Race as Algorithm:

Bored Techies Being Casually Racist

Abstract

Connecting corporate software work in the United States and Germany, this essay tracks the racialization of mostly male Indian software engineers through the casualization of their labor. In doing so, I show the connections between overt, anti-immigrant violence today and the ongoing use of race to sediment divisions of labor in the industry as a whole. To explain racialization in the tech industry, I develop the concept of race-as-algorithm as a device to unpack how race is made productive within digital economies, and to show the flexibility of race as it works to create orders of classification that are sensitive to context. Using evidence collected through observation in tech offices and through interviews with programmers over five years, I track race as an essential, but continually disavowed variable within the construction of global tech economies. The essay turns to historical racializations of casual labor in plantation economies to illuminate how casualness marks laborers whose rights can be muted and allows corporations to deny their culpability in promoting discrimination within and outside of the tech industry within a political field that divides “good” from “bad” migrants. Using the ethnographic symptoms that Indian tech workers identify in their environments, this essay reads these signs as an antidote to these continued denials.

Keywords: race; algorithm; labor.