I recently unearthed yet another blog I used to tend, nearly twenty years ago. As I wrestle with the brain fog of the Newly Retired, I thought I’d reprint some of those - the ones that aged well, obviously. Here was my attempt at “Back to First Principles for Knowledge Management,” sent into the void in 2009, and happily void of anything resembling A1 sauce…1

The title for this post is taken from a 1993 RAND report written by two friends and former colleagues. It is occasionally useful to revisit the first principles when discussing weighty matters such as KM. Or, as was the case for my friends, U.S. Strategic Forces.

A recent conversation on Twitter involved a fairly innocuous blog posting that discussed briefly the notion of tacit and explicit knowledge. The problem, for me, is the definition for tacit knowledge in this blog was “that which has not been recorded, written, printed, or otherwise captured in some medium.” Explicit knowledge, by contrast, has been. Therefore, the challenge is to make tacit knowledge explicit – because knowledge is only transferred through explicit mediums. To quote:

Unless converted into explicit knowledge, it cannot be shared because it is ‘trapped’ in one’s mind.

The post also referenced a second gentleman, who posed an even more pithy and awful definitional distinction:

He says that the tacit-explicit distinction is abstract and, in reality, knowledge is ‘either findable by your computer or it is not findable by your computer.’

Rather than just letting it go as the Bride often advises, I sent a brief message to the first gentleman, expressing my nonconcurrence with his definitions. Through the magic of Twitter, this became a conversation enjoined by several souls, and I was finally challenged to provide some primary sources that inform my apparent heartburn.

In all honesty, while the ensuing discussion may appear “abstract” to some, the nature of knowledge should be at least partially understood if one is to consider themselves a practitioner of knowledge management. Else, content yourself to the vital and growing field of information management – there is no shame in this whatsoever. [Edited for 2025: Ok, so that last phrase did not age well.]

It is important here to note that the original post was intended to briefly acknowledge the academic distinctions, but more to exhort people to share the knowledge trapped in their heads. I agree with this noble intent, but fear the post does violence to related theory. Believing that knowledge is only transferred once it has been made explicit leads to mechanistic, engineering approaches to knowledge management that have not proven their worth. Crank it out of people’s heads, churn it into a shared taxonomy or tag it somehow, and then – and only then – is it useful to others. I would like to know the exact date that the apprentice learning model was made obsolete by advanced information technology.

While a tidy approach to KM (actually more an approach to information management), the call to “make tacit knowledge explicit” ignores much of what we know about how the world actually works. To be more precise, we are learning the limitations of what we can know as a result of research across the disciplines of sociology, neuroscience, anthropology, and others.

Last caveat, I do not have much argument with the practitioners who offered via Twitter that tacit knowledge can be made “partially explicit,” or with the gentleman who offered that the fragmented chatter on Twitter was actually an idea way to begin sharing tacit knowledge. The promise of social media indeed is that serendipitous connections of people, linked via fragmented information, is a step towards knowledge management that recognizes the fruitlessness of other approaches – including ones that seek to harvest tacit knowledge into explicit knowledge bins.

Here then, my brief list of “first principles” to understand before drawing conclusions regarding the “implementation” of KM. If these are true, they should change your view on “making tacit knowledge explicit.”

0. Principle zero: define the terms. Where did we get this term “tacit knowledge?” Michael Polanyi described it this way:

Thus to speak a language is to commit ourselves to the double indeterminancy due to our reliance both on its formalism and on our own continued reconsideration of this formalism in its bearing on our experience. For just as, owing to the ultimately tacit character of all our knowledge, we remain ever unable to say all that we know, so also, in the view of the tacit character of meaning, we can never quite know what is implied in what we say.

While technically true that “not findable on your computer” agrees with this paragraph, I find that characterization falls short of Polanyi’s meaning.

1. We don’t know how we know what we know, or make decisions; and therefore unwittingly misrepresent what we know when asked to describe the process. Lakoff claims that understanding “takes place in terms of entire domains of experience and not in terms of isolated concepts.” He shows how these experiences are a product of:

• Our bodies (perceptual and motor apparatus, mental capacities, emotional makeup, etc.)

• Our interactions with our physical environment (moving, manipulating objects, eating, etc.)

