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清华大学教育研究[ISSN:1001-4519/CN:11-1610/G4]

卷:

期数:

2026年03期

页码:

10-22

栏目:

教育前沿

出版日期:

2026-06-20

文章信息/Info

Title:

The Impact of Arti?cial Intelligence on Occupational Skill Structures and Educational Responses:An Empirical Study Based on PIAAC Data (2011-2023)

作者:

吴凯霖 黄斌

南京大学 教育研究院

Author(s):

WU Kai-lin HUANG Bin

School of Education, Nanjing University

关键词:

人工智能; 人工智能替代; 人工智能与教育; 任务偏向型技术进步; 岗位技能

Keywords:

AI;  AI substitution;  AI and education ;  routine-biased technological changes;  occupational skills

分类号:

G40-05

DOI:

10.14138/j.1001-4519.2026.03.001013

文献标志码:

A

摘要:

基于任务偏向型技术进步理论，本研究综合利用国际成人能力评估调查（PIAAC）与职业信息网络数据（O*NET），采用机器学习方法测算2018－2022年各职业人工智能替代率，并运用强度双重差分模型就人工智能对岗位技能结构的多重影响进行了分析。研究发现，不同行业面临的人工智能替代率呈现明显分化，建筑业、采矿业等行业替代率最高，金融和保险活动、教育等行业替代率最低。不同学历层次与认知技能水平群体面临着不同的人工智能替代率，但相较而言，拥有高技能要比拥有高学历更能抵抗人工智能替代的风险。人工智能对于岗位技能造成结构性影响，问题解决能力与技能广度的重要性在不断提升，引领带动、沟通协调等方面技能的重要性在不断减弱。人工智能对于非常规手工型、常规认知与手工型、非常规认知与交互型等各类型职业的技能结构有着不同的冲击影响。面临最低替代率的非常规认知与交互型职业对于技能广度产生更高的要求，在所有类型职业中解决复杂问题能力的重要性都有所提升。本文发现揭示了在人工智能时代培养学生技能，尤其是学生高阶技能与技能广度的重要战略价值，建议从人才培养范式转向、学科专业结构与资源配置优化、国民技能培养体系构建等方面探索教育的政策应对。

Abstract:

Based on the theory of routine-biased technological changes, this study combines data from the Programme for the International Assessment of Adult Competencies (PIAAC) and the Occupational Information Network (O*NET) to estimate occupational AI substitution rates from 2018 to 2022 using machine learning methods. An intensity-based difference-in-differences model is employed to examine the impact of artificial intelligence on occupational skill structures. The results indicate substantial heterogeneity in AI substitution rates across industries. Although both educational attainment and cognitive skill levels are associated with AI substitution risk, higher skill levels provide stronger protection against displacement than higher educational credentials alone. AI also reshapes occupational skill structures by increasing the importance of problemsolving abilities and skill breadth, while reducing the relative importance of leadership, communication, and coordination skills. These effects vary across occupational categories, including non-routine manual, routine cognitive and manual and non-routine cognitive and interactive occupations. Notably, non-routine cognitive and interactive occupations, which face the lowest substitution risk, exhibit a growing demand for broader skill portfolios. Across all occupational types, the importance of complex problem-solving skills has increased.These findings underscore the strategic value of developing higher-order competencies and broad skill portfolios in the age of artificial intelligence, with important implications for talent cultivation paradigm, the restructuring of academic disciplines and specialties, and the national skills development system.

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更新日期/Last Update: 2026-06-20