"As far as the laws of mathematics refer to reality, they are not certain;
and as far as they are certain, they do not refer to reality."Albert Einstein (1879-1955)
"Yet we also stress that truth is not the only aim of science.
We want more than mere truth:
what we look for is interesting truth...
what we look for are answers to our problems."Karl Popper, Conjectures and Refutations, 1963
Scientists, in their attempts to maintain a detached 'objectivity' have always rejected the consideration of subjects, of values, of teleology, of purpose. This bias has had the unfortunate effect of throwing out the baby of 'meaning' with the bathwaters of 'delusion' and 'irrationality' by trying to force a continuous complex reality into a straitjacket of disjoint either/or 'factual' categories. Under the misguided assumptions of Aristotelian logic, if the 'objective' is 'true' then the 'subjective' must be 'false' and thus to be avoided at all costs. The results of this has been blindness to much of our human reality and it has allowed emotional and holistic indifference by thinkers full scope to destroy the very structure of our planet and our lives as sensing, feeling and acting organisms. A world of detached 'things' has replaced, under a scientifically falsified philosophy, a reality of connected 'processes'.
To repair this long-running erroneous worldview we must first realise that science is about people - no people, no science. It is humans that generate all scientific theories, that categorise the world, that act on those theories. To deny science has values is to deny ourselves, a self-contradiction quite absurd in its repercussions within both our academic and economic structures. A fully 'objective' world is one without observers of any sort, thus one without any 'facts' or distinctions at all - we deceive ourselves to pretend otherwise. Whilst values are often defined in rather abstract terms, with the implication that they are homocentric and static, we can instead relate these more concretely to the dynamic needs of living creatures and to their conscious or subconscious beliefs. By so doing we can return meaning to our scientific world and better understand how the forms of knowledge generated by science relate to each other and to our behaviours. In order to do this we need a form of logic that can encompass knowledge, belief and values as well as truth, a type of reasoning that can deal with fuzzy inferences and uncertain conclusions.
Rather than starting with humans, let us instead follow the path of evolution and start with
that simple lifeform studied in high school biology. The first thing that strikes us
in seeing a live amoeba is that it is active, it is not a passive 'object' pushed around
by external Newtonian forces in the manner of physical rocks, but is a active agent that
responds to its world by making decisions, it decides to move following internal
drives that crucially allow different responses to exactly the same external stimulus. If it
is hungry it will move towards food, if threatened chemically it will move away. In
other words the creature has a subjective memory, internal states that give it cybernetic
'needs' for balance or homeostasis, desired value norms that the organism attempts to
reach by acting in ways that show biological purpose.
This purpose isn't a single dimensional one, even for such a simple animal. Many needs occur simultaneously and vary in strength over time. Some of these the creature can actively affect (e.g. searching for food), others (e.g. water) may be an inherent feature of its normal environment and prove necessary but contingent upon external factors (e.g. rainfall or evaporation). The level of complexity of such primal values increases as we move up the evolutionary 'ladder', multicellular animals and plants have extra needs, invertebrates and vertebrates still more (including now some social interactions) eventually reaching primates and humans who may develop higher abstract or immaterial needs (which must be regarded as causally effective) such as the 'need to know' - science itself.
Each of our senses gives us some information, but the distinctions we make in this massive stream of data are not arbitrary nor are they fixed, we are not 'screens' on which the camera of reality projects a picture. We select out of the continuous data stream relevant information. This is initially done instinctively (using genetic distinctions which have enabled us to survive as a species), followed by neurally (categorising the contents of our environment with experiential learning), finally as humans we abstract out generalities, detached internal ideas that enable us to induce and deduce future plans from historical memory of past experiences. These plans are not physical and objective (any artefacts of this sort are merely prosthetic extensions of our minds) but relate to our inherent needs, they are teleological, action plans that are intended to improve our lives in some way, to move us from our current position on the fitness landscape to a better one (or at least to avoid us falling to a lower state, by making us aware of poor or erroneous options). We select from the available 'possibilities' based upon trial and error reinforcements from past experience, i.e. by testing our theories. This is of course exactly what science is all about, thus our internal 'subjective' learning and our reasons to believe it are not only valid science but are identical to it ! Science is itself simply a 'consensus subjectivity' form of experience.
