"Since the measuring device has been constructed by the observer…we have to remember that what we observe is not nature in itself but nature exposed to our method of questioning."
Werner Karl Heisenberg, Physics and Philosophy, 1958
"You see things; and say "Why ?"
But I dream things that never were; and I say "Why not ?"
George Bernard Shaw (1856-1950), The Serpent, Back to Methuselah
Recently some additional attention has been given to what are called WH questions, such as "why", "who", "what", "where", "when", "which" or "how", especially as to whether "why" should be regarded as more fundamental than the rest. Since this investigation raised also questions of valuation and of alternative logics, themes close to my own heart, I've been thinking some more about how WH questions could be better adapted to a complexity perspective. To do this we need, perhaps, a meta-perspective since that is the general complexity stance I take.
Each of these questions has inherent in its formulation a scope, in other words we have preconceived ideas as to how widely we expect it to apply. For example when we ask a "when" question we expect an answer phrased in terms of a particular time. But such events are not instantaneous, they always have durations, so naturally we can consider such questions to have a potential continuum of possible durations, and similarly, for all the other WH questions, we can imagine a scope stretching from near zero to near infinity. In our considerations of complexity science we frequently comment that this extends the scope of our thinking, so naturally we are led to consider how this impinges upon how we ask such basic questions in our scientific and human activities. Only if our methodologies are appropriate to the tasks that we attempt can we expect to get answers which are appropriate for our intended actions.
One of the main insights we get from complexity theory (as compared, say, to catastrophe theory and chaos theory - both nonlinear maths based) is that in complex systems we have not one attractor at a time but many of them active simultaneously. This occurs because we take the totality of the 'system' and do not reduce it to subsets (assumed to be isolated and independent) as do most other sciences. It is also found that the possible subsets can themselves maintain different 'local' attractors when they are all connected than any of them can maintain individually (e.g. multicellular differentiation) and this is the important idea of synergy or division of labour, possible due to good communications (explicit or implicit).
Thus the general idea that we can focus on one isolated form (whether we call our studies 'scientific' or not) remains a form of old-style reductionism, and we would query its validity. That does not mean that we can't study the individual attractors within a system, we certainly can, but what we can't do (or are ill-advised to do) is to assume that they are all independent and fixed, we must look to ask questions about how they affect and change each other contextually, which brings in issues of nonlinearity and deterministic unpredictability, often associated with chaos theory.
Some people continue to confuse complexity and chaos theories however, the latter strictly relates only to deterministic unpredictability of limited numbers of variables (often only one). Complexity theory in its 'true' form generalises this to holistic systems containing large numbers of variables. For example my own Boolean network models contain between 9 and 8100 nodes - the output of each of which is a control 'variable' in a real sense. Within such systems we can certainly have chaos, but we also have all the other sorts of attractors (point, cyclic, strange and transient), a mix of order and disorder which we call 'edge-of-chaos'. This is a difference between traditional 'analytic' approaches and our 'holistic' or synthetic approach.
Mathematicians often regard 'the analytic' as real (as in Plato's 'perfect' world) and 'the holistic' as imaginary (or delusional), but this seems to get the two back to front. Here we should bring in Korzybski's 'map' and 'territory'. The territory is clearly real and is holistic, thus the map is imaginary and analytic - the reduction of the real to a limited model. On a similar tack, the contrast between 'believe' and 'know' (often claimed by philosophers) is another delusion - both are simply less or more probable forms of the same thing, validated (or not) by experience.
Robert Rosen made the distinction between 'natural systems' (reality) and 'formal systems' (fantasy) and as part of this he emphasised the need for 'encoding' and 'decoding' procedures to connect these. This step is usually left out in science (a good review is by Mikulecky). This is of course the territory-map translation and if we get this wrong we cause ourselves endless problems and confusion.
One way this can occur is if we neglect the full range of possibilities for the system. Mikulecky's review goes on to illustrate some of these, where two simple (well understood) systems generate new possibilities when combined (i.e. synergically) that neither shows in isolation. So if our model ignores this, i.e. if we claim, say, that questions of some form are examples of a 'fold catastrophe' (which may be true enough), but neglect the fact that when two of them are combined (which they often are) then this shifts to, say, a 'cusp catastrophe', and to more complex forms with ever increasing connectivity, then our model becomes pretty useless or misleading too.
