The following is a guest post and opinion from Ahmad Shadid, Founder of O.xyz.
Under the flimsy pretext of efficiency, the Department of Government Efficiency (DOGE) is gutting its workforce. An independent report suggests that DOGE has slashed around 222,000 job cuts in March alone. The cuts are hitting hardest in areas where the U.S. can least afford to fall behind — artificial intelligence and semiconductor development.
Now the bigger question is beyond gutting the workforce – it is that Musk’s Department of Government Efficiency is using artificial intelligence to snoop through federal employees’ communications, hunting for any whiff of disloyalty. It is already creeping around the EPA.
DOGE’s AI-first push to shrink federal agencies feels like Silicon Valley gone rogue—grabbing data, automating functions, and rushing out half-baked tools like the GSA’s “intern-level” chatbot to justify cuts. It’s reckless.
Besides that, according to a report — DOGE “technologists” are deploying Musk’s Grok AI to monitor Environmental Protection Agency employees with plans for sweeping government cuts.
Federal workers, long accustomed to email transparency due to public records laws, now face hyper-intelligent tools dissecting their every word.
How can federal employees trust a system where AI surveillance is paired with mass layoffs? Is the United States quietly drifting towards a surveillance dystopia, with artificial intelligence amplifying the threat?
AI-Powered Surveillance
Can the AI model trained on government data be trusted? Besides that, using AI into a complex bureaucracy invites classic pitfalls: biases—issues GSA’s own help page flags without clear enforcement.
The increasing consolidation of information within AI models poses an escalating threat to privacy. Besides that, Musk and DOGE are also violating the Privacy Act of 1974. The Privacy Act of 1974 came into effect during the Watergate scandal which aimed to curb the misuse of government-held data.
According to the act — no one, not even the special government employees—should access agency “systems of records” without proper authorization under the law. Now the DOGE seems to be violating the privacy act in the name of efficiency. Is the push for government efficiency worth jeopardizing Americans’ privacy?
Surveillance isn’t just about cameras or keywords anymore. It’s about who processes the signals, who owns the models, and who decides what matters. Without strong public governance, this direction ends with corporate-controlled infrastructure shaping how the government operates. It sets a dangerous precedent. Public trust in AI will weaken if people believe decisions are made by opaque systems outside democratic control. The federal government is supposed to set standards, not outsource them.
What’s at stake?
The National Science Foundation (NSF) recently slashed more than 150 employees, and internal reports suggest even deeper cuts are coming. The NSF funds critical AI and semiconductor research across universities and public institutions. These programs support everything from foundational machine learning models to chip architecture innovation. The White House is also proposing a two-thirds budget cut to NSF. This wipes out the very base that supports American competitiveness in AI.
The National Institute of Standards and Technology (NIST) is facing similar damage. Nearly 500 NIST employees are on the chopping block. These include most of the teams responsible for the CHIPS Act’s incentive programs and R&D strategies. NIST runs the US AI Safety Institute and created the AI Risk Management Framework.
Is DOGE Feeding Confidential Public Data to the Private Sector?
DOGE’s involvement also raises a more critical concern about confidentiality. The department has quietly gained sweeping access to federal records and agency data sets. Reports suggest AI tools are combing through this data to identify functions for automation. So, the administration is now letting private actors process sensitive information about government operations, public services, and regulatory workflows.
This is a risk multiplier. AI systems trained on sensitive data need oversight, not just efficiency goals. The move shifts public data into private hands without clear policy guardrails. It also opens the door to biased or inaccurate systems making decisions that affect real lives. Algorithms don’t replace accountability.
There is no transparency around what data DOGE uses, which models it deploys, or how agencies validate the outputs. Federal workers are being terminated based on AI recommendations. The logic, weightings, and assumptions of those models are not available to the public. That’s a governance failure.
What to expect?
Surveillance doesn’t make a government efficient, without rules, oversight, or even basic transparency, it just breeds fear. And when artificial intelligence is used to monitor loyalty or flag words like “diversity,” we’re not streamlining the government—we’re gutting trust in it.
Federal workers shouldn’t have to wonder if they’re being watched for doing their jobs or saying the wrong thing in a meeting.This also highlights the need for better, more reliable AI models that can meet the specific challenges and standards required in public service.
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