Magical-thinking and knowledge-management
It started, as these things so often do, with a Tweet on Twitter.
(This has turned out to be an enormously long post – I’d better put a ‘Read more…’ link in here before continuing.)
This time the Tweet was from Cynefin creator Dave Snowden:
- snowded: NLP as Cargo-Cult psychology. Great paper http://jarhe.research.glam.ac.uk/media/files/documents/2009-07-17/JARHE_V1.2_Jul09_Web_pp57-63.pdf
The link points to a 7-page academic paper [PDF] by Gareth Roderique-Davies of University of Glamorgan, which purports to indicate that NLP (‘Neuro-Linguistic Programming‘ – a kind of self-hypnosis psychological tool) has no scientific basis, and is therefore ‘cargo-cult psychology’. I do take his point that there are some worrying flaws in NLP itself, and even more worrying flaws in many of the ways in which NLP is promoted and used these days. But I’ve seen this kind of ‘scientific’ review before, and I said so in my re-Tweet of Dave’s first message:
- tetradian: @snowded: “NLP as Cargo-Cult psychology. Great paper http://tr.im/IjbF ” <disagree: NLP has serious flaws but this is just a hatchet-job
The problem is that the reviewer is trying to assess NLP in conventional scientific terms – which makes no sense right from the start, though his world-frame would itself make it impossible to see why it makes no sense. (For enterprise-architects, by the way, this is the same underlying reason why IT-centrism or organisation-centrism is such a problem: the frame itself makes it impossible to see beyond the frame.) The title of Bandler and Grinder’s original book that defined NLP way back in the 1970s gives the reason why the scientific frame won’t work: it’s called The Structure of Magic.
Yup, that’s right: magic.
Most self-styled ‘scientists’ treat that word in the same way as IT-centric ‘enterprise’-architects treat business-architecture and beyond: namely a randomised, undifferentiated grab-bag of all the bits of reality (or business-reality, in IT-EAs’ case) that they don’t understand. And then complain that it’s a mess, and doesn’t make sense in their own chosen terms, and therefore doesn’t exist. Which is not exactly honest – and it’s certainly not helpful in practice, because magical-thinking is often the only way out of many everyday scientific, technological and business dilemmas and problems.
A small tale here. Everyone ‘knows’ that Isaac Newton was one of the world’s greatest scientists, yes? (Which he was, of course.) But not many people know that he was also interested in a great many other subjects, including religion, alchemy, astrology and much else besides: in fact he wrote more on alchemy, for example, than on all of his scientific studies put together. Edmond Halley, the then Astronomer Royal, was berating Newton for the latter’s studies of astrology: it was all nonsense, he said, ridiculous, utterly unscientific – or words to that effect, anyway. Newton’s short, sharp retort: “I have studied the subject, sir, and you have not!” End of conversation…
Which brings us back to NLP, and the structure of magic. As it happens, I have indeed “studied the subject, sir” – for more than forty years, in fact – and I guess most people reading this blog probably haven’t, so it might be useful if we do a quick tutorial here on the role and limitations of the scientific frame and mindset, and the contrasting role of magical-thinking. To do this I’ll pick up on another of today’s Tweets, from knowledge-management (KM) guru David Gurteen:
- DavidGurteen: Is KM a Pseudoscience? #KM http://www.greenchameleon.com/gc/blog_detail/is_km_a_pseudoscience/
This link points to an article by another key figure in KM, Patrick Lambe – much better thought-through and much more considered than the previous piece. Using a checklist from an article by Barry Beyerstein, he scores KM overall as having a score of only 5.4 out of 10 as a ‘rational endeavour’, and concludes that it is too close to a pseudoscience: “must do better”, he says. But what that article misses, yet again, is the bald fact that trying to assess most of KM in scientific terms makes no sense. The only way we can make sense of it is via a magical approach.
(Yes, I know I still haven’t explained yet what I mean by “a magical approach” – give me a chance, I’m getting to that in a moment! 🙂 )
Before we can look at magic, we need to understand science – as much for what it isn’t as for what it is. What it isn’t – as any competent scientist would admit – is “the answer to Life, The Universe, Everything”. Instead, it’s a particular body of knowledge, developed in terms of a specific set of methods and assumptions, and which can only make sense – or be useful and valid, rather – within a very specific set of constraints. Science has been extremely successful within those constraints – so successful, in fact, that many people fail to realise that by its own definitions it is not and cannot be successful outside of them. Therein lie many huge problems for KM, for enterprise-architecture and for many other disciplines – including magic.
This is perhaps best described in one of my all-time-favourite books, WIB Beveridge’s The Art of Scientific Investigation. First published in 1950, it’s been continually in print ever since, and remains one of the great classics of scientific research. I’ll have to quote from memory, as my copy is back in Australia, but his introduction starts like this:
Complex equipment plays a central role in the science of today, but it should never be forgotten that the most important instrument in research must always be the mind of the researcher.
