International Journal of Industrial Engineering and Management

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Vol. 15 No. 2 (2024)
Review Article

Generative Artificial Intelligence Technology for Systems Engineering Research: Contribution and Challenges

Yehia Ibrahim Alzoubi
College of Business Administration, American University of the Middle East, Egaila, Kuwait
Alok Mishra
Faculty of Engineering, Norwegian University of Science and Technology, Trondheim, Norway
Ahmet Topcu
College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait
Ali Osman Cibikdiken
KTO Karatay University, Konya, Türkiye

Published 2024-06-11

abstract views: 56 // FULL TEXT ARTICLE (PDF): 12


Keywords

  • Generative Artificial Intelligence,
  • ChatGPT,
  • Research,
  • Systems engineering

How to Cite

Alzoubi, Y. I., Mishra, A., Topcu, A., & Cibikdiken, A. O. (2024). Generative Artificial Intelligence Technology for Systems Engineering Research: Contribution and Challenges. International Journal of Industrial Engineering and Management, 15(2), 169–179. https://doi.org/10.24867/IJIEM-2024-2-355

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)

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