Another illustration of this synergic effect, one of the more rigorous, was given by Furusawa and Kaneko in a paper called "Emergence of Differentiation Rules leading to Hierarchy and Diversity". They used a cell model, which allowed signals to diffuse in and out. Using just one cell in a medium they found that only a single cell type or attractor was seen (called 'type 0'). If the cell divided the 'children' retained type 0 behaviour. But once 16 or so cells were present, some then differentiated due to their wider connectivity to a stable (under later division) type 1, or some to stable type 2. These could then differentiate further to types 3, 4 and eventually type 5 (a 'cancer' cell that took over and converted them all...). This is basically the same point Stuart Kauffman was getting at when he noted that complex systems have many possible types of attractor (which he also illustrated by cell types). Which combination(s) we actually get, and the balance that they maintain, is dependent upon the dynamical complexity of the global interconnections, and not to genes in isolation. The same applies to all forms of complex system.
Thus the forms we obtain are contextual and this is important for social areas too. A single person can have certain attractors, but not (in isolation) others. Two people can have a stable (sometimes !) 'marriage' attractor, a few together can have, say, a 'dinner party' attractor, large groups can have a rich variety of attractors (e.g. the roles on a 'cruise ship' or in a 'corporation'). By taking issues in isolation we miss all of this and this 'synergic' dimension is crucial I think in understanding any sort of complex system (and largely still ignored even in complexity science research !).
Now we can ask "what is the essence of synergy ?". One answer could be 'self-reference' or in less teleological or autopoietic terms 'circular causation'. Now we have it I think. Much scientific theory is formulated in terms of disjoint inputs and outputs (as is most maths). But in complexity theory there are strictly no inputs or outputs, they are all the same, since all outputs reconnect as inputs (e.g. all the outputs of a Boolean network are inputs to other elements of the same network - such labels are arbitrary and observer dependent). This gives us an entirely new ball game involving dynamical self-organization and this is why approaches neglecting this fact are often found to be inadequate.
Such bidirectional causality is an essential aspect of all social systems (even economics, that arch-bastion of reductionism !). It concerns 'feedback', the ability of systems to change their trajectories (positive feedback) or to resist such changes (negative feedback). But, given this extra complication, can we still have simple models that map adequately to 'reality' ? It may come back to that encoding and decoding process that Rosen emphasised. Currently we have (perhaps) a 1:1 relationship here, the 'reality' is assumed to consist of just what is in the model (i.e. the model is disconnected from all other models). Can we simply enhance this relationship, making it N:1 and 1:M (preferably N:M - but one step at a time !). We already have considerable expertise here, our many hierarchies are already phrased in 1:N terms, and in several areas concerned with networks N:M thinking is quite common (e.g. ecologies). Both forms of structure relate also to database design - where we have relational 1:1, hierarchical 1:N and network N:M structures. More on this later, but can these two approaches to causality coexist or even understand each other ?
A move from the real (reality) into the imaginary (model) realm reminds me of the incommensurability said to exist in quantum dynamics and brings to mind the apparent incommensurability of views from Muslim and Christian perspectives that we so often see today. I think we can make more of this.
In the East much use is made of the concepts of Yin and Yang. Here Yin is the feminine principle related to negativity, passiveness and receptiveness, which in complexity terms would be the static state of 'order'. Yang is related to masculine behaviour which is regarded as positive, active and creative, this would be the dynamic state of chaos in our terms. Now stability is low frequency and cannot perceive high frequency signals (just as we cannot detect the movement of atoms), and change is high frequency, so cannot detect low frequency signals (just as we cannot see the evolution of rocks). Thus again the two concepts are incommensurable, which gives another possibility. Instead of treating Yin and Yang (say) as extremes of one axis, we can give them each an axis, showing that they too are incommensurable, and going beyond to indicate that a view from one perspective simply cannot 'see' the issues relevant to the other.
