tools are being developed, there is more work needed in furthering this effort.This also suggests a need in not only acquiring knowledge to first develop an expert system, but also acquiring knowledge to update the expert system once it is built. Once the expert system is delivered, the life cycle does not end here. There will have to be some persons responsible for maintaining and updating the expert system. For some expert systems, this "maintenance team" might be fairly large. XCON, an expert system developed by DEC for configunng VAX computer systems, requires a maintenance team of about 30 individuals. With better aids for acquiring knowledge in the front-end and back-end of an expert system's life cycle, the cortstruction and maintenance of an expert system could be greatly facilitated. ConclusionEven though expert systems have made great strides over the past ten years, there is plenty more work needed to further increase their "intelligence." This paper discussed some of the major limitations of current expert system technology and applications. In the years to come, these limitations will be addressed and hopefully resolved in order to make expert systems even more used throughout industry, government, and universities. As the field matures, there will be more structured methodologies and standards set for expert system development and implementation [6,7,8]. As this is done, a greater standardization of techniques for building and implementing expert systems will result. Through the setting of standards, the expert systems field will become even more recognized and reputable. As this occurs, the question of "artificial stupidity" in expert systems will become moot!