Census Grossly Miscounts People of Color
New Census Algorithm Grossly Miscounts People of Color in the Name of “Privacy”
The Census Bureau is rolling out a new algorithm intended to protect respondents’ privacy — but experts warn the change will significantly miscount minority communities and rural areas.
Specifically, the Census Bureau plans to use a new “differential privacy” algorithm to obscure respondents’ identities, yet state experts warn that the data could result in population errors of 25 percent or more and misrepresent certain groups by 100 percent or more. This would have dramatic results on redistricting and funding.
The data released by the bureau is expected to be accurate on the state level but its sub-state level data — region, county, city, town — will be intentionally distorted. In the past, the bureau used “data swapping” to ensure individuals in small populations were not identifiable by certain statistics by aggregating their data with similar individuals while keeping the population totals accurate, according to the National Council of State Legislatures (NCSL). But concerns that the data could be cross-referenced with other information that could make individuals identifiable led the bureau to implement a “differential privacy” algorithm that will “inject noise” into the raw data.
Though the bureau is still working out how it will implement this, the move immediately raised concerns.
“Differential privacy will mean that, except at the state level, population and voting age population will not be reported as enumerated. And, race and ethnicity data are likely to be farther from the ‘as enumerated’ data than in past decades, when data swapping was used to protect small populations,” according to the NCSL. “This may raise issues for racial block voting analyses.”
The bureau released a demonstration to states to test out the new method using data from the 2010 census and experts quickly realized that the data was very different from the original 2010 numbers, particularly in rural areas.
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