机器人应用冲击、职业可迁移技能和职业—技能合意性

Robot Application Shocks, Occupational Transferable Skills, and Occupational-Skill Desirability

随着人工智能技术的不断突破,机器人作为其重要载体在生产领域广泛应用,对劳动就业和任务分配产生深远的影响。现有文献更多关注机器人应用的岗位更替效应,忽视其重塑工作流程和改变生产任务而影响劳动技能需求。本文基于微观个体层面考察机器人应用对职业—技能合意性的冲击,从任务去常规化和职业可迁移技能需求增加的维度,探究机器人应用对职业—技能合意性的影响机制,分类检验不同类型可迁移技能在其中发挥的作用,并进一步剖析部分学历不足的劳动群体就业状况、工资收入和职业地位的变化。研究发现:(1)机器人应用会重构机器与劳动间的任务分配,使劳动者从事的任务去常规化,也会增加职业可迁移技能需求,进而降低职业—技能合意性。(2)机器人应用通过增加复杂问题解决技能、资源管理技能和社交技能等不同类型的职业可迁移技能需求导致职业—技能合意性降低,这在新职业和数字职业中也有明显体现。(3)在机器人冲击下部分学历不足的劳动群体会借助智能化机器突破职业藩篱,推动职业地位向上流动;但也有部分劳动群体,被机器人替代而面临离职风险增加和工资下降等问题。技能深化能够帮助劳动者摆脱技能不足的困境,提高职业—技能合意性,进而缓解机器人应用的负向冲击。

With breakthroughs in the field of artificial intelligence, robots are a critical manifestation that is widely used in production,producing profound changes in employment and task allocation. Previous studies have mostly focused on the job substitution effects of robot applications, ignoring how they reshape workflows, change production tasks, and their impact on the demand for skills. Based on micro-individual data, we study the impact of robots on occupational-skill desirability, and examine the mechanisms in terms of task de-routinization and increased demand for occupational transferable skills, as well as the role of different transferable skills. We also analyze changes in the employment conditions, wages and occupational status of less-educated workers. Major findings are as follows.(1) Robots decrease occupational-skill desirability through task de-routinization and increasing the need for transferable skills.(2) Robot applications amplify the demand for transferable skills, such as complex problem-solving, resource management, and social skills, which are particularly evident in new and digital occupations.(3) Some low-skilled workers may be able to break occupational segregation through the use of intelligent machines and increase their occupational status;however, some will be replaced by robots and face increased risks of displacement and wage reduction. Skill deepening can help workers overcome skill shortages, improve occupational-skill desirability, and mitigate the negative effects of robots.