The philosophical & scientific foundations of Neuro-Linguistic Programming: a 6 day programme for NLP Master Practitioners


As a world first I have been training the Licensed NLP Business Practitioner™ at a top 100 university, i.e. the VU-university of Amsterdam, ranked #73 in The Times International University Ranking. My name is Joost van der Leij and besides being a Licensed NLP Master Trainer™ I also have a background in academic philosophy, having taught philosophy for three years at the University of Utrecht.

Currently I am collaborating with the Aubrey Daniels Research Institute for Behavior Analysis (ADRIBA) of the Economy and Business School faculty of the VU-university to develop a scientific & philosophical foundation for Neuro-Linguistic Programming™. The strategy that we are using is the same one that has been used to scientifically support Organizational Behavior Management (OBM). As I am also a VU-university certified OBM trainer/coach.

I am in the unique position to use OBM to build the scientific & philosophical foundations of NLP.

OBM has been validated using the significant scientific proof of Experimental Behavior Analysis by applying the same principles in a business environment as used in a laboratory. Given that enough positive changes were measured after intervening in the business environment to validate OBM, OBM is now considered scientifically proven.

We use the same strategy for NLP™. We apply the principles of Experimental Behavior Analysis to NLP™ to measure changes in behavior. Our research clearly shows that people improve when using NLP™.  Therefore, the better we are able to show how the principles of Experimental Behavior Analysis underpin the workings of NLP™, the closer we are to building a scientific foundation for NLP™.

For integration of OBM within NLP™ we use strategy elicitation. This is the way NLP™ maps behavior and translates that behavior into NLP™ terms. Furthermore we look at the underlying neurobiology. Finally, we use the correct philosophical fundamentals to tie it all together. All of this gives a very thorough understanding of NLP™. In practice NLP™ is very easy to use. Yet NLP™ is hard to understand. For that reason we organize the The philosophical & scientific foundations of Neuro-Linguistic Programming Training for NLP Master Practitioners to further help them understand NLP™. This way, as a NLP Master Practitioner,  all the philosophical and scientific material relating to NLP that we currently use at the university will be at your disposal.

Day one: Science, Pseudoscience & Protoscience

On day one we learn what science, protoscience and pseudoscience is. Neuro-Linguistic Programming (NLP) is not a science because of three reasons, namely:

  1. There is no scientifically valid formulation of NLP.
  2. There is no scientific research based upon a valid formulation of NLP
  3. There has not been any peer reviewed scientific research published in a scientific journal.

For these three reasons NLP cannot be a science yet! Some people might point to some published research to show that NLP has been proven, but all that has ever been researched are piecemeal parts of NLP. More importantly, that research fails to abide by the rules of the metamodel. For not only does science make demands on NLP, NLP in return also makes demands on science. The metamodel is the core of NLP. The rules of the metamodel indicate how you can communicate with the smallest risk of being misunderstood. Scientific research that violates, in a relevant way, the rules of the metamodel is bad NLP. Given that 99% of science makes use of cause and effect, that makes most of science incompatible with NLP. Fortunately, there are areas in science where the scientists also reject cause and effect statements and it is in these areas where we can team up to create (a) a scientific formulation of NLP, (b) do scientific research and (c) get it published.

To do that, it is very important that we refrain from making NLP a pseudoscience. To become a pseudoscience two things need to happen, namely:

  1. Major proponents claim something is a science.
  2. It is not a science.

We have already established that NLP is not a science. Now only what we have to do is to make sure that no-one claims NLP is scientific. That way we make sure that NLP is not a pseudoscience. If NLP is not a science and not a pseudoscience, then what is NLP? Fortunately, there is third option: NLP is a protoscience! A protoscience is a precursor to a science. (Stich 1996) Most famously we have alchemy as the protoscience to chemistry and astrology as the protoscience to astronomy. Although some people wouldn’t mind if NLP is on the same page as astrology and alchemy, many people might. Which brings us to a third protoscience. One that is currently taught at all universities, namely: psychology! (Stich 1996)

Philosophically there is a strong argument, one that we follow, that the current form of psychology as taught in the university is not a science at all, but only a protoscience, a precursor to a yet to be developed scientific psychology. If we can all agree that the current psychology is a protoscience to a future scientific psychology then it is a place of honor to also call NLP a protoscience to a future scientific psychology! And NLP has a good claim for that position, because in reality NLP is only a codeword for doing hypnosis! Hypnosis is nowadays completely scientifically validated. (Nash 2012) Yet, NLP is a much richer way of doing hypnosis than just hypnosis as a technique. NLP shows how the brain works hypnotically. As such NLP is the best candidate for a protoscience of a scientific psychology yet to be developed.

