Nonhuman Sound, Audio Culture, and the Politics of Machine Learning

My project examines the politics of AI systems that process, analyze, or produce sound, outlining the epistemologies and implications of voice recognition, signal processing, spatial analysis, and music generation. It uses archival research, interviews with engineers and users, participant observation, analyses of scholarship and vernacular writing, and walkthroughs of technologies themselves. As my research partner, you will be researching machine listening systems used for the analysis of nonhuman sounds such as environments, machinery, and animals. My primary interest is for-profit corporate projects and start-ups, but artistic uses, scientific, and open-source applications may also be of interest.

I seek a research partner with strong historiographic skills to read across disciplines. Specifically, I will be asking them to track how and where ideas about non-human sound emerge in the literature on machine learning, how those ideas developed and moved, and how they are operationalized (or not) in contemporary applications of machine listening, especially commercial applications. Together, we will also come up with other creative approaches to studying machine listening and nonhuman sound. A strong background in humanistic research methods, good writing skills, comfort with (or some background in) relevant technical fields, and an avid interest in sound would be assets.