A fuzzy system for mapping worker attributes to tasks

We developed a prototype of a rule-based expert system that facilitates a mapping from tasks comprising a job to the knowledge, skills, and abilities (KSAs) ostensibly required to perform the tasks. A variant of fuzzy logic was employed in the inference process. Signal detection theory was used to evaluate the performance of the system. The results indicated that the system performed well in terms of its ability to discriminate between the KSAs that are required of a task and those that are not. The discussion focuses on implications of the system and its use as an intelligent assistant in human resources planning.