管理科学系商务分析与运营创新研究中心学术讲座

时间：2023年12月11日（周一） 13:30-15:00

地点：管理学院思源楼524室

主题：Does AI Reduce Inequality?

主讲人：黄庭亮田纳西大学诺克斯维尔分校教授

主持人：冯天俊复旦大学管理学院教授

摘要：A central concern regarding artificial intelligence (AI) is its potential to replace jobs and exacerbate income inequality. However, Agrawal et al. (2023a,b) argue that AI may provide a path to decrease inequality through a "Turing Transformation" process: AI simplifies work tasks, reduces barriers to job entry, and consequently creates opportunities for a broader range of workers. In this paper, we empirically test the Turing Transformation hypothesis by examining AI's impact on job content and employment over the past decade. We develop a novel occupational AI exposure index using a sentence transformer model to compare the semantic similarity between the occupation descriptions (what people do) and AI patents (what AI technologies do). We find that, on average, occupations with higher AI exposure experience a decrease in the importance of both routine and non-routine work activities, along with an increase in job postings and employment. This provides the first empirical evidence supporting the existence of the Turing Transformation process in the U.S. over the past decade. However, the Turing Transformation effects are absent for low-skill occupations. For high-skill occupations, as their AI exposure increases, we observe large increases in job postings but little changes in actual employment, suggesting a talent gap for high-skill workers due to AI. These results highlight the central role of higher education in the race between human and machine with important implications for workers, firms, and policymakers.

简介:

Tingliang Huang is the Amazon Distinguished Professor of Business Analytics and Analytics PhD Program Recruiting Lead in the Department of Business Analytics and Statistics in the Haslam College of Business at University of Tennessee, Knoxville. He is also an Honorary Professor at UCL School of Management, University College London (UCL), the United Kingdom. He received his PhD in Operations Management from Northwestern University. Prior to that, he received the M.S. and B.S. degrees from the University of Minnesota and the University of Science & Technology of China, respectively. He is interested in business analytics, AI, operations-marketing interface, quantitative marketing, supply chain management, service operations, and sustainable operations. His research articles have been published in top business journals such as Manufacturing & Service Operations Management, Marketing Science, Management Science, and Production and Operations Management. His research & teaching awards include the 2023 INFORMS Workshop on Data Science Best Paper Award, 2018 POMS Wickham Skinner Early Career Research Accomplishments Award, the 2018 Most Influential Paper Award in Service Operations, and the 2015 Wickham Skinner Best Paper Award.