  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.
