Edward B. Kang
Assistant Professor of Media, Culture, and Communication
Media, Culture, and Communication
Edward B. Kang is a scholar of science and technology, and Assistant Professor in the Department of Media, Culture, and Communication. He is also the co-director of a multi-year project supported by the National Endowment for the Humanities (NEH) titled Machine Listening in the Age of Artificial Intelligence, and a co-organizer for the AI in Society working group at the Institute for Public Knowledge (IPK). Currently, he is writing a book (under contract, The MIT Press) that parses the scientific, social, cultural, and technological formats through which artificial intelligence (AI), voice, and listening are fastened together.
Kang’s work interfaces Science & Technology Studies (STS) and Sound Studies, which at present focuses on AI systems and the broader imaginaries and material practices through which they're enacted. He is also interested in how "intelligence" is made scientific beyond AI contexts. His peer-reviewed research on these topics can be found in Big Data & Society, Social Studies of Science, Science, Technology & Human-Values, and the Proceedings for the ACM Conference on Fairness, Accountability, and Transparency, among others.
In addition to his work on AI/ML systems, Kang has published research on digital platforms such as Spotify, Tinder and Thematic, as well as given talks on South Korean pop culture.
Kang holds a Ph.D. in Communication with a graduate certificate in Science & Technology Studies from the University of Southern California’s Annenberg School. At USC, he was a member of the Sloan-funded AI research collective Knowing Machines, as well as Assistant Editor for the International Journal of Communication.
Selected Publications
Ground truth tracings (GTT): On the epistemic limits of machine learning. Big Data & Society 10(1). (2023).
Biometric imaginaries: Formatting voice, body, identity to data. Social Studies of Science 54(2). (2022).
On the praxes and politics of AI speech emotion recognition. FAccT'23. (2023).
Audible crime scenes: Shotspotter as diagnostic, policing, and space-making infrastructure. Science, Technology & Human-Values 49(3). (2022). w/ Simogne Hudson
AI as a sport: On the competitive epistemologies of benchmarking. FAccT'24. (2024). w/ Will Orr