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.
Assessing the Trump Administration’s Executive Order on AI and Cybersecurity
English Summary
CATO’s analysis of the Trump Administration’s executive order on AI and cybersecurity reveals a strategy focused on bolstering national resilience against emerging cyber threats posed by advanced AI models like Anthropic’s Mythos and OpenAI’s GPT 5.5. The order mandates a 30-day pre-deployment testing process, overseen by the NSA, to identify and assess these models, alongside establishing an ‘AI cybersecurity clearinghouse’ to coordinate vulnerability scanning. Key actions include strengthening the Department of Defense’s information systems and directing CISA to issue binding operational directives for civilian cybersecurity. While intended to foster AI dominance and improve cyber readiness, the order’s opacity and potential for government overreach raise concerns about stifling innovation and transparency. Ultimately, the initiative represents a reactive, defense-oriented approach to managing AI risks.
中文摘要
CATO 對特朗普政府關於人工智能和網絡安全行政命令的分析顯示，其策略重點在於增強國家對來自先進人工智能模型（如 Anthropic 的 Mythos 和 OpenAI 的 GPT 5.5）的 emerging 網絡威脅的韌性。該命令要求在部署前進行 30 天的測試，由 NSA 負責評估和評估這些模型，並設立一個『人工智能網絡安全信息中心』以協調漏洞掃描。主要措施包括加強國防部的資訊系統，並指示 CISA 發布針對民用網絡安全的強制運營指令。雖然該命令旨在推動人工智能的領先地位並提高網絡準備程度，但其不透明性和政府可能過度干預的潛力引發了對扼殺創新和透明度的擔憂。總體而言，這一倡議代表了以反應式和防禦導向的方式來管理人工智能風險的方法。
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