SOLVING PROBLEMS IN GENERAL SEMANTICS

Problem Solving Expertise #38

SOLVING PROBLEMS

IN GENERAL SEMANTICS

One of the preludes to Neuro-Semantics was General Semantics—the field that Alfred Korzybski founded.  To a good extent, Neuro-Semantics came out of General Semantics.  And so did NLP.  When NLP arose, the founders specifically based the epistemology of NLP on the ideas of Korzybski, namely the distinction between map and territory.  From General Semantics (G.S.) they said. “We do not deal with reality (the territory) as such, but with the territory as interpreted through our mental maps.”  Later, this became the foundation of Cognitive Psychology.  Once I discovered this, I made a deep dive into General Semantics.  That’s when I found seven linguistic distinctions which I recommending adding to the Meta-Model in numerous NLP journals (1992).  Then seeing that there was so much in G.S., I put together a training “The Merging of the Models: NLP and General Semantics” in 1997. [Now on the shop titled, Flexibility Training.]

Korzybski’s classical work was titled, Science and Sanity (1933/1994).  And in that, he identified how he and General Semanticists think about problems.  Using the Scientific Model they identify the subject, define it clearly, and gather all the relevant information they can about it.  They then define the problem extensionally.  This means looking at how the problem shows up in the world in actions, movements, talk, interactions, etc.  In other words, the define the problem operationally.  Once a problem is operationalized by extension, then they make educated guesses about the processes in play which makes it work.  From that they can then propose a hypothesis about the factors and variables, the causes and consequences, etc. regarding some aspect of the problem.  With a hypothesis, they then test it to see how accurate or inaccurate their guesses.

Here’s a summary of problem-solving in General Semanticists according to Wendell Johnson in his  People in Quandaries: The Semantics of Personal Adjustment (1946/1989).

1) They start with the problem’s terminology to make the problem is stated precisely rather than vaguely. Wendell Johnson put it succinctly in this way: “The terminology of the question determines the terminology of the answer.”  A vague question cannot be answered.  Why not?  Because it is vague!  Only clear and precise questions of a problem can be resolved.  Beware of how words can go wild!

You can’t make headway in solving problems if you work with an uncritical assumption about how to define it.   A term in defined operationally by describing the operations involved in applying the term.  Be careful least you define your difficulties into existence — that often happens with labeling.

2) They recognize reality (the territory) as involving dynamic processes.  And if reality is comprised of processes, rather than ‘things,’ then the search is on for those processes.  This is true of literal ‘things,’ whether organic or non-organic, and it is especially true of experiences (i.e., leadership, management, depression, charisma, forgiveness, etc.).   They search for the dynamic processes and they use scientific language which deals with the differences, changes, and relationships of the processes.

For Korzybski, nothing is static, there is no sameness, there is only difference.  That’s why be aware of rigid classifications.  Take time to delay your reactions so your unquestioned assumptions don’t cause you to jump to unfounded conclusions.  Two-valued thinking (either-or/ black-or-white thinking) sets us up for polarizing and dichotomizing.  Ask, “What’s in-between?”  “To what degree?  What proportion?”

3) They stay conscious of their own levels of abstracting.  Since we don’t deal with reality, but our maps, then as we ‘abstract’ from our senses, experiences, and facts, being aware that we abstract and how we abstract helps us distinguish what we are referring to and our mental maps about it.  Our maps also have multi-levels because we abstract at different levels.   General Semantics argued that ‘consciousness of abstracting’ is what can save us from confusing ideas and words at different levels, treat words as real, and then fall into reactionary thinking.

“Science is so new in the world that few among us are quite certain of what it involves.  We speak glibly of our time as the scientific age, but we muddle through it ... in largely unscientific ways.” (Johnson, p. 383)

4) They test all ideas to see what happens and where the idea takes us.  If you have drawn a conclusions or developed a theory, then test it by asking questions which can falsify the idea.  If there’s no way to falsify it or test it, then the idea is a ‘belief,’ not an operational idea.  Then, upon testing your idea, be ready to change your mind depending on the results you get.  Re-evaluate your evaluations.  With engineering semantics or point of view, find out what works and what does not.  The point is not whether you are right or wrong, the point is whether the idea is useful and effective.  If not, then be ready to re-evaluate, update your mental maps, and keep learning.

There’s more to it than this, but this is the general approach.  It mostly involves scientific thinking and carefully recognizing that solving a problem inevitably entails handling language, how we think, how we draw conclusions, what we do with our conclusions, how open we are about results (feedback) and how flexible we are in how deal with errors and biases.