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.
Strategic Cooperation on AI: Core Functions
English Summary
The RAND report, "Strategic Cooperation on AI: Core Functions," asserts that effective international cooperation is crucial for managing the global impacts of advancing AI technologies. It identifies four core cooperative functions—research, standard-setting, monitoring, and verification—as essential for improving understanding, promoting reliable AI, and mitigating harms. By analyzing how 17 existing international organizations implement these functions, the report offers practical insights into potential institutional structures and common pitfalls. This analysis aims to inform policymakers on designing robust and adaptive strategic cooperation frameworks for AI, emphasizing the need for proactive groundwork despite technological uncertainties.
中文摘要
蘭德報告《AI戰略合作：核心職能》指出，有效的國際合作對於管理不斷發展的AI技術所帶來的全球影響至關重要。報告確立了四項核心合作職能——研究、標準制定、監測與驗證——這些職能對於增進理解、推動可靠AI發展並減輕其潛在危害具有關鍵作用。透過分析17個現有國際組織如何實踐這些職能，報告為潛在的體制結構和常見問題提供了實用見解。本分析旨在協助政策制定者設計一套穩健且具適應性的AI戰略合作框架，並強調儘管技術發展存在不確定性，仍需積極奠定合作基礎。
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