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Burning biases: Mitigating cognitive biases in fire engineering
Author(s) -
Kinsey Michael J.,
Kinateder Max,
Gwynne Steven M. V.,
Hopkin Danny
Publication year - 2021
Publication title -
fire and materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 58
eISSN - 1099-1018
pISSN - 0308-0501
DOI - 10.1002/fam.2824
Subject(s) - fire protection engineering , cognitive bias , heuristics , probabilistic logic , fire protection , risk analysis (engineering) , cognition , computer science , engineering design process , resource (disambiguation) , fire safety , engineering , architectural engineering , artificial intelligence , psychology , civil engineering , medicine , mechanical engineering , computer network , neuroscience , operating system
Summary Fire engineering has developed into a mainstream engineering discipline within the building design process. Building fire codes are increasingly complex, comprising thousands of requirements regarding a wide range of topics that must be considered. Fire engineers are required to possess increasingly complex knowledge about a variety of subjects, along with expertise in their application. This has been magnified with the proliferation of performance‐based methods using a range of computational tools. This coupled with increased project performance pressures, raises the potential for errors in judgment. Errors in judgment may be caused by limitations in a given resource (e.g. time, information available, knowledge, etc) and/or neglect/over‐focus on specific information (at the expense of other and more relevant information) through cognitive biases. This paper initially provides a broad overview of general decision‐making, including the use of heuristics and cognitive biases. Examples of cognitive biases are presented which may be linked to errors in fire engineer decision‐making. This study considers several fire engineering decision contexts where cognitive biases may exist which are associated with fire code application, modeling/calculations, probabilistic risk assessments, general fire engineering practice, and perceptions based on experience. Potential measures to mitigate some of these biases and prompt better decision‐making are discussed. Those that may benefit from awareness of such biases and mitigation measures include not only practicing fire engineers, but also building developers, fire code committees, evacuation/fire/structural fire modeling developers, approving authorities, and fire engineering researchers/students.