Differential Privacy in the 2020 Decennial Census and the Implications for Available Data Products

21 Pages Posted: 10 Jul 2019

See all articles by Danah Boyd

Danah Boyd

Microsoft Research; Georgetown University; Data & Society Research Institute

Date Written: July 8, 2019

Abstract

In early 2021, the US Census Bureau will begin releasing statistical tables based on the decennial census conducted in 2020. Because of significant changes in the data landscape, the Census Bureau is changing its approach to disclosure avoidance. The confidentiality of individuals represented “anonymously” in these statistical tables will be protected by a “formal privacy” technique that allows the Bureau to mathematically assess the risk of revealing information about individuals in the released statistical tables. The Bureau’s approach is an implementation of “differential privacy,” and it gives a rigorously demonstrated guaranteed level of privacy protection that traditional methods of disclosure avoidance do not. Given the importance of the Census Bureau’s statistical tables to democracy, resource allocation, justice, and research, confusion about what differential privacy is and how it might alter or eliminate data products has rippled through the community of its data users, namely: demographers, statisticians, and census advocates.

The purpose of this primer is to provide context to the Census Bureau’s decision to use a technique based on differential privacy and to help data users and other census advocates who are struggling to understand what this mathematical tool is, why it matters, and how it will affect the Bureau’s data products.

Keywords: census, differential privacy, statistics, demography

Suggested Citation

Boyd, Danah, Differential Privacy in the 2020 Decennial Census and the Implications for Available Data Products (July 8, 2019). Available at SSRN: https://ssrn.com/abstract=3416572 or http://dx.doi.org/10.2139/ssrn.3416572

Danah Boyd (Contact Author)

Microsoft Research ( email )

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Georgetown University ( email )

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Data & Society Research Institute ( email )

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