In electrical engineering terms the two axes are 'out-of-phase', they exist in different dimensions. We could extend this to 4 dimensions (quaternions) and here we could relate it all to the traditional four states of matter, earth, air, fire and water - regarded as metaphors for different styles of behaviour or 'phases'. But alternatively we can generate 4 quadrants in Cartesian geometry, and this can relate I think to the 4 aspects of Zen. So we have:
|Me, NotYou||Me, You|
|NotMe, NotYou||NotMe, You|
So top-right is 'both', bottom-left is 'neither'. Top-left and bottom-right are incommensurables, the usual dualist view - a diagonal of conflict. The alternative diagonal is maybe the axis of wisdom.
Here then the diagonal from top-left to bottom-right is the view from deBono's 'Rock logic' - the either/or dualism. The diagonal from top-right to bottom-left is the 'Water logic', the 'lateral thinking' perspective. The two are orthogonal, and so to most people are incommensurable also ! Which diagonal we take is I suppose the 'Po !' question (or is it answer ?) which seems close to my Holarchic (integral logic) position - we take both in appropriate contexts. Whether the 4 logic levels (modes of knowing) I use there can be related to Earth (solid or not), Air (variable pressure), Water (self-contained whole) or Fire (all encompassing) is perhaps straining analogy a bit much however...
In complexity thinking we usually represent the move from order to chaos as a linear progression of increasing bifurcations, rather like the Yin/Yang axis. But like the usual 'Pa-Kwa' picture of that the two aspects interrelate, they are in essence fractal. So we can instead, following our dual axis picture, relate the two views Me NotMe and You NotYou to two order-chaos axes (up-down and right-left). The meshing then of the two at either extreme gives us the both/neither Zen options. The incommensurability is the usual tendency of people to completely ignore the views of other parties, even when forced together ! By using order/chaos axes we also highlight the basis of conflict, the wish by both parties to 'fix' their world as static order and to resist any perturbation (move to chaos) implied by recognising incommensurable ideas. We treat this somewhat in our early paper "Conflicts as Emergent Phenomena of Complexity".
By merging these two dynamics in the complexity view we seem also to generate a circular flow pattern, and this can be made analogous to circular polarisation, whereas taking only one dimension at a time would be the usual vertical versus horizontal polarisation - where the one cannot see the other - 'no signal found'. Given that we really need lots of dimensions, one for each value, the propensity for such 'shadows' of poor reception in human dialogue seems immense ! Maybe circular polarisation would enable us to go round the corners ?
Perhaps I can expand somewhat upon this 'circular dynamic'. When (using an oscilloscope) we drive the x and y axes with two waves 90 degrees out of phase we get a circular pattern, called a Lissajous figure. It looks static but is rotating at the frequency of the wave. If we use two frequencies that are not the same, a more complex pattern results, more clearly seen to be rotating at a 'difference' frequency.
Relating this to people, if they have out of phase views then the dynamic will be an oscillation - rather like the idea of "Development through Alternation". Now people of course aren't static, they comprise a range of views and values, so in my terms they would be fractal - a very complex waveform. But any complex wave can be transformed by Fourier analysis into a sum of sine waves of different frequencies. So each combination of these (for two people or groups) would generate a separate Lissajous figure. All these dynamics would overlap so we would have a very pretty (!) evolving dynamic (if we could plot it - perhaps meditation 'mandalas' are a static version of this ?).
Now people are dynamically evolving also, so the Fourier function would have changing balances of frequencies, as each multidimensional person oscillated across the edge-of-chaos boundary (which has the effect of reducing the 'harmonics' as we become more static and increasing them as we become more chaotic). This brings us to the collection of 'strange attractors' I illustrated in my essay "Strange Attractors and Society".
What would such a change to a multifrequency view mean ? Well suppose 'reality' consists
of N interconnected units (e.g. people). If we take N=one unit this may map (1:1) to one
attractor (e.g. type 0), if we take N=a few we may get two attractors, e.g.
a 16:2 mapping, if N=100 we may get 5 and so on. In the reverse
direction our 2 attractors may map to 16 cells, 16 species, 16 M's
of any sort. So rather than having, say, 100 theories (one for each
discipline) we may have 100 mappings (based upon the complexity, equivalent to the number of harmonics, of the target 'real' system). These two 100's constitute the basic same level of complexity perhaps, but are differently organised - we would then need fuzzy specialisms concerning
'isolated' systems (physics), 'local' systems (biology), 'intermediate' systems (sociology) and 'global'
systems (religion). In Rosen's terms we have a scheme thus (using just 4 mappings for simplicity):
Would this still be 'simple' I wonder ? One possible problem would be what happens when the scope of our formal model does not match the reality involved, i.e. when the 'map' is not appropriate to the 'territory' of interest, and we'll treat this more later.
