The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market

• 成果类型: Article
• 署名作者: Hui, Xiang; Reshef, Oren; Zhou, Luofeng
• 署名单位: Washington University (WUSTL); New York University
• 刊物名称: ORGANIZATION SCIENCE
• ISSN/ISSBN: 1047-7039
• DOI: 10.1287/orsc.2023.18441
• 发表日期: 2024
• 页码: 1977-1989
• 关键词: Artificial intelligence; online labor markets; Large Language Model; generative AI

摘要

Generative artificial intelligence (AI) holds the potential to either complement workers by enhancing their productivity or substitute them. We examine the short-term effects of the recently released generative AI models (ChatGPT, DALL-E 2, and Midjourney) on the employment outcomes of freelancers on a large online platform. We find that freelancers in highly affected occupations suffer from the introduction of generative AI, experiencing reductions in both employment and earnings. We find similar effects studying the release of other image-based generative AI models. Exploring the heterogeneity by freelancers' employment history, we do not find evidence that high-quality service, measured by their past performance and employment, moderates the adverse effects on employment. In fact, we find suggestive evidence that top freelancers are disproportionately affected by AI. These results suggest that generative AI may transform the role of human capital in the organization and reduce overall demand for workers.