ABSTRACT
Loss of control has become a leading cause of aviation accidents and human error is often recorded as the cause in favour of other factors. This has the effect of downgrading the significance of corrective actions to address deeper systemic issues, and serves the bad-apple theory of human error. This paper uses a model of learning and memory to expand on the analysis of negative training from the AA587 accident, which documented the actions of the First Officer as the probable cause and training as contributory. Evidence from the investigation and our contemporary understanding of learning and memory is used to explain how the experiences of the First Officer fit the scenario in which the accident occurred, such that it is plausible to extend probable cause beyond his actions. The paper develops a model of causal inference that enables analysts to continue probing causality as part of a systems approach.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. For an example of this, see the NTSB (Citation2014) aviation accident report for Asiana Airlines Flight 214, which led to dissenting safety board member statements regarding the role of automation design versus crew mismanagement in the accident.
2. AOA is the angle between the oncoming air or relative wind and a reference line or chordline on the wing. The chordline is an imaginary straight line joining the mid-point of the leading edge of the wing with the mid-point of the trailing edge.
3. Flight with the thrust reduced on one or more engines on one side of the aircraft to simulate handling an engine failure(s), which causes a thrust-induced yaw.
4. The safety board members vote on the findings, recommendations, and probable cause(s) of the accident. Dissenting members may state their disagreement and include a written dissension for incorporation into the final report (NTSB, Citation2002, 46).
5. The NTSB permits the use of a military investigations manual to supplement information in the NTSB Aviation Investigation Manual (NTSB, Citation2002, p.i.).
6. The Safety Board's analysis concluded that it appeared the Captain believed the aircraft motion was caused by the wake turbulence (NTSB, Citation2004, 134).
7. ‘Attitude’ is a generic term used to describe the orientation of the aircraft with reference to a datum, such as horizontal and level flight, thus an ‘extreme roll attitude’ describes a high angle of bank reference level flight.
8. Six pilots from the Safety Board human performance group performed the simulator trial and four of them stated that they were surprised by the onset of the event. The pilots were instructed to recover the aircraft according to the method detailed in the AAMP ground training, which led to all of the pilots responding with aileron supported by rudder pedal input (NTSB, Citation2004, 90).
Additional information
Notes on contributors
L. Sherwin
Leith Sherwin: Leith obtained his Masters from the University of South Australia and has over 25 years’ experience in the aviation industry with 15 years in military aviation as a navy pilot. This included over 3 years as a flight instructor at the Australian Air Force Advanced Flying Training School. Leith holds Air Transport Pilot licenses for Aeroplanes and Helicopters and his work in aviation safety roles started with his first investigation of a maintenance error incident in 1999. Over the last 5 years, Leith has worked in the Airline industry and Offshore Helicopter industry in the Safety Systems role and in this time, conducted over 100 investigations. Leith holds a Masters degree in Human Factors and Safety Management Systems and is a member of the Human Factors and Ergonomics Society of Australia, and International Society of Air Safety Investigators.
A. Naweed
Anjum Naweed: Anjum obtained his doctorate from the University of Sheffield in the UK. Anjum has experience with simulation, cognition and human factors that spans over a decade. He is now a Senior Research Fellow at the Appleton Institute for Behavioural Science in Central Queensland University in Australia. Anjum's research is focused on collision avoidance in complex systems, including complex decision-making, knowledge representation, display design, simulator-based training transfer, and participative processes at work. He has experience with a broad range of research methods and is interested in all aspects of human factors, particularly the relationship between humans and machines.