{"title":"用于作业自动化的人工智能和机器学习","authors":"Gang Peng, R. Bhaskar","doi":"10.4018/jdm.318455","DOIUrl":null,"url":null,"abstract":"Job automation is a critical decision that has brought about profound changes in the workplace. However, the question of what drives job automation remains unclear. This study conducts an interdisciplinary review of five theoretical frameworks on job automation, paying particular attention to the role played by artificial intelligence and machine learning. It highlights the concepts and mechanisms underlying each of the frameworks, compares and contrasts their similarities and differences, and highlights challenges and suggests opportunities of job automation. It also proposes an integrated framework on job automation by addressing the research gaps in extant frameworks and thereby contributes to the research and practice on this important topic.","PeriodicalId":51086,"journal":{"name":"Journal of Database Management","volume":"1 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence and Machine Learning for Job Automation\",\"authors\":\"Gang Peng, R. Bhaskar\",\"doi\":\"10.4018/jdm.318455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Job automation is a critical decision that has brought about profound changes in the workplace. However, the question of what drives job automation remains unclear. This study conducts an interdisciplinary review of five theoretical frameworks on job automation, paying particular attention to the role played by artificial intelligence and machine learning. It highlights the concepts and mechanisms underlying each of the frameworks, compares and contrasts their similarities and differences, and highlights challenges and suggests opportunities of job automation. It also proposes an integrated framework on job automation by addressing the research gaps in extant frameworks and thereby contributes to the research and practice on this important topic.\",\"PeriodicalId\":51086,\"journal\":{\"name\":\"Journal of Database Management\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Database Management\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.4018/jdm.318455\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Database Management","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/jdm.318455","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Artificial Intelligence and Machine Learning for Job Automation
Job automation is a critical decision that has brought about profound changes in the workplace. However, the question of what drives job automation remains unclear. This study conducts an interdisciplinary review of five theoretical frameworks on job automation, paying particular attention to the role played by artificial intelligence and machine learning. It highlights the concepts and mechanisms underlying each of the frameworks, compares and contrasts their similarities and differences, and highlights challenges and suggests opportunities of job automation. It also proposes an integrated framework on job automation by addressing the research gaps in extant frameworks and thereby contributes to the research and practice on this important topic.
期刊介绍:
The Journal of Database Management (JDM) publishes original research on all aspects of database management, design science, systems analysis and design, and software engineering. The primary mission of JDM is to be instrumental in the improvement and development of theory and practice related to information technology, information systems, and management of knowledge resources. The journal is targeted at both academic researchers and practicing IT professionals.