Escalation of Commitment: A Case Study of the United States Census Bureau Efforts to Implement Differential Privacy for the 2020 Decennial Census

TL;DR

This study critically evaluates the US Census Bureau's shift to differential privacy for the 2020 census, revealing unreliable disclosure risk assessments and poor data utility, illustrating escalation of commitment despite compromised privacy and accuracy.

Contribution

The paper provides a rigorous critique of the Census Bureau's disclosure risk evaluation methods and highlights the consequences of escalation of commitment in implementing differential privacy.

Findings

Disclosure risk assessments were unreliable and inflated.

Data utility of the new procedures was poor.

Escalation of commitment led to compromised privacy and accuracy.

Abstract

In 2017, the United States Census Bureau announced that because of high disclosure risk in the methodology (data swapping) used to produce tabular data for the 2010 census, a different protection mechanism based on differential privacy would be used for the 2020 census. While there have been many studies evaluating the result of this change, there has been no rigorous examination of disclosure risk claims resulting from the released 2010 tabular data. In this study we perform such an evaluation. We show that the procedures used to evaluate disclosure risk are unreliable and resulted in inflated disclosure risk. Demonstration data products released using the new procedure were also shown to have poor utility. However, since the Census Bureau had already committed to a different procedure, they had no option except to escalate their commitment. The result of such escalation is that the 2020 tabular data release offers neither privacy nor accuracy.