Heuristics to Improve Human Factors Performance in Aviation

Heuristics to Improve Human Factors Performance in Aviation

Journal of Aviation/Aerospace Education & Research Volume 20 Number 3 JAAER Spring 2011 Article 8 Spring 2011 Heuristics to Improve Human Factors Performance in Aviation William A. Tuccio Follow this and additional works at: https://commons.erau.edu/jaaer Scholarly Commons Citation Tuccio, W. A. (2011). Heuristics to Improve Human Factors Performance in Aviation. Journal of Aviation/ Aerospace Education & Research, 20(3). https://doi.org/10.15394/jaaer.2011.1640 This Article is brought to you for free and open access by the Journals at Scholarly Commons. It has been accepted for inclusion in Journal of Aviation/Aerospace Education & Research by an authorized administrator of Scholarly Commons. For more information, please contact [email protected]. Tuccio: Heuristics to Improve Human Factors Performance in Aviation Heuristics Human Factors Aviation HEURISTICS TO IMPROVE HUMAN FACTORS PERFORMANCE IN AVIATION William A. Tuccio Abstract This paper reviews literature related to heuristic cognitive strategies as they are used by flight crews. A review of heuristic and naturalistic cognition is presented. An example set of heuristics and cognitive biases are presented and where possible exemplified by 19 airline accidents. The paper suggests two tentative research designs which could be pursued to quantitatively study heuristics and its impact on aviation decision making. The paper concludes that aviation pilot training would benefit by introducing pilots to the concepts and constructs of heuristic thinking. This paper reviews the literature related to a variety of only, whose purpose is to discover the solution of cognitive strategies under the broad umbrella of heuristics the present problem ... We shall attain complete and biases. Where possible, the heuristics are demonstrated certainty when we shall have obtained the against 19 example airline accidents. Following the complete solution, but before obtaining certainty cognitive introduction, an inventory of heuristics is we must often be satisfied with a more or less presented aimed at demonstrating that time limited decision plausible guess. We may need the provisional making is defined by heuristic cognitive strategies. A before we attain the final. We need heuristic research model is suggested to quantitatively study reasoning when we construct a strict proof as we heuristics in aviation. The paper concludes that aviation need scaffolding when we erect a building. (P6lya, pilot training would benefit by introducing pilots to the 1985, p. 113) concepts and constructs of heuristic thinking. P6lya is pointing out that many aspects ofproblem Human Factors and Heuristics Background solving may end up in a state of complete certainty, but In their book, The Limits ofExpertise, Dismukes, Berman, problems often require thinking which is sufficient for the and Loukopoulos analyze 19 airline accidents occurring problem at hand. Heuristic reasoning may therefore either be over a near ten year period. While the authors draw out a means or an end in problem solving: for probabilistic many themes and proximate causes of the accidents, Table solutions, heuristics can be an end, while for problems 1 (see Appendix) summarizes the cognitive aspects of each requiring certainty, heuristics may be a means to an end. accident. The cognitive aspects often point out faults in P6lya' s heuristics view supports and complements the views human decision making, such as plan continuation bias, the of Nobel Prize economist Herbert A. Simon who posited a anchoring heuristic and availability heuristic (Dismukes, view of problem solving known as satisficing. Simon Berman, & Loukopoulos, 2007). Throughout this paper, suggests real-world solutions by organisms and economics reference will be made to Table 1 as examples of cognitive are often practically defined not by rationality or even constructs. probabilistic, recursive optimization, instead by a solution Heuristic thought processes fall under the broader which is sufficient for the problem at hand, topic of naturalistic decision making and bounded Since the organism, like those of the real world, rationality. The term heuristic is an often misunderstood has neither the senses nor the wits to discover an term. In the popular mathematics book, How to Solve It, 'optimal path'---even assuming the concept of P6lya introduces heuristic as, optimal to be clearly defined-we are concerned Heuristic reasoning is reasoning not regarded as only with finding a choice mechanism that will final and strict but as provisional and plausible lead it to pursue a 'satisficing' path, a path that will JAAER, Spring 2011 Page 39 Published by Scholarly Commons, 2011 1 Journal of Aviation/Aerospace Education & Research, Vol. 20, No. 