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McCartan et al. (2023) call for "making differential privacy work for censusdata users." This commentary explains why the 2020 Census Noisy MeasurementFiles (NMFs) are not the best focus for that plea. The August 2021 letter from62 prominent researchers asking for production of the direct output of thedifferential privacy system deployed for the 2020 Census signaled theengagement of the scholarly community in the design of decennial census dataproducts. NMFs, the raw statistics produced by the 2020 Census DisclosureAvoidance System before any post-processing, are one component of thatdesign--the query strategy output. The more important component is the queryworkload output--the statistics released to the public. Optimizing the queryworkload--the Redistricting Data (P.L. 94-171) Summary File,specifically--could allow the privacy-loss budget to be more effectivelymanaged. There could be fewer noisy measurements, no post-processing bias, anddirect estimates of the uncertainty from disclosure avoidance for eachpublished statistic.

Noisy Measurements Are Important, the Design of Census Products Is Much More Important