Statistical agencies use a variety of techniques—known collectively as disclosure avoidance—to protect the confidentiality of the people and businesses represented in publicly released data.

On June 4, 2026, the U.S. Department of Commerce issued Department Administrative Order 216-26, "Disclosure Avoidance for Statistical Products." The order prohibits the use of differential privacy and other forms of noise infusion in Commerce statistical products—including those of the Census Bureau and the Bureau of Economic Analysis—and identifies coarsening as the preferred approach for protecting the confidentiality of the people and businesses behind the data.

Coarsening is an umbrella term for techniques that reduce precision, such as rounding values, aggregating small geographic areas into larger ones, and reporting ranges instead of exact counts. These methods have long histories in federal statistics, but they've generally been used in combination with other disclosure avoidance techniques rather than serving as the primary line of defense.

How the new order will be implemented in practice—and what it will mean for small geographic areas and population subgroups—remains to be seen. In the meantime, this Explorer shows how these methods could affect published data: select a method below and watch how it changes the values in a hypothetical census table of young children by census tract.

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For the full story behind this tool—and to share your questions, ideas, and feedback—read our blog post, What Does "Coarsening" Look Like?, and join the discussion on PRB's Federal Data Forum.

For the history behind these methods, see Why the Census Bureau Chose Differential Privacy, a brief produced by PRB with Census Bureau experts explaining why the Bureau adopted differential privacy for the 2020 Census and how it compares with earlier disclosure avoidance techniques.