周小川谈货币政策：慢变量需要慢处理

Core Viewpoint - The former governor of the People's Bank of China, Zhou Xiaochuan, emphasized that monetary policy is a slow variable and cannot respond quickly to daily fluctuations in vegetable prices, suggesting that rapid responses could lead to unnecessary volatility [1][3]. Group 1: Monetary Policy and AI - Zhou Xiaochuan noted that during his tenure, discussions at the Bank for International Settlements (BIS) concluded that the impact of AI on monetary policy was not yet significant [1][3]. - He highlighted that while AI can influence data collection and analysis related to prices and micro-behavior, monetary policy adjustments are inherently slow and tied to economic cycles [1][3]. Group 2: Financial Stability and Machine Learning - Zhou pointed out that financial instability risks can emerge suddenly, citing the abrupt failures of banks like Silicon Valley Bank and Silvergate Bank as examples [3]. - He proposed that machine learning and deep learning could be crucial in predicting financial instability by analyzing historical financial stability data and changes in the health of financial institutions [3]. - Zhou suggested that the financial system has traditionally relied on structured data, but the analysis of historical events and the emergence of economic bubbles require broader use of AI to process unstructured data and consider social sentiments [3].