James Parker0a
This is an open curriculum for machine listening’s study. Already the question arises, what is machine listening? That is addressed in the first section, Machine listening, but for now -
Our devices are listening to us. Previous generations of audio-technology transmitted, recorded or manipulated sound. Today our digital voice assistants, smart speakers, and a growing range of related technologies are increasingly able to analyse and respond to it as well. Scientists and engineers increasingly refer to this as “machine listening”, though the first widespread use of the term was in computer music. Machine listening is much more than just a new scientific discipline or vein of technical innovation however. It is also an emergent field of knowledge-power, of data extraction and colonialism, of capital accumulation, automation and control. It demands critical and artistic attention.
Like most curricula, this one is structured as a series of topics, each with a title, short explanation, texts and other learning resources, along with some ideas about how to use them. Whereas most curricula are structured according to the needs of academic calendars, however, this one is open ended. When we think of a new topic, or someone gets in touch about writing one, we just add it wherever seems right at the time.
This idea is derived from Nicholas Luhman’s famous Zettelkasten, but not necessarily faithful to it. We didn’t want to assume in advance that we knew how the study of machine listening should be organised, what the right ‘master categories’ might be, what should be emphasised, or how topics should relate to each other. A number of political commitments do orient our thinking. But otherwise, our hope is that the problem-space of machine listening will emerge relatively organically from the collective work of studying it, even or especially insofar as that involves contradictions or disagreements.
One way of situating this curriculum would be in relation to the longstanding practice of sharing course materials and reading lists online. In terms of recent examples, Tarleton Gillespie and Nick Seaver’s Critical Algorithm Studies reading list and Knowing Machines’ Critical Dataset Studies reading list both come to mind. But course materials are so institutionally bounded, and reading lists can be so dry. We wanted to make something a little different here: something a little more open, and maybe also with more room to be creative.
Another way of understanding this curriculum, therefore, would be in relation to the so-called ‘educational turn’ in recent art and curation, whereby ‘educational formats, methods, programmes, models, terms, processes and procedures have become pervasive in the praxes of both curating and the production of contemporary art and in their attendant critical frameworks’ (O’Neill and Wilson 2010). A curriculum can also be a curatorial platform and an art work.
Whatever else it might be, this is a curriculum without a school. If not necessarily anti-institutional, it is para-institutional: built without any particular institution in mind. There are many ways to use it.