From oral history to media archaeology, sensory ethnography to ecology, researchers are increasingly interested in what can be learned from the acoustic environment and from sonic, as well as textual resources. At the same time, computational methods afford opportunities to engage with sonic materials in new ways. This network brings together diverse disciplinary perspectives to consider the technical, epistemological and creative possibilities, as well as cultural and ethical implications, of listening with algorithms.

Existing machine listening methods are applied to tasks such as recognising melodies, identifying instruments or musical genres. Their power is evidenced by commercial IT products such as iPhone’s Siri, which uses voice recognition software, or Spotify’s recommender system that magically creates musical playlists based on our previous preferences. Driven by technical innovation and commercial interests, these tools are becoming at once more powerful, more complex and their inner workings more opaque. We believe that the design of future tools, optimisation of computational power must be accompanied by critical consideration of what it means to listen with and through algorithms: What new ways of listening might these active prosetheses afford? What kinds of relationships do we want to have? and how does this inform the way we design algorithms for future cultural, epistemological and creative applications?

A rich philosophical literature examines the active role that technologies play in mediating our relationship with the world. These ideas have been considered in the context of interactive computer music, where software agents that listen and respond as musical partners have been created, but have yet to be thoroughly explored in the wider contexts of technologically-mediated listening. Developing a critical framework is crucial, firstly to underpin the design of new computational methods in arts and humanities and wider research - for example to support the interpretation and discovery of large audio archives and the design of new creative sound-based technologies. And secondly to deepen understanding of the role that these listening algorithms play in our everyday lives, thus contributing to current global digital ethics policy-making efforts.

The Humanising Algorithmic Listening (HAL) network will bring together experts from across the humanities, computer science, critical theory, philosophy and interactive computer music to develop a research agenda for the design and development of computational methods for audio analysis - listening algorithms - in research and culture.