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The Census Bureau must balance the need to provide high quality data at fine granularity with its obligation to avoid disclosing sensitive information. In response to demonstrated reconstruction and reidentification attacks enabled by modern computing, the Census Bureau concluded that its traditional disclosure avoidance mechanisms were insufficient for the 2020 decennial census and adopted a modernized approach designed to achieve formal privacy guarantees. The methods used involve adding sampled random noise to results, which can introduce inconsistencies in the resulting data. JASON was asked to study the impact of these privacy mechanisms on consistency for two data products produced from the 2020 census data: the PL94-171 data produced for redistricting and the Demographic and Housing Characteristics file. This report provides findings and recommendations on the mechanisms adopted by the Census Bureau to achieve consistency, and the challenges of balancing utility and privacy for future Census Bureau data products.
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