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.
AI Legislation, Export Restrictions, and Free Speech Caught in Between
English Summary
The CATO analysis argues that while the proposed Great American Artificial Intelligence Act (GAAIA) addresses innovation and risk management, it critically fails to provide meaningful protections for free speech against government overreach. Concerns center on vague provisions, the threat of arbitrary executive actions like export controls (citing Anthropic's shutdown), and how voluntary standards could lead to 'collateral censorship.' For policy improvement, the author recommends replacing studies with direct anti-jawboning policies, implementing stronger preemption to prevent state law fragmentation, and restricting executive authority to safeguard AI development and speech rights.
中文摘要
CATO 的分析指出，雖然擬議的《美國大人工智能法案》（GAAIA）在應對創新和風險管理方面有所建樹，但它卻未能為言論自由提供有意義的保護，特別是針對政府越權行為。主要的擔憂集中於其條文過於模糊、存在任意行政行動（例如引用 Anthropic 關閉事件所指出的出口管制）的威脅，以及自願標準可能導致「附帶審查」（collateral censorship）的問題。為改善政策，作者建議用直接的反規避性政策取代研究報告，實施更強力的排除規定以防止州法律碎片化，並限制行政權力，從而保障人工智能發展和言論自由。
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