It could report that it knew the bird was a black footed albatross because it knew it was dark colored and an albatross. It could similarly justify how it knew it was an albatross. At other times, however, the explanations are relatively useless to the user. This is because the rules of an expert system typically represent empirical knowledge, and not a deep understanding of the problem domain. For example a car diagnostic system has rules which relate symptoms to problems, but no rules which describe why those symptoms are related to those problems.
Explanations are always of extreme value to the knowledge engineer.
They are the program traces for knowledge bases. By looking at explanations the knowledge engineer can see how the system is behaving, and how the rules and data are interacting. This is an invaluable diagnostic tool during development. In chapters 2 through 9, some simple expert systems are used as examples to illustrate the features and how they apply to different problems. These include a bird identification system, a car diagnostic system, and a system which places furniture in a living room.