{"title":"Can artificial intelligence contribute to the new energy system? Based on the perspective of labor supply","authors":"Chien-Chiang Lee , Jiangnan Li , Jingyang Yan","doi":"10.1016/j.techsoc.2025.102877","DOIUrl":null,"url":null,"abstract":"<div><div>Artificial intelligence (AI) is becoming a decisive force in driving humanity into the smart era. The energy sector has recognized AI as a powerful technological tool and extensively uses industrial robots to assist with energy production, transportation, and consumption. Meanwhile, changes in labor supply, including regional migration, demographic shifts, and improvements in workforce quality, are attracting attention. This paper explores the relationship between AI and the new energy system (ES) and examines the moderating effects of labor supply. The study finds that AI significantly enhances ES efficiency by improving production, reducing labor costs, and promoting innovation in new energy technologies. Increased migration of young adults leads local businesses to hire more external labor, which temporarily hinders AI technology adoption, with labor supply quantity negatively moderating AI's impact on ES. Deepening social aging drives industrial digitalization and automation, increasing energy demand among the elderly, with labor supply structure positively moderating the impact. Advanced education depletes household savings and limits investment capacity, with labor supply quality negatively moderating the impact. Quantile regression in the heterogeneity analysis shows that AI's positive impact is stronger at higher ES levels. Subsample regression indicates that higher openness, economic development, urbanization, and technical innovation, along with lower government intervention, are beneficial for AI's positive effects. Based on the predictions from the ETS model, we have developed new insights into the relationship between AI and the energy system. Existing literature on the development of AI and the energy industry has not taken into account the complexity of labor supply conditions in China. This paper, from the perspective of changes in labor supply, provides a valuable contribution to this field and offers insights for other scholars.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"81 ","pages":"Article 102877"},"PeriodicalIF":10.1000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology in Society","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0160791X25000673","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL ISSUES","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is becoming a decisive force in driving humanity into the smart era. The energy sector has recognized AI as a powerful technological tool and extensively uses industrial robots to assist with energy production, transportation, and consumption. Meanwhile, changes in labor supply, including regional migration, demographic shifts, and improvements in workforce quality, are attracting attention. This paper explores the relationship between AI and the new energy system (ES) and examines the moderating effects of labor supply. The study finds that AI significantly enhances ES efficiency by improving production, reducing labor costs, and promoting innovation in new energy technologies. Increased migration of young adults leads local businesses to hire more external labor, which temporarily hinders AI technology adoption, with labor supply quantity negatively moderating AI's impact on ES. Deepening social aging drives industrial digitalization and automation, increasing energy demand among the elderly, with labor supply structure positively moderating the impact. Advanced education depletes household savings and limits investment capacity, with labor supply quality negatively moderating the impact. Quantile regression in the heterogeneity analysis shows that AI's positive impact is stronger at higher ES levels. Subsample regression indicates that higher openness, economic development, urbanization, and technical innovation, along with lower government intervention, are beneficial for AI's positive effects. Based on the predictions from the ETS model, we have developed new insights into the relationship between AI and the energy system. Existing literature on the development of AI and the energy industry has not taken into account the complexity of labor supply conditions in China. This paper, from the perspective of changes in labor supply, provides a valuable contribution to this field and offers insights for other scholars.
期刊介绍:
Technology in Society is a global journal dedicated to fostering discourse at the crossroads of technological change and the social, economic, business, and philosophical transformation of our world. The journal aims to provide scholarly contributions that empower decision-makers to thoughtfully and intentionally navigate the decisions shaping this dynamic landscape. A common thread across these fields is the role of technology in society, influencing economic, political, and cultural dynamics. Scholarly work in Technology in Society delves into the social forces shaping technological decisions and the societal choices regarding technology use. This encompasses scholarly and theoretical approaches (history and philosophy of science and technology, technology forecasting, economic growth, and policy, ethics), applied approaches (business innovation, technology management, legal and engineering), and developmental perspectives (technology transfer, technology assessment, and economic development). Detailed information about the journal's aims and scope on specific topics can be found in Technology in Society Briefings, accessible via our Special Issues and Article Collections.