Why questions relate to meaning or 'semantics', whereas science often tries to reject or marginalise such issues. For us, the whole idea of a "why" is associated with values, and these are just as much a part of science as they are within other human areas. Here the value of a "why" question seems to me to be that it forces us to consider that there may be many reasons, i.e. multiple values, involved - in a way that most of the other WH questions tend not to do, in other words causality is multiple and nonlinear and is not single and linear. That does not mean that we cannot just treat a single issue with a "why" question, but the dualism then involved is what causes many of our social problems in the first place ! Thus I'd say that our many possible reasons are all attractors, and are all interrelated, changing one can change several others. Creative thinking, considering all aspects of the system (them as well as us), can help identify these wider ranging solutions, which often solve several problems at the same time.
This approach, of which Hawken's "Natural Capitalism" is a fine example, also incorporates deBono's 'water logic' I think, and sets itself in mild opposition to the one-problem-at-a-time methodology that I think most approaches still have. Here the insight that Gardner's 'kinaesthetic intelligence' is more important than 'rational intelligence' seems to hit the mark, since that is essentially a parallel holistic mode where all our senses/abilities act at the same time, in contrast to the serial mode of rationality.
In order to investigate this, here we will classify each question into 4 methodological scopes of increasing generality and parallelism. The first of these relates to the single issue/single answer mode normally associated with the sciences. The second relates to personal behaviours, where a small number of values are usually involved. The third is a more humanistic mode where a large number of simultaneous values and beliefs are relevant. The fourth is a more global or universal perspective and this we will call the spiritual scope.
|Question Type||Scientific Scope|
|When do I ask questions ?||Once ?||Occasionally ?||Regularly ?||Constantly ?|
|Where do I ask questions ?||One Place ?||A Few Places ?||Many Places ?||Everywhere ?|
|Which systems are relevant to my questions ?||One only ?||A Few ?||Many ?||All of Them ?|
|How do I ask questions ?||In One Way ?||In Several Ways ?||In Many Ways ?||Every Way ?|
|What questions do I ask ?||Single Issue Ones ?||Limited Issues Ones ?||Multiple Issue Ones ?||All Issue Ones ?|
|Whom do I ask questions for ?||Myself ?||Social Group ?||Humanity ?||All Stakeholders ?|
|Why do I ask questions ?||For Control ?||For My Quality of Life ?||For Group Quality of Life ?||For Development ?|
We can relate these scopes to complex systems attractors, where the single issue mode is the point attractor, the few issues mode relates to the cyclic attractor, the many issues mode to the strange attractor and the global mode to transient attractors (that fractal mix of attractors of all types existing at 'edge-of-chaos'). The first mode here is "material" in the usual focus of science on 'things', the second "living" in reference to the 'self-centered' behaviour of most individuals, the third "community" associated with our wider cultural mix and the fourth "holistic" associated with immaterial ideas like religion. In this sequence there is an implied growth of complexity both in terms of parts and in terms of connectivity. In valuation methodology we can of course treat humans and the whole as mere "material" to be used and controlled - but this is a disvaluation or 'transposition' as an axiologist would say, I'd call it a dysergy, and this neglect of personal, social and ethical values seems responsible for many of the negative effects associated with current scientific practice. In general axiological terms the first column, the scientific, is a systemic valuation mode - it concentrates on dualistic right/wrong approaches using Aristotelian or Boolean logic. The second, personal, is an extrinsic valuation mode - it concentrates on acquisition or maximisation and is a fuzzy logic approach, the third, humanistic, is an intrinsic valuation mode, it relates to the whole and to matrix logic. The fourth, spiritual, is my holarchic valuation mode, associated with integral logic.
