The Department of Government Efficiency, or DOGE, has gained access to sensitive federal databases, including those from the IRS and Social Security Administration. This access raises concerns about cybersecurity and privacy. But there's another worry: using this data to train AI systems for private companies.
DOGE personnel hold positions in companies owned by Elon Musk. This dual employment creates a pathway for federal data to potentially flow to Musk's enterprises, including xAI. The company's latest AI chatbot, Grok, doesn't clearly deny using such data.
For AI developers, government databases are incredibly valuable. They offer verified records of real human behavior across entire populations. This data is different from what's available online. Social media posts and web browsing histories show curated or intended behaviors, but government databases capture real decisions and their consequences.
Government databases track entire populations over time, not just digitally active users. This means training AI systems on the actual diversity of human experience, rather than just digital reflections. Current AI systems face limitations because they're trained on information that might be popular but isn't necessarily true.
Government data could change this. Training an AI system on actual treatment outcomes across millions of patients, for example, could provide insights that go beyond opinions about health care. A large, state-of-the-art model trained on comprehensive government data could understand the actual relationships between policies and outcomes.
A company like xAI could use this data to transform and potentially control how people understand and manage complex societal systems. Medicare and Medicaid databases contain records of treatments, outcomes, and costs across diverse populations over decades. A frontier model trained on new government data could identify treatment patterns that succeed where others fail.
Treasury data is perhaps the most valuable prize. It contains granular details about how money flows through the economy. An AI company with access to this data could develop extraordinary capabilities for economic forecasting and market prediction. It could model the cascading effects of regulatory changes, predict economic vulnerabilities before they become crises, and optimize investment strategies with precision.
Government databases also contain information about critical infrastructure usage patterns, maintenance histories, emergency response times, and development impacts. An AI system trained on this data would understand how transportation patterns affect energy use, how housing policies affect emergency response times, and how infrastructure investments influence economic development across regions.
A private company with exclusive access to this data could gain unique insight into the physical and economic arteries of American society. This could allow the company to develop "smart city" systems that city governments would become dependent on, effectively privatizing aspects of urban governance.
The threat of a private company accessing government data goes beyond individual privacy concerns. Even with personal identifiers removed, an AI system that analyzes patterns across millions of government records could enable surprising capabilities for making predictions and influencing behavior at the population level. The threat is AI systems that leverage government data to influence society, including electoral outcomes.
Since information is power, concentrating unprecedented data in the hands of a private entity with an explicit political agenda represents a profound challenge to the republic. The question is whether the American people can stand up to the potentially democracy-shattering corruption such a concentration would enable.
