An unpretentious introduction to knowledge management (or what for a goat accordion)
“You’re wrong, honey! There is nothing in the world from which it would be impossible to draw a conclusion. You just need to know how to get down to business.”
Lewis Carroll “Alice in Wonderland”
To tell the truth, today the phrase “knowledge management” (especially pronounced in conjunction with the stable stamp “Industry 4.0”) is perceived in the same semantic series with the concepts of “nanotechnology”, “Skolkovo” and “Panama”.
However, the time has come to put everything in its place and show that knowledge management is not at all purely declarative, but quite a usable thing.
And to begin with, we will try to understand the question: why exactly now “knowledge management” has become quite a hype concept.
Laziness is the engine of progress (or why the fourth one is not in a hurry to replace Industry 3.0).
By the will of the Creator, a person turned out to be a rather lazy being, and from the moment of his formation he began to make efforts to get what he wanted, spending as little effort as possible, and began to spend the remaining time from digesting food not only on sensual pleasures, but also on cognitive attempts to simplify own existence.
Let us omit the painful process of creating the first stone axes, steam engines and electric motors and immediately move on to the moment when a person at some point got tired of standing at numerous sensors, pressure gauges and pointers, practically manually controlling complex production systems with their help, and he With the help of numerous feedback systems and ingenious mathematical models, he began to make quite successful attempts to automate most processes, which, by the way, was successfully facilitated by the emergence of productive computing devices and high-speed communication channels. Automation won almost everywhere, allowing a lazy person to wash clothes in an automatic washing machine without hassle, and launch an automatic interplanetary station. This is how Industry 3.0 happened.
But this was not enough for the man. And he decided to start gradually transferring the right to make intelligent decisions to soulless technology, gradually moving to total robotization. Moreover, even 30 years ago it seemed that the capabilities of computer technology, mathematical modeling, means of data transmission and processing were quite enough for this.
But at the end of the 20th century, in all the surrounding technical progress and the inexorable onward movement towards industry 4.0, something strange happened – developing technologies, all the time drawing ideas for their development from scientific sources, seemed to hit an invisible wall.
As soon as the task actually appeared, at least as a first approximation in a fully automatic mode, to solve high-quality tasks that are accessible even to a child, from time to time it turned out that it was very, very far from solving the problem of creating a working model of thinking of a living person capable of making adaptive decisions.
Moreover, it is very likely that it was the dizziness from the successes of the first wave of automation based on the mathematical modeling of everything that led away from solving the problems of creating artificial intelligence, our lazy and pampered by the fruits of technological progress.
And the point here was not even that, as Stanislav Lemm famously remarked, “ethics cannot be measured by arithmetic.”
It turned out that in the transition to a comprehensive description of production and other processes, our models for their representation are not accurate enough, and predict not at all what we want and somehow not at all.
In addition, there is also a great many qualitative concepts that are difficult to formalize, but which are simply necessary to take into account.
In a word, it turned out that the science of knowledge and its practical application has not developed very much since the moment Socrates and Aristotle discussed the nature of things in the gardens of the Lyceum.
Although, of course, there are still some useful advances towards understanding the nature of knowledge today …
What Socrates didn’t say (or what we finally know)
From the point of view of today’s epistemology (the science of knowledge as such), the statement of the great Socrates “ἓν οἶδα ὅτι οὐδὲν οἶδα” (“I know that I know nothing”) is only partially true, since all the variety of scenarios that can be implemented in the process of formalizing knowledge , can be simplified in the form of not one, but four judgments that describe completely different situations of our attitude to knowledge:
I don’t know that I don’t know;
I don’t know what I know;
I know that I know;
I know that I don’t know.
Schematically, the relationship of these judgments can be represented in the form of a figure.
Obviously, the area “I don’t know what I don’t know” refers to the knowledge that we don’t even know exists today. And from the point of view of modern science, this area has infinite dimensions, due to our ideas about the infinity of the process of our knowledge of the world.
But three other areas, inextricably linked with our cognitive abilities, have a finite size and are related to what and to what extent we know about the world around us.
Our most enjoyable area “I know what I know” is the most structured and tested area of personal and collective experience gained in the process of knowing. This area includes not only confirmed and used in practice knowledge about nature and just theories that have not yet reached their practical implementation, but also the understanding of the inaccuracy of certain judgments (since we know that they are not correct). The knowledge in this area, as a rule, is well formalized and represents the so-called explicit (or implicit) knowledge, the acquisition of which, in fact, is the main goal of science. At the same time, it must be taken into account that the knowledge located in the “I know what I know” area may have certain assumptions or in general be not very accurate and even approximate. (And in this regard, it would be more correct to call this area: “It seems to me that I know that I know”).
The neighboring area “I know that I don’t know” actually represents the cutting edge of human knowledge, looking for answers to previously posed questions. Moreover, it is through the use of this area that the knowledge of mankind is slowly flowing from the area “I don’t know what I don’t know” to the area of explicit (and applied) knowledge: some questions are resolved, and in their place there are problems that still require research. It is obvious that in the area “I know that I do not know” there is much less self-confidence, which is so characteristic of the area “I know that I know.” But it also has a lot of pitfalls related, for example, to the fact that the methods used for research may turn out to be, to put it mildly, not very suitable. Therefore, this area would be better called “I think that I know that I do not know.”
The “I don’t know what I know” area is a little different. In this area, from year to year, confidently and without any hesitation, you use knowledge that you don’t even know exists. And they are by no means the result of unconditioned reflexes that mother nature and evolution have given us by birthright. A distinctive feature of this knowledge is its non-formalized nature, which means that for some reason they could not be clearly and unambiguously described. Such knowledge is usually called implicit (or tacit), and revealing it is another of the tasks that have to be solved.
A little about culinary tricks (or why best friends sometimes have disagreements)
Practical acquaintance with tacit knowledge should begin with consideration Best Friend’s Favorite Pie Recipe Paradox.
Consider the following situation: as a first approximation, let’s assume that you are a young lady, and you and your boyfriend (BMP) come to your best friend’s (BFP) birthday party, who offers a delicious pie for tea, which, as you notice, you really liked VMC.
You have far-reaching views of the MCH, and so the next day, you rush to the VLP with a box of her favorite chocolates in the hope of getting your hands on the most detailed recipe for her culinary masterpiece.
Then you spend the whole day in intense efforts to recreate the pie, but, alas, instead of a masterpiece, you get a whole baking sheet of so-so smelling slurry.
I won’t describe what will happen the next day, but if after the incident the VLP still not only remains safe and sound, but also wants to talk to you, the following will become clear …
There was no set-up: you just used different flour, different measuring containers, and your plates have different maximum temperatures. Those. handing you the VLP recipe, she unconsciously missed a number of very significant points from the category, as it seemed to her, completely obvious, and used in her family for several generations … but absolutely unknown in your family.
Thus, we have come to one of the most significant features of tacit knowledge – the non-formalization of implicit knowledge hinders their reproducibility. Therefore, tacit knowledge, cut off from its bearer, actually ceases to exist.
Now imagine that all this heterogeneous knowledge (and also related to different areas of human activity) is used within the framework of one enterprise by tens of hundreds of interacting employees to obtain a common workable result …
… and all this, taking into account the fact that this knowledge is not complete, sometimes they describe not quite the same thing, and a number of the knowledge used is not documented at all.
In general: the horror is comparable, except perhaps with unstructured file storage, the elements of which have random names, and the dates of creation of files and their authorship are missing.
Thus, it can be argued that the problem
effective knowledge management in solving complex problems exists … And about
how to start solving it, we’ll talk next time.