But just as we can ask meta-questions in this way, we can also phrase the answers in the same form:
|Question Type||Scientific Scope|
|When do I require answers ?||Now ?||For a Deadline ?||Soon ?||Eventually ?|
|Where do I require answers ?||One Place ?||A Few Places ?||Many Places ?||Everywhere ?|
|Which systems are relevant to my answers ?||One only ?||A Few ?||Many ?||All of Them ?|
|How do I require answers ?||As One Solution ?||A a Choice of Solutions ?||As Many Solutions ?||Every Possible Solution ?|
|What answers do I require ?||Single Issue Ones ?||Limited Issues Ones ?||Multiple Issue Ones ?||All Issue Ones ?|
|Whom do I require answers for ?||Myself ?||Social Group ?||Humanity ?||All Stakeholders ?|
|Why do I require answers ?||For Control ?||For My Quality of Life ?||For Group Quality of Life ?||For Development ?|
Again these relate to Scientific, Personal, Humanistic and Spiritual types of actions.
So by combining these perspectives in a 7 x 7 matrix we get, it seems, a much more comprehensive analysis of our behaviour from two perspectives, which we can call the 'rule' and 'act' utilitarian perspectives (or perhaps 'subjective' - incoming and 'objective' - outgoing also). Here we note that there are two different methodologies involved - 'how we arrive at an understanding', and 'how we apply the result to the world', i.e. those encoding and decoding perspectives (the internal methodologies contained within individual formal models are not being considered here). We can regard the first as qualitative and the second as quantitative.
|A \ Q||When||Where||Which||How||What||Whom||Why|
The actual meaning of the 49 'cell's is up for grabs (if it means anything useful at all!) but only along the diagonal do 'question' and 'answer' modes match, showing that the question has been correctly formulated. In a similar way, if we have analysed our questioning correctly and correctly applied the methodology, then the scope of 'question' and 'answer' should match. If they do not, in our 3-dimensional view of this (including a 'scope' axis), then either the answer is of narrower scope than the question, so disvaluing it (the results do not meet all our expectations) - i.e. the applicability is less useful and general than is really the case; or the scope of the answer proves wider than that of the question, so overvaluing it (the results are claimed to exceed our expectations) - i.e. the applicability is hyped as more useful and general than is really the case. We can illustrate this in a table, using Levels 1 to 4 to denote the scopes as we do in our Holarchic meta-ethics evaluations. The same matrix can be employed for all the possible WH questions:
|WH Answer\Question||Scientific Scope||Personal Scope||Humanistic Scope||Spiritual Scope|
|Scientific Scope||Matching Mode 1||Disvaluation 2 1||Disvaluation 3 1||Disvaluation 4 1|
|Personal Scope||Overvaluation 1 2||Matching Mode 2||Disvaluation 3 2||Disvaluation 4 2|
|Humanistic Scope||Overvaluation 1 3||Overvaluation 2 3||Matching Mode 3||Disvaluation 4 3|
|Spiritual Scope||Overvaluation 1 4||Overvaluation 2 4||Overvaluation 3 4||Matching Mode 4|
In some cases, probably rare, it may be that the answer formulation is correct for both disvaluational and overvaluational cases - here we will have used a wrong or inappropriate question scope but will have corrected ourselves somewhere along the way. We should mention also that although we have used labels such as Scientific, Personal, Humanistic and Spiritual for these scopes we do not imply that these are not more widely applicable, science can take a global, Level 4, perspective (we try to do so in our work), and as we know only too well religion often takes a dualist, Level 1, disvaluational stance ! The labels are just conventional ones to help focus the mind.
In most of our world, and especially within our educational systems, it is normal for questions to be asked individually, e.g. what is the speed of light ?; which gene is responsible ?; where is Iran ? This mimics the reductionism central to a dualist view of life often so obsessed by one-dimensional issues, and assumes that the formulation of the question is clear and unambiguous, i.e. that it is 'well-formed'. Yet one question often implies another, if we ask about a "when", then the event in question must also have a "where", the two cannot be considered in isolation, they both form part of the very definition of an 'event'. But even this will not do, some 'thing' or some 'process' must also be involved - there is a system, a "which", and the 'event' presumably concerns just one aspect of that system, a "what". And again, presumably, somebody is interested in answering the question, a "whom", and they have a method of doing so in mind, a "how", and the answer has value for them, a "why". Thus even a seemingly simple question requires at least implicit answers to all these WH questions, any question thus concerns a whole, it is 'holistic' by nature.
