The information technology hype can sometimes be misleading. It is often the case whenever knowledge comes into the information resources discussion. Readers can be confused by the high degree of inconsistency in the use of the word information, and this confusions seems to have increased since the introduction of consumer level information technology.
In fact, the word itself has come to include anything that is not raw materiel but is starting to include more and more the supporting computer technology. As the Information processing systems, equipment and data sources are becoming information resources, users feel the need to refer to a more synthetic concept to depict what is beyond their perceptions of data and machines.
Often, we have to try to decipher the boundaries between information and knowledge...almost as often as we have to make a solomonic judgement between intelligence and computing.
Three dimensions of information
Michael Buckland ( in Information as thing, Journal of the American Society for Information Science, 1991, Vol 42, no 5. pp 351 ss) has identified three pragmatic meanings to information:
In some cases, information is used to describe the process of informing, of communicating the knowledge. Information-as-process is a good way of describing an information desk, even an information centre service where people can acquire the news, the facts or the elements of data which are required for their action;
In other cases, information is used to describe what is perceived in the data or facts which result from the information-as-process. The best example of Information-as-knowledge is probably military intelligence and scientific communications where it is not the facts, statistics or the events which are of significance as much as the capacity to place these in a broader context. Information-as-knowledge is considered then as a means of decreasing (and sometimes increasing) uncertainty about the universe.
In the remaining cases, information is attributed to objects such as data, documents, books that are referred to as information because they are regarded as informative. Information-as-thing is conferred, by its user, the quality of imparting knowledge or communicating elements of information.
The technology constraint
It is easy to realize that there are significant differences between information-as-knowledge and the others. This type of information possesses the attribute of being intangible and therefore impossible to measure in a direct manner.
In other words, information as knowledge is perceived as a conceptual model of some factual information The boundaries between fact and appreciation of the facts rest in the mind of the user or the information producer. Conversely, once this information as knowledge is captured in writing or in another communicable form, the representation of information-as-knowledge becomes information-as-thing.
The confusion around information and knowledge stems from the fact that is this last type of information which is the central focus of information systems technology. Buckland proposed that:
"the distinction between intangibles (knowledge and information as knowledge) and tangibles (information-as-object) is central to what follows. If you can touch it or measure it directly, it is not knowledge, but must be some physical thing, possibly information-as-thing.... Knowledge, however, can be represented, just as an event can be filmed. However the representation is no more knowledge than the film is the event."
The Holy Grail: Knowledge technology
This leads to a need to establish the basic differences in definitions between knowledge-based technology and knowledge management. In essence, a knowledge-based system is a technology which is attempting to process information-as-thing using representations of knowledge.
Knowledge representations are themselves conversions of rules of logic or relationships into a series of information statements within the system. How this is achieved is a matter of discussion between the various schools of Artificial Intelligence specialists. What is critical remains that the so-called knowledge-based systems are converting rules into information-as-thing in order to achieve a proper fit with the technology.
In this process, knowledge is not created by the expert system. The system actually uses and re-uses the available rules according to a logical pattern imbedded in the computer program.
In some cases, it has been possible to generate inference through the emulation of logical patterns, and thus create an additional series of rules, considered as "new knowledge". But this kind of "knowledge" is far from being complete and has serious problems of scope.
An appropriate metaphor would be to compare an artificial intelligence system to a human being whose behavior and decisions would be solely based on an assessment of facts against a set of beliefs contained say in four chapters of the Bible and guided by a strict adherence to the principles of the book. The person would be at loss in front of an incoming train, because the concept is not necessarily contained in the Bible. Still, there are probabilities, that the person can infer adequate behavior, all would depend on the quality of the logic and the capacity to recognize the threat presented by the train.
The essential limitation is that knowledge so acquired is event-driven not driven by a particular purpose. This is a can of worms which compares easily with the debate on pre-destination between the Protestant Reform and the Catholic Church.
GCM Sherpa Inc. 95.4 INFOKM.asc