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 and Global Food Security: A Focus on Crop Breeding
English Summary
AI-enabled technologies are set to transform crop breeding by accelerating the development of more resilient, higher-yielding, and nutritious crops essential for global food security. These advancements improve data management, enhance data collection and analysis, and provide novel genomic tools, addressing increasing food demand and ecological pressures. However, challenges such as unequal access to AI tools and genetic data, particularly in the Global South, and the need for aligned regulatory frameworks could hinder progress. To leverage AI's full potential, policymakers must support foundational sciences, build institutional capacity, establish coherent regulations, and promote global collaboration to ensure equitable deployment and long-term benefits for food systems.
中文摘要
AI 賦能技術將透過加速開發更具韌性、更高產量和營養的作物，從而徹底改變作物育種，這對於全球糧食安全至關重要。這些進步改進了數據管理，增強了數據收集和分析，並提供了新穎的基因組工具，以應對日益增長的糧食需求和生態壓力。然而，諸如 AI 工具和遺傳數據獲取不平等（特別是在全球南方國家）以及需要統一的監管框架等挑戰可能會阻礙進展。為了充分發揮 AI 的潛力，政策制定者必須支持基礎科學、建設機構能力、建立連貫的法規，並促進全球合作，以確保公平部署和糧食系統的長期效益。
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