In a bold and controversial move emblematic of Elon Musk’s unconventional approach to governance, the Department of Government Efficiency (DOGE) has placed a college student in charge of using artificial intelligence to rewrite and dismantle federal regulations. The student, a 21-year-old from the University of Chicago currently on academic leave, has been tasked with deploying AI models to streamline regulations within the Department of Housing and Urban Development (HUD), raising serious questions about oversight, qualifications, and the future of public policy.
Despite having no prior experience in government or law, the student was granted access to internal HUD systems and regulatory databases to begin work on simplifying what the administration has called “bloated and inefficient” bureaucratic processes. The AI models he leads are designed to scan thousands of pages of federal housing regulations, identify perceived redundancies or overreach, and generate suggested rewrites. In many cases, HUD staff must now respond to these AI-generated suggestions by justifying the necessity of the existing rules.
The initiative is part of a broader government push under Project 2025, an aggressive deregulatory agenda championed by DOGE and backed by Musk’s vision of leaner, tech-driven government. While some insiders have praised the move as a much-needed shake-up, many observers in Washington and across the regulatory field have expressed alarm at the use of an unvetted AI system led by someone with limited real-world experience.
Critics argue that housing regulations protect some of the most vulnerable populations in the country, including low-income families, seniors, and people with disabilities. Entrusting this system to a college student, they say, not only risks errors in judgment but also raises ethical concerns around privacy, policy bias, and accountability. Lawmakers have started to question whether this AI overhaul is a genuine attempt at reform or a reckless experiment in governance.
Nevertheless, the student has already expanded his role, with AI systems now targeting other areas of HUD policy and potentially other departments. He reportedly works closely with a small team of data scientists and policy analysts but remains the central figure in the initiative, shaping how AI is used to rethink the rules that govern housing, urban development, and possibly beyond.
The case highlights a growing trend in government and industry alike: the rush to use AI for complex decision-making without fully understanding its implications. In this instance, it also underscores the tension between innovation and institutional responsibility. As the AI-driven deregulation push continues, many are left wondering whether the benefits of speed and efficiency outweigh the risks of inexperience and overreach.