• Our interactions with other people within our culture (in terms of social, political, economic, and religious institutions) p.117

Gompert, et al., examined the dual roles of information and intuition in decision-making in their investigation into how to increase “battle wisdom” for U.S. forces. Asking General Patton how he made the decisions he did will not prepare you to respond similiarly in like circumstances.

Snowden puts it this way:

There is an increasing body of research data which indicates that in the practice of knowledge people use heuristics, past pattern matching and extrapolation to make decisions, coupled with complex blending of ideas and experiences that takes place in nanoseconds. Asked to describe how they made a decision after the event they will tend to provide a more structured process oriented approach which does not match reality.

Medina agrees:

The brain constantly receives new inputs and needs to store some of them in the same head already occupied by previous experiences. It makes sense of its world by trying to connect new information to previously encountered information, which means that new information routinely re-sculpts previously existing representations and sends the re-created whole back for new storage. What does this mean? Merely that present knowledge can bleed into past memories and become intertwined with them as if they were encountered together. Does that give you only an approximate view of reality? You bet it does. p.130

2. We learn through fragmented input and internal cognitive patterns, embedding extensive context from our environment at the time of learning. Medina, discussing the work of Nobel Laureate Eric Kandel (2000), relates how the brain rewires itself.

Kandel showed that when people learn something, the wiring in their brain changes. He demonstrated that acquiring even simple pieces of information involves the physical alteration of the structure of the neurons participating in the process. p.57

Fauconnier and Turner discuss cognition – in part – in terms of guiding principle for completing patterns, as humans seek to blend new concepts onto what they already know.

Pattern Completion Principle: Other things being equal, complete elements in the blend by using existing integrated patterns as additional inputs. Other things being equal, use a completing frame that has relations that can be the compressed versions of the important outer-space vital relations between the inputs. p.328

Brown, et al, take on traditional teaching methods in their work showing that “knowledge is situated, being in part a product of the activity, context, and culture in which it is developed and used.”

The activity in which knowledge is developed and deployed, it is now argued, is not separable from or ancillary to learning and cognition. Nor is it neutral. Rather, it is an integral part of what is learned. Situations might be said to co-produce knowledge through activity. Learning and cognition, it is now possible to argue, are fundamentally situated.

The context within which something is learned cannot be reduced to information metadata – it is an integral part of what is learned.

3. We always know more than we can say, and we will always say more than we can write down. For my third principle, I am borrowing directly from Dave Snowden’s extension of Polanyi. (Snowden’s blog should be at the top of your KM reading list):

The process of taking things from our heads, to our mouths (speaking it) to our hands (writing it down) involves loss of content and context. It is always less than it could have been as it is increasingly codified.

Having read through the first two principles, it should now be evident that relating what we know via conversation or writing or other means of “making explicit” removes integral context, and therefore content. Explicit knowledge is simply information – lacking the human context necessary to qualify it as knowledge. Sharing human knowledge is a misnomer, the most we can do is help others embed inputs as we have done so that they may approach the world as we do based on our experience. This sharing is done on many levels, in many media, and in contexts as close to the original ones so that the experience can approximate the original.

The grandfather above will not conduct after-action reviews regarding his fishing experiences, write a pamphlet about fishing, and upload it to the family intranet. Rather, he will take the boy fishing – where he will show him to tie lures, cast effectively, breathe in the experience, and hopefully learn to love what he loves.

References:

Brown, J. S., Collins, A., & Duguid, P. (1989). Situated Cognition and the Culture of Learning. Educational Researcher, January-February, 32-42.

Fauconnier, G., & Turner, M. (2002). The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities. New York, NY: Basic Books, Perseus Books Group.

Gompert, D. C., Lachow, I., & Perkins, J. (2006). Battle-Wise: Seeking Time-Information Superiority in Networked Warfare. Washington, DC: National Defense University Press.

Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. Chicago, IL: The University of Chicago Press.

Medina, J. (2008). Brain Rules: 12 Principles for Surviving and Thriving at Work, Home, and School. Seattle, WA: Pear Press.

Polanyi, M. (1974). Personal Knowledge: Towards a Post-Critical Philosophy. Chicago, IL: University of Chicago Press.

Snowden, D. J. (2008, October 10). Rendering Knowledge. Retrieved January 5, 2009, from http://www.cognitive-edge.com/blogs/dave/2008/10/rendering_knowledge.php