Date/Time
Thursday
12 Dec 2024
2:15 pm - 3:25 pm

Location
202 South Hall

Event Type
Non-CSTMS Event

Beth Semel
Assistant Professor of Anthropology, Princeton University

How might AI reshape the sensory norms and moral economies of discernment of American mental healthcare?

Since 2015, the US has witnessed a rise in mental healthcare-related vocal biomarker AI (VBAI), machine listening technologies trained to identify supposedly objective and/or biological indicators of mental distress conveyed in the sounds of the voice. The technologists, entrepreneurs, and clinical researchers invested in this subfield suggest that AI can unlock more accurate techniques for screening patients, superseding the need to rely on a clinical worker’s interpretive acumen alone to parse the ill from the well.

This talk draws from ethnographic fieldwork with several VBAI makers to show that bringing this promise of enhanced clinical precision into fruition also involves sensing certain features of mental distress out of technoscientific and bureaucratic legitimacy, generating modes of algorithmic legibility and illegibility side-by-side throughout the technology development pipeline. To illustrate these dynamics in practice, I focus on the “data workers” (Miceli and Posada 2023) tasked with processing the datasets of “mentally distressed voices” that are essential to the creation of VBAI, which requires them to make value-laden determinations about which aspects of mental distress — including their own — ought to be counted as computationally tractable signal versus unquantifiable and discardable noise.

This lecture will be held both online & in person. You are welcome to join in South Hall or via Zoom. For more information about this event, please visit the UC Berkeley School of Information website. If you have any questions about this event, please contact Peter Marchetti, Academic Personnel Manager, at pmarchetti@ischool.berkeley.edu.