Generative Artificial Intelligence Technology for Systems Engineering Research: Contribution and Challenges
Published 2024-06-11
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Keywords
- Generative Artificial Intelligence,
- ChatGPT,
- Research,
- Systems engineering
How to Cite
Copyright (c) 2024 International Journal of Industrial Engineering and Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
The advancement of artificial intelligence technology in recent years has had a significant impact on various industries, including the field of systems engineering. Generative Artificial Intelligence (AI), like OpenAI's ChatGPT, is one such tool that has garnered attention. While this technology offers researchers in systems engineering intriguing possibilities, it also introduces certain risks to the traditional research framework. The aim of this paper is to investigate the advantages and drawbacks associated with embracing generative AI. We conducted a comprehensive literature review utilizing resources like Google Scholar, Web of Science, and the Scopus database, along with professional websites and white papers. The analysis highlights the potential benefits of generative AI in systems engineering research, including data processing, analysis, hypothesis formulation, prediction and forecasting, and collaboration enhancement. However, it also underscores various risks, such as potential data bias, the generation of human-like text, potential loss of analytical capabilities, and difficulties in analyzing output from these AI tools. As emphasized in this paper, numerous concerns still need to be addressed regarding the use of generative AI tools due to their relatively new nature and evolving capabilities.
Article history: Received (December 20,2023); Revised (April 21,2024); Accepted (May 27, 2024); Published online (June 5, 2024)