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A major complaint of people who use "decision-making" computer programs is that these programs merely provide a final decision, and fail to present the supporting argumentation, in terms the user can understand. This article presents an approach that makes computer programs more "human-like" by basing them on human decision making behavior.
Decision making processes of student financial analysts are captured by asking them to think aloud during their evaluation. These verbal traces, called protocols, are analyzed at various levels of detail, resulting in specific models of the decision making processes involved, the strategies used, and the task-specific (financial) knowledge that is required to perform the task. The models and strategies are translated into executable computer programs. Extensive comparisons between human behavior and model simulation output are provided, assessing the extent that the computer program "thinks" and "talks" like a human decision maker. Although the model clearly suffers from "linguistic rigidity," it does appear to perform the evaluation in a similar manner as the human decision maker examining the same information in the same order, making the same inferences, and reporting the same conclusions.