Beveridge expresses concern that “perhaps not enough attention is paid to making the best use of it”. To this end he focusses on the actual practice of science, rather than solely on the end-products of that practice. Hence his book includes detailed descriptions and examples on strategy, hypothesis, the use of chance and intuition, and “the hazards and limitations of reason”. (Most of his examples come from his own field of biology and biochemistry, but they’re just as applicable to every other branch of science.) The summary in his chapter on reason is particularly important, though forgive me if I again have to quote from memory:
The origin of discoveries is beyond the reach of reason. The role of reason in science is to come afterwards, to review and reassess and to build a general theoretical scheme. … Most biological ‘facts’ are so uncertain that at best we can only reason on probabilities and possibilities.
And that last sentence remains just as true as ever, despite the advances of molecular biology and the like over the past half-century: the only certainty in science is that many things will always remain uncertain. But it’s all too easy to forget that fact: that’s where the problem starts.
It’s also all too easy to forget that ‘the scientific method’ depends entirely on its base-assumptions: it cannot be relied upon outside of their remit. For our purposes, the most important of these assumptions include:
- causality – all events are connected via cause/effect chains in a linear ‘arrow of time’
- repeatability – given the same conditions, all experiments and results must be repeatable by others
- falsifiability – every hypothesis must be framed in such a way as to enable its negation by experiment
- consistency – the results and hypotheses in each domain of science cannot contradict those of other domains of science
Within those constraints, science works extremely well – and likewise, usually, any technology based on that science. But it’s essential to realise that it only works within those constraints – and there are plenty of conditions where those assumptions break down. Repeatability and falsifiability will seem to make sense whilst we’re dealing with the mid-range of scales, but in fact they break down as we move more towards the very small – down into quantum levels, as per Heisenberg’s Principle – or to the very large – where experimentation and repeatability are often inherently impossible (at least on the kind of time-scales that we live in!). The same applies as we move more towards unique events: chaos-mathematics makes the level of unpredictability more predictable, but does not reduce the unpredictability itself. Consistency also frequently breaks down between domains: last I heard, for example, the most likely theory of star-formation requires a universe much older than ‘permitted’ by the most likely theory of cosmology. And out at the fringes of science – particularly in nuclear physics – there are plenty of examples where any linear concept of causality will break down, and at times looks remarkably like traditional magic. For example, the old magical notions of ‘action at a distance‘, teleportation and telepathy are all ‘permissible’ in current quantum-entanglement physics, and in some cases have even been demonstrated in laboratory-experiment – even if only at quantum scales.
And there are plenty of real-world, everyday examples of where those assumptions will break down – especially in KM and the like, where we’re often dealing with contexts which, by definition, are either unique or near-unique. So complaining that KM might be considered by some to be a ‘pseudo-science’ is to miss the point, because there’s no way that it can be a ‘science’ in those formal terms above. Instead, to make sense of what’s going on, we may well need to turn to other approaches: science is one approach that we might use, but it’s not the only one.
Which, by a round-about route, brings us back to where we started, with Dave Snowden and the Cynefin framework. Starting from the unknown – what Dave describes as the domain of ‘Disorder’ – we have four distinct methods to ‘make sense’ of what’s going on:
- the Simple domain: apply rules to ‘categorise – sense – respond’
- the Complicated domain: apply algorithms and logic to ‘sense – analyse – respond’
- the Complex domain: apply guidelines and heuristics to ‘probe – sense – respond’
- the Chaotic domain: force change through action, to ‘act – sense – respond’
I know Dave can get ‘curmudgeonly‘ when we place these Cynefin domains in a simple two-axis frame, but in this case there’s one frame that aligns extremely well, and does add quite a lot to our understanding of Cynefin itself. These two axes are value versus truth, and inner (personal) versus outer (collective), which gives us four domains: inner truth, outer truth, outer value, inner value. These domains map almost exactly to those four main Cynefin domains and their sense-making tactics:
- ‘inner truth’: Simple domain – rules or supposed ‘universal truths’ that purport to apply to everyone, everything, everywhere
- ‘outer truth’: Complicated domain – algorithms and the like, often with multiple factors and complicated interactions and delays, but always amenable to causal analysis
- ‘outer value’: Complex domain – use ‘seeds’ and experiments to probe into the context, to allow meaning to emerge
- ‘inner value’: Chaotic domain – any meaning that may be derived is context-dependent and probably personal only
(The chapter ‘Can’t we explain this scientifically?‘ in my 1990 book “Inventing Reality” likens each of these modes with a means to survive within a swamp: run too fast to sink; climb up a pole; weave a platform between a group of poles; or spread your weight on swamp-shoes. The advantages and disadvantages of each mode are summarised in some detail there: might be worthwhile to read that chapter now and then come back here.)
In practice we would – or should – usually switch between each of these modes, much as Beveridge implies in The Art of Scientific Investigation. But the key point here is that a ‘scientific’ approach – which depends on causality and logic – can only make sense in the two ‘truth’ domains. Trying to use ‘truth’ tactics in the ‘value’ domains is not a good move: we risk ending up with what Dave Snowden calls ‘pattern entrainment’, such that in effect we use a quasi-religious belief as a substitute for true science or sense – which is not a good idea. (For more on this, see, for example, Amory Lovins’ video on “How the practice and instruction of engineering must change“.). Which means that we need to use entirely different approaches in the two ‘value’ domains. We could use terms such as ‘non-rational’, ‘arational’ or ‘meta-rational’ for this, but we might as well use the term that already exists for this: magical.
