H-CoBIT: Human Cognitive Bias Identification Technique for accident Analysis
Salah Ali1, Aekavute Sujarae2
1Salah Ali, Department of Computer Science, Shinawatra University, Thailand.
2Aekavute Sujarae, Instructor, Department of Computer Science, School of Science and Technology, Shinawatra University, Thailand.
Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 2226-2231 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2517059120/2020©BEIESP | DOI: 10.35940/ijrte.A2517.059120
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: H-Co BIT is a technique initially developed with help of system analyst and designers in safety critical domains to anticipate human involvement failures that may be challenging once the system design becomes operational. This paper outlines and introduces a means of identifying cognitive biases using H-Co BIT method retrospectively (following an accident), where ‘human error’ is a convenient and all-encompassing explanation given in ninety per cent of cases. This we assert is because existing investigative approaches largely concentrate on observed actions rather than intrinsic thought processes. By teasing out the presence of cognitive bias as a causal factor for incorrect actions, safety recommendations can be made towards their mitigation. Analyzing a real-world case study by anticipating potential cognitive biases using H-Co BIT and comparing the results with the observed biases helped validate that this approach can also be used retrospectively.
Keywords: Human Failures, Accident Analysis.
Scope of the Article: Identification Technique