Appendix Four: Expert Systems and Hypertext: (Larson, 1989) An expert system moves through a set of rules in much the same way as an individual who selects paths in a decision tree. AUTOMATIC PATH SELECTION: An expert system can monitor time, pressure, temperature, etc. to automatically eliminate certain decision paths in the search for answers. In contrast, hypertext systems depend upon operator responses to make selected paths to answers. (limitation) CALCULATED DECISIONS: Expert systems often include formulas that convert any number of variable inputs into a single path selection. Instead of this parallel processing (multiple inputs - single answer), hypertext decision systems use a sequence of decision points (serial processing) in order to convert multiple inputs into a single path. (limitation) SPEED: An expert system may reach the appropriate decision within a fraction of a second (ie. avoiding an aircraft collision). With hypertext, speed is limited by the ability of the user to complete multiple sequences of reading, understanding, and selecting choices at each decision point. (limitation) However, hypertext has several significant advantages over expert systems in dispensing information or finding solutions: construction speed, time to learn, knowledge representation, ease of modification, sensitivity analysis, and transmission of knowledge. CONSTRUCTION SPEED: A good 200-rule expert system may take a team of knowledge engineers two years to build. In contrast, most experienced computer users can build in one day a good 200-node decision tree leading to relevant advice. (attribute) TIME TO LEARN: It often takes many years for experts in other fields (e.g., PROLOG, LISP, SMALLTALK) to efficiently embed their knowledge into automatic systems. In contrast, experts can master the tools of the hypertext system craft with just a few weeks effort. (attribute) KNOWLEDGE REPRESENTATION: Two major difficulties exist in building expert systems. First, how can users acquire expert-level knowledge? (often the expert can't even explain it). Second, how can this knowledge be represented so that a machine can generate solutions from it? In hypertext systems, the knowledge is represented using existing everyday formats (i.e., text, diagrams, pictures). (attribute) MODIFICATION EASE: Once completed, expert systems tend to be notoriously difficult to update or modify (many interactions are often hidden from users) and then to validate again (who knows when an expert machine starts or stops producing expertise?). With hypertext systems, modifications and improvements are as easy as adding branching comments and footnote text using a word processor. (attribute) TRANSMISSION OF KNOWLEDGE: Expert machines generally do not explain to users the actual methods that will lead to a particular decision. With hypertext, users directly participate in each and every decision that leads to a particular expertise. This process of openly displaying the structure and uses of knowledge readily transmits it to users of hypertext systems. (attribute) SENSITIVITY ANALYSIS: Expert machines usually provide a single answer supported perhaps by a confidence factor such as 82 percent certainty. Hypertext systems allow users to rapidly test alternative paths to see how sensitive the advice may be to changes in the initial assumptions. (attribute) Index to the Appendices Glossary of Hypertext