The Risks of Private AI Access to Government Data
By Allison Stanger, Published March 9, 2025
The Department of Government Efficiency (DOGE) has gained unprecedented access to several sensitive federal databases, including those of the Internal Revenue Service and the Social Security Administration. This access has ignited concerns about potential cybersecurity vulnerabilities and privacy violations. However, a less discussed but equally significant issue is the possible use of this data to train the artificial intelligence systems of a private company.
While White House officials have stated that the government data collected by DOGE is not being used to train Elon Musk’s AI models, despite Musk’s control over DOGE, evidence suggests a potential conflict of interest. DOGE personnel simultaneously hold positions within at least one of Musk’s companies, creating a potential pathway for the transfer of federal data to Musk-owned enterprises, including xAI. The company’s latest AI chatbot, Grok, has conspicuously avoided offering a clear denial regarding the use of such data. As a political scientist and technologist familiar with government data applications, I believe that the possible transmission of government data to private companies presents far greater privacy and power implications than is commonly reported.
Value of Government Data for AI
For AI developers, government databases are something akin to the Holy Grail. While companies such as OpenAI, Google, and xAI currently depend upon information scraped from the public internet, nonpublic government repositories provide something much more valuable: verified records of actual human behavior across entire populations. This isn’t merely more data – it is fundamentally different data. Social media posts and web browsing histories reflect curated or intended behaviors, but government databases capture real decisions and their consequences.
For example, Medicare records reveal healthcare choices and outcomes. IRS and Treasury data reveal financial decisions and long-term impacts while federal employment and education statistics reveal career paths.
What makes this data particularly valuable for AI training is its longitudinal nature and reliability. Unlike the disorganized information available online, government records follow standardized protocols, undergo regular audits, and adhere to legal requirements for accuracy. Every Social Security payment, Medicare claim, and federal grant creates a verified data point about real-world behavior. This data exists nowhere else with such breadth and authenticity in the U.S. Most critically, government databases track entire populations over time, not just digitally active users; they include people who never use social media, don’t shop online, or avoid digital services. For an AI company, this would mean training systems on the actual diversity of human experience, rather than just the digital reflections people cast online.
The Technical Advantage
Existing AI systems are limited in ways that no amount of internet data can overcome. When ChatGPT or Google’s Gemini make mistakes, it’s often because they’ve been trained on information that might be popular but isn’t necessarily true. They can tell you what people say about a policy’s effects, but they can’t track those effects across populations and years. Government data could change this.
Consider training an AI system not just on opinions about healthcare but on actual treatment outcomes across millions of patients. Imagine the difference between learning from social media discussions about economic policies and analyzing their real impacts across different communities and demographics over decades. A large, state-of-the-art AI model trained on comprehensive government data could understand the relationships between policies and outcomes. It could track unintended consequences across different population segments, validate complex societal systems model with real-world data and also, predict the impacts of proposed changes based on historical evidence.
For companies seeking to build next-generation AI systems, access to this data could be an overwhelming advantage.
Control of Critical Systems
A company like xAI could do far more with models trained on government data than building better chatbots or content generators. Such systems could fundamentally 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 government data could identify treatment patterns that succeed while others fail, and so dominate the health care industry. Such a model could understand how different interventions affect various populations over time, accounting for factors such as geographic location, socioeconomic status, and concurrent conditions. A company wielding the model could influence healthcare policy by demonstrating superior predictive capabilities and market population-level insights to pharmaceutical companies and insurers.
Treasury data represents perhaps the most valuable prize. Government financial databases contain detailed information about how money flows through the economy, including real-time transaction data across federal payment systems, complete records of tax payments and refunds, detailed patterns of benefit distributions, and government contractor payments with performance metrics. An AI company with access to this data could develop extraordinary capabilities for economic forecasting and market prediction.
Infrastructure and Urban Systems
Government databases contain information about critical infrastructure usage patterns, maintenance histories, emergency response times, and development impacts. Every federal grant, infrastructure inspection, and emergency response creates a data point that could help train AI to better understand how cities and regions function. The power lies in the potential interconnectedness of this data. Private companies with exclusive access could gain unique insight into the physical and economic arteries of American society, allowing them to develop what they call “smart city” systems that city governments would become dependent on. When combined with real-time data from private sources, the predictive capabilities would far exceed what any current system can achieve.
Absolute Data Corrupts Absolutely
A company such as xAI, with Musk’s resources and preferential access through DOGE, could overcome technical and political obstacles much more easily than competitors. Recent advances in machine learning have also reduced the burdens of preparing data for the algorithms to process, making government data a veritable gold mine – one that rightfully belongs to the American people.
The threat of a private company accessing government data transcends 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. I believe that the question is whether the American people can stand up to the potentially democracy-shattering corruption such a concentration would enable. If not, Americans should prepare to become digital subjects rather than human citizens.
Allison Stanger, Distinguished Endowed Professor, Middlebury
This article is republished from The Conversation under a Creative Commons license.
