Explaining quantitative systems to uninitiated users

摘要

The importance of explanation in expert systems has been documented from the early days of their development; there is an equally pressing need for explanation in systems that employ a decision-making process based on quantitative reasoning. This is particularly necessary for users who do not have a sophisticated understanding of the formal apparatus that the system employs to reach its decisions. In order to generate meaningful answers to questions asked by such unsophisticated users, an explanation facility must translate the formal structures of the problem solving system into the concepts with which the user understands the problem domain. Previous work on the explanation of quantitative systems is based on the assumption that the user has at least a basic grasp of the formal approach of the problem solving system. However, in realistic application situations, it is more likely the case that in order for the human user to understand why a mathematically-based advice-giving system makes the suggestions that it does, the problem solving rationale of the system must be explained in the user's own terms, which are typically different from those of the mathematical system. To develop an explanation methodology that is capable of justifying the results of a system based on quantitative reasoning to an uninitiated user, we employ a representation that enables our explanation facility to translate the abstract mathematical relationships that make up a quantitative system into the domain-specific concepts with which a typical user approaches the problem solving task. In our system, the process of generating explanations, therefore, involves translating one set of concepts into another. An added feature of this system is that it is capable of providing explanations from two perspectives: that of the quantitative problem solving system, and that of the human user who is familiar with the domain problem but not with the mathematical approach. We have implemented this approach to explaining quantitative systems by creating an explanation facility for a problem in the manufacturing domain. This facility responds to user queries about a scheduling system that uses a mathematically-based heuristic to choose jobs for an annealing furnace.