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.
Developing a Risk-Scoring Tool for Artificial Intelligence–Enabled Biological Design: A Method to Assess the Risks of Using Artificial Intelligence to Modify Select Viral Capabilities
English Summary
RAND developed a dual-axis risk-scoring tool to evaluate the biosecurity threats posed by AI-enabled biological design, focusing on five critical viral functions such as host range and transmission dynamics. The framework assesses both the potential severity of biological modifications and the technical capability required by actors, specifically measuring the 'uplift' that advancing AI provides to lower-skilled individuals. Researchers concluded that as AI tools become more accessible, the technical barriers to engineering dangerous pathogens will continue to decrease, necessitating new oversight mechanisms. Consequently, the report proposes using this scoring system as a foundation for establishing regulatory redlines and federal funding requirements to manage AI-driven biological risks without stifling innovation.
中文摘要
蘭德公司（RAND）開發了一套雙軸風險評分工具，旨在評估由人工智慧賦能的生物設計所帶來的生物安全威脅，並聚焦於宿主範圍與傳播動態等五項關鍵病毒功能。該框架同時評估生物改造的潛在嚴重性以及行為體所需的技術能力，特別衡量了先進人工智慧為低技術門檻個人提供的「能力提升」（uplift）。研究人員得出結論，隨著人工智慧工具日益普及，工程化危險病原體的技術門檻將持續降低，因此有必要建立新的監督機制。據此，報告建議將此評分系統作為劃定監管紅線與聯邦資助要求的基礎，以便在不阻礙創新的前提下，有效管理由人工智慧驅動的生物風險。
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