Magical-thinking isn’t a mistake: it’s what we need to use in the two ‘value’-domains – or, in Cynefin terms, the Chaotic domain and, especially, the Complex domain.
This post has rambled long enough already, so I’d better not go into too much detail. 🙂 But one of the key tactics here is to deliberately use beliefs as tools, especially in the Complex domain, using them as if they are true whilst still recognising that they may not necessarily be ‘true’ in absolute sense. In classic scientific terms, another name for this tactic is hypothesis, as contrasted with idea (Chaotic domain), theory (Complicated domain) and law (Simple domain). It’s what we do in most technology-development: for example, we might use ideas from science, but we might also use analogy, metaphor, serendipity or even images from a tarot-deck – what works is whatever happens to work. And the fundamental question here is not science’s ‘How does it work?’, but ‘How can it be worked?’ – not how do we make it more ‘true’, but how do we make it more effective, more efficient, reliable, elegant, appropriate, integrated.
(Incidentally, this is one of several reasons why using the term ‘applied science’ as a synonym for ‘technology’ is misleading and even dangerous, because we end up applying the wrong criteria to measure that technology’s value – assuming ‘technology’ in the original sense of ‘tekne‘, a body of knowledge and related practices rather the rather incomplete sense as ‘machines and stuff’. Another concern is that by purporting to be ‘science’, a usage of technology can also attempt to claim science’s status as ‘value-free’ – and hence supposedly not subject to the ethical and other value-constraints that, by definition, are actually the core of every technology. And magic too, for that matter :-). In this sense, technology and science are fundamentally different from each other, whereas technology and magic are fundamentally the same. In fact the only real difference between the latter is that magicians tend to be a bit more ‘way out’ in their choice of beliefs, especially when the technology is more about mind than matter.)
Whichever mode we use at any given time, the key to all of this is discipline. (This applies in magic as much as in any other technology: as the pseudonymous author of the influential SSOTBME put it, “all those boring meditation books are just the magical equivalent of a school chemistry primer”. But that’s another story… 🙂 ) Which, finally brings us to why I wrote this post in the first place, because we need a disciplined approach not only to the use of each domain, but also to how not work work within each domain, and how instead to switch between the domains in an effective, intentional manner.
Most readers of this blog would know me as a specialist in whole-of-enterprise architecture. But my real interest, and real work, is in methodology and meta-methodology – the design of methodologies to suit each specific context and need. Behind that, what really concerns me is the process of developing skills as true skills capable of dealing with the complexities and chaos of the real world – rather than as glorified ‘trainings’ that are only usable in the safe, easy purported-predictability of the ‘truth’ domains. I’ve been engaged in this work for well over forty years: for example, one of the tools I developed that you may have seen is the Skills Labyrinth, a live-metaphor for the skills-learning process.
But one of my primary test-cases for this – mainly because it’s almost the closest I can find to a ‘pure’ interpretive-skill, with very little manual-skill and technical-knowledge required to get started – is what’s known in Britain as dowsing, the generic for ‘water-divining’ and the like. (Each country has their own term for this: Americans would know this as ‘water-witching’, for example, whilst Dutch might call it ‘wichelen’.) It’s a classic ‘magical’ skill, sufering – as so many do – from an overdose of idiots, and much-derided by self-styled ‘skeptics’ who rely only on ‘scientific’ theory rather than technological practice and hence don’t have any real grasp of what they so obsessively dismiss. (As it happens, we know a great deal about the physics, physiology and psychology of the skill: one key point we now know for certain is that there is no single mechanism involved, but rather a complex ‘weighted-sum’ merge of multiple mechanisms. Hence most of the classic means of scientific enquiry – “how does it work?” – make little sense, whereas technological enquiry – “how can it be worked – does indeed work well here.)
Worldwide, I’m actually better known as a writer on dowsing and related subjects than on IT or enterprise-architecture: my first book on this – nowadays known as The Diviner’s Handbook – was first published in 1976, translated into some dozen languages, has been in print continuously ever since, and is regarded as one of the standard reference-works on the subject (or learning-guide, rather, because that’s its real purpose). And I apply exactly the same rigour to my work in that field as I do to anything else: I insist on keeping myself, and others, strictly to the correct discipline in the appropriate domain. Which at times is not ‘scientific’, of course – but so what? If the ‘scientific’ mode is not appropriate in that part of the technology, don’t use it! Which is exactly the same principle as we need to apply in KM, or enterprise-architecture, or anything else that is inherently complex and in any way inherently unique, and hence where the usual constraints of ‘rational repeatability’ and the like do not and cannot always apply.
Hence yet another book of mine, co-authored with the archaeographer Liz Poraj-Wilczynska, and published late last year, called Disciplines of Dowsing. (You can download the e-book version for free from the website, though please consider buying the print version if you’re going to use it in practice!) Parts of this work have also been published in the Berg peer-reviewed academic journal on archaeology, Time & Mind. In it we explore the application to dowsing practice of the same four approaches to sense-making and action, linked to Cynefin as above, and cross-linked to standard quality-improvement tactics such as kaizen, the Deming/Shewhart PDCA cycle, ISO-9000:2000 and reflective methods such as After Action Review. It’s the same principles, applied in a slightly different area to what most KMs and EAs might know, but otherwise no different at all. What is different – and which we haven’t seen anywhere else – is an explicit emphasis on how and when and why to switch between each of the disciplines. Which, in turn, we could – and, I would argue, we should – apply in turn to our other everyday work-domains such as KM and EA and the like.
