The third Digital Aesthetics Workshop event of the Spring quarter is coming up next week: on May 26th, at 5 PM, we’ll host a workshop with Xiaochang Li, via Zoom. Please email Jeff Nagy (jsnagy at stanford dot edu) for the link by May 25th.
Professor Li will share research from her current project, How Language Became Data: Speech Recognition Between Likeness and Likelihood. Beginning in 1971, a team of researchers at IBM began to reorient the field of automatic speech recognition away from the study of human speech and language and towards a startling new mandate: “There’s no data like more data.” In the ensuing decades, speech recognition was refashioned as a problem of large-scale data acquisition and classification, one that was distinct from, if not antithetical to, explanation, interpretability, and expertise. The history of automatic speech recognition invites a glimpse into how making language into data helped make data into an imperative, opening the door for the expansion of algorithmic culture into everyday life.
Xiaochang Li is an Assistant Professor of Communication at Stanford University. Her research examines questions surrounding the relationship between information technology and knowledge production and its role in the organization of social life.