Artificial Intelligence and Machine Learning for Job Automation: A Review and Integration
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 ro...
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| Veröffentlicht in: | Journal of database management 2023-01, Vol.34 (1), p.1-12 |
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| creator | Bhaskar, Rahul Peng, Gang |
| description | 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. |
| doi_str_mv | 10.4018/JDM.318455 |
| format | Article |
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| source | Alma/SFX Local Collection |
| subjects | Artificial intelligence Automation Computational linguistics Data base management Language processing Machine learning Natural language interfaces Simon, Herbert Alexander |
| title | Artificial Intelligence and Machine Learning for Job Automation: A Review and Integration |
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