The Trump administration has identified a key weapon in its campaign to remake the federal government: information control. Shortly after taking office, it ordered federal health agencies to freeze their communications with the public. The government promptly scrubbed many of its websites of data about climate change, public health, foreign aid and education. The Department of Government Efficiency slashed federal data-gathering activities, and the president fired the commissioner of the Bureau of Labor Statistics after a middling July jobs report.
As a scholar of information law and policy, I see a dangerous transformation: Instead of using data to determine how to govern, the administration is manipulating, ignoring and even jettisoning data altogether. Those who balk at the administration’s wishful thinking about reality face threats to fall in line or leave, as Jerome Powell, Lisa Cook and now the C.D.C. director, Susan Monarez, have all experienced.
The administration has clearly embraced the strategic cultivation of uncertainty and ignorance. It is not just trying to trim the fat from its statistical agencies, which were already underfunded before President Trump took office. Nor is it simply trying to spin the available data to its political advantage. Instead, it is turning away from the government’s responsibilities as a steward of information by minimizing, cherry-picking, misusing and sometimes even destroying data.
The idea that government ought to make decisions using evidence and hard data is a cornerstone of our political order. The Administrative Procedure Act, for example, proscribes “arbitrary” or “capricious” agency decisions. And the Foundations for Evidence-Based Policymaking Act of 2018 requires agencies to develop data and evidence to support their policymaking. Those laws reflect our expectation that the government will make rational judgments.
To be sure, Mr. Trump’s cavalier attitude toward evidence and the truth is well documented. This is different. The president isn’t just trying to manipulate his image or public opinion. He is reshaping the state’s relationship to data and evidence altogether. Because many of the government’s statistical and informational responsibilities are invisible, the changes afoot will not garner the same kind of outrage as the administration’s efforts to target political opponents or minorities.
Of all the targets of Mr. Trump’s ire, the federal statistical system might seem the least important. The work of counting, calculating, analyzing and tabulating information sounds like the pinnacle of bureaucratic drudgery, unseen and underappreciated. That’s certainly how DOGE typecast it when it promised to eliminate information-gathering activities it deemed overkill.
But in the United States, statistics are practically baked into the structure of government. Article I, Section 2 of the Constitution requires the government to count the nation’s population every 10 years to apportion representatives. Congress passed the Census Act in only its second session. The decennial census was one of the earliest efforts by a nation-state to enumerate its population.
The government’s collection of data and its production of statistical information count among its core responsibilities. Increasingly, however, the administration is abandoning those functions. Consider Mr. Trump’s announcement that the Census Bureau should stop counting undocumented immigrants in the data collection. Though his proposal is fuzzy, a purposefully misleading census will change not only how congressional maps are drawn and federal funds distributed, but also how we understand the nation.
Across the government, the administration appears to be winding down many efforts to collect, validate and produce reliable information. In March, the Trump administration announced that it would not enforce provisions of the Corporate Transparency Act that required corporations to disclose the identities of their anonymous owners — information critical to the enforcement of anti-money-laundering rules. The administration is reportedly decommissioning perfectly useful satellites, leaving at least one of them to incinerate in the atmosphere rather than using it to collect important data about emissions.
These decisions not to collect, produce and validate information are stark departures from historical practice. Without accurate information, it’s impossible to enforce federal laws, monitor economic conditions, assess risks and allocate resources. That’s why since the New Deal, the United States has built a vast administrative apparatus around the collection of information. Spread across more than a dozen agencies, operating under different statutory authorities, these efforts result in the collection and production of statistical information of all sorts, about things such as crime, climate, H.I.V./AIDS and housing.
This year, The Wall Street Journal described the government’s statistical efforts as among its “least political tasks.” But statistics has never been unpolitical — it has always been about the state. Before a German professor began using the term “Statistik” in the 18th century, the field was known as “political arithmetic.” From its earliest days, statistics was a means to govern populations, measure risks and predict outcomes. As self-described “statists” developed the discipline in the 19th century, they linked themselves explicitly to the state, seeking to give a factual basis to governance.
For well over a century, data and information have been central to the idea of a rational and beneficial government. During the Progressive era, reformers deployed statistical analysis to make regulation more of a science and less of a guessing game. Alongside sunshine laws and muckraking journalism, statistics and data were part of a political project meant to limit the exercise of arbitrary power. During the Cold War, quantitative approaches like operations research, economic analysis and game theory remade policy again in a more scientific mold. Now the availability of huge quantities of data, algorithmic decision making and artificial intelligence promises a new age of data-driven governance.
Today, real people and institutions depend on government data to inform and guide decision-making. Even before Mr. Trump fired Erika McEntarfer, the commissioner of labor statistics, this month, economists were warning that mucking about with the government’s economic statistical activities was risky: Changing the expectations about economic conditions can shape investment decisions and the Fed’s decision-making about interest rates. If economic statistics go wrong, it isn’t just a problem for government bureaucrats or pointy-headed researchers. The nation’s captains of industry will also be adrift in a sea of uncertainty.
Now Mr. Trump is amping up his war on economic reality by targeting the integrity of the Federal Reserve — one of the oldest and most significant producers of economic indicators and banking data — as he tries to pressure it to cut interest rates. His effort to fire the Fed governor Lisa Cook over unproven allegations of mortgage fraud underscores how information is also a critical weapon when the administration wants it to be.
A government based on deliberate indifference to information and data is a dangerous one. By turning away from evidence when it doesn’t suit, the administration is showing that it doesn’t think it matters whether it has the better argument, so long as it has the power to rule as it desires.
Of course, data-driven decision-making has never been as effective at limiting power as we might have imagined. But what I see is an administration that is not just trying to distort data or represent it differently. The administration is rejecting the idea of rational governance altogether, looking away from its responsibility to produce and validate evidence in favor of a return to policymaking through instinct, hunch and preference.
Hannah Bloch-Wehba is a professor at Texas A&M University School of Law.
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