what is lost when a small set of corporate research groups becomes responsible for the data collected, the tools developed, and the techniques shared? What strategies of resistance might be found in exploiting these techniques, data, and concepts for artistic purposes? What alternative tools are at our disposal for working (playing!) creatively using machine learning?
We will be following a hands-on approach, using publicly accessible, state-of-the-art techniques to consider what new critical, conceptual, and aesthetic strategies are made possible through machine learning. The participants have prior experience working with digital audio processing, machine learning and/or experience writing code (python or javascript).
Luke Fischbeck
Luke Fischbeck is an artist, composer, and organizer based in Los Angeles; a PhD candidate in the Interdisciplinary Media Art and Practice program at the University of Southern California, researching music, affect, and machine intelligence; and a contributing member of the collaborative group ‘lucky dragons’.
Image: ‘Rainbowgrams’ of a series of notes reconstructed by the WaveNet autoencoder. “Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders” Engel et al, 2017.
The workshop is produced in collaboration with Notam, as part of a workshop series that we jointly arrange for experienced artists. The workshops will be held in English, and will be arranged alternately in Oslo and Bergen between 2017 and 2020. There is a limited amount of places and highly qualified participants will therefore be prioritized. The series is supported by Arts Council Norway.