Experiments with Social Good: Feminist Critiques of Artificial Intelligence in Healthcare in India

Abstract

In contemporary India, AI-enabled automated diagnostic models are beginning to control who gets access to what kind of medical care, with the most invasive systems being aimed at underserved communities. I critically question the dominant narrative of “AI for social good” that has been widely adopted by various stakeholders in the healthcare industry towards solving development challenges through the introduction of AI applications targeted towards the sick-poor. Using feminist theory, I argue that AI systems should not be seen as neutral products but complex sociotechnical processes embedded with gendered knowledge and labor. I analyze the layers of expropriation and experimentation that come into play when AI technologies become a method of using diverse bodies and medical records of the sick-poor as data to train proprietary AI algorithms at a low cost in the absence of effective state regulatory mechanisms. I posit that an overwhelming focus on “spectacular technologies” such as AI derails public efforts from solving the actual needs of populations targeted by the “AI for social good” narrative, and from the development of sustainable, responsible, situated healthcare solutions. Lastly, I offer social and policy recommendations that would enable us to envision inclusive feminist futures in which we understand and prioritize the needs of underserved populations over capitalist market logics in the development, deployment, and regulation of AI systems.