Poll reveals that voters are divided on the concept of DOGE and Elon Musk's handling of government efficiency cuts

Despite these numbers, when voters were asked about their general feelings towards DOGE, the tide turned. The favorability shifted with 47% holding negative views about the initiative, while only 41% held positive opinions. This flip in sentiment shows that while the public may endorse the goal of reform, its execution under Musk has stirred significant concern.


Elon Musk’s involvement in government reform doesn’t come without baggage. The poll found that 51% of respondents hold negative views of Musk, compared to 39% who view him positively. This unpopularity seems to have a direct influence on how voters perceive DOGE. Musk’s reputation for controversial statements and high-risk ventures has led many to view his approach with skepticism, particularly when it comes to something as crucial as government restructuring.

Musk’s Department of Government Efficiency, tasked with reducing government spending and workforce size, has faced backlash from both the public and political figures. Early moves by DOGE, including attempts to access sensitive information, cut jobs, and cancel contracts, have prompted multiple lawsuits and calls for caution. President Trump, despite supporting the cuts, has attempted to dial down the controversy by suggesting that department heads manage job reductions with precision, likening the approach to using a "scalpel" instead of a "hatchet."


While the concept of reducing government inefficiencies is generally supported, most Americans are not convinced that cutting back is the solution to the nation’s problems. According to the poll, 56% of voters believe the government should do more to address the needs of the public, while only 42% think that it is overstepping and that more responsibilities should be left to businesses and individuals. This preference suggests that many Americans feel the government still has a vital role to play in solving societal issues, even if its operation isn’t flawless.

Despite growing calls for government downsizing, federal workers seem to retain some public support. While the number of positive views on federal employees has dropped since 2019, with only 49% expressing favorable opinions now, this figure still marks an increase from past years, such as in 2011 when only 42% felt positively. This indicates that while dissatisfaction with inefficiency is common, there’s still an appreciation for the work federal employees do.


The real-world effects of DOGE’s actions are already being felt across the country. The poll reveals that 27% of voters—roughly one in four—say they or someone they know has been negatively affected by cuts to federal programs, benefits, or services due to DOGE’s initiatives. This group, particularly among self-identified Democrats, reports direct and personal consequences, such as nonprofit organizations losing funding, federal workers facing layoffs, or uncertainty surrounding job security in government roles.

While some respondents shared personal stories of job losses or cuts to critical funding, others expressed broader fears of future reductions. Concerns were particularly high among those who feared potential cuts to essential services like Medicaid, seeing DOGE’s actions as a harbinger of broader Republican-led budget changes. Around 14% of voters reported knowing someone directly affected by layoffs resulting from DOGE’s budget reductions, showing just how widespread the concern is.


The poll shows a complex picture of public sentiment towards Elon Musk’s DOGE initiative. While voters largely support the idea of government reform, the speed and execution of those cuts under Musk’s leadership are deeply divisive. With a significant portion of the public feeling negatively impacted by these changes, it’s clear that the debate over DOGE’s future is far from over. As the public weighs the benefits of reduced government inefficiency against the potential harm to vital services and federal workers, the path forward remains uncertain.