Abstract
Abstract: Although MIS professionals had predicted that expert systems would improve productivity enormously, and a number of expert system application success stories have been reported, the expert system revolution has not yet happened. Moreover, there have been many cases, less well publicised, where expert systems have failed. Most problems concerning expert systems failure stem from non‐technical issues such as cognitive and psychological problems, rather than such purely technical issues as an inference engine and an expert system shell. Here, the major reasons for expert systems failure and the need to consider human factors are discussed. We then propose human factor principles that can help designers handle most of these non‐technical problems and many technical ones elegantly, improving the performance and acceptance of expert systems. Finally, some human factor guidelines for expert systems are presented so that these considerations may be incorporated into expert systems development in a clear and comprehensible manner.
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