There’s also a strong emphasis in the book on how to identify and avoid some all-too-common pitfalls, the ‘seven sins of dubious discipline’ such as the Hype Hubris, the Newage Nuisance and the Meaning Mistake. (‘Newage’ is perhaps a more accurate term for much of what purports to be ‘new age’: it rhymes with ‘sewage’, ‘the discarded remnant of what was once nutritious’… yup, I can be a cynic too! 🙂 ). But the point here is that, again, there are exact equivalent of the ‘seven sins’ in every other kind of skill, including those in the sciences: for example, Roderique-Davies’ paper on NLP includes several all-too-obvious examples of the Meaning Mistake. If we don’t understand the limitations of science, and worry too much about seeming ‘unscientific’ or ‘pseudoscience’, we’re likely to end up damaging the quality of our skill and our results rather than improving it. In that specific sense at least, magic is real – and as Cynefin shows us, it matters just as much as science and the like to the quality and validity of our practice.
In addition to the e-book of Disciplines of Dowsing, there’s also a two-page reference-sheet that summarises the four sets of disciplines, and that’s perhaps more immediately usable in practice. (The material on the ‘seven sins’ is only in the book, though.) It’s written for dowsers, of course, but it doesn’t take much translation to apply it direct to KM, EA, software development or any other complex-domain skill. Download it, perhaps, and let me know how it works for you? And thence it might be worthwhile writing another version specifically for KM or whatever. Something different to play with, anyway.
You have to remember that NLP claims to have a scientific basis. If it just made a new age claim or similar then it might be more tolerated, but a lot of its commercial success comes from what is in its essence a false claim. Oh, and astrology is nonsense, even if Newton studied it. Sorry, but KM really needs to move away from pseudo-science. Also in the complex domain of Cynefin the principle is safe-fail experiments. That means that coherent theories are tested experimentally. It does not mean that any belief is valid.
Point taken about “NLP claims to have a scientific basis”, and the commercial misuse of that – though the original books don’t make any such claim beyond what was available at the time (Erikson et al? again I’m working from memory here).
“Astrology is nonsense”: depends what you mean by ‘nonsense’, or even more what you mean by ‘sense’. 🙂 Agreed that in current scientific terms it makes no sense at all (e.g. action-at-a-distance, scale etc), and in my opinion any literal interpretation (“what sign are you?” etc) is usable/valid only as a conversation-gambit. Symbolic interpretations, though, can have real value, much like any symbol-rich framework such as the Shakespearean-period ‘Art of Memory’ (Frances Yates) – it ‘makes sense’ in terms of its *use*, not its ‘truth’.
I *strongly* disagree with “KM needs to move away from pseudo-science” – not the statement itself, but the implication that KM should or even can be assessed and validated in scientific terms alone. The ‘science-versus-pseudoscience’ dichotomy only makes sense in the ‘truth’ domains, which would only make sense here if we assert that KM is only about ‘truth’-based systems such as IT – which I know you wouldn’t agree with at all. You would agree with me, I’m certain, that KM needs to cover all of the Cynefin domains – which means that we need to balance ‘truth’-based assessment (science etc) with ‘value’-based assessment (technology/’magic’ etc – much as described in detail in Beveridge’s ‘The Art of Scientific Investigation’). If we don’t get that balance right, we actually *create* pseudoscience in the attempt to reduce it – much like IT-centric ‘KM’ turns any real KM into a complete shambles.
On Cynefin and the complex-domain, I’m well aware that you’re Cynefin’s creator, but remember that one of the characteristics of pseudoscience is a body-of-knowledge that belongs to a single person. 🙂 I’m trying in this article to show you something different about the complex-domain, which you seem to have skipped straight over because it wasn’t what you expected and isn’t how you use it in your own practice. If, as you say, “the principle is safe-fail experiments” only, we’re right back in the hard-systems worldview, with little if any space for soft-systems etc – and no space to assess the experiments to arrive at the design etc of those experiments. Within the latter, it *does* mean that “any belief is valid” – or may be valid, rather, if only as an intermediate step to something that is more valid in a practical sense. Just about the only difference between technology and magic is that the former tends to cling onto the safety-line called ‘applied science’, whereas magic frequently doesn’t bother. (Paradoxically, magical-thinking often works best under conditions of secrecy – the exact opposite of technology’s retreat to ‘best-practice’. Which can also be problematic, of course. 🙂 If you’re interested, there’s more detail on that, and why secrecy is important, in the book ‘SSOTBME’. Just don’t ask me to explain the long-winded joke in the book’s title, though. 🙂 ) This ‘freedom to wander’ is especially important for the idea-generation phase (i.e. Chaotic-to-Complex rather than Complex-to-Complicated) where pattern-entrainment is such a serious problem. Magical-thinking allows us to play deliberate games with belief, to break free of that entrainment: as psychologist Stan Gooch put it, “things have not only to be seen to be believed, but also have to believed to be seen”. I really do believe, from working with Cynefin over the past half-dozen years or so, that there’s a lot more in the Complex-domain than you seem to be willing to allow for at present: might be worth a discussion over a pot of beer somewhen? 🙂
The commercialisation of NLP was a key aspect of the early founders – read the history.
