  In an era where external data and computational capabilities far exceed
statistical agencies' own resources and capabilities, they face the renewed
challenge of protecting the confidentiality of underlying microdata when
publishing statistics in very granular form and ensuring that these granular
data are used for statistical purposes only. Conventional statistical
disclosure limitation methods are too fragile to address this new challenge.
This article discusses the deployment of a differential privacy framework for
the 2020 US Census that was customized to protect confidentiality, particularly
the most detailed geographic and demographic categories, and deliver controlled
accuracy across the full geographic hierarchy.