This idea that decisions relate to trajectories in state space means that we understand that knowledge gives us options, alternative behaviours that each have implied consequences (each 'fact' is an additional distinction or bifurcation in state space). Evaluating these consequences is inherent to science, we desire 'good' theories (a valuation !) by which we mean theories that 'work', that have positive-sum results. All of our knowledge is used to contribute to this end, we integrate whatever aspects of past data that can help us to meet the values we currently favour (even if academically these are limited to publishing scientific papers in prestigious journals !). But since so many of our values are held subconsciously this causes a problem, in understanding just which values we possess, which ones are implicitly active in any situation and which have been sidelined. Clearly to answer this question we must make these values explicit and justify our choice. Our best methodology for justification of our knowledge is science, and thus we must employ a metascience of values, transcending our prejudices against such concepts.
Breaking down the dualism between academic 'objective' science and technological 'subjective' application allows us to discard that ancient Greek attitude to life itself that sees it as problematical and messy, something to be ignored as far as possible in our intellectual pursuits. Allowing consciousness, values, teleology and, we must say, reality a full place in our science allows us instead to bring back honesty into what has degenerated into a nest of self-deceit and dogma. Once science is freed from these taboos perhaps we can use it to free the rest of our social behaviours from similar delusions and those unjustified ideologies that cause so much pain to people and planet.
To do this we ask ourselves three simple questions:
The first identifies just what we are trying to achieve, which unmet goals or values we have, which of our inherent needs as animals or humans we are trying to satisfy. The second asks what theories we have as to means, how we believe the world works (and critically now this includes ourselves), and what influences and interconnections are at work. The third relates these two, asking how our theories relate to our needs, which values are involved and how are these affected by acting on our beliefs. This latter step rejects the idea that knowledge can be divorced from its effect upon us and instead prioritises our theorising, allowing us to concentrate on issues that are of real importance to our values rather than assuming all knowledge (whether trivial or world-shattering) is of equal value - in a modern, more realistic view of humanity and our world, it is not. Quantity is not Quality, we must choose our studies carefully.
Scientists, despite occasional delusions to the contrary, never search for data per se, only for knowledge that has meaning to them, e.g. a count of the number of atoms within Mt. Everest has no meaning to a biologist, nor probably to a geologist. Facts are useless unless we can do something with them, and that means unless they have value for the scientist or others. What that value may be depends upon the number of potential uses, in other words upon how many different trajectories through state space that fact generates or affects. Thus the connectivity of the fact to other facts is crucial, since the greater this is then the more new paths become available. Thus we can quite easily prioritize factual searches, since the more needs that any desired knowledge affects then the more potentially worthwhile it is. To maximise the fitness value of knowledge therefore we should concentrate on facts which have the maximum pragmatic usefulness with respect to our total world needs, since ultimately this is the only criterion of importance from our human point of view.
It is strange then that, within academic research, grants concentrate on trivial projects and not those related to the major problems affecting our societies. Indeed, it seems evident that many academic researchers value abstract knowledge (e.g. theoretical physics) or personal financial gain (patents) far more than socially beneficial knowledge (e.g. saving human lives) and have managed to persuade the funding and control agencies also to adopt these skewed values (and they are values after all). Whilst there is certainly a place for speculative research, it must be said that the balance of needs targeted globally for urgent research exhibits some very odd biases. Most academic work could well be regarded as irrelevant in value terms ! Note that the status of 'objective' used to justify such a focus is itself a matter of persuasion, the result of a form of rhetoric used to sway public opinion in a certain direction (in just the same way that other groups promote their own prejudices). If I can persuade you that my subjective 'object' is exactly the same as yours, then philosophically it is just as possible to persuade you that my 'value' is the same as yours - the two cases are logically isomorphic, equally 'objective'. Validating belief requires only a willingness to question and to listen - those very qualities science is said to promote !
