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.
Toward a Mature AI Economy: Policy Priorities for the Road Ahead
English Summary
The article argues that the AI economy has not matured and that sustained value will not come from merely improving existing processes, but from using AI as a catalyst for fundamental, innovative redesigns of entire workflows. As true operational costs become visible, current process-improvement models are likely to face margin compression, necessitating a shift toward high-margin, innovation-enabling business models. To facilitate this transition, policymakers must adopt an industry-specific regulatory approach, prioritize data privacy certainty, and invest heavily in upskilling the workforce. Ultimately, the focus of geopolitical competition should be on enabling scalable, innovative AI use rather than simply increasing AI capacity.
中文摘要
本文論述指出，人工智慧（AI）經濟尚未成熟，其持續的價值來源將不會僅限於優化現有流程，而是必須利用AI作為催化劑，對整個工作流程進行根本性、創新的重塑。隨著真實營運成本的顯現，現行的流程改善模式可能面臨利潤壓縮，有必要轉向高利潤、能促進創新的商業模式。為促成此類轉型，政策制定者必須採取產業特定的監管方法，優先確保資料隱私的確定性，並大力投資於勞動力的技能提升。最終，地緣政治競爭的焦點應放在推動可擴展、具創新性的AI應用，而非單純增加AI的算力。
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