The implications of ignoring relevant questions in conventional methodologies should now be clear. By ignoring aspects of systems that are not 'in front of the mind', as it were, we effectively completely ignore all their consequences also, i.e. the effect of our decision, our answer or action on those other aspects of the system. Even if we get the single question of interest exactly right, and the result is 'positive' for that aspect, a collection of negative consequences involving other aspects (due the interconnectivity within the system) can easily negate all resultant gains - leaving our world worst off overall. Is that what we want, our 'success' causing other people's pain ? Taking such inherent connectivity into account is very much the province of complex systems thought, especially within the technical sub-field of multiobjective optimization. Here the 'epistasis' or knock-on effects on interdependent values are explicitly recognised, and we remain open to the overall picture and to the necessary synergy of balancing all the issues within our (often large) 'solution set'.
The division we made into 7 questions/answers is rather interesting, since in complexity theory (my subjective formulation anyway) there are also 7 levels of emergence easily visible, these are the physio-chemical (matter), the biological (life), the psychological (mind), the sociological (culture), the ecological (community), the planetary (global), and the universal (virtual). These are an adaptation/improvement of a scheme I've used in a recent paper. So in theory we could expand our scopes also to a 7, adding intermediaries related to animal biology, sub-cultures and overall environment. In other work we have subdivided the valuation categories into twos, as these can be said to apply differently to objects and to humans (that objective/subjective focus). We should note that science has had most of its success at lower levels e.g. physics and chemistry, which correspond to the simpler systems treatable from Level 1 methodologies, but as we go up the emergence hierarchy success diminishes. This is due to the disvaluation methodologies employed, where, due perhaps to 'physics envy', scientists try to force Level 1 thinking upon systems that really need Levels 2, 3 or 4, with all the negative consequences to other aspects that we mentioned above. Only recently has serious attention started to be given to holistic thinking, and to what this implies for our scientific methodologies and to the perceived need for a form of metascience.
If we are really keen on this 7 stage classification, then I also note in passing that in my own Metascience my HDE method also has a seven (values, goals, alternatives, hypotheses/laws, experiments, fitnesses, deductions - see later) which may (or may not) match up well with the following 7 stage dynamical set as used in my higher logic paper:
If we are to clarify the real world systems that we are modelling, and thereby derive a suitable questioning methodology for each of them, then we can identify the following 7 stage progression for any 'agent':
Value Need (for change in that value) Preference (ranking of alternatives) Belief (fulfilment theory) Action (environmental output) Reaction (feedback) Update (belief and need changes).
It will be noted that this is an essentially teleological approach, but despite many delusions about 'objectivity' in science that is precisely what real science is all about - 'scientists' are also 'agents' !
Considering how we approach the modelling of our world is analogous to outlining our 'gestalt', the set of patterns that we apply in our thinking - the 'figure' as compared to the 'ground'. The basic complexity gestalt (as with the earlier systems movement) is that reality consists of "elements in mutual interaction" which gives rise to emergent properties that are unavailable reductionally. And this is what the scope axis is all about (they are not aggregates here, an aggregate has no emergent properties). The general focus of our work is on dynamics, on evolution, on the trajectories of systems and how best to influence these. I'm not sure if the earlier 'systems' movement is happy with this (in discussion recently, one ISSS Sig.Chair was very against 'evolution' in any sense), but it's "in our blood" as complexity people I think. Each of the complexity specialisms could be regarded as having its own gestalt or methodology, which may (or may not) be a practical one. In more general terms the list of axioms I include in my Philosophy of Complexity introduction could be regarded as defining our overall gestalt. This can be augmented by the issues outlined on our Action page, in particular Senge's list and my additions.
All in all however the approach we take 'sees' far more than is generally considered in science, it adopts a metaposition or metaview in which all those conventional part views are seen to be present, but are now interrelated. What is new (perhaps), when compared to earlier 'holistic' viewpoints, is that the dynamics of the interconnected part views come to the fore, the holism, i.e. the overall system, emerges from these dynamics and we can transcend the usual dualism between whole and part typified by mind versus matter approaches (subjective versus objective).
