STS research has devoted relatively little attention to the promotion and reception of science and technology by non-scientific actors and institutions. One consequence is that the relationship of science and technology to political power has tended to remain undertheorized. This article aims to fill that gap by introducing the concept of sociotechnical imaginaries. Through a comparative examination of the development and regulation of nuclear power in the US and South Korea, the article demonstrates the analytic potential of the imaginaries concept. (...) Although nuclear power and nationhood have long been imagined together in both countries, the nature of those imaginations has remained strikingly different. In the US, the state’s central move was to present itself as a responsible regulator of a potentially runaway technology that demands effective containment. In South Korea, the dominant imaginary was of atoms for development which the state not only imported but incorporated into its scientific, technological and political practices. In turn, these disparate imaginaries have underwritten very different responses to a variety of nuclear shocks and challenges, such as Three Mile Island (TMI), Chernobyl, and the spread of the anti-nuclear movement. (shrink)

A common theme in social science studies of algorithms is that they are profoundly opaque and function as “black boxes.” Scholars have developed several methodological approaches in order to address algorithmic opacity. Here I argue that we can explicitly enroll algorithms in ethnographic research, which can shed light on unexpected aspects of algorithmic systems—including their opacity. I delineate three meso-level strategies for algorithmic ethnography. The first, algorithmic refraction, examines the reconfigurations that take place when computational software, people, and institutions interact. (...) The second strategy, algorithmic comparison, relies on a similarity-and-difference approach to identify the instruments’ unique features. The third strategy, algorithmic triangulation, enrolls algorithms to help gather rich qualitative data. I conclude by discussing the implications of this toolkit for the study of algorithms and future of ethnographic fieldwork. (shrink)