This issue of balance is a crucial one in maximising fitness. It is extraordinarily immoral to achieve knowledge, of say Pluto, if the cost is several million human deaths. Absurd ? Hardly ! At present some 30 million people die each year from neglect, because of lack of food and medicine. The world has no shortage of these things, yet we would rather finance a mission to the stars than use the same money to save those lives...why ? Now there is nothing wrong with astrophysics as such, this is just one example of so many in today's world, many equally bad, e.g. the greed of one man's profit destroying the livelihoods of billions of other lifeforms (in the destruction of rainforests by excessive logging). If there is a reason (beyond sheer selfishness) then it must come down to the sort of blinkered thinking typical of non-systemic worldviews, the idea that what I do in field A has no connection with what happens in field B. Nothing could be further from the truth, there are knock-on connectivity effects associated with everything we do, it is no longer an adequate defence to claim "I didn't do anything to harm them", you are guilty as charged if you "didn't do anything to help them..." ! From Asimov: "The First Law of Robotics: A robot must not injure a human being or, through inaction, allow a human being to come to harm" - is there any excuse for humans to behave less compassionately than robots ?
And here it is what humans actually do that is significant, i.e. the choices we collectively make from those many alternatives open to us. In the mythical 'objective' world of Newtonian science the observer has no effect on the world, they are detached outsiders. In the real world of human endeavour our teleological behaviours impact on the planet and our neighbours in endless ways, most of them unseen and negative in effect. As Dewey said (327):
"So long as we ignore this factor, its deeds will be largely evil, not because it is evil, but because, flourishing in the dark, it is without responsibility and without check"
Rather than treating the world as static, we need today to take account of these human initiated changes and how they relate to our behaviours and to the intrinsic value of our planetary support system (without which we all die...). Studies of the overall effects of such agent-driven societies and worlds are still at an early stage, but we can generate effective models of many such teleologically driven scenarios using computer simulations.
We can model a teleological entity in a quite simple way, although real life versions would be more complex in practice. In this picture we start with a set of needs which generate goals (e.g. hunger would generate the goal of eating). Our organism also has a number of internal states or memories and these include monitors of key needs (which are fed to the goal generator to activate or deactivate goals). The entity senses the environment and these possibility inputs are merged with the goals and internal states to generate a strategy for action based upon our beliefs as to the effectiveness of the available actions. This is a multidimensional arrangement, it would use the associative matrix (which in brains comprises our interconnected neurons) to settle on an attractor (one of many such states available) this then driving actions via whatever motor responses are available. For embodied organisms, this is however not enough, we must then monitor the results of our actions, using environmental feedback to refine our beliefs, discarding those that do not meet our needs whilst reinforcing those that do - thus improving our knowledge scientifically.
From the perspective of a science of values we should employ, in evaluating theories about ourselves and our needs, the same methods that we use to scientifically evaluate theories about the external world. Our behaviours or actions can be based upon six categories of belief:
The first corresponds to a scientifically tested procedure used within its bounds of validity. The second to a model used outside its valid area of competence (e.g. over generalised or used in conditions where the necessary constraints do not hold). The third to misuse of models, e.g. failure to understand the model or inability to apply it correctly. The fourth is due to an invalid belief in a model that has not been tested or has been incompetently tested. The fifth implies no reality checks at all, the untested (or untestable) assumption of correctness as in dogma. Finally the sixth relates to insanity or similar chaotic or inconsistent forms of belief.
