Human factors and folk models
common-sense models are not necessarily incorrect, but compared to articulated models they focus on descriptions rather than explanations and are therefore very hard to prove wrong. This article examines the characteristics tht set apart folk models used to explain human performance from other models and that limit their ability to effectively further the growth of human factors knowledge.
Characteristics of folk models
Explanation by substitution
One unifying characteristic of these models is that assumptions about non-observable constructs are conveniently endowed with the necessary causal power without any specification of the mechanism responsible for such causation.
The first and most evident characteristic of folk models is that they define their central constructs, the explanandum, by substitution rather than decomposition or reduction. So instead of explaining the central construct by statements that refer to more fundamental and presumably better known explananda, the explanation is made by referringto another phenomenon or construct that itself is in equal need of explanation.
In the examples used above, complacency is equated with boredom; overconfidence; contentment; unwarranted faith; overreliance; a low index of suspicion; and self-satisfaction.
Immunity against falsification
Following Popper’s rejection of “inductionism”, […] theories and hypotheses can only be deductively validated by being falsified or refuted. This usually involves some form of empirical testing to look for exceptions to the postulated hypothesis, where the absence of contradictory evidence becomes corroboration of the theory. Falsification deals with the central weakness of the inductive method of verifiation, which, as pointed out already by the 18th Century philosopher David Hume, requires an infinite number of confirming empirical demonstrations.
models that do not allow for proper falsification are highly suspect, and should be kept at arm’s length.
Overgeneralisation
the Yerkes-Dodson law. Ubiquitous in textbooks, the inverted U-curve couples arousal with peformance, usually without clearly stating the units of either, in such a way that a person’s best performance is claimed to occur between too much arousal (or stress) and too little.
Overgeneralisations take narrow laboratory findings and apply them uncritically to any broad situation where behavioural particulars bear some prima-facie resemblance to the phenomenon that ws investigated under controlled cirumstances.
Models and measurements
Most models are structural: they represent the functions of a system (in particular, of the human mind) by means of hypothetical structures as well as by the relations between them.
This description implies that measurements should be related to the theoretically defined functioning of these units, as well as to the links (or information channels) between them.
In the 1960s and 1970s the modelling efforts focused on the fundamental information processes, particularly those related to perception and memory. Measures were defined according to the models, as for instance limited capacity central processing or levels of processing in multi-store memory models. The details of the mdoels, and the constrained character of the phenomena being studied, allowed very specific measurements to be proposed. Later on, when the interest turned down from the mechanisms of perception and memory to the cognitive functions that were part of, for example, problem solving or reasoning, it became more difficult to propose theory-based measurements.
Since there are cases where an articulated theory is not available, measurements an also be derived from a general understanding of the characteristics of the system and of the conditions of human work.
Folk models describe measures that reflect an important aspect of the operators' situation, but related to intermediate “cognitive” states rather than to the actual performance. It is assumed that the measurement is a valid substitute for acutal performance measurement, because it refers to an essential intermediate or intervening state. It is also assumed that the measurement is affected by the performance conditions to the same extent and in the same manner as the actual performance. Yet it defies reason why it should be more important to look for measurements of hypothetical internal states than for measurements of the performance that admittedly is determined by internal states.
Measurement possibility versus interpretation
Folk models versus young and promising models
Although folk models clearly have their problems, one risk in rejecting them outright is that the baby is thrown out with the bath water. In other words, theere is the risk of rejecting even those models that may be able to generate useful empirical results, if only given the time and opportunity to do so.
We may therefore rightly ask what opportunity the newer folk models should receive before being reject as unproductive? The answer to this question hinges, once again, on falsifiability. Progress in science is often described as the succession of theories, each of which is more falsiable (and therefore more informative) than teh one before it. Yet if we assess “loss of situation awareness” or complacence as more novel explanations of phenomena that were previously covered by other explanations, if it is easy to see that falsifiabilityhas actually decreased rather than increased.
The vulnerability to folk modelling
The deceptive ease by which we can extrapolate our everyday experiences (getting lost, forgetting, not paying attention, and so forth) to understand the complex events we hear or read about make us blind to the fact that such descriptions are not scientific explanations. Human factors, being both a science and a practice, may well be specifically vulnerable to this erroneous belief, hence to the use of folk models.
The greatest risk of folk models is that they appear to make sense, even though statements and conclusions may not be falsifiable. They may therefore seem more plausiable than articulated models, since the latter require an understanding of the underlying mechanisms.
Conclusions
focus on the characteristics of performance rather than on inferred and uncertain states of the mind. In other words, to study what has come to be known “cognition in the world” – although this term is meaningful only as an antithesis to “cognition in the mind”. (We should furthermore not be too concerned about cognition, but rather be concerned about performance.) One point in favour of that is that we actually do have recorss of performance. That is exactly what is contained in the systematic recordings of system status, if we change the focus from the performance of the individual to the performance of the joint system. Following the principles of cognitive systems engineering, we should not be overly concerned with the performance of the plot per se, but rather with teh performance of the pilot + aircraft = in other words, the joint pilot-aircraft system.