The Answer is in the Question
Knowledge Creation
As a graphic design/advertising student twenty years ago, I was less concerned with producing good advertising as I was with the creative process behind it. As a result, I spent much of my time in those early years researching the term creativity and trying to understand how to practically define it.
In my last year of college, much of this effort culminated in the discovery of a new creative method that I called “Directional Categorization.” The concept was very simple.
I created a matrix with the all-encompassing category headings of who, what, when, where, why. Then I created two rows on the matrix, one for the as is or ‘known’ state and one for the future or ‘unknown’ state.
In the ‘known’ row, I listed words that described or represented current approaches and solutions. Since at the time I was focused on advertising, I would list elements of a particular advertising approach that had been used in the past, or were being used. In the ‘unknown’ row I brainstormed a list of possibilities and questions in each category—I placed anything here that was not a current approach. This area of the matrix typically included a mixture of new ideas and questions.
After using this method for awhile, I realized that it helped me to quickly and methodically create new advertising and design solutions. At first I wasn’t even sure how it worked, but it did work in an almost predictable and scientific manner, especially if I approached the problem with an intent to exhaustively categorize the unknown.
This discovery unfolded during the years when various creative scientists and their respective creative methods were rising in popularity. I’m not sure why now, but I decided at that time, rather than go public with this particular method, I would explore it across all disciplines to better understand how and why it worked from the vantage point of other disciplines.
I spent long hours at the local library, studying terms like creativity and innovation across many disciplines and found that every single mind discipline and creative method was somehow leveraging, or seeking to discover, this simple process of converting questions, lack of structure, data, or the unknown to logical structure.
Over time, I came to understand that Directional Categorization operated by a fundamental premise of the human mind—that is, by structuring the unknown as it relates to any topic or knowledge context, humans can quickly and easily create a new knowledge, come up with a solution, solve a problem, or be creative and innovative.
I also discovered that this method worked in cooperation with all other creative methods. For example, one would use brainstorming to fill in the unknown categories with ideas; or use TRIZ to exhaustively list physical properties in each category; or use DeBono’s lateral thinking to change direction of thought; or use opposites to create new areas for consideration. The overarching goal was to exhaustively categorize the questions that surrounded a particular knowledge context—In effect, ‘mind mapping’ the unknown.
By exhaustively categorizing the unknown, I found that solutions emerged automatically and that there was a thin line, the cutting edge, between that which is known and that which is not known. I also realized that questions and problems were permanent fixtures and not temporary encounters. Today we tend to see problems and questions as things that arise or that we often encounter, when in fact, questions and problems are permanent fixtures that always emerge just beyond the cutting edge. That is, until they are structured and become knowledge. But typically, all questions related to a knowledge context are not answered at the same time, so when one piece of the problem is converted to knowledge structure, other areas remain beyond the cutting edge. It is therefore possible to map this holistically and use this map as a guide for discovery.
The fundamental premise behind the Directional Categorization is that questions are the perceivable unknown and they form an antithetical structure or ‘Anti-Knowledge’ to existing knowledge. Anti-knowledge and knowledge have a yin and yang relationship.
By structuring these and looking at them as a collective, instead of looking at each question one at a time, we begin to map the problem and create solutions at the same time.
Here is a detailed example of this exhaustive quesitoning approach.
Interestingly, when I originally researched the word question in dictionaries and reference books, I expected to find deep theory and concepts around the term (as was the case with creativity and innovation), but instead I found very basic and simplistic definitions like “to ask a question.” I eventually realized that the real definition and concept behind the question had not been discovered yet. I also realized that every mind science, for example, cognitive psychology, metaphysics, knowledge management, information technology, artificial intelligence, linguistics, semiotics, semantics, etc., were all at various stages of advancing what I will call ‘question science’ from their own perspective and using their own distinct terms.
Essentially, all of these disciplines had some advance to contribute to the cause of the question, but they each tended not to share advances across disciplinary boundaries and they were often unaware of the discoveries and advances made in other disciplines.
As a result, every discipline had a piece of the whole, but the knowledge creation cycle was yet undiscovered.
The Knowledge Creation Cycle
When I compiled all of these individual disciplinary views and advances together into one, I used the following diagram to represent these consolidated (converging) views:
This diagram likens knowledge to a spherical structure. Outside of this logical structure of knowledge, in the perceivable unknown, is an antithetical structure of problems/questions. Between that which is known and the unknown is the cutting edge or leading edge in each discipline of study. The knowledge creation cycle operates on this cutting edge.
