程实：AI让传统经济信号失灵，货币政策亟须前瞻布局

Group 1 - The traditional labor market frameworks, namely the Phillips Curve and the Beveridge Curve, are facing systematic challenges as labor market dynamics in developed economies, particularly the U.S., deviate from historical patterns [2][4] - The Phillips Curve is flattening, indicating a weaker relationship between unemployment rates and inflation, as AI alters the labor supply dynamics and reduces the sensitivity of wage growth to labor market tightness [4][5] - The Beveridge Curve is shifting outward, reflecting a structural mismatch in the labor market where high vacancy rates do not correspond to lower unemployment, primarily due to AI's impact on middle-skill jobs [5][6] Group 2 - AI's influence on the labor market is primarily task-based rather than job-based, leading to a reduction in marginal labor demand for tasks that AI can perform more efficiently [3][4] - The introduction of AI has resulted in a significant increase in the elasticity of effective labor supply, meaning that a decrease in unemployment does not necessarily indicate a tightening labor market [4][5] - The wage formation mechanism is becoming more stratified, with non-replaceable tasks commanding wage premiums while replaceable tasks face downward pressure, thus diminishing the average wage's sensitivity to labor market conditions [5][6] Group 3 - The efficiency of wage growth in transmitting inflation signals is weakening, as AI enhances labor productivity without a corresponding increase in employment levels, leading to a potential overestimation of inflation persistence when relying solely on wage data [6][7] - Unemployment rates are responding more slowly to economic changes, necessitating a shift in monetary policy focus to potential risks before significant labor market deterioration occurs [6][7] - Future monetary policy may adopt a forward-looking risk management approach, allowing for preemptive easing measures even before core employment indicators show clear signs of weakness [7]