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

Qi Zhong, Robert W. Proctor, Jeremiah Blocki, Ninghui Li, Aiping Xiong

Research output: Contribution to journalConference articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)2072-2076
Number of pages5
JournalProceedings of the Human Factors and Ergonomics Society
Volume66
Issue number1
DOIs
StatePublished - 2022
Event66th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2022 - Atlanta, United States
Duration: Oct 10 2022Oct 14 2022

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics

Fingerprint

Dive into the research topics of 'Application of Differential Privacy to the 2020 U.S. Census and American Community Survey: Researchers’ Understanding and Reactions'. Together they form a unique fingerprint.

Cite this