Part Seven: Whether the Public Receives Useful Data

A successful census must do more than produce a national population total. The resulting data must be detailed enough to support redistricting, civil rights enforcement, funding decisions, program administration, research, and public understanding of communities across the country.

That requires Census to balance two responsibilities. It must protect the confidentiality of individual responses, and it must publish information that remains accurate and useful at the geographic and demographic levels where important decisions are made. Neither responsibility can simply displace the other. Data that expose individuals are unacceptable, but data that are excessively altered, suppressed, or consolidated may also fail to serve the purposes for which the census is conducted.

This balance is becoming more difficult. Modern computing and the growing availability of outside data have increased the possibility that published statistics can be linked with other information to infer facts about individuals. At the same time, communities, governments, and researchers need increasingly detailed data to understand small populations and local conditions.

The Census Bureau’s use of differential privacy for the 2020 Census generated intense controversy about whether the published data preserved enough detail and accuracy. For 2030, Census must address those concerns while responding to a new constraint: a Commerce Department policy that prohibits or sharply restricts the use of noise infusion, the central mechanism used in the 2020 disclosure avoidance system.

The result is not a simple return to older methods. The privacy risks that motivated stronger protections remain, while a major protection available in 2020 may no longer be permitted. Census could therefore face pressure to rely more heavily on suppression, aggregation, data swapping, or limits on the tables and geographic detail it publishes.

This part examines whether Census can develop a lawful and scientifically defensible disclosure avoidance system that protects confidentiality without making communities disappear from the data. The central question is: Will the public receive information detailed and accurate enough to understand the nation and make consequential decisions, while individual census responses remain protected?