The Psychology of Expertise: Cognitive Research and Empirical AI

By Robert R. Hoffman | Go to book overview

7
Knowledge Acquisition and Constructivist Epistemology
Kenneth M. Ford and Jack R. Adams-Webber
Introduction
The most fundamental step in the knowledge acquisition phase of the development of an expert system is the elicitation of knowledge from a skilled individual. The knowledge acquisition phase has typically involved the knowledge engineer's working closely with a specialist to elicit relevant knowledge from the latter's domain. This is typically a tedious and ad hoc cycle that consists of extensive verbal interviews followed by the construction of prototypes, testing, and more interviews. This approach has two significant drawbacks -- it has been extremely laborious, and domain experts often have difficulty articulating their knowledge in forms useful to the knowledge engineer. Indeed, it has been suggested ( Feigenbaum & McCorduck, 1983) that "the problem of knowledge acquisition is the critical bottleneck in artificial intelligence" (p. 80).A commonly proposed partial solution to the knowledge acquisition bottleneck is the design and implementation of automated tools for the purposes of interacting with domain experts, acquiring and organizing knowledge, and automatically generating a prototype expert system. Among the expected benefits of automating at least a portion of the knowledge acquisition process are the following:
1. An automated approach may be moreefficient than manual interviewing methods, thereby reducing the great expense presently incurred in the knowledge acquisition phase.
2. Automated approaches may prove able to elicit expertise not easily obtained by manual interviewing methods, thus producing systems with greater expertise.

To provide these desired benefits, automated approaches to knowledge acquisition must assist the knowledge engineer in avoiding the domain experts' cognitive defenses and reduce the representation mismatch -- the difference between the manner in which the domain expert normally states knowledge and the way it is represented in the expert system knowledge base. The design and construction of knowledge acquisition tools have recently become areas of intense research and development.

As noted by Bradshaw and Boose ( 1990), a major difficulty has been that much of the aforementioned work lacks a plausible theoretical foundation:

As a consequence of incomplete theory and a limited repertoire of practical approaches to the dynamics of the modeling process, knowledge engineers have had to rely on intuition and experience as the primary means of developing and testing effective procedures. (p. 129)

Many of those engaged in knowledge acquisition (as researcher or practitioner) may be classified as toolmakers and/or tool users. Toolmakers should exploit theory as a means of building their tools on a sound footing and as a framework in which to make explicit their epistemological assumptions. Furthermore, theory may offer toolmakers a useful infra-

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