What is required for any action is a correspondence between what is desired and what results. Note that only the first category displays the type of behaviour that we would regard as satisfactory in this sense. The next two lead to failure of our actions to achieve the desired effects, whilst the last three may occasionally and accidentally obtain the correct result, but in a way that almost certainly would lead to future failures. Note also that any theories held only 'objectively', i.e. in a way not leading to any testable human actions fit the fourth or fifth of our categories, divorcing a theory from meaning or value destroys it as a valid theory, it becomes mere noise (even the most determined rejecter of a link between fact and value must accept that their pet theories have inherent value for themselves). Knowledge is thus efficacious correspondence or correlation with 'reality'. Since this match between prediction and result is so crucial to success and to fitness we need to examine in more detail these six categories and what problems they can generate.
1. The Fallibility of Correct Predictions
Is the first type of scientifically valid model above the cause for absolute confidence, as seen in the infallibility claims of many traditional scientists ? There are a number of reasons that they are not. Firstly we never have absolute accuracy, all measurements are limited by the resolution of the instrument, hence good scientists always show 'error bands' for measurements. Future 'better' instruments may show the theory to be fallible (as proved to be the case for Newtonian Mechanics when compared to the more accurate Quantum Mechanics). Thus predictions are approximations at best, in this category all we can say is that our accuracy is adequate for our current needs. Secondly there may be many theories that fit the same facts equally well, we have no 'a priori' reason to think ours is the best or the only one. Thirdly the world is not static, it evolves. Thus a 'fact' or theory valid at one time may prove invalid at a later point (e.g. saying "The Empire State Building is the tallest building in New York" was once true, then it was false and perhaps it is now true again). The validity of our knowledge is always contextual.
2. Bounding Our Enthusiasm
The second category highlights some aspects of that over-enthusiastic extrapolation of scientific theories that we see so often today (irresponsible scientists can rarely resist ego trip excesses...). Each theory is about a limited aspect of our world. To obtain any such theory we must make some assumptions, i.e. apply boundary conditions or limitations that allow us to proceed. Firstly we must assume that all non-considered variables remain constant (the 'controlled' conditions underlying most scientific experiments). But when we apply the theory these 'theoretical' assumptions collapse, few 'real world' situations are as isolated as our models make them, so we apply the model with some risk. This risk escalates with the complexity of the system (the number of variables) and with the nonlinearity of the system (the interconnectedness of the variables). Secondly we must assume that all the cases to which we subsequently apply the theory are similar (homomorphic) to the test cases, i.e. they are effectively indistinguishable within the important parameters that the theory treats. This may be true for atoms, but is often not so for creatures or societies. This particularly applies where the systems in question have internal states or memory since even exact correspondence of external conditions still does not ensure correspondence of internal goals and a match to theory predictions (especially where theories completely ignore these goals !). How far the correspondences actually apply will vary with the intent of the theory and cannot be assumed 'a priori'.
3. Getting the Details Wrong
Humans are very good at making errors, far more efficient at this than any machine. Given a complex world, we need complex theories, thus our propensity for error grows. This is compounded the more people we involve and the more mathematical we make our theories (since people are generally poor at maths !). One of the most common errors in science however is the error of omission, this relates not to what we have in our theories but to what we leave out. This often takes the form of non-systemic assumptions, i.e. we neglect the weaker interconnections between aspects of our system. In linear systems this small error only leads to a small error in the result, thus the neglect of 'higher-order terms' can be justified. In complex system dynamics however the chaotic and nonlinear nature of many interactions means that this can prove problematical and even small omissions and miscalculations can invalidate the predictions of the model.
4. Non-Causal Prejudices
"I think, therefore I'm right" could be an epitaph for many humans. Our willingness to jump to conclusions based on the flimsiest evidence is legendary, as is our equally strong unwillingness to change our beliefs despite the most damning contradictory facts (politics and economics provide numerous examples). A little knowledge is truly a dangerous thing ! In these simple "off the top of my head" models we make arbitrary associations between external events and then induce generalities as if our theory was a proven fact. We do not attempt to verify such connections, often going from just one example to a belief in universality, e.g. if one 'black' commits a crime we assume therefore 'all blacks are criminals'. That such beliefs are incredibly easy to disprove seems not to matter, the facts are neither sought nor wanted. These sorts of prejudices, based upon invalid models and reasoning (or outright lies !) sadly litter human behaviour patterns...
