Differential Privacy


Differential privacy is a new mathematical procedure devised by the Census Bureau that will be applied to the 2020 Census data before it is released to enhance data privacy protection. Our analysis indicates that data accuracy at the sub-state (region, county, city, town) level will be sacrificed as a result of this new approach to data release. This inaccuracy may lead to misallocation of funds, poor capacity for planning, substandard service provision, and a competitive disadvantage in economic and workforce development. 

As a result, we are making great efforts to educate local government officials, state agencies, members of congress, the governor and other thought leaders about the potential impacts of the differential privacy procedure with the hope that our collective voice can reverse the Census Bureau's plans to implement differential privacy procedures. Read our memo to the Governor of Virginia.

Differential privacy for census data explained | National Conference of State Legislatures

Census 2020 may count everyone in the right place... | StatChat web series



Out Reach Efforts

  • Meetings and Workshops
    • Attended the Workshop on 2020 Census Data Products: Data Needs and Privacy Consideration, organized by the National Academy of Sciences Committee on National Statistics | Dec. 11-12, 2019
    • Meeting with Kelly Thomasson, Secretary of the Commonwealth | Feb. 14, 2020
  • Correspondence and Briefings
    Sent correspondence to the following to brief them on the differential privacy plan and encourage them to express their concerns to the Bureau in the hope that the Bureau will reverse their plans:
    • Governor of Virginia | Jan. 23, 2020
    • The National Governors’ Association, the nation-wide Federal-State Cooperative Program for Population Estimates network, the nation-wide State Data Center network | Jan. 23, 2020
    • Over 100 staff of Virginia state agencies | Feb. 3, 2020
    • Our members of congress | Feb. 4, 2020



Media Coverage



ANALYSIS of virginia data