I don’t buy the truth/value dichotomy you are creating, sounds like an excuse for total relativism
However reading the rest I think you are happy with an anything goes relativism which you want to term”Magic” (although having spent some years of my life working on shamanistic knowledge I don’t think you would find much support for your use of the word in those communities).
It is total nonsense to say that safe-fail experiments are hard systems not soft systems (which is a dubious distinction anyway). It is, I think, foolish to ignore the test for coherence. An experiment is an experiment, it may be social or whatever. Its a principle of action by the way, the addition of “only” is your POV not my view.
The history of scientific advance is not one of randomness, there are accidents, but trained people pay attention to those accidents (Fleming). There are mavericks, but they base their work on sound theory (Harrison).
You create another dichotomy between technology and magic – a near medieval delusion. Technology is a tool, few human processes or activities are not tool dependent, but they are not tool determined.
A complex system by its nature has constraints, without constrains there is no evolution. Yes you allow and encourage a freedom to wander, but that freedom should be free of basic constraints. I actually think you are really limited the complex domain by equating it with this quaint notion you have of “magic”.
I’ll bow to your knowledge on the history of NLP. I’ve found it a (sort-of) useful frame on specific occasions – particularly its use of different language-styles for different audiences, which makes practical sense (though the Spiral Dynamics frame, for example, gives more precision for that). I don’t buy into its ‘scientific’ claims, and they’re frankly not relevant to what I do.
What I’d described would be an ‘anything goes’ relativism if there were no disciplines behind it. As you would know from your work around shamanistic communities, the definition of ‘the real’ and ‘the possible’ can become usefully fluid under those circumstances – but without some pretty solid anchors it’s easy to get a long way adrift. (That’s one of the reasons I insist on visioning-work as a first stage of enterprise-architecture.) Beyond that, I don’t think there’s much point in trying to explain this specific usage of the term ‘magic’: to quote an old Dr Johnson story, about two women yelling at each other from house-windows on either side of the street, “they can never agree, for they are arguing from different premises’. 🙂
Same applies, I suspect, to our respective understandings of ‘science’, ‘technology’, or even ‘complex’. (FWIW, the theoretical base is use for understanding science is writers like Beveridge and Feyerabend – “the only approach which does not inhibit progress (using whichever definition one sees fit) is ‘anything goes'” – plus a decade working in Australia’s Aeronautical and Maritime Research Laboratory; for technology, it’s nigh-on forty years of practice in a wide range of industries. I don’t have anything like your amount of high-level consulting experience, but I’ve used my time well in other ways, shall we say?) And yes, I can quote many classic examples from the history of science – “chance favours the prepared mind” (Pasteur), for example, or “gentlemen, we must learn to dream!” (Kekule). But the sad thing is that it still seems unlikely to get the point across. You’re clearly not listening, and not willing to listen, so there’s no point in continuing on with this. I’m disappointed, to say the least: closed-minded dogmatism is depressing at any time, but especially when it comes from someone like you, whom I’d previously regarded as one of the more valuable thinkers in this field.
What I find frustrating is that you’re so quick to dismiss subjects of which you appear to have little or no knowledge – quote “this quaint concept you have of ‘magic'”. Go read Feyerabend, for example: ideology is not a substitute for thought, and a very poor guide for action. But your choice, of course. Best leave it here, I think?
Chance favours the PREPARED mind, note the prepared. Its the point I made about Flemming’s discoveries. Kekule was a brilliant chemist, he may well have dreamt, but he would also apply his scientific training. Your examples from the history of science disprove rather than prove your point. You are confusing openness to novelty, a willingness to imagine and experiment (all of which are good things) with a willingness to accept anything even after its tenets have disproved. Adding language such as “magic” or worst still creating dichotomies between values and truth is a way of avoiding the consequences of knowledge.
Please don’t introduce spiral dynamics as well. Another set of witch doctoring, with another commercial split and Ken Wilber to boot. Are you a turquoise person? After all only those who have obtained higher levels of enlightenment can truly speak with wisdom. God help us all, its even more bullshit than NLP and that is saying something. And before you ask, yes I have studied that one as well. I have a general interest in cults and their ability to seduce intelligent people.
Your language in this later post is now the language of cults by the way. You are not understood, you can’t really explain the concept to an unbeliever, you are in a different place (possibly with turquoise coloured walls). People who do not agree with you are not listening so you will have to withdraw from the argument. You are the possessor of disciplines that prevent you falling into error, lessor mortals who do not appreciate this are dogmatic, they disappoint you. Come to think of it you may be mirroring Wilber. So I can preserve some thread of belief in a rational future please tell me that you are not taking the return of the Green Feathered Serpent God of the Mayans in 2012 seriously as well?
I do not want to be a thinker, valuable or otherwise in a world of new age pseudo-science and pscho-babble. Sorry about that, but I have but too much thought into the nature of knowledge of the years to fall into that particular trap.
