AI in Global Health: The View from the Front Lines
Azra Ismail, Neha Kumar
Abstract
There has been growing interest in the application of AI for Social Good, motivated by scarce and unequal resources globally. We focus on the case of AI in frontline health, a Social Good domain that is increasingly a topic of significant attention. We offer a thematic discourse analysis of scientific and grey literature to identify prominent applications of AI in frontline health, motivations driving this work, stakeholders involved, and levels of engagement with the local context. We then uncover design considerations for these systems, drawing from data from three years of ethnographic fieldwork with women frontline health workers and women from marginalized communities in Delhi (India). Finally, we outline an agenda for AI systems that target Social Good, drawing from literature on HCI4D, post-development critique, and transnational feminist theory. Our paper thus offers a critical and ethnographic perspective to inform the design of AI systems that target social impact.