So far, we have thought of the knowledge in a decision support system as monolithic - that is, as a single entity, without considering how it comes about or how it works in an expert system or artificial intelligence. It turns out the knowledge base of a decision support system is about as monolithic as a jet engine, which from a distance can be considered as one object - yet when considered in detail, is actually fantastically complex in its construction (how it was made) and composition (what's in it). (As an aside, many aspects of the course can be considered this way - after all, systems are by definition a massive part of what we study.)

In a classwork post (or a document attached to one), please complete the following:

1. Identify some of the factors that make knowledge acquisition complicated.
2. Evaluate the importance of knowledge validation in a decision support system's knowledge base.
3. Describe a situation in which a decision support system (a) requires and (b) does not require the ability to provide sophisticated explanation and justification for its advice.
4. Read the infobox on pages 216-217 and answer the question at the end.