When National Statistics Die, Democracy Dies With Them
Image Credit: The American Statistical Association Project Team
By Sevastian Sanchez
Since January 2025, the Trump administration has struck down over 3,000 publicly funded datasets. Data purging is a classic political weapon, but with stark policy ramifications: Objective national statistics serve as the backbone of effective, evidence-based policymaking. Most Americans rarely examine these data points, yet they underpin everyday policies, from tracking foodborne disease outbreaks to confirming what every New Yorker already knows about rent. But this is about much more than numbers or policymaking. This is about the survival of our ability to source information that protects us from authoritarianism.
The erosion of data threatens American democracy because objective national statistics are one of the most powerful tools we have to contest authority. As Finland’s Director General of Statistics Jeskanen-Sundström asserted at the 60th United Nations Statistical Commission: “The independence of official statistics has the same status as the freedom of speech.” When governments weaken institutions that protect data from political interference, they gain the power to distort reality.
Manipulated or erased information undermines journalists, civil society, and any effort to hold governments accountable. Democratic backsliding often unfolds incrementally, targeting information systems as mechanisms of control. Without reliable data, how do we advocate for policy change, hold leaders accountable, or even cast an informed vote? What happens to democracy when we are stranded in a data desert engineered by the very governments we are meant to trust?
As a data professional, I know that data enthusiasts are always parched in a desert of “missing data.” But today, even policy practitioners are racing against time. There’s a new anxiety about data loss radiating beyond data science classrooms into the academic halls of public health, environmental science, and social work.
Much critical research remains on hold as academics rush to archive thousands of costly federal datasets before they disappear. GIS classmates scramble to replace EJScreen in their geospatial analyses. Public health students are suddenly cut off from the very health surveillance data they are being trained to interpret. When these policymakers lack granular data on their constituencies, they struggle to identify and address disparities in marginalized communities. Without reliable evidence, they cannot craft effective responses to economic, health, or social challenges affecting all 340 million Americans.
Critics of federal data collection often conflate two fundamentally different concepts: individualized surveillance and population statistics. That confusion is convenient, because it lets data deletion masquerade as a privacy measure when it is really a tactic to restrict access to information. With existing safeguards, public data cannot be used to target individuals: Census data, labor statistics, and public health metrics are anonymized through rigorous disclosure‑avoidance techniques and in accordance with federal privacy laws.
When properly redacted, data cannot be weaponized against people. What it can do, however, is expose government failures. Deleting entire datasets to control political narratives around economic performance, immigration, and public health is as strategic as it is repressive—and existing federal provisions are not strong enough to stop it.
Federal regulations offer little protection when political actors choose to destroy information that challenges their agenda. Regrettably, political leaders have brandished “ideological capture” before a politically aligned Department of Justice and federal government to justify removing critical datasets from the National Institutes of Health (NIH), the National Oceanic and Atmospheric Administration (NOAA), and the Centers for Disease Control and Prevention (CDC), as well as sidelining the experts who produce and defend those statistics. Rather than serving as a medium for ideological capture, uncoordinated data purges merely waste taxpayer dollars already invested in decades of data infrastructure and cripple policymakers’ ability to make cost-effective decisions. Meanwhile, firing statistical commissioners immediately after they release unfavorable employment data does not eliminate bias—it fuels bias.
We need constitutional protections for national statistics and stronger state-level legal safeguards to guarantee regular data collection. Lawmakers must update legislation to enshrine statistical independence and shield data from ideological interference. Many of my peers will become the policy leaders shaping our future information systems; I urge you to defend the critical data infrastructure that keeps our country running. U.S. democracy depends on trusted, independent statistics—and we cannot afford its continued erosion.