报告题目：Does AI Reduce Inequality? A Study with a New Occupational AI Exposure Measure

报告时间：2024年11月14日 22:00-22:55

报告地点：腾讯会议394742121

报告人：刘传仁 博士 美国田纳西大学商业分析与统计系副教授 ECRA高级编辑 IEEE数据挖掘国际会议注册主席

邀请人：郭艳红 教授

报告摘要：

  A central concern regarding artificial intelligence (AI) is its potential to replace jobs and exacerbate economic inequality. However, recent research argue that AI may provide a path to decrease inequality through a Turing Transformation process: AI simplifies work, reduces barriers to job entry, and consequently widens job opportunities for more workers. In this paper, we empirically test the Turing Transformation theory by examining AI’s deskilling and job opportunity effects. 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 for a wide range of work activities, along with an increase in job postings and employment. This provides the first empirical evidence for the existence of the Turing Transformation process. However, the beneficial job opportunity expansion 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-skilled workers due to AI.

报告人简介

Dr. Chuanren Liu is an Associate Professor in the Business Analytics and Statistics Department at the University of Tennessee, Knoxville. He holds a Ph.D. in Management (Information Technology) from Rutgers, the State University of New Jersey, USA, the M.S. degree in Mathematics from the Beijing University of Aeronautics and Astronautics (BUAA), and the B.S. degree in Mathematics from the University of Science and Technology of China (USTC). His research interests include data mining and knowledge discovery, with a particular focus on their applications in the field of business analytics. He has published papers in refereed journals and conference proceedings, such as IEEE Transactions on Knowledge and Data Engineering, INFORMS Journal on Computing, Decision Support Systems, European Journal of Operational Research, Annals of Operations Research, Information Sciences, Knowledge and Information Systems, SIGKDD, ICDM, SDM, AAAI, IJCAI, IEEE BigData, and DSAA, etc.