It’s a glorious thing. The joy and excitement of starting anew job, project, or incorporating something new into our lives. It’s theunknown, the life adventure that gives us direction and purpose. Not all of us likethese kinds of life adventures, but an Entrepreneurmagazine survey has found that 63 percent of “20-somethings” want to start abusiness, and other surveys have found that at least 35 percent of employees considerlearning to be a prime reason for staying with an employer.
What is fascinating about knowledge, and learning, is that itis massively expansive and intricately interconnected. One idea always relatesto another idea. It is the ultimate puzzle. And, as a condition of survival,people are naturally motivated to learn and grow because, in the end, our livesand lifestyles depend upon it. The problem is that organizational cultures andtechnology work against this innate motivation. Here’s why.
The roots of the Great Big BeautifulPuzzle
Our amazingly powerful learning engine, the human brain, isnot well understood. No, not only the neurological mechanism of the brain, butthe powerful organizational principle of the mind. When our DNA, the chemical building blocks that determine thephysical and functional characteristics of each species, reached the end of itscapacity to advance intelligent life, Nature conjured up the brain.
The humanbrain, in fact all brains, allow us to remember. It is memory that allows us tostore lessons-learned knowledge beyond the predefined limitations of DNA. It isto our brain’s capacity to remember that we owe thanks for the knowledge thathas been passed down from one generation to the next. Memory, and the knowledgeit stores, is the ultimate gift.
The astrophysicist Carl Sagan defines this principle of brains andmemory in his book The Dragons of Eden,which he later explained in “The Persistence of Memory,” episode 11 of the 1980 TV miniseries Cosmos.
Theinsights from Sagan’s work were further defined by my mentor, Dr. Richard L.Ballard. In 1976, while Ballard was at the University of California–Irvine, he was cited for the first application of artificial intelligence to conceptual learning(Expert Systems in Business) by the National Science Foundation. Later, Ballarddeveloped the principles of “theory-based semantics,” which is at the heart of the Great Big Beautiful Puzzle.
As an experimental physicist, Ballard’s work demanded apractical outcome. Part of that effort was to redefine and transfer theabstract study of “knowledge” from the philosophers over to practitioners, educators,and technologists. The reason for this is that Ballard considered theunderstanding and application of knowledge to be an empirical science ratherthan a speculative study. Based on his theory-based semantic principles, Ballardthen developed two knowledge-computing technologies to prove his theories. Theywere called Mark 1 and Mark 2. These technologies were successfully developedand implemented through as many as 50 projects of national importance with the USDoD, DARPA, NASA, DEA, and NIH.
The exploding n-dimensional puzzle
Wegenerally think of a puzzle as being a flat three-dimensional object composedof hundreds of interconnecting pieces. Practical knowledge takes the puzzleprinciple many steps beyond. The knowledge puzzle is n-dimensional. It includesa fourth dimension of time, as well as primitive knowledge domains, and a host ofvariables such as concept associations, dependencies, and contingencies that arederived from sensory input, interpersonal exchanges, and millennia oflessons-learned knowledge.
Ballard consideredevery concept in our brain as being defined, in part, by one of three time states:(1) time occurrence (occurring within less than five seconds); (2) timecontinuant (occurring longer than five seconds); and (3) time universal (unboundby time). These elements of time help to define our sense of consciousness, ourreality within the Great Big Beautiful Puzzle, by providing a minimal orientationof how we fit into the puzzle.
Inaddition to each concept’s time signature, our conceptual ideas also fall intothree primitive knowledge domains. These include: (1) metaphysical, occurringonly in the mind; (2) semiotic, expressions that represent or refer to otherconcepts or elements of the physical world, and a host of situations andcircumstances; and (3) physical, representing the measurable “see, touch, andfeel” world around us (Figure 1).
