According to Gregory Bateson, "If you want to think about something, it is best to think about that thing the same way in which that thing thunk." Bateson's notion of code congru
ency asserts that the most effective and ecological models are those in which the relationships between the elements within the model match the relationships between the system of elements of the phenomenon which we are modeling.
Bateson points out, for instance, that we can describe a human hand as "five banana shaped objects" or as "four relationships" between adjacent digits. Bateson suggests that one important question is, "Which form of description is more like that used by the DNA and other genetic processes which actually created the hand?" Another question would be, "What difference does it make to think of a hand as four relationships instead of five objects, if we were attempting to make or reproduce one?" Bateson maintains that models which are more "code congruent" are generally more elegant (simpler), useful, and ecological.
Is a Hand Five Objects Or Four Relationships?
A good example of the value of code congruency in model
ing is that of the shift which occurred in the conception framework and mathematics of astronomy in the late Renais
sance. Medieval astronomers had assumed that the Earth was the center of the solar system. As a result, they thought that all of the planets revolved around the Earth instead of the sun. In order to describe the orbits of the planets, with the Earth as the center, they had to develop elaborate and complicated mathematical descriptions of the paths traveled by the planets. (When you presuppose that the Earth is the center of the solar system, the planets appear to make strange little sub-loops and 'curly-queues' in their orbits. )
Paths of the Planets with the Earth Assumed as 'Center' of the Solar System
When the model was finally changed to place the sun at the center of all of their orbits, it became evident that the planets followed relatively simple elliptical paths, and the mathematics required to plot the movement of the planets suddenly became much simpler.
120 MoDELING WITH NLP
Paths of the Planets with the Sun Assumed as 'Center' of the Solar System
Another example of code congruency from science is the change that came with Albert Einstein's relativistic approach to physics. By shifting from the notion of "absolute" time and space, to relative time and space, Einstein's model was able to encompass all of Newton's mechanical laws of physics (as special cases), but was also able to explain and predict more phenomena; yet require fewer distinctions to do so.
While models that are not code congruent may be useful in some cases, their scope and longevity is limited. AB a metaphor (and a biological example of the importance of code congruency), Bateson used to cite the example of an unfertil
ized frog's egg. An frog's egg is essentially a sphere; and as such, it is missing quite a bit of the information needed to become a frog. A sphere has no obvious "front," "back," "left,"
"right," "top, or "bottom." Because the nucleus of the frog's egg is slightly off center, however, it determines what is to be the "top" and "bottom" of the frog. In order to begin to turn into a frog, though, the egg needs information about what is to be "front," "back," "left" and "right." This information is usually provided by the entry of the spermatozoan from the male frog. The place the sperm enters marks the spot that is to be the front of the frog. If the egg can determine the "top"
and the "front" of the frog, then the "back," "bottom," "left,"
and "right," become obvious.
Right
Frog' s Egg
Nucleus Top
Entry Point of Sperm (or Camel' s Hair)
Front
A Camel's Hair is a Type of 'Model' of a Frog's Sperm that is Not Completely 'Code Congruent'
The interesting issue that arises with respect to code congruency comes from the fact that the tip of a camel's hair is about the same size as frog's spermatozoan. If the frog's egg is pricked with the camel's hair, the egg will begin to divide and evolve into a living, breathing, fly catching frog.
The camel's hair is a type of "model" of the frog sperm. A frog produced in this manner, however, cannot reproduce, because it is missing the other half of the chromosomes, which would normally be provided by the male's sperm cell (it is what is known as a "haploid"). Thus, the camel's hair is not com
pletely "code congruent" in that it is missing some of the information, or code, necessary to make a fully reproducing frog.
Applying this example as a metaphor for modeling in general, it could be said, in the terms of the NLP Logical Levels model, that camel's hair is able to provide capability level information, but does not carry any of the necessary identity level information. Thus, one important criterion for
"code congruency" in modeling would be to check and include as many different levels of process into a model as possible.
122 MoDELING WITH NLP
Collateral Energy
Another aspect of code congruency in living systems, emphasized by Bateson, is that of "collateral energy." Collat
eral energy relates to the fact that in many dynamic systems (such as biological and social systems) all of the parts carry becomes distributed and dissipated in a predictable manner as each ball hits another.
