FILE PHOTO: The exterior of the Marriner S. Eccles Federal Reserve Board Building is seen in Washington, D.C., U.S., June 14, 2022. REUTERS/Sarah Silbiger/File Photo
TOKYO (Reuters) -A simulated Federal Reserve meeting that used artificial intelligence agents modeled on real-life policymakers showed political pressure polarised members of the board in their rate-setting deliberations.
In the study released on August 31, academics at George Washington University simulated a Federal Open Market Committee meeting using AI agents modeled by each member based on their historical policy stances, biographies and speeches.