Figure 1: Knowledge spectrum
Knowledge = theory + information (data)
Beyond theorientation of time and knowledge domains,theory-based semantics alsostates that the binding element of human thought is theory. There is abstracttheory (think Albert Einstein) and applied theory—the everyday, practical,lessons-learned theory that people across the globe rely upon to negotiate life’smany challenges. Applied theory is all about the “how-to,” “why,” and “what-if”knowledge that allows us to contribute value, and it’s how we work with othersto accomplish great things. Applied theory is the binding element of everypractical, lessons-learned concept stored in our brain’s memory.
Theory ispowerful; it connects the dots. Theory, along with data and information, providesevery idea in our brain with context, meaning, and purpose. This also includes theconcepts and ideas that lie at the core of every organization. Einstein said, “Whether youcan observe a thing or not depends on the theory which you use. It is thetheory which decides what can be observed.”
What isimportant about lessons-learned theory, gained through life experience,enculturation, education, and deep analytic thought, is that the applied theorywe learn is considered a prioriknowledge—it knows in advance. This means that once we gain practicallessons-learned theory about a situation or circumstance, our brainsautomatically know how to apply that same theory to similar situations orcircumstances as they arise.
As anexample, if you did not have a prioriknowledge in your brain’s memory related to opening an office door, you wouldjust stand in front of the door until you figured out that you needed to turn adoor knob, or push down on a lever, then pull the door out, or push the door in,before it would open. Once you learn the theory of opening a door, it does notmatter if the door is made of wood, glass, or stone; the a priori knowledge in your brain knows in advance how to open thedoor. This is true of all a prioriknowledge: It endures and serves us for a lifetime. It is estimated that theoryrepresents about 85 percent of knowledge.
On theother hand, information and data are known as a posteriori facts. A posterioriknowledge represents the facts, data, and information that occur moment-to-momentas situations and circumstances unfold. Though essential to knowledge, informationand data represent only about 15 percent of the knowledge equation (Figure 2).
Figure 2: Knowledge = theory +information
Thinking through and across theGreat Big Beautiful Puzzle
The puzzleis not just about theory, facts, time signatures, and primitive knowledgedomains; it is also about how we think, rationally.
The appliedtheory in our brains today, such as our social values and protocols, has been passeddown from one generation to the next, beginning with our oldest ancestors. Likewise,most of the applied theory that underlies organizations of every kind was alsoconceived and developed over decades, centuries, and millennia. The principle of“buy low, sell high” is a prime example. Applied theory endures because itworks. Organizational models may change, but the rational patterns of thoughtthat make those models work endure throughout most cultures.
Rationalthought, or patterns of thought, such as lists, arrays, compositions,taxonomies, sequences, and analytic models such as comparisons and correlationsare all based on time-tested a priori knowledge.
Each of theserational models represents a pattern of thought that can be reliably applied toan endless array of possibilities. They are what should be taught to studentsand employees, because once initiates begin to see these patterns of thought manifestwithin each knowledge expression, they experience the true power of knowledge. Thatis, they become armed with the conceptual tools they need to look deeper into newand existing situations and circumstances. It allows them to more effectivelyevaluate each situation and circumstance’s completeness, validity, and value. Theirskills of observation sharpen. Their critical thinking skills evolve. They gainsapient authority—i.e., the most knowledgeable person in the room who “knows,” whocan assess and solve problems, who can make decisions on matters where there areno right answers, only trade-offs.
Why not goto the source? Once initiates learn how people think, they themselves learn howto think; and, as they do, their efficiency, performance, and job satisfactionall increase—exponentially. Their depth of understanding increases, as doestheir value to their associates, to their organization, and to society.
The Great Big Beautiful Puzzle and technology
Measuredagainst the standards of theory-based semantics, conventional eLearning technologiesfail to deliver the full measure of direct experience that students and knowledgeworkers need and want most.
Technologiesthat are based on the theory-based semantics approach allow non-programmingprofessionals to easily model the complexity of organizational knowledge simplyby applying the same principles that those technologies rely on. These advancedsystems demonstrate that as organizational knowledge faithfully representscommon patterns of thought, they directly communicate and transfer to usersboth the broad perspective, and the detailed depth, of any real-world knowledgedomain.