5. Wish Fulfilment
Psychologically we are dreamers. We like to believe in things that appeal to us, that 'spark' our fancy (a value in itself !) whether fairies, alien abductions, Grand Unified Theories or Gods. We often generate, as a belief, the first thing that comes into our mind. It seems not to matter that we have no reason for adopting such beliefs, if we can imagine them then we seem to think that we can assume they are 'true' (a mode of thought strangely reminiscent of an old 'proof' of God that goes "if we can imagine a perfect being, then it must exist" !). These beliefs motivate and direct our lives in complex and sometimes very destructive ways, forming self-justifying worldviews or 'belief systems' that are often immune from contact with external reality and critical feedback altogether (being able to 'reinterpret' any and all data to fit the fantasy - in other words, the reverse of science, the facts are forced to fit the theory rather than vice-versa).
6. Stochastic Disruption
Despite our best efforts, the world is not a predictable place, it is far too complex for simple-minded humans to comprehend fully. Thus all our plans and schemes are susceptible to random and unpredictable events (e.g. earthquakes, computer crashes) that can disrupt our needs. Not least amongst these random perturbations are those irrational acts that emanate from deranged humans, those sudden rushes of blood to the brain under stress that explode in mindless violence and destructiveness. Additionally, in new situations, we have no basis for theories and thus need to try random guesses in the absence of anything better. It should be noted that until these are tested, and their effects are determined by feedback, then they have no higher status than any other fantasy.
Given the fallibility of our beliefs, as shown above, it is essential that we focus upon what their actual effects are upon our full range of values, and do not make the mistake of treating only single dimensions of value in isolation (due to their interdependencies). Understanding the validity of interactions is the province of reason and this is formalised by using logic. Most forms of logic relate to either/or truth values, and since we are dealing with continuous needs then this will not suffice. Whilst it may be possible to generate a formal logic which can encompass the full implications of interacting values, here we will concentrate more on relevant aspects of practical reasoning, the more informal ways in which we can bring values into rational focus. Hence we can regard our six categories in reverse order as successive approximations to 'truth' and consider how we can get from the last to the first.
Before we start it would be wise to highlight the difference between conscious reasoning and the unconscious sort that occurs most of the time. Let us assume that an adult has one million items of knowledge stored within their brain at any one time, these can be in the form of 'facts' (the isolated trivial pursuit variety), 'laws' (e.g. Newton's gravitation), 'beliefs' (e.g. Tom will phone me), 'needs' (e.g. I'm hungry), 'values' (e.g. I like the Beatles) or 'preferences' (e.g. better beef than beans). How many of these influences have a conscious effect in any situation ? Clearly very few, our conscious reasoning concerns a very small subset of our overall knowledge. Yet we still run our lives from minute to minute, taking account all the while of much of that hidden knowledge. Thus we must reason and make judgements subconsciously (e.g. when we drive on 'autopilot' whilst thinking of other things). This implies that if we are to understand our practical reasoning then we must also understand how our subconscious (or intuition ?) can make decisions (and often surprisingly wise ones) without our conscious knowledge, and if that is the case then what does consciousness add to this process ?
In general we can say that consciousness is employed where there is a problem, when our usual ways of doing things don't meet our situation or generate inconsistent actions. In these cases we abstract out from our vast knowledge base those elements comprising the difficulty. Conscious logic then attempts to resolve the problem and restore a rational understanding and a solution. This then can be 'rewritten' into the subconscious to be applied automatically to future cases of the same or similar situations. These clashes however need not be internal, we can identify clashes between the views of ourselves and another, or between two other groups or between entire cultures. Here we can use logic to 'referee' the situation, helping the parties to overcome their difficulties and to transform their 'thesis' and 'antithesis' into a new 'synthesis'. It may even be the case that we, as outsiders, need to point out that there is a difficulty - where the parties involved either do not recognise it or suppress the truth. This scenario is particularly prevalent where ideas are taken to be static and unquestionable (a fixed Platonic reality) whilst actually acting within our real, dynamically changing, world.
