Title

Surprise, Attraction, And Propagation: An Aircraft Is No Place For A Catastrophe

Abstract

The management of off-normal operational events, such as an aircraft in-flight loss of control, present a formidable challenge to the stakeholders of commercial aviation. This paper posits that present solutions to off-normal events are grounded in linear models of accident causation that are insufficient in today's complex socio-technical domain-where change propagates through systems to produce instability and system state shifts. These prior methods of system safety are predominately predicated upon the notion that system failure can be mitigated to acceptable levels of risk by using defenses, constraints, and controls in design and practice; such perspectives also influence post-accident investigation and remediation. This paper provides a new theory of aircraft accident causation, Catastrophic Information Entropy Theory (CIET), which offers that an increase in information entropy during an off-normal event, produces emergent changes in system state that prevent a return to normal flight. Therefore, in the face of runtime accident factor propagation, surprise, and attractors, the management of off-normal events, utilizing rigid feed forward procedures may make recovery inaccessible. CIET suggest that existing safety strategies need to be expanded to include the recognition of the time-critical role of the pilot, who must attempt to understand and control a complex system which is behaving in a novel and emergent way. CIET offers a theoretical perspective from which aviation stakeholders can design tools for actionable solutions for pilots during real time emergent events and tools for post-event analytic approaches.

Publication Date

1-1-2014

Publication Title

Proceedings of the Human Factors and Ergonomics Society

Volume

2014-January

Number of Pages

105-109

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1177/1541931214581023

Socpus ID

84957677316 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84957677316

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