Designing Decision Support Systems to Help Avoid Biases & Make Robust Decisions, With Examples From Army Planning

摘要

This paper is concerned with two sets of issues related to optimality in planning. The first is a proposal that design of decision support systems (DSS's) for planning should aim to support the planner in generating a plan that is robust, i.e., has satisfactory performance even when reality differs from assumptions. Such a plan would sacrifice optimality when reality is as assumed for reasonable performance over a larger range of situations. We discuss how this proposed refocus follows from the in-principle incompleteness, and common errorfulness, of domain models required to assess the performance of plans. The second issue related to optimality is the degree to which human judgment in planning is subject to a number of biases, all detracting from optimality. The Framing Bias arises from the Bounded Rationality of human cognition. The Transitivity Bias is a result of treating small and large differences in the criteria values as of equal importance. Our analysis leads to design recommendations for DSS's that provide a measure of protection against these biases. The ideas are motivated and illustrated with Army planning examples.