This need to criticise our existing theories is often overlooked, we tend to keep adding new rules and new theories to our systems of law and science, new 'fixes' to overcome small problems. Yet we neglect to check that the growing edifice is truly valid, and is not becoming a nest of 'Ptolemaic epicycles' concealing false (or at best inadequate) theories whose social cost far exceeds their benefits. This is especially the case where, as here, we need to look at overall systems of values, rather than artificially isolated subsets of reality or specialised academic fields. It is particularly important that when we evaluate our old ideas we discover the full knock-on effects on our wider webs of belief and value, and that we evaluate our automatic responses, those in-built (mindlessly followed) instincts, customs and norms, checking their validity in a more rational manner.
Let us now clarify the three logics we find associated with the three standard types of values. Firstly there are 'systemic' values, the values of existence or non-existence, of 'in' our system or 'out' of it. These can be treated adequately within the traditional Aristotelian two-valued logic of 100% true or 100% false. In this syllogistic tradition, isolated formal premises must be either true or false and the logic consists of reasoning how these fit together and how we can deduce new valid conclusions from their combinations (theoretical truths). This analyses existing facts to extract new knowledge from them, and is a timeless logic (hence 'objects' and 'facts' being regarded invalidly as unchanging). The second type of values relate to scientific measurements and are called 'extrinsic' values and these need a multivalued form of logic, of which fuzzy logic is the best known, which allows us to define states such as 70% true, i.e. partial truths - hence we evaluate the temporal truth values of the premises also. Here we generally consider one value or variable as a linear function of others, e.g. y = F(x) and the role of the logic is to enable us to induce valid functions that can relate variables in instrumental empirical ways (applied truths). This is a creative act, and increases the number of facts under consideration, i.e. it generates new premises, new hypotheses which operate in time. Before taking action we must determine past and current data, so that the formula can be correctly applied to achieve the desired result.
In our world of disjoint values this is as far as we have gone, yet a further type of value exists and this is called 'intrinsic' value. Here we need to relate all our values together, since this is an holistic valuation, and we find that in general this proves to be nonlinear (the values do not just 'add-up' but interfere with each other). Thus we need a corresponding logic that can determine the truth about such interconnecting values, in other words can help us to reason about complex systems of interacting knowledge, beliefs and needs (overall truths). This is an integrative act which brings together the two previous modes of logic, but it is also an emergent process which increases the number of values we have, generating new modes of synergic action. No current logic is fully adequate to treat this mode of value, which is generally approached by appeals to 'intuition' or 'wisdom', i.e. subconscious reasoning. This logic is one of future worlds, we need to analyse how the overall system will evolve, given the set of extrinsic actions proposed.
These three types of values can be related to three forms of judgement. In the first, typified by
plans and computer programming, we take a number of known facts and relate them in deductive ways, so that
a conclusion (the result) follows logically from the order of the steps as implemented. In this 'how to do it' mode there is no value clash, we either can achieve the result (logical truth) given the available
entities and connections (i.e. A AND B AND C...
D) or we cannot (logical falsity or NOT D), hence this is the systemic value mode. Our second mode requires a choice between two or more alternatives, where external resource availability precludes us implementing them all (i.e. (A OR B) but NOT(A AND B). This is an extrinsic (measurement) mode of value and requires a cost/benefit evaluation to determine the optimum choice given the limited means. It relates to fulfilling one need and leaving the others untouched, where all these needs are assumed independent (similar to choosing between different goods). The third type of judgement is an intrinsic value mode where theories are interdependent and falsify each other. It relates to incompatible internal ends, opposing alternatives (i.e. A NOT B ) where we must reject inconsistent data or theories, or alternatively
step up a level to a new emergent synthesis which can encompass both within a wider worldview. In these
scenarios it is usual for the implementation of one choice to have negative effects upon the
other(s), resulting in a dysergy (a loser), this we can relate also to the many conflicts in our world.