Applying these sorts of views to our WH questions we can see that they too are part views and must all be combined to create a whole. But more than this, not only are there many occurrences within a complex system of any possible WH question (e.g. many "where"s or "when"s), but there are also many different levels to consider (our scopes), each relating to different forms of human behaviour. Ultimately which we choose to consider (and as they are infinite we simply cannot consider them all) will depend upon "why" we are questioning in the first place, and this is related to our values, i.e. our teleology or "final cause" (in Aristotle's terms). Thus ultimately we see that, indeed, "why" questions become the most fundamental ones in complexity science.
Given that we now understand the need for a less blinkered and reductionist approach to scientific questioning, then how do we proceed ? Transcending single valued views of the world, and encompassing all those multiple values (metaneeds) that make up the real human, requires a methodology that rises above those consciously adopted in both science and life. Neither area acknowledges the current need to take into account possible alternatives, full human goals, conflicting values or evolutionary consequences.
In our metascience we augment the normal hypothesis deductions experiment theory or 'law' methodology of the hypothetico-deductive method by adding an extra four evaluative stages relating to these missing aspects (which we call the HDE method). The four stages are:
This suggests that we augment our basic methodology by asking another 7 'gestalt' questions:
Does it need some of the traditional scientific assumptions, and if so can a reformulation widen its generality (perhaps moving an existing axiom to a local constraint instead) ? This question helps us to understand the contextual limitations that result from our normal thought processes and the possible benefits of relaxing them. It makes explicit the boundaries of the proposed theory and indicates whether it is a systemic theory applicable to all levels or is restricted to specific modalities or subjects.
Here we explicitly widen the search space, using the characteristic of this theory to help prompt our imagination to discover alternatives. We can also use the identified scope to formulate more general hypotheses applicable to wider areas of our reality. Here we look to identify the best formulation of our theory, the one with potentially the greatest effect.
Traditionally this could be pure knowledge, but we can ask what others needs are potentially affected and what knock-on effects this theory may have on other existing theories and views of life. This aspect asks about the value of the theory for humanity, i.e. what use it can be. Does it force changes in social and/or scientific norms ? Can we use it to question current assumptions and our wider expectations ?
How does it inter-relate to our current associations. Does it clarify any of our values, does it add any new ones ? Here we look to understand what practical effect the theory can have on our world view, in other words what additional fitness information it potentially supplies.
Does the theory increase positive-sum options and/or reduce negative sum ? Does it help us to generate new life options and if so are these positive or negative in overall effect ? This relates to how the various values created interconnect and compromise in producing an overall fitness evaluation.
Does it have a stabilising or destabilising influence on our society ? Does it help to unify matter, mind and spirit or separate them ? Does it reduce conflict, prejudice and specialisms or increase them ? This is the highest level holistic value, the global 'ought' and relates to a viewpoint that rates every level equally as contributing to universal fitness. This means that nature, society and individual must operate as one towards ends that meet all their fitness needs - this being assumed to result in the best overall result.
All of these questions emphasise the dynamical nature of reality and of the needs that we wish to satisfy, and is very much an evolutionary approach.
So, what do we conclude from our investigations ? Certainly we have found that questions cannot validly be treated in isolation, they all imply each other. We also find that ultimately "why" questions are the most important, and if we take the view that science is our most important form of knowledge then the neglect of such questions within science has serious consequences. But we have suggested that we can overcome such problems if we so choose. By considering the scope of our systems (which is related to the evolutionary emergence of different levels of reality) and by building into science what we can call 'reality checks' so avoiding the out-of-sight-out-of-mind "garbage in, garbage out" scenario, and by explicitly making evaluations of how all the separate aspects of our world (plus our associated questioning methodologies) interact, then we can better understand the bidirectional circularity of the understanding/action sequence, that ongoing dynamic relating 'qualitative' and 'quantitative' perspectives. Here we have suggested how complexity science concepts can help position our questioning towards this end, and have suggested some meta-questions that can provide such 'reality checks' and can help to generate more successful evolutionary trajectories towards that 'better world'.