Day two: from Introspectionism to Behaviorism to Cybernetics to Radical Enactivism

On day two we dive into the historical philosophical roots of NLP. A lot if known about the psychological roots of NLP, but few people are aware that Richard Bandler also studied philosophy and that NLP is much more influenced by philosophy than psychology.

The first major philosophical school that comes close to NLP is Introspectionism. As the name says these, nowadays unknown, philosophers and psychologists tried to introspect and study the subjective experience we call consciousness. That sounds a lot like NLP! Yet, they made some big mistakes. For instance they might spend up to two hours trying to describe a three second experience. Nevertheless, the other core part of NLP, submodalities, has a lot in common with Introspectionism. Yet, the way NLP uses submodalities, steers clear from the major errors of Introspectionism as we will learn on day two. (Beenfeldt 2013)

Introspectionism was heavily criticized by Behaviorism, but we will see that (a) those criticisms were wrong (even though Introspectionism failed for other reasons) and (b) Behaviorism does not dislike Introspectionism as much as people nowadays think. What NLP learned from Behaviorism was that it was important to map human behavior. That is what the essence of NLP is: a method to map human behavior in the form of NLP strategies and techniques. The big difference with Behaviorism is that NLP has more emphasis on internal behavior, i.e. what you feel, imagine and tell yourself. (Skinner 1978)

Cybernetics was the first step away from Behaviorism. NLP is completely cybernetic because of the introduction of the TOTE model. The TOTE model is a cybernetic model that assumes that human behave in order to change their environment so that it matches their plans. Of all the sources used by NLP cybernetics is the strongest for cybernetics is a completely accepted hard science. (Ashby 1958)

Unfortunately, nowadays cybernetics has been taken over by cognitivism. And whereas cybernetics, being developed in the forties and fifties of the previous century, was still predominantly behavioristic, cognitivism becomes through time more and more functionalistic and then even starts to believe their functions. Cognitivism thinks that beliefs, desires, motivation are real things rather than constructs. Again, the metamodel comes to the rescue as we know that these constructs are nominalisations and that we need to find out what process is behind those nominalisations, i.e. which internal and external behavior constitutes these constructs. (Stich 1996)

Fortunately, cybernetics is currently making a big come back and it is smart for NLP to ride that wave as well. Cybernetics is the basis of Radical Enactivism. This new school within philosophy makes clear why it is important to work with the processes rather than the content of what people experience. As we see in NLP in most cases it is much more helpful to change the form how people experience reality rather than the content of what they experience. Radical Enactivism explains why that is the case. (Hutto 2017)

Day three: Evolutionary Behavioral Patterns: Cybernetic Big Five Theory

Both NLP and Behaviorism have been unjustly criticized. But there is one criticism that really bites both Behaviorism and NLP. Because both work with the idea that a human being is born with a blank learning machine, what is called a tabula rasa within philosophy. Behaviorism thinks that once we are born the environment conditions our behaviors. NLP thinks that once we are born our brain learns patterns of behavior which we then can map in the form of a NLP strategy. Both are right of course. We do learn a lot in our life and our environment has a big influence on how we develop.

But both are wrong to think that our brain is a blank learning machine at the start. Human beings and brains are the product of millions of years of evolution and evolution simply doesn’t produce anything without specialization. In other words: nothing produced by evolution can start with a tabula rasa, or a blank learning machine. This may seem like a small point, but in terms of science this would be nothing less than a complete show stopper. If NLP (and Behaviorism for that matter) cling to the idea that humans start out with a blank learning machine neither one of them will ever be scientific because evolutionary psychologist can always point out that these theories run aground with evolution.

