"Enabling organizations to capture, share, and apply the collective experience and know-how of their people is seen as fundamental to competing in the knowledge economy. As a result, there has been a wave of enthusiasm and activity centered on knowledge management. To make progress in this area, issues of technology, process, people, and content must be addressed. In this article, we develop a road map for knowledge management. It begins with an assessment of the current state of the practice, using examples drawn from our experience at Schlumberger. It then sketches the possible evolution of technology and practice over a 10-year period. Along the way, we highlight ways in which AI technology, present and future, can be applied in knowledge management systems."

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Collective Knowledge Bases. From the University of Washington Artificial Intelligence Research Group. "The production and use of knowledge is a collective enterprise, and communication between its participants is the bottleneck. Some of the costs of this bottleneck are duplicated work, misdirected work, slower progress, and suboptimal decisions for lack of knowledge that is actually available.... In particular, we are developing methods to improve the composability of knowledge by semi-automatically learning to translate between the vocabularies of different sources. This can potentially lead to an exponential increase in the number of questions answerable by a collective knowledge base. We are also developing methods to automatically learn the quality of knowledge sources and elements, to properly take advantage of sources of widely variable quality, to automatically resolve inconsistencies between sources, and to automatically give feedback, credit and guidance to contributors, such that a collective knowledge base can grow and improve harmonically without centralized control."

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