On December 15, the academic conference “Opportunities and Challenges for the Labor Market in the Age of Artificial Intelligence” was successfully hosted by the School of Economics, Shanghai University of Finance and Economics (SUFE). The event brought together experts and scholars from Fudan University, Shandong University, Jilin University, Chongqing University, SUFE, Zhongnan University of Economics and Law, South China Normal University, Huaqiao University and other institutions for in-depth discussions on how artificial intelligence shapes the labor market.
The first half of the conference was chaired by Professor Chen Yuanyuan, Vice Dean of the School of Economics, SUFE.
Professor Zhou Yahong, Dean of the School of Economics, SUFE, delivered the opening address. He extended a warm welcome to all participants and highlighted the growing importance of artificial intelligence in economic research. He also briefed the audience on recent progress of SUFE’s labor economics discipline and wished the conference every success.
Professor Dong Zhiqiang, Vice Dean of the School of Economics and Management, South China Normal University, presented the paper Can LLM Replace Human Recruiters? Evidence on Decision Divergence and Algorithmic Stratification. In this study, the same set of resumes was evaluated both by LLMs such as ChatGPT and DeepSeek and by human HR professionals, and their assessment outcomes were compared. The results show that under current technical conditions, large language models cannot fully replace human recruiters and only serve as auxiliary screening tools with limited utility. Rather than replicating human HR judgment, AI generates structurally different screening rules.
Professor Shi Zhilei, Dean of the School of Economics, Zhongnan University of Economics and Law, delivered the presentation Resident Medical Insurance Reform and the Unified National Labor Market. Drawing on the 2011–2018 China Migrants Dynamic Survey dataset, the study finds that provincial pooling reform of urban-rural medical insurance boosts intra-provincial labor mobility yet hinders cross-provincial labor reallocation. It reinforces segmentation between intra-provincial and inter-provincial labor markets and impedes the formation of a unified national labor market.
Professor Wang Linhui from the Center for Quantitative Economics, Jilin University, presented Impacts of Digital Technologies on Workers’ Occupational Skills — Evidence from Chinese Micro Survey Data. The paper documents a sharp divergence between AI and non-AI digital technologies. AI significantly raises workers’ social skills, while non-AI digital technologies strengthen technical skills at the cost of social skills.
Professor Liu Yulin from the School of Public Administration, Chongqing University, spoke on Artificial Intelligence and the Intertemporal Evolution of the Middle-Income Group. Focusing on AI and the evolving vulnerability of the middle-income group, the research finds that AI’s creation effect lags behind its substitution effect, generating pronounced intertemporal impacts. In the short run, AI amplifies the vulnerability of the middle class, though such adverse effects gradually subside over the long term.
The second half of the conference was chaired by Associate Professor Jiang Helu from the School of Economics, SUFE.
Professor Wei Xiahai from the Institute of Economic Development and Reform, Huaqiao University, presented AI Exposure and Individual Retirement Decisions. Based on long-term panel tracking of workers and measuring occupational exposure to AI, the study examines how AI affects delayed retirement choices. It concludes that higher AI exposure in an older worker’s occupation reduces the probability of delayed retirement, driven by falling labor-force participation, lost job returns and weakened future confidence.
Professor Song Hong from the School of Economics, Fudan University, delivered Smart Elderly Care, Family Caregiving and Elderly Well‑being: A Multidimensional Impact Analysis. Against the backdrop of population aging in China and using the “Smart Health and Elderly Care Pilot Program” as a policy shock, the research finds that smart elderly care persistently improves older adults’ non-functional well‑being, while temporarily worsening functional health outcomes; this negative effect fades over time. The pattern may stem from improved lifestyles and attitudes alongside risks of improper or excessive technology use.
Associate Professor Liu Kaihao from the School of Economics, Shandong University, presented How Does the Digital Economy Empower the Development of Agriculture, Rural Areas and Farmers? Evidence from the National E-Commerce into Rural Areas Comprehensive Demonstration Program. Exploiting staggered rollout of rural e-commerce pilots across regions, the empirical evidence shows that the digital economy fosters stable rural development, lifts agricultural productivity and yields sustained income gains for farmers. Key mechanisms include the cultivation of local specialty brands and accelerated development of rural industrial systems.
Professor Huang Feng from the School of Economics, SUFE, delivered AI Human Capital Investment and Firm Total Factor Productivity: New Measurement and Evidence from Large Language Models and Job Posting Big Data. Leveraging LLMs to parse job-posting data, the study constructs a firm-level measure of AI human capital investment and investigates its effects and transmission channels on total factor productivity. AI human capital investment raises firm productivity by stimulating innovation through digital adoption and curbing overhead costs. Further analysis identifies an inverted-U relationship: AI human capital investment has an optimal moderate range.
