Key Issues in The New Knowledge Management (2003), by Joe Firestone and Mark W. McElroy, is for me a welcome library addition. A strong point is the focus on the epistemological issues. The summary of various theoretical underpinnings is clearly laid out.
I have felt uncomfortable with the traditional knowledge pyramid which has a base of raw data, then information, knowledge and a capping of wisdom. The traditional model is superficially seductive. It assumes that pure data are converted into information and then semantically assimilated into a body of knowledge. The question asked by the authors is how can such data be primary, let alone pure? How can perception be primary? Without existing propensities or expectations, agents or their computers cannot perceive anything. An agent’s pre-existing information provides structure to the world of experience. Data are types of information. Without structure experience is not data. What is normally treated as information is in the authors’ view, “just information”, that is to say information with conceptual commitments plus interpretations.
Knowledge is a subset of information (not a superset) that has been evaluated without ever being proven. Knowledge is an outcome of knowledge production and integration processes. It is an object (thing) that is uncertain but testable. Wisdom is knowledge coupled with value judgments and actionable assessments, it has untested metaphysical qualities.
Thus rather than a model based on a pyramid, it seems to be epistemologically more appropriate to picture a Knowledge Life Cycle in which data, “just information” and knowledge are types of information. New data and knowledge are made through this Knowledge Life Cycle from pre-existing information. That is from “just information”, data, knowledge, and problems.
Karl Popper, to whom the authors are indebted, said that all life is problem solving. One might say that all knowledge management is problem solving. Corporations depend on validated information but this is not the same as saying they depend on true or certain information. The critical method is that of making all knowledge claims testable i.e. capable of being falsified by a non-empty universe of test statements. Those claims that have not been falsified are preferred to those that have failed testing, without the luxury of ever being content that the knowledge cycle has found a utopia of certain knowledge.
It is important in knowledge management to reject the notion that the function of knowledge systems is to be a bucket for pure data. The knowledge cycle exists to solve problems and the problems in turn structure the questions to be asked and the information model that is tentatively appropriate.
In the space of this review I have left out a lot of solid content. The book is an extremely valuable resource for its definitions sections alone, for instance it is pointed out that there is no consensus on the nature of knowledge. I agree heartily with their rejection of the venerable but circular “justified true belief” definition so beloved by empiricists who believe knowledge claims can be justified by, rather than tested against, facts.
The New Knowledge Management framework is based on Karl Popper’s worlds of knowledge:
• World 1 knowledge – encoded structures in a physical system e.g. DNA
• World 2 knowledge – tacit, beliefs and belief predispositions in minds about the world, the beautiful and the right that we believe have survived our tests and evaluations
• World 3 knowledge – shareable linguistic formulations, knowledge claims about the world, the beautiful and the right e.g. books, wikis
Popper’s three worlds’ model is particularly useful for conceptualizing information systems. Far too often epistemologists have been blind to objective knowledge and been obsessed with tacit knowledge. It is a blind spot equivalent to humans in a pre-Darwinian age not seeing the evolutionary linkage between naked apes and furry apes. In this age of understanding of DNA and computer systems the existence of objective knowledge is surely not controversial. Animals and plants and humans know things without knowing that they know them. In fact most of our knowledge is not visible to us in any passage of time. Who would deny that a logarithmic table is knowledge, even though possibly no one memorizes it? Organizational data, information, and knowledge are World 3 objects.
A datum is the value of an observable, measurable, or calculable attribute or experience. Data are more than one attribute value. Information is always provided by a datum or data, because data are always specified in some conceptual context. One should avoid talking about data flowing like water into buckets, rather the agent via its senses acts as a searchlight that codes experience into data.
I recommend this book not only to information technology systems professionals but also to managers in general, psychology and philosophy students. There is much wisdom in it and the meta-context it provides could help prevent the building of systems that meet a dead end due to lack of focus on the cycle of knowledge.