Machine Learning
This movement marks the composer's decision to move away from using data for music composition and towards solely using composition techniques for communicating aspects of a scientific topic.
Music-based sonifications (that is the use of data mapped to sound, for interpretation purposes) which attempt functional use, often produce results that are could be described as random sounds, despite being termed music. This poses a barrier to engagement and disappointment for those who expect a listening experience which is more consistent with their expectations of what music sounds like. Conversely, when composers deliberately seek a more musical outcome, the data-music connection becomes looser. This is due to the creative decisions composers make to arrive at more musical outcomes. However, the claims that the music and data are closely related, or that the music can facilitate data interpretation, then becomes tenuous or misleading. There is a potential for scientific fact to be misrepresented through the way in which composers present their work.
Focusing solely on composition techniques may lead to a more accessible and musically satisfying result, while adding clarity as to the indications to the listener, in what is being heard. Full rationale for advocating a move away from data use, is detailed in the upcoming thesis.
Whereas Can’t Stand Standing deals with negative themes such as the ME experience, this movement provides a sense of hopefulness. Focus is given to advances in technology and the positive potentials it has for ME research.