When Bandler, Grinder, Dilts, etc. first formalized NLP, they certainly did it using the terminology of mathematical models, particularly calculus.(1).

The early NLP literature (Structure of Magic, NLP Vol I) talks about “4-tuples” (or 5-tuples, if you go back far enough), and “operations” that can be done to 4-tuples.

This was an early attempt to make NLP a calculus. Math-phobics, suspend that phobia. We aren’t talking mathematical calculus, but a general calculus. That just means they defined distinctions to pay attention to, operations on those distinctions, and rules telling how they all went together and what produced what results.

In Math, distinctions called “numbers” include 4, 5, and 9. Our operators include something called “addition.” The rules of math say when you combine 4 and 5 using addition, you get 9.

In NLP, we have distinctions called “4-tuples” with a specific set of internal/external sight, sound, small, taste, etc. We have an operators, “set anchor” and “fire archor.” Given two different 4-tuples, we can anchor both. When we combine them using the operator “fire off anchors,” we get a new 4-tuple with elements of the original two.

So NLP, itself, is a model. It has distinctions like 4-tuples, physiological state, internal images, auditory voices, submodalities, the unconscious mind, etc. It has operators like anchoring, shifting submodalities, etc. It also has rules for how those combine: if someone has Friends coded in one set of submodalities and Acquaintances in another, they can make an Acquaintance a friend by shifting the set of submodalities.

When they were developing NLP, existing therapies weren’t this rigorous. They didn’t have well-defined distinctions or operators, and had no real idea why or when their stuff worked. NLP was (and to some extent, still is) novel in that it attempted to be as rigorous as a mathematical model.

(To this day, the DSM-IV, the traditional therapeutic Diagnostic and Statistical Manual, has many descriptions that are too vague to be used as good, rigorous distinctions.)

Producing models with NLP

NLP can also be used to produce models. You can use the NLP distinctions to build a model of a skill. The famous spelling strategy, for example, uses the NLP distinctions to produce a model of how some good spellers spell: they create a mental image of a word properly spelled and anchor it to the sound of the word. That’s a super-simple model, but it reflects how the process operates.

B&G originally hoped people would go out and use NLP to produce models of how people did all sorts of skills. In practice, this hasn’t happened. I’m not sure why, but I suspect that successful modeling is a specialized skill that isn’t terribly useful in daily life, so few people get good at it.

Models by themselves aren’t very useful. Their usefulness comes from applying them. You can develop one model and then spend a lifetime applying it. The paradox is that those who love building models rarely enjoy applying them once the model seems to work. And those who like application are rarely good at building them.

Some professions are pure model-building professions. Linguistics, mathematics, physics, computer programming, academic research, and some forms of management consulting (e.g. business process re-engineering) are all model-building professions. Look closely at that list and you’ll find that those professions sort by task/system, not by people. They may be good at building models, but those practitioners rarely spend their time developing fine distinctions about people. Rather, they model things and systems.

So is NLP a model? Yes.
Can NLP be used to build models? Certainly.
Is NLP used to build models? By a few people, but rarely.
Is NLP necessarily model-building? Not at all. You can be highly skilled at using NLP for therapeutic interventions and not do any model-building.

Addendum from a conversation on 18 Aug 2007

A key piece of modeling is choosing the distinctions your model will have. Physics, for example, uses the distinctions “FORCE,” “MASS,” and “ACCELERATION.” Newton is very famous for finding and proving the relationship FORCE = MASS * ACCELERATION (F=MA).

What is often (always?) overlooked is that the very choice of Force, Mass, and Acceleration to measure is, itself, genius. If he had chosen WEIGHT, DENSITY, and SPEED, he likely would have found no relationship.

Bandler’s greatest genius, in my mind, is that he simply slices up reality a bit differently from the rest of us when watching people. He creates new models not because he has great skill in modeling (though that helps), but because he can slice up his observations in ways no one has ever done before. His ability to articulate what he does is relatively rare, and lets him teach portions of it.

For example, he noticed voice tone and tempo when talking to Erickson. Others simply hadn’t noticed it before. Is the genius in noticing that Milton would embed commands through his tone or tempo (relatively easy to hear, once you know you’re listening for tone and tempo changes)? Or is the genius noticing that tone/tempo might be relevant in the first place.

Maybe it’s both.

That’s why I find Bandler irreplaceable in many ways. He perceives differently, and that is a powerful piece of his modeling.

I came across this when modeling software engineers long ago. After many frustrating hours trying to figure out how one superb programmer broke down his solutions into code, he simply shouted (words translated to a metaphor for the non-programmers), “Stever, you just don’t get it. HAMMERS aren’t used to pound nails, they’re just a way to provide bracing while you use the door frame to pound the nail.”

His definition was radically different from how everyone I knew thought about hammers. But with his definition (his way of slicing up the world), many previously hard problems suddenly became simple. Ditto for the entire concept of recursion, by the way. Many extremely hard problems, when expressed recursively, can become absurdly simple.

Modeling = the distinctions you make AND the relationships you find between them.

The magic resides in both halves of the definition.

(1) For those of you who have taken group theory, think “Rings” and “fields.”back

NLP

NLP: Model, modeling tool, or both?

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