Again, fortunately there is an excellent way out of this pickle by using Cybernetic Big Five Theory (CBFT). CBFT is based on hard neuroscience. As such NLP has to adopt CBFT as it is the way the brain works. Adopting CBFT is easy for NLP as it is formulated, just like NLP, in cybernetic terms. What CBFT does, is that it shows that the biological hardware structure of our brain already gives us, from birth, a certain evolutionary behavioral package, a set of typical behaviors that makes us who we are. NLP is all about what we call the software of the brain, i.e. the patterns of behavior you learned growing up. CBFT is all about the behavioral patterns that are based on the hardware of the brain. As most programmers know: you can do almost anything with the software, yet it helps a lot if you know the hardware that the software runs on.

For that reason, on day three, you learn CBFT through the Neurogram® model as the Neurogram® is the easiest and most helpful way to access the hardware layer of typical evolutionary behavioral patterns. You learn how these patterns turn negative in times of stress and positive when you start to relax, again demonstrating how handy it is to combine this with NLP. We will also point out how this differs in a big way from metaprograms. (DeYoung 2015)

Day four: The Linguistic Turn, the philosophy of language.

All the terms used in the metamodel did not fall out of the sky. Instead they come from the philosophy of language from the fifties and the sixties. Unfortunately, many of these terms are misunderstood because people lacked the background of the philosophy of language. On day four we take an in depth tour throughout the metamodel and the Milton model to explain every single language pattern. This will strongly enhance your ability to use these patterns elegantly and effectively.

We will concentrate a lot on presuppositions using set theory to explain what a presupposition does in the brain. For all these language patterns came to language because of the way our brain works. So in fact the metamodel is more than “just’ a metamodel of communication. In fact it is the only way we can come close to the model of the world and the model of ourselves as it is coded in the brain. On day four you’ll learn how to use your voice to make a presupposition out of anything. And we take a peek at the “forgotten” presuppositions from The Structure of Magic, the first book on NLP.

On day four you learn the Triangulation model as an updated version of the deep and surface structure. The Triangulation model shows you why human beings are social creatures. Sometimes NLP is described as an intellectual mind game, but the fact is that NLP is all about what you feel. Yet, other people play a minimal role within NLP. The Triangulation model shows you that the surface structure is a social structure and that we human beings need each other to function well. The Triangulation model shows that NLP is a much more social methodology than many people think it is. (Davidson 2011)

Day five: Mathematical modelling of behavior

NLP is famous for modelling excellence. Yet, in reality nobody models anything within NLP. Most people within the field of NLP have no idea what modelling is. And that is okay because modelling as was done in the seventies did not always turn out to be okay. For that reason we have replaced modelling by NLP strategy elicitation. Strategy elicitation works much better than modelling. Nevertheless, many people think that strategy elicitation is actually modelling whereas in reality it is only part of modelling.

The biggest clue that no-one is doing any modelling in the field of NLP is that Richard Bandler makes clear that to model someone means to make a mathematical model of the internal and external behaviors of that persons. This is based on the work of Donald Boyd. (Boyd 2001) No-one within the field of NLP is making any mathematical models of behavior. On day five you learn how to do it though.

There are actually two ways you learn how to model behaviors mathematically. The first one is the easy one: you learn a mathematical way of using submodalities. This way you learn how NLP strategy elicitation in fact is a way of mathematical describe human behaviors.

The second way is not used in NLP currently, but you learn how to build a mathematical model for behavior using subjective Bayesian statistics. Subjective Bayesian statistics is not only the best way of doing statistics, it is also a match made in heaven with NLP. Like NLP subjective Bayesian statistics is subjective! Like NLP it abhors cause and effect statements. And like NLP it’s main value is freedom. Yet, with subjective Bayesian statistics you can create behavioral models that a very accurate in predicting future behavior.

Not only that, but we also learn on day five that the Triangulation model make use of subjective Bayesian statistics. This way the Triangulation model also makes no use of cause and effect statements and hence fits NLP perfectly.

Nowadays almost all philosophers and many neuroscientists come to the conclusion that our brain is a Bayesian machine to predict the future. Even psychiatry today has a new field called “computational psychiatry” where they make mathematical models of issues such as depression and schizophrenia. That sounds like even psychiatry is turning into NLP! All of this is based on Predictive Theory (PT) which you will learn on day five. (De Finetti 1990)

Day six: ABC-NLP, the marriage between NLP and Behavioral Analysis

Here is our trick in how we can scientifically proof the validity of NLP. We have copied this way of proving NLP from Organizational Behavior Management (OBM). OBM is a form of Behaviorism where they apply operant conditioning on the employees of organizations and businesses. How did they proof scientifically that OBM works? They could not do double blind randomized trials as that would mean creating two exact copies of a business. What they did do instead is (a) show that they work according to the principles of Experimental Behavior Analysis, a scientific method for studying behavior in the laboratory that has a strong scientific basis with many peer reviewed research published in scientific journals and (b) show that their measurements show a strong and positive change after their intervention in a business. Both reasons provide OBM with the scientific proof they need.

