If you think about it, these three disciplines have a close relationship to the three disciplines of AI. Specifically we could identify relationships between management
and cognitive psychology, knowledge and linguistics, and technology and computer science.Management at its most basic level consists of cognitive psychology processes supported by linguistic processes, in the form of verbal
communications, specifically adjusted to management processes. The knowledge aspect of knowledge work is related to cognitive psychology (representation and processing) and computer science (algorithms, representation, and
implementation). Lastly, technology is allied with computer science because in the case of knowledge work, technology is primarily computer-based. We can say that AI and knowledge-work are homomorphic (sharing conceptual
principles).
Although AI might not be the ultimate answer to the problems of knowledge management, you might consider drawing from the extensive contributions of AI to represent knowledge. For example, you might choose to use
frames, semantic networks, rule-based knowledge representation, or neural networks as a means to represent knowledge captured knowledge.
But That's Just A Technology and That's Easy
Interestingly, I hear lots about why
knowledge work is so difficult to explicitly introduce into an organization. Even so, there are many people who continue to describe knowledge management as important and key to business. AI technologies might provide tangible
deliverables making knowledge work more easily understood. Why not view AI as a concrete way to provide an approach to the introduction of knowledge work?
For example, suppose you work in an organization that uses an expert in a
particular domain and there are so few experts in this field that your expert is the only one based in the United States. Because of the esoteric nature of the expert's discipline, there are no new students in the pipeline, and to
make matters worse, this individual must retire soon due to company policy. What do you do?
You could go to management and suggest that a knowledge effort would be appropriate; that it would be a way to retain the expert's
knowledge. Based on management's familiarity or lack thereof, with knowledge work this request might not be sufficiently tangible to win management support.
A slightly different approach might be to recommend a project to codify
the expert's knowledge in such a way that the expert's knowledge could be used. You could show bonified examples (frames), and show how the expert validated these. Furthermore you could show ways these could be readily used for
knowledge sharing and transfer (up until now this knowledge only rested in the expert's mind). By doing this and showing tangible and concrete deliverables, management becomes better able to understand and support projects like
this. Remember for every one enlightened manager there are hundreds of those who are neither enlightened nor interested.
I've tried to describe one view of the relationship between AI and knowledge-work. The point, I think, that
is most important is that AI has a rich history of exploring knowledge-based problems. Although AI cannot claim to have found solutions to all problems there is a rich base of formalisms and methods supporting knowledge work. When
asked the HOW-question, we should not lose sight of this rich background. As knowledge work professionals these techniques should be as important to you as those considered more relevant by many because they are more tangible.
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