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Part 1 of 4
This Article is in four parts. The first establishes the context for understanding and using this material. Part Two, covers the first 11 Aspects of Memory. Part Three, the final 11 Aspects. Part Four, outlines the required capacities, that applying this Method to the creation of dynamic systems, are necessary in order to accomplish the aim of this System and Method. It also addresses some aspects, in terms of this Method, that memory is not.
This material is based on several sources. Aspects of the patent as issued, patent applications in pending, other sources related to the invention as well as documentation of various 7 Domains Workshops, and classes that I have conducted on the Taylor System and Method. Some material that has been, until this publication, held in trade secrete is also included. Originally, the material was organized in the same framework as the patent as issued. Over time, this has given way to a more informal and accessible presentation. My purpose here is not to represent the Patent in the narrow sense - nor, even the invention in all its technical aspects. My intention is to provide information that provokes a thought process useful for thinking about the design of complex adaptive processes and systems and the role which memory plays in their development. I am particularly interested in how memory can be built-into human processes and organizations.
There are three primary ways to get “into” the Taylor Method. One is to learn the habit of the way of working. This is accomplished by doing under the instructions of those who have achieved a certain mastery of the Method. Another is to learn the intellectual and technical aspects of the method including the Modeling Language and all the formal distinctions that support the work. The third is to understand the 22 Aspects of Memory and the the 22 Habits of Creative People and EMBED these in the environments you build and employ. Of course, there is a fourth way which is some combination of the first three. Each person has to choose their own path through this material. There is no one right way to achieve mastery. Whatever you path, a combination of historical learning, the experience of doing and understanding the theory has to be fused in real-time work in order for knowledge of the Method to be achieved.
A method that does not have multiple channels of access is weak and will ultimately fail. Most KnowledgeWorkers will adopt some combination of these three strategies depending on their cognitive orientation, the application of the method to their work and other circumstances in their environment: time, resources and so on. Of the three, the most powerful tool, for the investment involved, is the latter. If you truly understand the implications of memory and creativity and if you function as a designer to make these intrinsic to the processes, artifacts and environments you build, you will be able to generate a variety of useful solutions to a broad number of systemic challenges. This is a principle of Biomimicry [link] and organic design [link]. Study nature and apply this to design challenges.
This is so because complex systems are life-like. I have arrived at the principles outlined below by applying the method, itself, to the discovery and creation of the method through an iterative process of Design/Build/Use. The goal has been to discover design principles and that function over a broad range of applications in many level of system recursions. The primary source of these discoveries has been the study and facilitation of humans - as individuals and groups - as they grappled with and solved difficult problems by using the method itself. This has been done by applying “Black Box Theory” as developed by cybernetic practices a half century ago. This, if done correctly, is a self adapting process - it learns. As complex systems cannot be predicted or controlled, traditional methods cannot deal with them. This is the basis of our present condition: the failure to be requisite with the systemic consequences of the sum of our own actions. Humans and groups of humans are the most complex systems we presently know. They provide a rich knowledge-base of design strategies. So above, so below.
All this said, the following employs Taylor terms-of-art ToA and Modeling Language in fairly terse language. The purpose of which is to be a precise as possible. Even so, you will bring your own experience to this language and understand it in your own way. This is fine as long as you bring rigor and consistency - within your own framework - to the exercise.
Design Assumptions ToA [link] related to the nature of mind and memory functionality and the executive routine [link] ToA of any intelligent Agent [link] ToA are a core aspect [link] of this System and Method. I have conducted mind experiments [link] ToA, related to the nature of mind, executive functions and memory since 1966 - these have proven predictive in several areas of scientific research and technology development [link].
Between 1980 and the present, tests have been run, by Gail Taylor myself and others, in various DesignShop ToA and PatchWorks ToA events and in Various Management Center ToA and NavCenter ToA environments, to refine this model of Memory and the processes that support the building of “strong” [link] memory in intelligent Agents and complex systems.
These various experiments and observations formulate the basis of this Model (of memory). This Model is not offered as hard, verified, science - although many aspects of it qualify as such. It is a conceptual Model built for the purpose of building and employing certain systems. The processes, tools, environments required to do this are described elsewhere [link].
It is not necessary for an idea to be totally true or verifiable to be useful. This statement, itself, is an insight of this System and Method. “The only valid test of a concept or theory is what it enables you to do” [Taylor Axiom]. What is necessary is that the idea can be applied as an algorithm, process 2 or artifact of this System and Method and produce reasonably consistent, useful results as specified by the Appropriate Response [link] Model. In other words, not all natural systems employ all aspects of this Model, nor does the Model cover all aspects of natural memory phenomena. The Model is, however, complete enough to do two things: be employed to build “artificial” memory processes and systems and facilitate significant memory processes of many living beings - notably humans.
While the following statements are not presented as science, they are presented as engineering design assumptions ToA useful for generating practical insights about memory-systems [link] across a wide band width of type, scale, application and system media ToA. These assumptions, and the algorithms presented with them, make up an example of a generalized design tool-kit that can be successfully aplied to a wide variety of design challenges.
These assumptions are useful for creating the architecture, processes, artifacts, tools and rule sets (algorithms) of the method and many expressions of it on multiple levels of recursion [link] ToA in many different kinds of application environments.
In the following explanation, each of the 22 design assumptions (or memory aspects and functions) are stated with examples (in the realm of Environment, Process and Tools) for each assumption along with a brief explanation. Following each set of examples, are some general observations relevant to the assumption. The examples are specific to some aspect, on a designated level of recursion and a particular Subsystem, of the System and Method. These examples are stated as system specifications, rules, algorithms or pseudo-code. While not exhaustive of the System and Method nor it’s full practice (which remains in Trade Secrete), these examples indicate the potential range and scope of the design assumption as rules for building specific expressions, artifacts and processes of the System and Method. The detail provided is sufficient for thinking about the process of building significant “mind-like” processes, tools, environments, systems and artifacts across a broad range of applications in a wide range of media.
Recap of Recursion Levels:

To facilitate understanding of what Level of Recursion T0A a given description or definition is applied to, the following convention is employed:

rL1 = neural nodes, computer code, small parts scale;

rL2 = machine environment, molecular scale;

rL3 = human scale;

rL4 = human team and group scale;

rl5 = human environments and organizations scale;

rL6 = social, ValueWeb ToA and regional economy/ecology scale;

rL7 = global network and economy scale.

These scales are roughly derived from and related to Miller’s system [link]. This code is part of an Agent Definition Code [link] which is an aspect the “Agent Builder” toolkit - Subsystem 3 Ss3.

In the following examples, the Principle of Minimum Claim [link]  ToA is employed. The statements are made in a way that claims the least amount of certainty and information necessary to support the design assumption in focus, and the examples and rules necessary to implement this principle, in some operating subsystem or component in some part of and level of recursion of the Taylor System and Method.
The best approach to “learning” this material is to apply it, as active design principles, in the creation of real processes and systems. The is the way most true to the material itself and why the material is presented in the way it is. In a nut shell, this material is best used as meta-programming [link] in a specific design process. In time, the precepts become ingrained -as an understanding - a one aspect of how complex systems evolve and behave. This approach, to learn by design [link] is employed throughout the Taylor Method.
Go to part Two of this Article for the first 11 of the 22 Aspects of Memory.
Return to Taylor System and Method Outline
goto 2 of 4 of Memory
Return to INDEX
GoTo: Creative habits
Matt Taylor
Palo Alto
May 12, 2000

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posted: September 20, 2002

revised: June 15, 2005
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(note: this document is about 55% finished)

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