3 [2011], Art. 8 Heuristics Human Factors Aviation permit satisfaction at some specified level of all of solution is to use Bayesian methods, which use statistical its needs. (Simon, 1956, p. 136) methods ofprobability to define an optimum solution named Simon advances P6lya's heuristic concepts into a after the 18th century mathematician (International society framework where problem solving is defined holistically by for Bayesian analysis (ISBA), 2010). However, it is often considering both the person making the decision and the the case resources do not exist to find a solution ofcomplete environment where the decision is made. Gigerenzer and certainty, furthermore, the environment in which one Todd build upon Simon, and contrast the views of operates does not permit a solution of certainty. The unbounded rationality and ecological rationality (1999). As environment may be sufficiently constrained to support a shown in Figure 1, unbounded rationality, characterized by limited number of outcomes discoverable with heuristic Gigerenzer and Todd as "Demons", assumes a complete, thinking: A bounded solution-what Gigerenzer and Todd logical solution exists and resources are available to find call ecological rationality and Simon calls satisficing. such a solution, or as P6lya says, a solution of complete certainty. One common measure of an ideal, probabilistic Visions of Reality I I I Demons Bounded Rationality I I I I I I Optimizations Fast and Unbounded Under Satisficing Fn1gal Rationality Constraints Heurisitcs Figure I. Visions ofreality, adapted from "Fast and Frugal Heuristics: The Adaptive Toolbox," by G. Gigerenzer and P. M. Todd, 1999, Simple Heuristics Which Make Us Smart,p. 4. Copyright 1999 by Oxford University Press. Page40 JAAER, Spring 2011 https://commons.erau.edu/jaaer/vol20/iss3/8 DOI: https://doi.org/10.15394/jaaer.2011.1640 2 Tuccio: Heuristics to Improve Human Factors Performance in Aviation Heuristics Human Factors Aviation A common theme of the accidents shown in Table Klein points out NDM research funding started in the early 1 is that, while preventable, the accidents did not point to 1980s by the U.S. Army and later by the U.S. Navy deficiency or negligence by an individual, rather to a failure following the shoot down of an Iranian airliner by the USS of the aviation system. As the ICAO Safety Management Vincennes in 1988. Various researchers agree that the way Manual (SMM) points out, the safety adage that 70% of all people make time pressured decisions is not via a process of accidents are caused by human error is a flawed perspective, generating internal probabilities and comparing rational "Simply put: humans design, manufacture, train, operate, option sets, rather, decision makers use categorization of manage and defend the system. Therefore, when the system prior experience to solve new problems, often including breaks down, it is ofnecessity due to human error. From this rapid mental simulation of outcomes. These mental perspective and depending upon the level of observation, simulations are inferential based on past experiences and one hundred per cent of accidents are arguably caused by training (Klein, 2008). human error'' (International Civil Aviation Organization Gigerenzer and Todd's view of unbounded [ICAO], 2009, p. 7-14). rationality versus bounded rationality and Klein's Jn the language of Safety Management Systems perspective on NDM are part of the F AA's Risk (SMS), the accidents of Table 1 had a certain chance of Management Handbook. After pointing out the distinction occurrence, given the probabilistic nature of the between analytical decision making as a method useful environment intersected with human decision making as when time is available, the handbook goes on to discuss opposed to a deterministic endeavor (Dismukes et al., 2007). automatic and naturalistic decision making as a useful tool Spoken in a different vernacular, in Fate is the Hunter, in time critical situations. While the handbook mentions Gann says, NDM, it makes no direct mention of heuristics and has only And sometimes they [accident investigators] two references to the general topic ofbiases, which are often discover a truth which they can explain in the hard, a byproduct of heuristic thinking (Federal Aviation clear terms of mechanical science. They must Administration, 2009). If the cognitive processes of pilots never, regardless of their discoveries, write off a are in fact modeled by heuristics, then it is plausible to crash as simply a case of bad luck. They must suggest decision making education and training should never, for fear of ridicule, admit other than to include a discussion of heuristics. themselves, which they all do, that some totally While cognitive issues discussed thus far offer a unrecognizable genie has once

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