Richard Karash wrote:
> Mark, what is the definition of "knowledge" in the modern KM arena?
>
> I follow Senge and others in using: Knowledge is the capacity for
> effective action. That is, it's "know-how" not "knowing facts." Learning
> is an increase in knowledge.
Rick:
Ultimately, the question you raise is an epistemological one.
Philosophers through the ages have wrestled with the "nature of knowledge"
problem for centuries. More recently, researchers and scholars in the
twentieth century took up the quest once again in their attempts to create
artificially intelligent computers (e.g., the Turing machine). These
efforts were ultimately unsuccessful, in part due to the inability to
infuse such systems with "intentionality," "self-awareness," "emotion"
and any number of other human idiosyncrasies. In the end, several
prominent members of the AI community, like many philosophers before them,
actually walked away from the seductive idea of creating synthetic
intelligence, not to mention the search for a suitable, satisfactory
definition of knowledge itself. Their shared conclusion was that it can't
be done.
As for the "best" mainstream thinking on the nature of knowledge in
contemporary KM circles, I'm afraid I have little good news to report.
Even in my own organization, official proclamations of what knowledge
means, as evidenced in the marketing messages coming down from on high at
Lotus and elsewhere in the IBM complex, are embarrassingly shallow and
often circular. Consider the following text from current IBM/Lotus KM
marketing materials: Knowledge consists of "Insights and context from the
mind - what the knower knows." Given that definition, all we need to know
is what "knowing" means and what a "knower" is. But that, of course,
requires some knowledge of knowledge - in advance!
Turning elsewhere, Tom Davenport and Larry Prusak, both of whom I deeply
respect, provide a somewhat fuller, if not rambling, definition of the
term in their highly acclaimed book, Working Knowledge (1998): "Knowledge
is a fluid mix of framed experience, values, contextual information, and
expert insight that provides a framework for evaluating and incorporating
new experiences and information. It originates and is applied in the
minds of knowers." Again, we seem to be dealing with arms-length, and
persistently circular, self-referencing definitions wherever we turn.
At the end of the day, I suspect our quest for "knowledge of knowledge"
is unachievable. There's a conspicuous sense of logical circularity in
the very idea - it seems to me. To acquire such knowledge, we would first
have to agree on what knowledge would look like when we see it, or at
least agree on certain validation criteria beforehand. But that would
require a certain degree of familiarity with knowledge in advance, which
of course, is precisely what we're trying to discover in the first place.
On another encouraging front, I've just become familiar with the work of
James Falconer, whose thorough account of the evolution of thinking on
this subject in a paper of his entitled, "Knowledge Management at a
Branchpoint," is one of the best reads I've had in a while on where the KM
profession has been, and where it needs to go (falconer@nortel.com). In
his paper, Falconer offers his own definition of knowledge as "thought
patterns," which he argues can be held at both an individual and an
organizational level. He then goes on to cite chaos and complexity theory
as the most promising fertile ground for future insights concerning the
ontology of knowledge and the means by which it escalates from the minds
of individuals to the mind of the collective (my words). All of my own
thinking on KM (and OL, incidentally) is, itself, substantially derived
from the same line of thought (i.e., complexity theory). Human
organizations are nonlinear adaptive feedback networks and should be
"unmanaged" accordingly.
As you probably know, I have been deeply involved with the Knowledge
Management Consortium's (KMC) efforts over the past two years to unpack
complexity theory's implications in the realm of social cognition, and to
repackage them into a body of practice that I now call "second-generation
KM." With this in mind, the KMC's current definition of knowledge is one
that I personally subscribe to. According to this
complexity-theory-inspired definition, knowledge - strictly speaking -
cannot be defined, per se, but can be REPRESENTED in the form of rules and
rule sets. With all due respect to "the map is not the territory"
argument, I and many others, believe, nonetheless, that we can build
surrogate models of knowledge and cognitive processes that provide us with
satisfactory replicas, imaginary worlds, that mimic the embryology and
diffusion of knowledge in living systems, and which we can use as the
basis of formulating KM practice in the real world. Complexity theory
provides the most credible framework in this regard.
Having said all of that, my brand of KM is one that reflects a very real
and significant convergence in thinking between KM, OL and complexity
theory. I may still be in the minority on this subject, but it's clear to
me that as others inexorably come around, our numbers are rapidly growing.
Regards,
Mark
--"Mark W. McElroy" <mmcelroy@vermontel.net>
Learning-org -- Hosted by Rick Karash <rkarash@karash.com> Public Dialog on Learning Organizations -- <http://www.learning-org.com>