Cognitive Task Analysis: An Approach to Knowledge Acquisition for Intelligent System Design

Publisher Summary This chapter discusses some of the common pitfalls that arise in building intelligent support systems and describe a pragmatic knowledge acquisition approach for defining and building effective intelligent support systems. The cognitive task analysis provides an umbrella structure of domain semantics that organizes and makes explicit what particular pieces of knowledge mean about problem-solving in the domain. Acquiring and using such a domain semantics is essential (l) to specify what kinds of cognitive support functions are needed, (2) to specify what kinds of computational mechanisms are capable of providing such functions, (3) to clearly delineate machine performance boundaries, and (4) to build less brittle machine problem-solvers, for example, through features that enable the human problem-solver to extend and adapt the capability of the system to handle unanticipated situations. This is in contrast to technology-driven approaches where knowledge acquisition focuses on describing domain knowledge in terms of the syntax of particular computational mechanisms. In other words, the language of implementation is used as a substitute for a cognitive language of description. The cognitive task analysis approach redefines the knowledge acquisition problem: knowledge acquisition, first, is about deciding what kinds of intelligent systems would make a difference and, second, about what domain specific knowledge is needed to fuel those systems.