Ah, Dave, c’mon… We can keep going hammer-and-tongs like this till kingdom-come or whatever, and it still ain’t gonna get anywhere useful. You’ve got your fixed views, and that’s fine (well, it isn’t, actually, but let’s let that pass for now? 🙂 ) So let’s just put this down to you having a bad day, or bad lifetime, or bad G&T or something, shall we? 🙂
What’s frustrating in all of this is that ten minutes of enquiry with people you know who know me – people like Shawn over in Aus, or Sally B here in Britain – would give you the clear fact that whilst I may be an eccentric of sorts, I ain’t no new-age flake. A quick trawl of your own memory of that Cynefin course back in Sydney would remind you of the same. One quick search on my website would show you several detailed in-depth critiques of Spiral, complete with several references to the said Mr.W, each preceded by the adjective ‘odious’. And there’s plenty more besides – and you *know* all of this. So c’mon, give me a bit of benefit of the doubt, will you? Then I can do the same for you? 🙂
As for the Green Feathered Serpent bit, um, well, yes, I’ll have to admit that I did come back from a tour of part of the Maya country in Guatemala just last week. Sadly, it wasn’t nice pretty-pretty new-agey stuff, though – in fact it was high-end enterprise-architecture work (including a small smattering of Spiral, as it happens) with the senior execs and line-staff of a major multinational bank, a large credit-union and an automotive-industry manufacturer. I’ll admit that there was some visioning work in amongst that lot, but hardly what one would call ‘new-age’: more like about how to ensure business survival and business growth in very hard times. And let’s just say that Guatemala City is, um, *interesting* in the wrong sense of the word, shall we? – saw my first body-bag lying in the street on the first day there, to give you some idea, and it wasn’t the last body-bag, either. Armed guards with pistols and pistol-grip shotguns absolutely *everywhere*, in every shopping mall, every side-street; most street-side shops have heavy grilles to reduce the risk of armed robbery. Not much new-age ‘all sweetness and light’ there, I can tell you. And yet people adapt, life goes on somehow, because it has to: that’s the most interesting point, isn’t it?
So let’s just drop the accusations of psychobabble and pseudoscience on both sides for a while, shall we, and drink to realism instead? 🙂 Might be a bit more constructive in this Happy Holiday Season or whatever it’s called?
Enjoy?
Happy to give anyone the benefit of the doubt, I’ve just been responding to what you have written.
So happy to leave it be, although your first paragraph is amusing. Actually I was having a good day, and a reasonably good life time and the G&T was excellent. Suggesting that someone only disagrees with you because they are in a bad mood is not good practice. If I was female would you have blamed it on PMT? I meant what I said, and I thought about what I wrote. Oh and fixed views? Odd that one, present me with some evidence and I’ll happily examine any position I have taken. However no evidence just assertion you can’t expect change. Obviously if you accept anything as valid then you are being flexible, but so flexible as to be meaningless.
So wipe out that bit of silliness and I’ll given you the benefit of the doubt on spiral dynamics. I’m afraid the psychobabble and pseudoscience statements stand until I see some evidence to the contrary. Avoiding those positions is critical to realism, and to finding solutions to the problems of areas such as Guatemala.
Oops. Looks like I made a mistake in trying to lighten the tone in this. Oh well.
I did try to present you with a tool to handle situations where tests of science versus pseudoscience don’t work, and you gave me acid-in-the-face instead. Unfortunate, that, but your choice, of course.
As for evidence of fixed mind, one of the proven characteristics is the misuse of emotion and name-calling in defence of the purported ‘truth’. In effect, science becomes dysfunctional religion as soon as emotion enters the picture. (Responding, you’ll note, isn’t necessarily the same as thinking, and I must admit that I haven’t yet seen much evidence of the latter. Plainness of thought, yes – “plain as a fart”, to quote Ursula le Guin – but clarity of thought, no.) So re-read your posts and mine here and on Twitter with that in mind. Notice who indulges first and most in name-calling and other distractive rhetorical tricks? Strangely enough, it isn’t me. Notice who uses put-downs (“silliness”, “psychobabble”, “mediaeval delusion” etc – go count ’em, there’s a lot of ’em) in place of evidence or debate? Notice who uses repeated assertion that something ‘is so’, rather than engage in actual debate? Notice who calls on spurious ‘authorities’ to dismiss the work without any actual experience of the specific tasks in question? Notice who sarcastically rejects every item presented by the other, asserting a position of purported superiority, without giving any evidence for that rejection other than, circularly, the purported ‘superiority’ itself? Notice who calls on other people to join in with the mockery of the other? In all of those, you’ll notice that it isn’t me. So perhaps it might be you?
So yes, perhaps just in this dialogue (if that’s the right word?) there’s evidence enough to warn you of this. If you’re willing to notice that fact. Which seems unlikely, unfortunately; more likely that you’ll put me down yet again instead. Yet in addition to some appropriate colloquial epithets that describe those kinds of behaviours, there also are some standard psychological terms for it that, by custom and by law, require serious personal responsibility and serious personal action – but no doubt you’d dismiss all of that as ‘psychobabble’ too? Which is kind of worrying.
At the very least, you’ve successfully proven that although there are plenty of our professional colleagues who *do* understand what I’m perhaps rather falteringly trying to describe, there’s no point in my trying to work with you. Well done! Congratulations! An excellent outcome for you! But kind of sad, really, because the only one who’s really losing out in this is you.
