The article argues that the Federal Reserve's recent rate hike decision, while justifiable on inflation grounds, highlights a critical lack of an underlying, transparent policy framework. The core problem is that the Fed's decisions appear discretionary, leading to market uncertainty because the committee's judgment, rather than clear data, dictates policy shifts. The author proposes that the Fed adopt a formal monetary policy rule—an algebraic formula linking the target rate to indicators like inflation and unemployment—to replace subjective guidance. Implementing such a rule would provide market predictability, enhance transparency, and shield the Fed from political attacks by making deviations from the standard easily quantifiable.
What Trump's National Security AI Memo Gets Right—and Leaves Unresolved
English Summary
Trump's NSPM-11 directs accelerated AI adoption in national security agencies while maintaining safeguards through contracts and in-house testing, treating speed and accountability as joint requirements. The memo reflects an 'assured intelligence model' that manages U.S. dependence on frontier AI by building government leverage through competitive vendor relationships and strict control over deployed systems, directly responding to the Pentagon-Anthropic dispute over autonomous weapons use. A critical unresolved tension concerns who holds authority to set legal boundaries on AI use—the labs, executive branch, courts, or Congress. The CFR experts recommend Congress codify safeguarding mechanisms into defense legislation, though implementation credibility remains questioned given concerns about executive power constraints.
中文摘要
川普的NSPM-11指令要求國家安全機構加速採用人工智慧，同時透過合約和內部測試機制維持安全保障，將速度與問責制視為共同要求。這份備忘錄反映了一種「確保情報模型」（assured intelligence model），旨在透過建立競爭性的供應商關係和對已部署系統的嚴格控制，來管理美國對前沿人工智慧的依賴，從而提升政府的議價能力。此舉直接回應了國防部與Anthropic關於自主武器使用爭議。然而，一個關鍵未決的張力點在於誰擁有設定人工智慧使用法律界限的權威——是研究機構、行政部門、法院還是國會。戰略與國際事務中心（CFR）的專家建議國會應將保障機制編纂成國防法規，儘管由於對行政權力限制的擔憂，其實施的可信度仍存疑問。
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