机器人应用与劳动就业:基于任务偏向视角的经验分析

Robots Application and Employment: An Empirical Analysis Based on Task-Biased Perspective

文章运用国际机器人联合会数据和中国劳动力动态调查数据,从任务的常规属性、认知属性以及社交属性三个维度,实证检验了机器人应用的任务偏向对就业的影响。研究发现:机器人应用具有显著的任务选择偏向,能提升非常规型任务、认知型任务和社交型任务的劳动力需求;机器人应用对不同学历劳动者的任务选择偏向具有异质性,能显著提升高学历非常规型、常规型、认知型及社交型任务的劳动力需求,但会减少低学历常规型、认知型和非认知型,以及高学历非社交型任务的劳动力需求。因此,要注重对劳动者特别是从事常规型、非认知型以及非社交型任务劳动者的综合素质培养和再培训,以助推更高质量和更充分就业。

Using data from the International Federation of Robotics and the China Labor Force Dynamics Sur-vey,we empirically examine the impact of the task bias of robots on employment from the three dimensions of routine,cognitive and social attributes of task.The findings reveal that robots have a significant task selection bias,which can enhance the labor demand for non-routine,knowledge-based and social tasks;the task selec-tion bias effect of robots on workers with different education levels is heterogeneous.Robots can significantly enhance the labor demand for high-education non-routine,routine,cognitive and social tasks,but reduce the labor demand for low-education routine,cognitive and non-cognitive tasks,and labor demand for highly edu-cated non-social tasks.Therefore,it is important to focus on the comprehensive quality development and retraining of workers,especially those engaged in routine,non-cognitive and non-social tasks,in order to pro-mote higher quality and fuller employment.