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.
The US government’s latest U-turn on Anthropic’s Mythos sends mixed signals on AI governance
English Summary
The US government's fluctuating regulatory approach to advanced AI models, exemplified by its repeated policy reversals regarding Anthropic’s Mythos, sends mixed signals on global AI governance. This volatility stems from a tension between promoting innovation (deregulation) and managing national security risks, leading to ad hoc controls like limited access for 'trusted partners.' While the latest moves aim to broaden international access, the unpredictable nature of these restrictions creates significant market uncertainty and undermines confidence in US policy stability. Consequently, this protectionist regulatory environment complicates efforts toward necessary global governance and hinders cooperation with allies on shared AI safety risks.
中文摘要
美國政府對於先進人工智慧模型（AI）的不穩定監管態度，以其針對 Anthropic Mythos 等模型的政策反覆為例，在全球 AI 治理上發出了複雜的訊號。這種波動性源於推動創新（放寬管制）與管理國家安全風險之間的張力，導致了「僅限可信賴合作夥伴」等臨時性的管制措施。儘管最新的舉措旨在擴大國際接入，但這些限制的不確定性卻造成了顯著的市場不確定性，並削弱了對美國政策穩定性的信心。因此，這種保護主義式的監管環境，使得推動必要的全球治理變得複雜化，並阻礙了與盟友在共同 AI 安全風險上進行合作。
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