Abstract
The rapid advancements in Industry 4.0 technologies have created both opportunities and challenges for industrial researchers, who now require a diverse set of knowledge and skills spanning robotics, ergonomics, computer science, and many other disciplines. Although interdisciplinary collaboration is always welcomed and beneficial, immediate access to expertise is not always available. Artificial Intelligence (AI) has increasingly filled this gap, offering support across various industries. However, the collaborative paradigm between AI and industrial researchers remains underexplored. This study introduces a Human-AI teaming paradigm for industrial engineering researchers who require multidisciplinary knowledge and skills. By leveraging computational, perceptual, and cognitive intelligence, AI can assist researchers in operational and tactical tasks and enables researchers to pay more effort to strategic tasks such as visioning and decision-making. Researchers can form teams of AI experts (”AIxperts”) using large language models to access immediate support in specialized areas. A case study in aviation human factors research demonstrated the efficacy of this paradigm, where an ergonomist lacking knowledge in aviation cockpit settings and classification algorithms successfully developed a model to identify pilots'”Out-Of-The-Loop” status with the help of”AIxperts” in aviation engineering, computer science, and coding. This Human-AI team effectively supplemented the researcher's expertise, completing the task successfully. The study highlights the potential and future trends of Human-AI teaming, providing valuable insights for enhancing human-AI interactions in industrial research.
| Original language | English |
|---|---|
| Pages (from-to) | 495-502 |
| Number of pages | 8 |
| Journal | Proceedings of International Conference on Computers and Industrial Engineering, CIE |
| Volume | 2024-December |
| Publication status | Published - 2024 |
| Event | 51st International Conference on Computers and Industrial Engineering, CIE 2024 - Sydney, Australia Duration: 9 Dec 2024 → 11 Dec 2024 |
Keywords
- Human-AI teaming
- Industrial engineering
- Knowledge-driven
- Large Language Model
- Management level
ASJC Scopus subject areas
- General Computer Science
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering
- Safety, Risk, Reliability and Quality
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