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

TL;DR

This paper analyzes the controversy over the US Census Bureau's adoption of differential privacy, highlighting how it affects trust, legitimacy, and perceptions of data quality through an STS perspective.

Contribution

It offers an ethnographic and theoretical analysis of the epistemic and trust issues surrounding differential privacy in census data.

Findings

Differential privacy introduces uncertainties affecting data trustworthiness.

Stakeholders' trust is weakened due to perceived statistical illusions.

Rebuilding trust requires reconstructing the 'statistical imaginary'.

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.'