Doctoral Dissertation Research: Designing Voice Analysis Technologies for Mental Health Applications in the United States

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This project, which trains a graduate student in methods of conducting empirically-grounded scientific research, asks how new, artificial intelligence (AI)-enabled technologies reshape not only the future of mental health care in the United States, but also basic assumptions about the relationship between language, mind, and brain. This research explores these questions through an ethnographic study of interdisciplinary research teams at three U.S. universities that are seeking to develop computer-assisted speech analysis technologies for mental health applications. In the research teams that this study focuses on, neuroscientists, psychiatrists, psychologists and engineers are working together to develop technology that can be used to diagnose and track mental illness by analyzing the formal, acoustic properties of speech (such as pitch, timbre, intonation, and speed), bypassing its semantic content (what the words mean) altogether. The project will have implications for the mental health researchers themselves as they move into uncharted ethical domains in regards to privacy, surveillance, and the increased diagnostic reliance on experimental technologies.Beth Semel, under the supervision of Dr. Graham Jones at the Massachusetts Institute of Technology, explores how experts across disciplinary boundaries collaborate to design, develop and test artificial intelligence-enabled technologies when they appear to hold very different assumptions about the relationship between language and inner, psychological states. The researcher hypothesizes that collaborations surrounding the development of these technologies not only enact fundamental tensions within dominant views about how language works, but also reflect a re-working of claims of authority and expertise within U.S. mental health care. Increasingly, mental health researchers are eschewing traditional techniques of psychiatric diagnosis, which depend upon patients' subjective, verbal accounts of their psychological states and clinicians' observational and interpretive skills. Instead, they are enlisting the expertise of computer engineers who use AI techniques of pattern recognition to decipher the biomedical significance of behavioral symptoms. Using ethnographic participant observation, the researcher will collect data about how psychiatrists, psychologists, neuroscientists and engineers work together to design, test, and develop voice analysis technologies. Focusing on teams situated at the confluence of academic, commercial, and military arenas, this study explores the variety of ways in which mental illness is conceptualized in terms of scientific, public health, and national security concerns. By exploring how listening practices can shape assumptions about speech, and how the production of new listening techniques and technologies can reshape such assumptions, this research contributes to ongoing debates in linguistic anthropology about how culture affects understandings of the way language works.