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.
Government Ownership Isn’t the Answer to AI Anxiety
English Summary
Government ownership stakes in AI companies—whether through Trump's equity partnerships or Sanders's proposed sovereign wealth fund—would create dangerous conflicts of interest between the government's regulatory role and shareholder incentives, potentially stifling competition and enabling government control over algorithms and user data. The article argues such ownership raises constitutional takings concerns, risks government picking winners at a critical early stage of AI development (comparable to backing MySpace or Yahoo in 1996), and could compromise free expression and privacy protections. Instead, policymakers should adopt a light-touch regulatory framework that keeps government as a neutral regulator, maintains low barriers to entry, addresses underlying labor and infrastructure concerns through targeted policy tools, and allows competition and innovation to drive AI development.
中文摘要
政府在人工智能公司中的股權投資—無論是透過川普的股權夥伴關係或桑德斯提議的主權財富基金—將在政府的監管角色與股東利益之間造成危險的利益衝突，可能會抑制競爭並使政府能夠控制算法和用戶數據。該文章論證此類股權投資引發憲法財產徵收問題，冒著政府在人工智能發展的關鍵早期階段選擇贏家的風險（類似於1996年支持MySpace或Yahoo的做法），並可能損害言論自由和隱私保護。相反，政策制定者應採取輕手觸式監管框架，使政府保持中立監管者的角色，維持低進入壁壘，透過有針對性的政策工具解決根本的勞動力和基礎設施問題，並讓競爭和創新推動人工智能發展。
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