Application of Differential Privacy to the 2020 U.S. Census and American Community Survey: Researchers’ Understanding and Reactions

Author:

Zhong Qi1,Proctor Robert W.1,Blocki Jeremiah1,Li Ninghui1,Xiong Aiping2

Affiliation:

1. Purdue University

2. The Pennsylvania State University

Abstract

The U.S. Census and the related American Community Survey (ACS) are used for studies of many types by researchers in a variety of domains. The U.S. Census Bureau discovered that the methods intended to preserve the privacy of individuals used for the 2010 survey were not adequate. Thus, a decision was made to apply differential privacy (DP) to the data from the 2020 Census. DP methods introduce noise into the data set with the intention of allowing the group statistics still to be useful, while protecting the individual data by way of random perturbation. Researchers expressed concern as to how much this application of DP will impact research. We report results of a survey conducted of researchers who published studies based on the 2010 U.S. Census data or the ACS data to assess their understanding of and concerns about DP.

Publisher

SAGE Publications

Subject

General Medicine,General Chemistry

Reference21 articles.

1. Abowd J. M. (2018). Protecting the confidentiality of America’s statistics: Adopting modern disclosure avoidance methods at the census bureau. https://www.censusgov/newsroom/blogs/researchmatters/2018/08/protecting_the_confi.html.

2. Differential Perspectives: Epistemic Disconnects Surrounding the U.S. Census Bureau’s Use of Differential Privacy

3. "I need a better description": An Investigation Into User Expectations For Differential Privacy

4. Calibrating Noise to Sensitivity in Private Data Analysis

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