Knowledge creation in
collective intelligence
Bruce LaDuke
1Intelligence
Definitions of intelligence across disciplines proposed to date are both broad and varied. They include concepts like judgment, application, problem-solving, adaptation, cognition, goal-setting, physical capacities, analysis, environmental response, and pattern-recognition. Artificial intelligence is simply an artificial capacity to have and/or execute intelligence. But what is intelligence?
The first issue to confront involving the definition of intelligence is whether or not intelligence is an umbrella term for several capacities of the mind or a standalone description of a single capacity of the mind. If intelligence is an umbrella term that encompasses many mental capacities, then we can only understand its definition by understanding the definitions of the component parts that comprise it.
If intelligence is a standalone description of a single capacity of the mind, then understanding that single capacity will make it plain. If the intelligence is both an umbrella term and a standalone term, then we need to be able to differentiate between these two.
Mental Faculties vs. Knowledge Interactions
If intelligence is defined in the context of mental faculties, we’re looking at intelligence from the context of the individual as distinct from society. But to truly understand intelligence, we need to look at how the individual interacts
1 Bruce LaDuke has 20 years of Fortune 500 experience in a broad range of roles and
has conducted private interdisciplinary studies in knowledge working for most of his adult life. He is author of a blog on the future of knowledge working called HyperAdvance. http://www.hyperadvance.com.
with social knowledge. We need to understand intelligence in the context of social knowledge working.
Looking at intelligence in this way shows it as it truly is; a function of the human mind that interacts with the social mind. In the human experience, intelligence largely comes from without and not from within the human mind. In other words, intelligence is largely acquired from society, so to fully understand it; we need to understand human knowledge working and how the individual interacts with society in it. What are the components that comprise knowledge working on this level? I call these ‘knowledge interactions’ and have listed them below:
Individual Level
• Sensing—The acquisition of data from reality. • Learning—The acquisition of existing knowledge. • Ignorance—Purposefully ignoring knowledge.
• Knowledge creation—The creation of knowledge that has never existed before.
• Exposure—Society sensing or recognizing knowledge expressed by individuals.
• Expression and non-expression—The choice of the individual to express or not express their knowledge.
• Questions—The recognition of a lack of logical structure. • Theory—Projected logical structure.
Social Level
• Instruction—The impartation of existing knowledge.
• Social Acceptance—The acceptance by society of individual knowledge
• Language design—The logical construct of language for a society.
Both Individual and Social Levels
KNOWLEDGE CREATION
• Knowledge storage—The memory, recollection, and storage of knowledge.
• Compilation—The categorical structuring of knowledge. • Collaboration—Group knowledge working
• Sharing—The free dissemination or mutual dissemination of knowledge.
• Connectivity—The physical vehicle or media for any form of knowledge transfer
Knowledge application is not a knowledge interaction. Knowledge is applied to create things within industry. Industry is the science of making things. It is important to differentiate between working knowledge and applying knowledge. Intelligence can exist without ever being applied, but intelligence is a requirement for any application to occur.
Knowledge Interaction Flows
Knowledge interactions are not linear. One interaction does not necessarily follow directly into another, but they rather interact with one another. To define intelligence accurately, the next step is to understand the flow of knowledge interactions from the individual to and from society. The following is a linear example of what is, in reality, a non-linear flow:
1. An individual is conscious and as such has awareness of his or her own existence within the environment.
2. The same individual learns a lingual construct from his or her society, and uses that language to learn knowledge. He or she learns by extracting knowledge from the social knowledge base, and then storing it in the biological brain.
3. This individual grows in knowledge to become an instructor and, using language, imparts knowledge from the social knowledge base to other learners, who store it in the biological brain.
4. The learner takes his or her knowledge gained and applies it to personal performance within industry.
5. This learner grows in knowledge to become a thought leader, using language, questions advanced concepts, creates knowledge, stores it in the biological brain, and expresses that knowledge to society.
6. Society accepts that knowledge, transfers it from the individual to society, and stores it in the social knowledge base where it is ready to be extracted by another individual through learning.
In reality, this process is not linear, but three-dimensional and interactive. Knowledge creation flows through social acceptance and into the social knowledge base, while learning flows out, typically through an instructor. And both are leveraged in industry, which uses knowledge to make things.
KNOWLEDGE CREATION
The social knowledge base is comprised of science and technology. Science is converging empirical logic and associated with the discovery of reality. Technology is expanding rational logic and associated with creativity and invention.
Learners extract both science and technology and knowledge creators input both science and technology. And both science and technology are applied within industry.
Polanyi’s Error
Michael Polanyi was a physicist turned philosopher who taught that “We know more than we are able to express.” Much of modern knowledge management was founded on this erroneous premise. Much of the modern view of what knowledge working is, has been influenced by Polanyi’s view.
Polanyi taught that some knowledge within individuals was ‘tacit’ or silent and difficult for that individual to express. Polanyi also taught that the key to knowledge working was to draw out this tacit knowledge from the minds of individuals.
The whole concept is very ill-defined and in terms of practical use and knowledge management has struggled within industry to apply it. Unfortunately, this premise will never be successfully applied because it is false. In reality, all knowledge can be expressed or it isn’t really known.
And while knowledge is not difficult to express, it is the choice of the individual as to whether or not to express it. In this sense, knowledge can be tacit—Not because individuals don’t know it or have difficulty expressing it, but rather because individuals choose to express or not express it.
Knowledge is a logical structure of concepts. Humans ‘know’ when they have stored logical structure in the brain and can recall it when needed or wanted. It is the area of the question, where logical structure is lacking, that humans find difficulty expressing what the mind contains. It is the question that Polanyi saw and attempted to describe.
Questions are also processed in the brain, but they are not stored as logical structure. Polanyi skipped over the question and this caused him to confuse the illogic of questions with the logic of knowledge. As others before him, and
those that followed after him did, he only saw knowledge, and ignored the question.
Knowledge Creation
Polanyi was brushing up against the process of knowledge creation, which is the conversion of questions (a recognized lack of logical structure) into knowledge (logical structure). Knowledge creation is the source of all knowledge and society cannot advance without it, but the process is almost entirely hidden or misconstrued in modern scholarship. Figure 2 shows how knowledge structure, questions, and the unknown interact with one another in a unified knowledge model.
Figure 2: Directional Categorization
In Figure 3, who, what, when, where, why, and how represent all- encompassing categories for any problem.
Knowledge is one, and all knowledge can be categorized. Categorizing knowledge is structuring it. By placing the ‘problem’ into categorical structure we start to uncover questions of where our knowledge is not structured. The line between what we know, and questions and the unknown, is the cutting edge. By recognizing and structuring questions at this cutting edge, we are creating knowledge.
KNOWLEDGE CREATION
Creativity, creative problem solving, innovation, genius, creative methods, scientific method, and more can all be understood in the context of a simple and universal process of knowledge creation. This process is:
1. Definition/Solution/Structure (knowledge context) 2. Question/Problem
3. Logical Operation (connects/structures/defines) 4. Result: Advanced Definition/Solution/Structure 5. Return to step 1
Knowledge creation is the missing link in an accurate definition of intelligence and will prove to be the key to the implementation of true artificial ‘intelligence.’ Once we clearly see knowledge creation as it really is, the various roles of knowledge interactions, along with intelligence, become intuitively obvious.
On a final note, only individuals create new knowledge, not society has a whole. As such society is dependent on the individual expression of new knowledge for its own advance. If society wants to advance more quickly, the challenge isn’t to try to find knowledge in individuals, but rather to reward individual knowledge creators for expressing new knowledge.