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.
America and China Can Make AI Safer
English Summary
AI development presents transnational risks—such as engineered pathogens, autonomous cyberattacks on critical infrastructure, and deepfake disinformation—that transcend the geopolitical rivalry between the US and China. The article argues that neither nation benefits from an unchecked AI race, as the technology poses existential dangers regardless of where they originate. Therefore, managing these shared, catastrophic risks requires a shift from pure competition toward international cooperation and safety standards. Policymakers must prioritize global governance frameworks to mitigate the potential for misuse and ensure AI development is stable and secure.
中文摘要
人工智慧的發展帶來了跨國風險——例如人工合成病原體、針對關鍵基礎設施的自主網路攻擊，以及深度偽造的虛假資訊——這些風險超越了美國與中國之間的地緣政治競爭。本文論點指出，任何國家都不會從不受約束的AI競賽中受益，因為無論這些技術源自何處，它們都構成了存在性威脅。因此，管理這些共同的、災難性的風險，需要從純粹的競爭轉向國際合作與制定安全標準。政策制定者必須將優先順序放在建立全球治理框架上，以減輕潛在的濫用風險，並確保AI的發展是穩定且安全的。
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