Tuesday, October 4, 2022

Marisol Vasquez Non-Core Post 3/10

Since I am taking Professor Kara Keeling's and we are reading about technology and Blackness, I thought it might be useful introduce some of Simone Brown's concepts in Dark Matters and pair her concerns with Wendy Chun's essay on Cambridge Analytica. Reading these two works together helped me think through some of my initial concerns regarding the differences and similarities between the colonial archive and big data. Browne—who fills in the  gap within surveillance studies by problematizing surveillance through blackness—argues for a racializing surveillance as a technology of social control" to effectively address the racial order upheld by a surveillance "that first accompanied European colonial expansion and transatlantic slavery" (17). In other words, this hearkening back towards surveillance in the archive of slavery mobilizes a critique on the other side of big data, in which racializing surveillance insists on seeing "how racism and antiblackness undergird and sustain the intersecting surveillances of our present order" (8). 

Coupling racializing surveillance with Wendy Chun's discussion on Cambridge Analytica helped me draw out the mechanisms and logic in which big data operates, and more precisely, how big data attempts to fix the identities of marginalized identities. For example, the structured dichotomous value models that elicited the desired results for the future placed bodies and identities into fixed categories that are at once sexist, homophobic, etc (pp. 46). Once these computational strategies of regression and correlation inform such fixed categories of difference, how do we understand the body once it's made into data? This question was posed in Professor Keeling's class and while Simone Browne's *Dark Matters* perhaps intimated such a question, Chun's discussion on Cambridge Analytica actually unveiled the mechanisms as to how a body is made into data. 

Works Cited

Browne, Simone. Dark Matters: On the Surveillance of Blackness. Duke University Press, 2015.


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