Expert Evaluation of ChatGPT Performance for Risk Management Process based on ISO 31000 Standard

6 Pages Posted: 17 Jul 2023

See all articles by M.K.S. Al-Mhdawi

M.K.S. Al-Mhdawi

Trinity Dublin College; Teesside University

Abroon Qazi

American University of Sharjah

Ammar Alzarrad

Marshall University

Nicholas Dacre

University of Southampton; University of Warwick

Farzad Rahimian

Teesside University

Mohanad K. Buniya

Universiti Teknologi PETRONAS,

Hanqin Zhang

University of Southampton, Southampton Business School, Department of Decision Analytics and Risk

Date Written: July 8, 2023

Abstract

ChatGPT is widely known for its ability to facilitate knowledge exchange, support research endeavours, and enhance problem-solving across various scientific disciplines. However, to date, no empirical research has been undertaken to evaluate ChatGPT's performance against established standards or professional guidelines. Consequently, the present study aims to evaluate the performance of ChatGPT for the risk management (RM) process based on ISO 31000 standard using expert evaluation. The authors (1) identified the key indicators for measuring the performance of ChatGPT in managing construction risks based on ISO 31000 and determined the key assessment criteria for evaluating the identified indicators using a focus group session with Iraqi experts; and (2) quantitatively analysed the level of performance of ChatGPT under a fuzzy environment. The findings indicated that ChatGPT's overall performance was high. Specifically, its ability to provide relevant risk mitigation strategies was identified as its strongest aspect. However, the research also revealed that ChatGPT's consistency in risk assessment and prioritization was the least effective aspect. This research serves as a foundation for future studies and developments in the field of AI-driven risk management, advancing our theoretical understanding of the application of AI models like ChatGPT in real-world risk scenarios.

Keywords: ChatGPT, ChatGPT Performance, AI, Risk, Risk management, ISO 31000

Suggested Citation

Al-Mhdawi, M.K.S. and Qazi, Abroon and Alzarrad, Ammar and Dacre, Nicholas and Rahimian, Farzad and Buniya, Mohanad K. and Zhang, Hanqin, Expert Evaluation of ChatGPT Performance for Risk Management Process based on ISO 31000 Standard (July 8, 2023). Available at SSRN: https://ssrn.com/abstract=4504409 or http://dx.doi.org/10.2139/ssrn.4504409

M.K.S. Al-Mhdawi (Contact Author)

Trinity Dublin College ( email )

College Green Dublin 2
Dublin, D02 PN40
Ireland

Teesside University ( email )

Middlesbrough
United Kingdom

Abroon Qazi

American University of Sharjah ( email )

P.O. Box 26666
Sharjah
United Arab Emirates

Ammar Alzarrad

Marshall University ( email )

Huntington, WV 25755-2300
United States

Nicholas Dacre

University of Southampton ( email )

University Rd.
Southampton SO17 1BJ, Hampshire SO17 1LP
United Kingdom

University of Warwick ( email )

Gibbet Hill Rd.
Coventry, West Midlands CV4 8UW
United Kingdom

Farzad Rahimian

Teesside University ( email )

Middlesbrough, TS1 3BA
United Kingdom

Mohanad K. Buniya

Universiti Teknologi PETRONAS, ( email )

Seri Iskandar
Perak, 32610
Malaysia

Hanqin Zhang

University of Southampton, Southampton Business School, Department of Decision Analytics and Risk ( email )

Building 2, 12 University Rd
Highfield
Southampton, SO17 1BJ
United Kingdom

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