We do the same with NLP. Because NLP is a method to map human behaviors, it is quite easy to elicit the strategies of Experimental Behavior Analysis and use those strategies to ground the work we do within NLP. In fact having done these brought us to the ABC-model of Behavior Analysis. As it turns out the brain has three major ways of learning, namely:

  1. Imprinting
  2. Associative learning
  3. Instrumental learning

Imprinting only happens just after birth and therefore has very limited appeal. NLP is a star in associative learning. Associative learning is where the brain builds a probabilistic relation between two sensory experiences. For instance if you see smoke, your brain expects there to be fire. Not only do we use anchoring as a way of building positive associations. But we also use NLP to break negative associations and build more positive associations with almost every NLP technique we use.

But what we missed within NLP is the third way our brains learn, i.e. instrumental learning. Instrumental learning is where our brain creates a probabilistic relation between our behavior and the likelihood of certain outcomes. The most obvious example is that we open doors the way we do because our brain has learned that that behavior is the best instrument to get us what we want: a space to walk through a wall.

The ABC-model is the best explanation of how instrumental learning works. The B in the ABC-model stands for Behavior. The A for Antecedents which is everything that happens before someone behaves or things someone needs in order to be able to behave in such a way. Almost everyone, including most people in the field of NLP, focuses on Antecedents. They tell other people how to behave, they train and coach them etc. All of this happens before someone is going to behave in a certain way.

The C in the ABC-model stands for Consequences, i.e. everything that happens after someone has behaved in a certain way. Almost nobody pays much attention to what happens afterwards. Nevertheless, research clearly shows that what happens afterwards has a much stronger influence on future behavior that what happens before. Or in other words: the influence of the Consequences are much stronger than the influences of the Antecedents.

The beauty of the ABC-model is that it is a model through time. First you have the Antecedents, then the Behavior and then the Consequences. As such it is also a probabilistic model. It only shows what relations make certain behavior more or less probable. Like NLP the ABC-model is strongly against cause and effect statements, yet the ABC-model is still scientific. As we said out in the beginning to find those areas of science where they have no use for cause and effect statements, we now have found them! For triangulation, subjective Bayesian statistics and the ABC-model all work without cause and effect, yet are scientifically and philosophically sound.

On top of that we can expand the use of modern day NLP techniques, like the fast phobia cure and working with timelines, to also break negative patterns based upon instrumental learning and replace them with positive patterns in the same way NLP already does with negative patterns based on associative learning. All of this you learn of day six. (Skinner 1978)



Beenfeldt, Christian. The Philosophical Background and Scientific Legacy of E.B. Titchener’s Psychology: Understanding Introspectionism. Springer, 2013.

Boyd, Donald W. Systems Analysis and Modeling a Macro to Micro Approach with Multidisciplinary Applications. Academic Press, 2001.

Davidson, Donald. “Three Varieties of Knowledge.” Subjective, Intersubjective, Objective, 2001, pp. 205–220., doi:10.1093/0198237537.003.0014.

Deyoung, Colin G. “Cybernetic Big Five Theory.” Journal of Research in Personality, vol. 56, 2015, pp. 33–58., doi:10.1016/j.jrp.2014.07.004.

Finetti, Bruno De. Theory of Probability: a Critical Introductory Treatment. Wiley, 1990.

Hutto, Daniel D., and Erik Myin. Radicalizing Enactivism: Basic Minds without Content. MIT Press, 2017.

Nash, Michael R. The Oxford Handbook of Hypnosis: Theory, Research, and Practice. Oxford University Press, 2012.

Skinner, Frederic Burrhus. Science and Human Behavior. The Free Press, 1978.

Stich, Stephen P. From Folk Psychology to Cognitive Science: the Case against Belief. MIT Press, 1996.