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Accepted Paper:

Validation of AI and avantgarde music composition  
Govert Valkenburg (NTNU Norwegian University of Science and Technology)

Long abstract:

The accomplishments of AI in the field of music composition (AIM) have so far been underwhelming. For example, only mediocre chorales in the style of J.S. Bach have so far been produced, which is considered only a very basic compositional task. AIM is mostly validated by its success at mimicking existing repertoires, evaluated either by human listeners ('Turing test') or data-analytical methods, Bach chorales being a prominent test case. The practice of AIM thus comprises a bias towards the conservative and towards 'easy listening' music: music is good if enough people accept it as beautiful music.

Yet, advances in music have historically not been made in easy listening. Avant-garde music (AGM) are all those works, composers and movements where the purpose is not to have people 'like' the work but rather to push boundaries, confront audiences with those very boundaries and express messages that have an importance regardless of whether or not they are likeable.

How does validation in contemporary avant-garde music production relate to validation of AIM? What are the biggest challenges for AIM to accomplish such creative work? What challenges does AGM production experience from emerging AIM technologies? Do creative symbioses between human composers and AIM systems emerge, and how are their relative contributions negotiated?

Thinking through the relation between AGM and AIM is crucial to answer questions of creativity and critique. It stands model for a broader problematic of how AI relates to critical thinking, which is a crucial ingredient of citizenship, democracy and public life.

Traditional Open Panel P231
STS, AI Experiments, and the social good
  Session 2