When the Numbers Lie

What happens when the government’s facts no longer align with the public’s reality—and data becomes a tool of power instead of a public good.

Federal data. Yawn, right? But what’s happening to it is terrifying—and we need to pay attention.

There are countless ways to lie with numbers. So when we can no longer trust government data, the consequences run deeper than statistical error. We lose our bearings. As this administration continues to politicize federal agencies and staff them with loyalists, the risk isn’t just that the data will be wrong—but that it will be weaponized to support the president’s gaslighting and falsehoods.

There’s a threshold that’s easy to miss but unmistakable once crossed: the moment when government data no longer reflects reality. A little distortion is enough to render the facts unreliable. And when that happens, the trust that holds shared understanding together begins to fray.

We’re seeing this now across multiple domains. It’s a pattern, sometimes subtle, sometimes blatant, that shifts data from a means of governance to a mechanism of control. As it progresses, the gap between official narrative and lived experience widens. At a certain point, the gap becomes a rupture.

Employment numbers offer a clear example. The headline unemployment rate suggests progress, but it leaves out millions—those working multiple jobs, stuck in gig work, or who’ve stopped looking altogether. If they’re not counted, they’re not addressed. And what doesn’t get addressed is allowed to fester.

The Consumer Price Index, the most widely cited inflation metric, has been retooled in ways that systematically understate rising costs. The most punishing expenses—housing, food, healthcare—are softened through formulas that assume quality gains offset price increases. But for those watching rent and grocery bills climb, abstract gains don’t count. When they’re told inflation is easing, but their paychecks don’t stretch far enough, disbelief isn’t irrational—it’s earned.

The damage to the credibility of CDC data during the pandemic—delayed reports, redactions, politicized framing—hasn’t been repaired. We still see incomplete reporting on vaccine uptake, long COVID, and chronic illness. In many states, disaggregated data isn’t submitted at all. The public health narrative becomes partial by design. When the numbers are obscured, the response can be, too.

Robert F. Kennedy Jr.’s ongoing anti-vaccine campaign feeds on this mistrust. He exploits the vacuum created by real lapses in transparency and builds a movement on partial truths and skewed interpretation. The damage isn’t limited to public health—it extends to how data itself is understood and contested.

The Centers for Medicare and Medicaid Services have adopted new prior authorization rules in the name of efficiency. But in practice, what’s tracked is throughput—not whether patients received appropriate care. The appearance of functionality replaces the substance of it.

Government data is not just information—it’s infrastructure. It underpins decisions across nearly every sector of society. When that foundation is corrupted, planners can’t plan, businesses can’t forecast, researchers can’t track trends, and communities can’t prepare. The damage isn’t contained to public trust. It seeps into the daily operations of hospitals, schools, housing authorities, disaster agencies, and courts. A broken dataset isn’t just a political failure. It’s a systems failure.

These distortions don’t happen by accident. They serve someone. A suppressed CPI lets employers dodge wage increases. Claim denials help insurers cut costs. Softened climate projections give political cover to delay action. The damage isn’t evenly distributed. The profits are.

EPA reporting follows a similar path. Reports warn of worsening air quality, hazardous sites, and heat extremes—but the language is muted, the enforcement mechanisms weakened, and risk thresholds adjusted. The science is clear, but its policy implications are buried. In 2023, the Supreme Court’s West Virginia v. EPA decision and recent administrative actions recast CO₂ as a “naturally occurring gas,” not a pollutant. Industrial polluters continue expanding with fewer checks, and communities bear the cost.

Climate data, once a technical field, is now a terrain of political messaging. Agencies issue warnings but often soften the language or decouple forecasts from immediate decisions. The science persists, but its framing is filtered. The reports keep coming, but nothing follows. People stop listening not because they’re in denial, but because they no longer believe the reports will lead to action.

In education, test scores and graduation rates are up—but so is teacher attrition. Budgets are slashed, classrooms overcrowded, and basic literacy suffers. The statistics say the system is holding. Inside the system, everyone knows it’s falling apart.

The decline of public data doesn’t mean there’s less data. There’s more—only now it’s behind paywalls. Wall Street, tech firms, and logistics companies have access to real-time analytics: geolocation, purchase history, consumption patterns. The public gets headline stats. The powerful get foresight. This isn’t a crisis of information scarcity—it’s stratification.

From an anthropological view, data regimes are moral frameworks. They define what counts, and who counts. They assign recognition. If a category disappears from the data, it disappears from policy, and eventually, from view. “Disabled,” “unhoused,” “underemployed”—these aren’t neutral descriptors. They determine access to resources, or exclusion from them. When the definitions shift to save money or protect image, it isn’t reform—it’s erasure.

Data doesn’t simply record the world. It organizes it. It renders some lives legible to institutions and leaves others out. From a political ecology standpoint, that has material consequences. Without reliable climate data, communities can’t plan. Without honest health statistics, vulnerabilities go unmanaged. Risk accumulates—unseen, unmeasured, unaddressed.

The threat doesn’t stop at public statistics. When data becomes a tool of political control, personal data is not immune. Health records, tax filings, credit histories, even digital identity markers—these are all governed by systems vulnerable to manipulation. Once the precedent is set that official data can be shaped to serve power, the door opens to targeted abuse. The same apparatus that hides inflation or distorts climate risk could quietly alter a medical file, a criminal record, or a voting roll. A society that tolerates statistical deceit will find it harder to resist the weaponization of personal data. What begins as a breakdown in public trust can become a mechanism of private harm.

And when data fails, people don’t stop trying to understand the world—they turn elsewhere. To anecdote, rumor, partisan media, or conspiracy. That shift isn’t just a symptom of polarization. It’s a rational adaptation to the collapse of institutional credibility.

Some call this politics as usual. But what we’re seeing is more than spin. It’s systemic. It’s the gradual withdrawal of accountability disguised as modernization. The data is still there—just not where the public can use it.

When official numbers are shaped to protect the powerful, public reasoning breaks down. Shared problems become private burdens. Collective risk becomes individualized confusion. Decision-making turns into performance, presented in graphs but disconnected from reality.

Rebuilding trust in public data isn’t just about better charts or cleaner dashboards. It’s about reclaiming the idea that information belongs to the people it affects. That data should serve the public, not manage its expectations.

Because when the numbers lie, what’s at stake isn’t just accuracy—it’s whether people can act on what they know, or are left to guess in the dark.

Suggested Readings

Eubanks, Virginia. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York: St. Martin’s Press, 2018.

Foucault, Michel. The Birth of Biopolitics: Lectures at the Collège de France, 1978–1979. Edited by Michel Senellart. Translated by Graham Burchell. New York: Picador, 2010.

Jasanoff, Sheila. The Ethics of Invention: Technology and the Human Future. New York: W.W. Norton, 2016.

O’Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown Publishing, 2016.

Porter, Theodore M. Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. Princeton: Princeton University Press, 1995.

United States Centers for Disease Control and Prevention (CDC). COVID-19 Data Tracker. Atlanta: U.S. Department of Health and Human Services, 2024. https://covid.cdc.gov/covid-data-tracker.

Vélez-Ibáñez, Carlos G. The Rise of Necro/Narco-Citizenship: Belonging and Dying in the National Borderlands. Tucson: University of Arizona Press, 2025.