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Cybernetics, SMC-12(3), 389-393.
Two experimental studies were used to develop and evaluate a scheme for classifying human
errors in troubleshooting tasks. The experiments focused on looking at errors in diagnosis by
advanced aviation maintenance trainees. Experimenters were able to decrease the amount of
errors with experimental changes. A modification of the classification system of van Eekhout
and Rouse (1982) was used to classify errors into five general categories in the second
experiment. These categories are observation of state errors, choice of hypotheses errors, choice
of procedure errors, execution of procedures errors, and consequence of previous error. The new
classification system led to the redesign of the training program and a decrease in the frequency
of particular types of human error.
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Johnson, W. G. (1980). MORT: Safety assurance systems. New York: Marcel Dekker, Inc.
The MORT (management oversight and risk tree) logic diagram is a model of an ideal safety
program which is good for analyzing specific accidents, evaluating and appraising safety
programs, and indexing accident data and safety literature. MORT is useful in safety program
management for three reasons. It prevents safety related oversights, errors, and omissions. It
identifies and evaluates residual risks, and their referral to appropriate management levels for
action. Thirdly, it optimizes allocation of safety resources to programs and specific controls.
MORT is basically a diagram that presents a schematic representation of a dynamic, idealized
safety system model using fault tree analysis. Three levels of relationships exist that aid in the
detection of omissions, oversights, and defects. These are generic events, basic events, and
criteria. Furthermore, MORT explicitly states the functions that are necessary to complete a
process, the steps to fulfill a function, and the judgment criteria. A step by step outline is
provided for using the MORT system. The system is illustrated with examples. A major fault
with MORT is described as affirmation of the consequent. This is the fallacy of inferring truth of
an antecedent from the truth of the consequence.
Kahneman, D. & Tversky, A. (1984). Choices, values, and frames. American Psychologist,
39(4), 341-350.
The paper conducts a discussion of the cognitive and the psychophysical factors of choice in
risky and riskless contexts. A hypothetical value function is developed that has three important
properties. These properties are that the value function is defined on gains and losses rather than
on total wealth, it is concave in the domain of gains and convex in the domain of losses, and it is
considerably steeper for losses than for gains. This last property has been labeled loss aversion.
Three main points are made apparent. First, the psychophysics of value lead to risk aversion in
the domain of gains and risk seeking in the domain of losses. Second, risk aversion and risk
seeking decision making can be manipulated by the framing of relevant data. Third, people are
often risk seeking in dealing with improbable gains and risk averse in dealing with unlikely
losses.
Kashiwagi, S. (1976). Pattern-analytic approach to analysis of accidents due to human
error: An application of the ortho-oblique-type binary data decomposition. J. Human
Ergol., 5, 17-30.
An ortho-oblique-type binary data decomposition is proposed as a means of classifying patterns
of human error. The method is described mathematically and then applied to accidents in freightcar
classification yard work. The ortho-oblique-type of binary data decomposition is useful
because it tends to produce results that are very easily interpretable from the empirical point of
view. The main reason for adopting the method is that it allows data in the form of documents to
be made feasible for numerical classification by use of binary data matrices. The analysis of the
data showed that there are specific patterns of relevant and background conditions for most
accidents that are due to human error.
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Kayten, P. J. (1989). Human performance factors in aircraft accident investigation. Human
Error Avoidance Techniques Conference Proceedings (pp. 49-56). Warrendale, PA: Society
of Automotive Engineers.
The author examines that evolution of human performance investigation within the National
Transportation Safety Board (NTSB). The importance of the background of the accident
investigator is explored. An argument is made that a background in the domain of the accident is
helpful, but definitely not required to be effective. Relevant facts to be collected, ignored, and to
be further thought about are discussed. It is greatly stressed that investigative techniques and
　
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