Computer-aided decisions in human services: Expert systems and multivariate models

Abstract

Two approaches to the development of computerized supports for decision making are compared. Expert systems attempt to codify the formal and heuristic knowledge of human experts in the form of rules. However, estimates of relationships and probabilities provided by experts are prone to error and distortion. In contrast, multivariate procedures derive rules and relationships empirically by using the accumulated evidence from hundreds of cases on a data base. Results from several fields have consistently demonstrated that conclusions generated using statistical models are equal or superior to the decisions made by clinicians. The major strength of expert systems is the use of natural language and explanation facilities which make them more intelligible to the user. Combining this aspect of expert systems with the power of multivariate procedures may allow for the development of an approach that achieves optimal performance but is also more acceptable and accountable to the user.