Some creative methods, like brainstorming, suspend judgment to reach out into the unknown. Others, like lateral thinking, focused on directional or morphological movement into new areas of possibility. I began to realize that all functional creative methods were valid components of this larger model.
The knowledge creation cycle operates by structuring of collective questions/the unknown to create knowledge. This five step process has gone on for centuries largely undetected, but every knowledge advance ever achieved is a result of this simple cycle.
This five step cycle, which embodies creativity, innovation, logic, and scientific method, is as follows:
- 1. Definition, Solution, Structure (knowledge context)
- 2. Question, Problem (realizing the lack of structure)
- 3. Logical Operation (test, connect, structure, define)
- 4. Result: Advanced Definition, Solution, Structure
- 5. Return to Step 2
By applying logical structure to that which is not yet logical (questions/problems), we create knowledge. This involves both gathering questions (brainstorming) and structuring them. The process works without fail and is as reliable and as dependable as scientific method itself.
The almost mechanical predictability of this process opens up a new realm of thinking as it relates to true artificial intelligence, or more accurately, artificial knowledge creation.
Two Question Types
Behind this more reliable and predictable knowledge creation cycle is a more clear understanding of exactly what questions are.
Questions are a perceived lack of knowledge structure. All data lacks structure, but questions are the act of perceiving this lack of structure. One, for example, would not be able to formulate a question if they do not have knowledge context around a particular topic. Consider an engineering professional trying to formulate a question that advances nuclear physics. While there may be parallels and similarities between the two fields, it takes knowledge context to be able to answer questions that arise in a particular knowledge context at the cutting edge level that advances that discipline.
There are two fundamental types of questions, knowledge creation questions and learning questions. Knowledge creation questions are questions about knowledge that does not yet exist while learning questions are questions about knowledge that does exist. Knowledge creation questions are asked at the cutting edge, while learning questions are asked by the learner within the knowledge context.
For the learner, questions are everything that they perceive they do not know, but want to know. When a learner is being instructed, they are forming logical connections and knowledge structure in their own minds from the knowledge they are receiving. For the knowledge creator, questions lie outside of the known. They are typically advanced thinkers in a particular discipline that question areas outside of the current social understanding.
For the knowledge creator, questions are raised in reference to the particular knowledge context they are working with. In most cases today, these knowledge creation questions are seen as individual questions that are confronted one at a time, versus being managed as a collective of all questions related to that knowledge context.
In fact, everything a society knows, all knowledge, has an antithetical "structure" of knowledge creation questions surrounding it. The collective of knowledge creation questions, or questions about knowledge that does not yet exist, can be manipulated as a group so as to expedite, or even mechanize, knowledge creation. This process is true 'artificial intelligence,' or more accurately termed 'artificial knowledge creation.'
The mind bending aspect of the question is that it is often very difficult to know what society actually knows and does not know. This is why the concept of the question, in particular the two types of questions, has been so elusive. It is from this arena that the concept of tacit knowledge needs to be confronted.
Tacit Knowledge and Social Acceptance
After discovering the concepts described above, I came to the conclusion that, if I didn’t tell someone there was a chance that no one would ever know these things. At best, I surmised that it would take society longer to get to this point if I did not express these concepts.
Michael Polanyi, a physicist turned philosopher, introduced the concept of ‘tacit knowledge,’ which was popularized within knowledge management circles. Polanyi said that we know more than we are able to express. In this way, Polanyi ascribes some knowledge to have a fuzzy and unclear quality. As I looked at this concept in the context of the knowledge creation cycle, I realized that the ‘fuzzy’ aspect of knowledge that Polanyi was trying to describe was really not knowledge at all, but rather, it was this realm of collective questions.
Collective questions are that fuzzy and unclear mental space that we all have surrounding things that we know. The powerful thing about this understanding is in realizing that, when we structure this space, we instantaneously create new knowledge. Then, as individuals, we choose whether or not to express this newly created knowledge to society. The silent aspect of knowledge (the word tacit means silent) puts expression of new knowledge squarely into the hands of the individual knowledge creator.
Of course, new knowledge absolutely must be expressed and subsequently accepted by society in order for society to benefit. In a nutshell, three things must happen for society to advance:
- - New knowledge must be created (by logically structuring questions)
- - That new knowledge must be expressed to society
- - That expression must be accepted by society and subsequently incorporated into its social knowledge base.
So then, there is a required cooperation between the individual and society. This cooperation includes the expression of new knowledge to society and its subsequent acceptance, but is also much broader and extends to include all knowledge pillars and knowledge interactions.
