Human Cognitive Bias Identification for Generating Safety Requirements in Safety Critical Systems

Abstract

Safety critical systems are systems whose failure could result loss of life, economic damage, incidents, accidents or undesirable outcome, but it is not doubt that critical system safety has improved greatly under the development of the technology as the number of hardware and software induced accidents has been definitely reduced, but number of human deviations in their decision making found in each accident range remains more. We deeply reviewed traditional human error approaches and their limitations and propose approach of Human Cognitive Bias Identification Technique (H-CoBIT) that identifies, mitigates human potential cognitive biases and generates safety requirements during the initial phase of system Design. This proposed method, analyses the design of safety critical systems from a human factors perspective. It contributes system analyst, designers, and software engineers to identify potential cognitive biases (metal deviations in operator’s decision-making process) during the system use. To ensure the validity of the proposed method, we conducted an empirical experiment to validate the method for accuracy and reliability comparing different experimental outcomes using signal detection theorem.