摘要
Abstract
The rapid proliferation of artificial intelligence,particularly generative AI,is driving a technological transformation centered on cognitive automation,exerting a profound impact on the structure of global labor markets.Unlike previous technological advancements that primarily substituted for physical or routine cognitive tasks,the current AI revolution is characterized by task routinization and cognitive pervasiveness,with its effects extending to numerous knowledge-intensive occupations.This paper,based on task models and theories of institutional adaptation,develops an"adaptability gap"analytical framework to systematically examine how AI triggers structural trends such as accelerated job polarization,deepened human-machine collaboration,transformations in work organization forms,and divergence in labor productivity through task reorganization and skill structure reconstruction.Moreover,it further investigates the systemic risks facing labor markets when the pace of technological diffusion outstrips the capacity for human capital accumulation and institutional adjustment,including structural frictions,widening inequality,and increased pressure on social protection systems.By comparing policy practices in major developed economies,this study explores the roles of active labor market policies,education system reforms,social security restructuring,algorithmic oversight,and multi-stakeholder governance mechanisms in mitigating the impacts of the transition.Research shows that the ultimate impact of AI on employment and distribution depends heavily on institutional adaptive capacity,rather than on the deterministic power of technology itself.Thus,this paper integrates the analytical logics of technology,task,and institution to propose a systematic framework for understanding the interaction between AI shocks and institutional responses.关键词
人工智能/人机协作/就业极化/适应性鸿沟Key words
artificial intelligence/human-machine collaboration/job polarization/adaptability gap分类
管理科学
