Recently, researchers from George Washington University conducted a revolutionary experiment: they simulated a meeting of the Federal Open Market Committee (FOMC) of the U.S. Federal Reserve, replacing real politicians with artificial intelligence agents. The study published on August 31, 2025, showed how political pressure polarizes decision-making regarding rates, even in a virtual environment.

The simulation recreated the July 2025 FOMC meeting. Each AI agent was modeled based on the biographies, speeches, and historical positions of real committee members, such as Fed Chair Jerome Powell. The agents discussed monetary policy, responding to hypothetical pressure from President Donald Trump to lower rates. The results are shocking: under "external pressure," the agents split into factions, leading to polarized voting. "This simulation demonstrates that the Fed is only partially insulated from politics, and external oversight shapes internal decisions, even in an institution with formal rules," the authors of the study noted.

The Fed is already using generative AI to analyze meeting minutes, while the European Central Bank applies machine learning to forecast inflation. The Bank of Japan tracks price factors using AI, and the Reserve Bank of Australia tests tools to enhance research efficiency. However, as a Fed representative emphasized, "we do not use AI for policymaking, only to improve efficiency."

This experiment highlights the risks of political interference in the independence of the Fed and the potential of AI to model scenarios. While a complete replacement of people with AI agents is still far off, the technology is already changing economic research. The future of monetary policy may become more predictable but also vulnerable to manipulation. The research calls for strengthening the Fed's isolation from politics to avoid real crises.

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