Your choice too, of course.
You didn’t lighten the tone with your first paragraph, you made the assumption that people could only disagree with you if they were having a bad day. As for the rest, at least I called on authorities, you called on your own opinion. Dismissing an academic authority as spurious because they don’t agree with your own perception of your experience and completely ignoring counter arguments to your examples of scientific change does not make it easy to conduct any exchange. Representing a series of artificial and false dichotomies as a “tool” doesn’t help much either. I think you are defending the indefensible, its your call but are are right there is no point in continuing. Its your blog, so here you are welcome to have the last word. I won’t reply unless you specifically request it.
I’ve read most of the classical NLP books, and I would say NLP is very explicitly non-scientific from the beginning. It defines a way of working in which most validation (“does it work?”) is immediate, based on short-term trial and error, and is in principle disposable.
Starting out with simple trial and error (the basic biological learning strategy if you will), science tries to improve on it by using complex procedures that (presumably) increase reliablity and intersubjectivity. The feedback loops are very long. NLP is almost the opposite, attempting to keep the feedback loops extremely short and improve them in other ways instead. But, and here is the most interesting thing I think, NLP claims that you can take advanced theory from linguistics and epistemology, and use them in these short feedback loops. This is somewhat analogous to the way technology uses physics and mathematics to do experiments on a small scale and make stuff that eventually either works or doesn’t. Figuring out whether it works or not is not difficult, unlike most scientific questions these days. And if it doesn’t work, it doesn’t help that the theory is correct.
Above all, NLP is epistemologically interesting. It’s theoretically deep but paradoxically that depth is not appreciated by most of its practictioners.
Many thanks for this, Dagfinn. Very helpful and exactly to the point (perhaps especially that its epistemological depth and, in particular, methodological depth “is not appreciated by most of its practitioners” – many of whom fall into exactly those errors about which Dave so vociferously complains).
You’ve reminded me that the key concern here is around *methodology* (‘value’) rather than taxonomy/ontology (‘truth’). The distinguishing characteristic, as you say, is short feedback-loops to improve the value, rather than long feedback-loops to verify the finest minutiae of the ‘truth’. As per Deming’s PDCA and the like, there’s a useful guideline that shorter feedback-loops deliver more value whereas longer feedback-loops deliver more ‘truth’ (i.e. taxonomic/ontological certainty). (There’s a diminishing-returns limit to this, though. In agreement with Dave here, it’s notable that many proponents of pseudosciences push for infinite-length feedback-loops so that the chosen ‘truth’ can never be challenged, but it also means that it delivers no value. 🙂 At the other end of the scale, as we trend towards infinitesimal feedback-loops, we end up in the kind of subjective chaos that only ‘makes sense’ to an artist.) Part of the purpose for the recursive methodology I’ve been trying to explain here is to help get the balance right according to the needs of the context.
Interesting, too, how a constructive comment like this creates conditions under which new ideas arise (I hadn’t previously recognised that point about the link between length of feedback-loop and the value/’truth’ spectrum) – hence, in effect, everyone wins. By contrast, destructive comments block that kind of collective creativity, forcing retreat into defensive positions – hence everyone loses, because no-one has any chance to move. So thanks again – much appreciated.
Hi there, I have come relatively late to this conversation and indirectly as I became curious about an individual that had such a sharp axe out for the Practice of NLP (Dave Snowden). What amazes me is that so much of the heated discussion around NLP is generally just conjecture, based on little or no direct experience at all. The cult of personality surrounding Richard Bandler has done the field of NLP no favours and the negativity and sheer polemic that some people display when discussing NLP strikes me as largely neurotic (i.e. it says more about them than the practice of NLP). Put simply, NLP was founded on a precise systemic approach to modelling human behaviour (i.e. Grinder/Dilts) and the structures of subjective experience. We all modelled on the people around us as children and developed language patterns, character styles and behaviours etc accordingly. The process of modelling is well known in the world of Acting and is essentially how those who follow method acting, for example, generate such complete characterisations and physiological transformations. In NLP we still have the practice of modelling (although it is the technique based version that attracts the crowds and the criticism) which includes eliciting the core beliefs that someone of excellent behaviour holds and then, along with a number of other insight tools, ‘try on’ the world view of the individual we are modelling. When you apply this new (and temporary at this stage) state of being to a specific problem you may have faced before, perhaps in the business context which is a large part of my experience, then whole new areas of insight open up and new strategies emerge creating choice for the application in the ‘real’. Essentially at this point we are now talking about the study of the relationship of epistemology to ontology and how this influences our perception and how this co-creates our experiences. We have the state of mind we came to the task with, our existing frame of reference, how we have edited reality to date etc. We then have the exterior world that we interface with, only this time we do it as a slightly different person. Therefore we edit this new information differently and get different results accordingly. The reason that science has a field day with NLP is because the arena of study is the complete human experience – we are literally made up of both the Independent and the Dependent variables of any experiment you could care to attempt to validate based on NLP methodology. The scope for confounding variables is wide and that is a massive obstacle even before we get into the issues of sampling. However, every time I work with either a client or a workshop the results are very strong and indeed measurable in terms of quality of life and transformation of businesses and organisational behaviour. I am also informed by the work of Ken Wilber, spiral dynamics and this is largely due to the total inclusiveness of these models, and not their exclusiveness. The detractors of Ken Wilber and of the work of Clare Graves (Spiral Dynamics) invariably focus on what they call pseudo science and new ageisms – if you have actually read the works of either both are of the highest calibre in terms of a rational exposition of their models and possessed of rare clarity in their communicating sometimes highly complex and multi level logical maps of reality. As person who has spent the majority of their life building businesses and as personal interest focused on human development, I am all about the application of persons theory. If it has no application in the now then it is possibly a nice idea in need of some grounding in experience – and i would be happy to discuss it. But I don’t instinctively need to take an axe to it… so I would challenge the motives of anyone who instinctively does. Parting thought: Every time you learn something new you believe something different to that which you believed before, and every time that you believe something different you become a different person to the one that you were before… even just ever so slightly.. so then does it not follow that in order to change ourselves more effectively we should change how we learn and subsequently what we believe becomes a matter of conscious experience as opposed to tautologies and rigid ideas and exclusive realities.