Gregory Bateson used the analogy of Alice in Wonderland playing a game of croquet using a hedge hog as a ball, and a flamingo as a mallet to express how, when each part of a living system carries its own source of energy, interactions and their results become much more complex and unpredict
able. Bateson pointed out that if you kick a ball, you can determine where it will end up with a fair degree of accuracy by calculating the angle of the kick, the amount of force put hungry dog to expend a lot of energy to come home for dinner.
The wink of an eye from an attractive individual can release quite a bit of energy from an interested suitor. Consider how
the abduction of Helen of Troy, lead to many years of war.
Similarly, the writings of Karl Marx have stimulated many people to revolution. Beliefs are a good example of how information mobilizes energy.
Many natural scientists still make the error of thinking of living systems as functioning mechanically, rather than as a result of collateral energy. Traditional Western medicine, for example, tends to focus on the mechanical aspects of healing.
The Pavlovian notion of the "reflex arc" is an example of applying mechanical thinking to living systems.
Many of the social, political and psychological problems that plague us today are a result of applying mechanical thinking to living systems. The use of force, coercion and manipulation to create social change are examples of igno
rance of collateral energy.
Some people even approach NLP methods with a mecha
nistic perspective. The process of anchoring could be viewed either in terms of mechanical cause-and-effect or as the utilization of collateral energy. The steps of an NLP tech
nique are not like hitting billiard balls on a pool table.
Working with people is more like Alice in Wonderland's game of croquet.
124 MoDELING WITH NLP
Code Congruency in Behavioral Modeling
The importance of applying the principle of code congru
ency in behavioral modeling can be illustrated in a story coming from the early days of NLP. Bandler and Grinder had decided to conduct a "Modeling Seminar" in which they were to model the work of Virginia Satir. The two-day seminar was structured such that Virginia would work with a family on the first morning, demonstrating her approach to family therapy. In the afternoon, Bandler and Grinder would reflect on her work and describe some of the key linguistic and behavioral patterns that she had applied during the therapy session. Then, the next morning, Virginia would work with another family, leaving the last afternoon for a final reflection and closing remarks .
As the story goes, Virginia did her usual superb job with the family she worked with on the first morning. In the afternoon, Bandler and Grinder proceeded to explain how Virginia had "anchored" various family members using non
verbal cues, how she had led various individuals into certain states, and how she had created and triggered various responses in the family members.
The following morning, when Virginia worked with the next family, it was a disaster. Virginia was unhappy with her work, the family was dissatisfied and the audience was frustrated and confused.
The typical conclusion people draw from this experience is that it can be dangerous to "know what you are doing,"
because your conscious mind will interfere. Bateson's notion of 'code congruence', however, offers a different explanation.
Bandler and Grinder had described Virginia's action in mechanical, cause and effect terms, placing Virginia as the controller of the interaction. Most probably, this was not the way that Virginia herself thought about it, either consciously or unconsciously. From this perspective, her poor� perfor
mance on the second morning was brought about not merely
by the fact that she was conscious of her process, but rather because the code used to model her process was not congru
ent with the structure of her actual process. [John Grinder relates the story of how, when Bateson first read Handler and Grinder's work on the Hypnotic Techniques of Milton Erick
son, Bateson dismissed it with the comment, "Shoddy episte
mology," because it had described Erickson's use of language in too mechanical of a manner.]
We have probably all had experiences in which having a way to understand and talk about something we were doing unconsciously and intuitively greatly empowered us and increased our appreciation for and mastery with what we were doing. We have probably also had the experience that knowledge about what we were doing unconsciously brought about a type of self-consciousness which interfered with our ability to perform. Bateson would say that the difference has to do with the congruency of the code being used to the process we are enacting.
When a model is not code congruent, it is like trying to
"stick a square peg into a round hole. "
Notice that code congruency does not have to do with the
"accuracy" of the content of the code or model. A code could be completely metaphorical and still be "congruent" with the process it is representing. The significant aspect of code congruency is that the relationships between the elements and events in the model be congruent with the relationships between the elements and events making up the system we are modeling.