Expert systems and their implementation in chromatography
Mary Mulholland · 1992
Abstract Artificial intelligence (AI), and expert systems (ES) in particular, have been the subject of much hype and media-built expectation. This is mainly due to the human factor of this technology. ES apply human terminology to non human things and use their own peculiar language of fuzzy logic, demons, rules, and frames. All this surrounds them with an aura of mystery. It is interesting to speculate on why ES receive so much attention: there seem to be several reasons. Firstly, they promise to make information technology (IT) and computer software more human and less algorithmic. This allows computers to tackle a whole new arena of human problems. The ability of ES to imitate real experts also raises expectations that these problem solvers are easier to use and learn from than conventional software. Secondly, workers increasingly need to access expertise from outside their own subject domain. This is particularly true for the modern biochemist, who is expected to be a combination of statistician, analytical chemist, information technologist, mechanic, plumber ... the list could go on and on. Finally, it is a well-known business maxim that a company’s most valuable asset is its personnel. ES can allow this experience and skill to be preserved within a company. Taken all together, these reasons can leave no doubt as to why there is currently a huge market for this technology.