Hi Mark – thanks for the detailed comment – much appreciated!
To be honest, I think it’s best to ignore the critiques from Himself: as so many others now have likewise experienced from that person, it’s long since proved impossible to have any kind of rational discussion there. The key, perhaps, is that person’s near-obsession with (largely spurious) notions of ‘science’, and an apparent near-total inability to distinguish between science, pseudo-science and technology. To my mind NLP fits firmly in the latter category: it’s best described as technology rather than science, and hence should be assessed primarily in terms of technology, too – for example, a focus on contextual-effectiveness and quality-management, rather than on purported ‘truth’. Trying to assess technologies solely in terms of ‘science’ does nothing useful at all: all it does is create an opening for idiots who are more concerned with propping themselves up by putting others down than on getting anywhere towards anything of practical use. Sigh…
(One line summary: yes, NLP can be useful; but if misused or misunderstood, it can also be not-useful. Skills and (common)sense are both very important in this. Use it wisely; use it well. 🙂 )
On Wilber, Spiral, and the dreaded ‘Integral-this-that-and-the-other’ not-quite-cult, I’ll have to admit to a very strong dislike here, on grounds of both theory and practice. I’ve very considerable respect for Clare Graves’ work (no relation, btw! 🙂 ) – it’s solid, well-documented, well-grounded in decades of real-world research. Yet to my mind, Wilber’s work is none of those things, and Don Beck’s mangling of Graves’ work even less so. (Chris Cowan’s adaptation and application of Spiral is a different matter: I have a lot of respect for that.)
Yes, Wilber’s own work is a masterpiece of synthesis, yet to me it ends up presenting and promoting a really unpleasant and dysfunctional linear-hierarchical view of reality. As with another disastrously-foolish American ‘philosopher’, Ayn Rand, my first-hand experience of too many self-styled ‘Wilberites’ is that it seems to incite and extol some of the worst possible human characteristics: obsessive self-centredness in Rand’s case, and a particularly ghastly smug ‘holier-than-thou’ cultural-imperialism in Wilber’s case. Unfortunately, the latter aligns almost perfectly with the linear-hierarchy of Beck’s version of Spiral – which, to be blunt, completely fails to understand the difference between individual development (which is somewhat linear, and which Graves’ model describes very well – especially the parallels with child-development and the ‘arrested’-development that occurs when key stepping-stones are missed or not traversed) versus collective development (which is definitely not linear – a point that I know Cowan does strongly emphasise). The resultant Wilber/Beck ‘AQAL Integral’ framework looks good, and is very appealing to those of a millennial bent, but can be lethally dangerous in practice – particularly when attempts are made to apply it to whole cultures – because its rigid assumptions about the linearity of ‘progress’ simply do not match up with the real complexities of the real world. Not a good idea…
Wilber/Beck is possibly quite useful in work with individuals: you’d be able to answer that one much better than I can. But in my opinion it should not be used at a collective level – though a Cowan-type version of Spiral combined with futures-techniques such as Causal Layered Analysis (aka ‘poststructuralism as method’) can work very well indeed. I’d emphasise again that it’s the pseudo-linearity that’s the problem there – not Clare Graves’ original analysis.
In my own work I’ve found that Graves’ model actually makes more sense not as a ‘spiral’, but as a set of near-orthogonal dimensions – of which the most obvious, highlighted even in Spiral, is the ‘individual vs collective’ dimension. If we take that view, then the supposed ‘spiral’ is better understood as a series of Gray-code-type transitions that expand or contract an overall set of capabilities in response to environmental and other conditions within an overall context-space. For example, small indigenous communities often demonstrate high levels of Spiral ‘Turquoise’ or ‘Yellow’ – awareness of systems-as-whole – yet with little or no ‘Blue’ or ‘Orange’ – which seem necessary largely as response to increasing community-size. Would be happy to discuss this further with you, if you’re interested – perhaps arrange a meetup in London somewhen?
But again, going back to the start-point regarding the predations of Himself in relation to NLP, the only practical tactic is to apply Bob Sutton’s ‘No Asshole Rule‘, and just ignore him – unfortunately it really is the only way that works. Oh well.