Knowledge Management History - What Evolved When

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The History Of Knowledge Management Part I: The Search for Artificial Intelligence

The first stage in the development of knowledge management focused on replacing human intelligence with artificial intelligence. Artificial intelligence had been a subject for debate long before computers were available. Philosophers such as Descartes debated whether people could be thought of as machines. With the advent of computers, the debate focused on whether they could be made to think. An early attempt at an `intelligent’ program was made by Newell, Shaw and Simon in the 1950s. The aim of the work was to produce a general problem solver (GPS). The generality of the GPS meant it was inefficient and superficial in its analysis.

The lesson from early systems such as the GPS was the realization that the successful encapsulation of knowledge is most easily attained within a specific and narrow problem domain. This led to the concept of expert systems as systems which model expertise within a narrow and specific domain. Within such domains, some notable successes were achieved; for example XCON was used by DEC to configure computers for many years from the 1970s onwards. It is noticeable, however, that the same case-studies are constantly quoted.

Today, there is still a mystique surrounding the subject of AI and consequent confusion about what can be achieved in practice. So let’s address these issues. Computers do not think for themselves. An AI application is a program like any other. It is a set of procedures, which the computer follows, with inputs and outputs. AI programs use a symbolic representation of the world. All computer programs are based upon a model of the problem they seek to solve. In conventional information systems, this model is constructed in terms of numbers. In an AI program, the model is constructed in terms nearer to a human view using symbols, such as text or pictures. The computer’s view is still a model, but is simply expressed in different terms.

Machine intelligence is not human intelligence. Human intelligence is a very broad and varied thing. Some of the characteristics of intelligent behaviour are reasoning, deduction, learning and adaptability. Machine intelligence seeks to model this behaviour, but is only able to do so in limited domains and in limited areas. Many machine intelligence techniques focus on only one or two aspects of human intelligence.

The History Of Knowledge Management Part 2: Adaptation to Support Human Decision Making

Because of the limitations noted above, the technology adapted to support human decision making instead of trying to replace it. This led to the first development of knowledge based decision support systems. These used rules to encapsulate knowledge which in turn was used to support human decision making. These systems had some notable successes, but suffered from the brittleness and narrowness of their knowledge base. They dealt with only limited knowledge domains, and could not determine when they had exceeded the boundaries of this knowledge base, leading to wild and inaccurate conclusions.

The History Of Knowledge Management Part 3: The Growth of Knowledge Repositories

Modern knowledge management has built on its history but instead of building complex heuristics on narrow knowledge bases, they tend to have simpler heuristics applied to large knowledge repositories. Here are some of the modern applications of this type:

Knowledge Management Systems for IT Helpdesks. IT Helpdesks have systems to collect and record queries from users seeking support. The system logs the queries and records the responses. From the responses given, the system builds a database of answers for the most common queries. Next time the same query comes in, the answer can be given straight from the system, and eventually published as a list of answers to frequently asked questions.

Patient Safety Decision Support. Prescribing errors kill an alarming number of patients every year. Modern electronic prescribing systems check prescriptions against a knowledge base of known drug interactions and the other prescription drugs you may be taking. They will also check dosages to ensure they do not exceed maximum safe doses. If it has access to your medical record, it can also check against your personal allergies or other factors which might be adversely affected by the prescribed drugs such as blood pressure or diabetes.