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Open Access
Race and Robots
American quarterly, 2020-03, Vol.72 (1), p.291-300
2020

Details

Autor(en) / Beteiligte
Titel
Race and Robots
Ist Teil von
  • American quarterly, 2020-03, Vol.72 (1), p.291-300
Ort / Verlag
College Park: Johns Hopkins University Press
Erscheinungsjahr
2020
Link zum Volltext
Quelle
Project MUSE
Beschreibungen/Notizen
  • Amy Sue Bix's cultural history of automation, which is weighted toward the 1930s; David F. Noble's social history of numerical control; Shoshana Zuboff's study of the computerization of pulp mills and office work; Ruth Schwartz Cowan's work on household technology; and Venus Green's book on race and the Bell System's switch to direct dial are indispensable resources for understanding these periods.1 But now, in the wake of the Great Recession of 2008, we are in a third era. If liberal political commentators have tended to use automation as a foil to Donald Trump's border policies—they claim that robots, not immigrants, are to blame for lost jobs—Atanasoski and Vora's analysis of the Latinx science fiction short "M.A.M.O.N." (2016), which depicts Trump as a giant robot guarding the border, suggests that the border is an automation policy. The whiteness of automation can thus be understood as the sociotechnical dimension of what Aziz Rana has called the "two faces of American freedom," or the entanglement of settler colonial and republican notions of self-rule with claims that slaves, Native Americans, Asians, and Latinxs are outsiders whose exclusion and internal domination are necessary for settler liberty.4 Atanasoski and Vora's major intervention in the automation debate is their argument that automation imaginaries are shaped by liberal humanism and the racial hierarchies embedded in it. Treating automation as "technoliberalism," the authors claim that robots and other automated systems function in racial capitalism as technical surrogates for the slaves, servants, immigrants, housewives, and colonized others who have long been tasked with ameliorating the lives of more fully human subjects.

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