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) 

<gfile01> Index to the Appendices
<gfile41> Glossary of Hypertext