Decision Training for Human Rule-Based Reasoning under Time Pressure
In many emergency situations, human operators need to derive countermeasures based on contingency rules whilst under time pressure. Since it has been found that people tend to process information intuitively and to be overconfident regarding their performance level, it is necessary that operators be well trained in decision making for the safety-related domain. In order to contribute to the human success in playing such a role, the present study intends to examine the effectiveness of using expert systems, an excellent rule-based reasoner, to train for the desired decision performance. Emergency management of chemical spills was selected to exemplify the rule-based decision task. An expert system in this domain was developed to serve as the training tool. Forty subjects participated in an experiment in which a computerized information board was used to capture subjects' rule-based performance under the manipulation of time pressure and training The experiment results indicate that people adapt to time pressure by accelerating their processing of rules where the heuristic of cognitive availability was employed. The simplifying strategy was found to be the source of human error in rule-based reasoning, and also the root resulting in confirmation bias that led to overconfidence. The results also show that the decision behavior of individuals who undergo the expert system training is directed to a normative and expeditious pattern, which leads to an improved level of decision accuracy and appropriate realism of confidence judgment. Implications of these findings for human decision behavior, computer-aided training, interface design, and industrial safety are examined in the present study.
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