Statistical Bias and Perception Management: Kahneman’s Insights and the Department of Government Efficiency

In Thinking, Fast and Slow[1], Daniel Kahneman argues that people struggle with statistical thinking and instead rely on intuition, leading to biases and judgment errors. He identifies several cognitive biases, including neglect of base rates, the law of small numbers, overconfidence in intuition, and the availability heuristic. These biases shape how people interpret information, often leading to misleading conclusions.

Kahneman’s Ideas and the Department of Government Efficiency (DOGE)

Kahneman’s insights help explain the perception management occurring in the U.S. regarding Elon Musk’s Department of Government Efficiency (DOGE). By emphasizing small departments or specific cases, DOGE shapes public opinion about government inefficiency in a way that broader statistical trends do not support.

Neglect of Base Rates: Ignoring the Big Picture

A common narrative suggests that the U.S. federal government workforce is excessively large and inefficient. However, the data tells a different story. In 1980, the federal government employed 2 million people to support a population of 220 million. In 2024, that number remains at 2 million, now supporting 360 million people—a significant efficiency gain over 45 years.

In contrast, state and local government employment has grown steadily, reaching nearly 20 million workers in 2024 due to population growth and service expansion. Of these, about 5.5 million are state employees and 14.6 million are local employees, with the majority in education. In 1980, state and local governments employed approximately 14.8 million people, reflecting a long-term expansion in education, healthcare, and law enforcement.

Yet, DOGE’s focus remains on the federal level, reinforcing a misleading perception of inefficiency while overlooking broader employment trends.

The Law of Small Numbers: Drawing Big Conclusions from Small Cases

A few cases of corruption or misconduct in government agencies can create the illusion of widespread inefficiency, even when these cases are statistically rare.

For example, reductions in wasteful spending within USAID have minimal impact on overall government expenditures. In fiscal year 2024, USAID spent approximately $32 billion[2] out of a $6.75 trillion federal budget—less than 0.5% of total spending. However, by selectively highlighting such expenditures, narratives can suggest a larger systemic issue, even when broader statistical data tells a different story.

Over 80% of the federal budget[3] is managed by four departments: Health and Human Services (27%), Social Security (22%), Treasury (19%), and Defense (13%). Yet, discussions rarely focus on these, except when the Republican Party announces major cuts to Medicare and Medicaid to fund tax cuts for the wealthy and border security[4].

Availability Heuristic: What’s Most Visible Seems Most Important

Repetition in the media significantly influences public perception. White House Press Secretary Karoline Leavitt frequently emphasizes specific examples of waste, fraud, and abuse, reinforcing the belief that government inefficiency is widespread.

Examples put forward by the administration include[5]:

• $1.5 million to “advance diversity, equity, and inclusion in Serbia’s workplaces and business communities”
• $70,000 for a “DEI musical” in Ireland
• $2.5 million for electric vehicles in Vietnam

While these expenditures may warrant scrutiny, their selective emphasis distorts the broader picture. The availability heuristic leads people to judge government efficiency based on isolated cases rather than comprehensive analysis.

How This Is Used for Political Confusion

By focusing on small departments or specific cases, different groups manipulate public perception. A small case can be amplified to suggest systemic corruption or bias. The complexity of government operations allows cherry-picking of data to confirm existing biases.

Although federal agencies operate on a national scale, the focus on isolated cases, specific divisions, or temporary shifts in priorities can lead people to believe these cases reflect a broader systemic failure.

Bottom Line

Kahneman’s work explains why people are easily swayed by narratives focusing on small, emotionally charged cases rather than broad statistical reality. The way legal and political issues are framed by the White House often plays on these cognitive biases, making it difficult for the public to see the full picture objectively. By applying these insights, it becomes clear that Musk’s Department of Government Efficiency is leveraging cognitive biases to shape perceptions of inefficiency, even when broader data suggests that government efficiency (as measured by employment) may have? improved significantly over time.

Sources:

1. Kahneman, Daniel, 1934-2024, author. (2011). Thinking, fast and slow. New York :Farrar, Straus and Giroux
2. https://www.cato.org/commentary/usaid-failed-because-foreign-aid-doesnt-work
3. https://fiscaldata.treasury.gov/americas-finance-guide/federal-spending/#:~:text=Federal%20government%20spending%20pays%20for,primary%20categories%3A%20mandatory%20and%20discretionary.
4. https://www.politico.com/news/2025/01/10/spending-cuts-house-gop-reconciliation-medicaid-00197541
5. https://www.dailymail.co.uk/news/article-14344255/trump-millions-dei-foreign-aid-programs-funding.html