“Recoding Affective Labor: Feminist Perspectives on Algorithmic Care Work”

From humanoid robots providing care for the elderly in Japan, to algorithmically-driven forms of psychotherapy, to the use of apps to diagnose and treat mental health challenges and neurodevelopmental difference, artificial intelligence (AI) is redefining affective labor in the contemporary era. Our research brings intersectional feminist perspectives to bear on newly emerging forms of AI-centered care work, asking how “care” is itself being recoded through these new technologies. Care, as a form of affective labor, has long been feminized and racialized. How do the algorithms produced through new AI technologies articulate with gendered and racialized assumptions about intimacy, empathy, and personhood? To what extent do new AI-generated technologies of care reinforce or reconfigure hegemonic discourses of gender, race, and culture?

Funded by a CSW/Streisand Center Faculty Grant, we are conducting preliminary interviews with app developers, medical researchers, software engineers, CTOs (Chief Technology Officers), and venture capitalists in the San Francisco Bay Area and Los Angeles who are focused on applying machine learning to mental health and neurdevelopmental diagnosis and treatment. We are asking those involved in developing these technologies how they conceptualize their work and endeavor to use AI to facilitate the diagnosis and treatment of mental health challenges and neurodevelopmental difference. At a time when rates of diagnoses in both these domains are steadily increasing, our research asks how gendered and racialized conceptions of normativity, neurotypicality, and sociality are encoded into AI-focused care strategies down to the very algorithms on which they rely.