MS NOW95%

DOGE was a dishonest sham — that still hurt our country0%

By Zeeshan Aleem0%

12/25/2025, 11:00:00 AM

BS Summary: This article contains 19 faulty reasoning types, including Framing Effect, Confirmation Bias, and Appeal to Authority, with Negativity Bias as the most egregious example at 59.6% saturation with 327 hits. Analysis detected 1,639 faulty-reasoning hits from 549 analyzed words, generating a BS Score of 0% and a BS Rank of 0% (0 of 16,813 articles). This article is better (less manipulative) than 100.00% of the article peer group.

Perhaps nothing so succinctly defines the brief and terrible existence of President Donald Trump’s Department of Government Efficiency, which appeared to shutter quietly in November, as much as deception. 
A comprehensive New York Times analysis found some startling data on DOGE that indicate its claims of having slashed government spending were packed with false advertising. 
According to the Times, DOGE’s 13 largest claims about cuts were all incorrect, and many were totally false: 
At the top were two Defense Department contracts, one for information technology, one for aircraft maintenance. 
Mr. Musk’s group listed them as “terminations,” and said their demise had saved taxpayers $7.9 billion. 
That was not true. 
The contracts are still alive and well, and those savings were an accounting mirage. 
Together, those two false entries were bigger than 25,000 of DOGE’s other claims combined. 
Of the 40 biggest claims on DOGE’s list, The Times found only 12 that appeared accurate  reflecting real reductions in what the government had committed to spend. 
When you put all the numbers together, they help explain why federal spending went up even as DOGE chief Elon Musk took a chainsaw to the government’s programs. 
As early as the spring there were signs that the claims of savings in Musk’s “wall of receipts” were riddled with misinformation. 
There was at least some hope that we’d eventually get an accurate accounting of what had been cut as Musk took down and tweaked information in response to call-outs from the media. 
But that didn’t happen. 
Like so much of the Trump era, the hype went unfulfilled. 
It’s hard to assess how much DOGE succeeded at what it set out to do. 
But we do know that it never even came close to achieving its absurd goal of saving $2 trillion. 
Just months into its existence it became clear that DOGE itself was inefficient in the way it executed its cuts  because obstacles and new costs, including lawsuits over its firings, lost productivity, re-hirings and huge amounts of paid leave, were expensive. 
At the same time, it was very clear that “efficiency” was largely a pretext for Trump to cut and discipline the federal civil service in an effort to create a government of unwavering loyalists. 
The chaos DOGE produced along the way undermined the putative goal of fiscal austerity, but it did succeed to some extent in degrading social services and cutting or intimidating government workers who might’ve been less compliant with some of Trump’s more extreme orders. 
As The New Republic summed it up, “DOGE’s legacy is both very stupid and very sad: It decimated the federal workforce, including Social Security personnel at local offices, and made it easier for hackers to access your data. 
The agency tore apart USAID, which resulted in hundreds of thousands of lives lost globally. 
And all this for projected savings—numbers that grew smaller and less ambitious every time Musk mentioned them.” 
That duality of stupid and sad  or as my colleague Hayes Brown has memorably put it, the achievement of “the dumbest dystopia”  is a useful analytic lens for the Trump era. 
We can be thankful that DOGE ran haphazardly into obstacles and that the project demoralized Musk. 
But it nevertheless degraded the government and left our country and the world worse off. 
Actor-Observer Bias
0%
Anchoring Bias
7.3%
Availability Heuristic
0%
Blind-Spot Bias
0%
Confirmation Bias
42.8%
Dunning-Kruger Effect
0%
Framing Effect
54.1%
Fundamental Attribution Error
6.2%
Halo Effect
0%
Hindsight Bias
16.8%
Horn Effect
0%
In-Group Bias
6%
Loss Aversion
0%
Negativity Bias
59.6%
Optimism Bias
5.8%
Out-Group Homogeneity Bias
6.2%
Overconfidence Bias
0%
Pessimism Bias
0.7%
Primacy Effect
0%
Recency Bias
0%
Representativeness Heuristic
0%
Self-Serving Bias
2.9%
Status Quo Bias
0%
Sunk Cost Effect
0%
Ad Hominem
6.2%
Ambiguity (Equivocation)
11.1%
Anecdotal
0%
Appeal to Authority
26%
Appeal to Emotion
2.7%
Appeal to Nature
0%
Bandwagon
0%
Begging the Question
0%
Burden of Proof
0%
Circular Reasoning
0%
Composition/Division
0%
False Dilemma
0%
Gambler’s Fallacy
0%
Genetic Fallacy
6.2%
Hasty Generalization
11.7%
Middle Ground
0%
No True Scotsman
0%
Personal Incredulity
0%
Post Hoc (False Cause)
18.4%
Red Herring
0%
Slippery Slope
7.8%
Special Pleading
0%
Straw Man
0%
Tu Quoque
0%

549 words analyzed.

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.