Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau’s Use of Differential Privacy

boyd, danah, & Sarathy, Jayshree. (2022). Differential Perspectives: Epistemic Disconnects Surrounding the U.S. Census Bureau’s Use of Differential Privacy. Harvard Data Science Review, (Special Issue 2). https://doi.org/10.1162/99608f92.66882f0e

48 Pages Posted: 20 Apr 2022 Last revised: 19 Nov 2024

See all articles by Danah Boyd

Danah Boyd

Microsoft Research; Georgetown University; Data & Society Research Institute

Jayshree Sarathy

Northeastern University

Date Written: March 15, 2022

Abstract

When the U.S. Census Bureau announced its intention to modernize its disclosure avoidance procedures for the 2020 Census, it sparked a controversy that is still underway. The move to differential privacy introduced technical and procedural uncertainties, leaving stakeholders unable to evaluate the quality of the data. More importantly, this transformation exposed the statistical illusions and limitations of census data, weakening stakeholders’ trust in the data and in the Census Bureau itself. This essay examines the epistemic currents of this controversy. Drawing on theories from Science and Technology Studies (STS) and ethnographic fieldwork, we analyze the current controversy over differential privacy as a battle over uncertainty, trust, and legitimacy of the Census. We argue that rebuilding trust will require more than technical repairs or improved communication; it will require reconstructing what we identify as a ‘statistical imaginary.’

Keywords: epistemology, science & technology studies, differential privacy, census

Suggested Citation

Boyd, Danah and Sarathy, Jayshree, Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau’s Use of Differential Privacy (March 15, 2022). boyd, danah, & Sarathy, Jayshree. (2022). Differential Perspectives: Epistemic Disconnects Surrounding the U.S. Census Bureau’s Use of Differential Privacy. Harvard Data Science Review, (Special Issue 2). https://doi.org/10.1162/99608f92.66882f0e, Available at SSRN: https://ssrn.com/abstract=4077426 or http://dx.doi.org/10.1162/99608f92.66882f0e

Danah Boyd

Microsoft Research ( email )

One Memorial Drive, 12th Floor
Cambridge, MA 02142
United States

HOME PAGE: http://research.microsoft.com/

Georgetown University ( email )

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Suite 311
Washington, DC 20057
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Data & Society Research Institute ( email )

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11th Floor
New York,, NY 10011
United States

HOME PAGE: http://www.datasociety.net

Jayshree Sarathy (Contact Author)

Northeastern University ( email )

Boston, MA 02115
United States

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