The extrinsic mode is sometimes called 'economic' (in the wider sense of including all types of resources and using then efficiently) and the intrinsic mode called 'ethical' (as in a higher form of 'moral' decision). Yet these labels are misleading, since the true distinction is between single disjoint values and multiple interacting ones. Often ethical and judicial theories treat only single simplified values considered in hypothetical isolation, whilst economics can treat multiple complex trade-offs, as in 'quality of life' discussions. It should be noted that these three modes overlap, and in complex processes what is an 'end' for a sub-process can become one of the 'means' for a later end, and a later 'unplanned' result can feedback and invalidate an earlier decision. There is therefore a continuum between sets of isolated 'value-free scientific facts' and sets of mutually exclusive and interdependent 'value systems' - our labels are, as ever, just abstractions.
The logical analysis of such judgements requires inferences. In the dynamic systems we consider here (our teleology implies changes over time) we need to consider an uncertain future, so we infer from what we know (the present) to what we desire (the future). Given our propensity for error in general reasoning (our common sense beliefs), our science generally restricts the scope of our systems to such an extent that our inferences then have adequate validity. Before we can apply these specialist results however to our wider world contexts, we need to judge their validity from a more comprehensive point of view - we need to put back all those aspects that science threw to one side whilst looking for its theory. Our specialist forms of philosophy are often unable (or unwilling) to help in this, so we need to extend our philosophical approach into an experimental mode which incorporates values and reasoning, along with empirical results, in a mode similar to scientific methodologies. Only then can we verify that what we believe (in our internal world) is actually justified by its overall fitness results.
In this viewpoint we recognise that the data we employ in conscious reasoning is only a narrow subset of the overall data on which we base our judgements, we include both our own subconscious and our common social framework (e.g. we pick up a pen to write but ignore the knife, matchbox and newspaper that also exist within our vision field - whose usefulness for our purpose we have automatically rejected). This selection process uses our background beliefs and the associations between our concepts to bias consciousness towards only those actions relevant to the fulfilment of our current needs. This 'subconscious reasoning' is not normally recognised, but clearly plays a large part in our valuations of complex situations and in affecting our moods and interests.
How are you feeling ? You would probably answer this question in general terms, e.g. "I'm fine" or "I feel terrible !". Such feelings are holistic states, they merge together all the various aspects of our being into one 'conclusion' result. Funnily enough, that is just what we want to do consciously here, if we are to logically decide how all our separate values merge together into an overall result ! Study of our subconscious is of course hard, but we do know that our brain comprises many sets of neuron groups extensively connected together by axons and dendrites. This associative network concept is what we model within neural networks and similar complex system specialisms. In these cases we know attractors form, so we can speculate that our overall state is also such an attractor. This relates also to our worldviews, which are also forms of attractor containing many interacting and mutually supportive concepts. As we change our views then we change our attractors and this implies an instability in our internal states strongly coupled with environment and context. As new facts and values arise, then new attractors do also, new modes of behaviour, new emotional understanding or intrinsic valuation.
It is well known how difficult it is for us to 'escape' our prejudices. This relates to escaping the 'basin of attraction' of our self-supporting worldview and generally needs novelty, a perturbation sufficiently strong to create a new mode, a jump to a new attractor. In our subconscious this happens automatically, our new experiences change the neural weights and connectivity within our brain and this naturally redefines the active attractors. This is however unpredictable, we cannot determine automatically if our modes of belief are well grounded and fitness creating rather than fitness reducing, i.e. whether these are truly applicable to our current situation (i.e. all laws, whether scientific, legal or moral, have limited validity within our wider contexts). This is a function of consciousness, where we can select out various aspects of our actions and establish on a rational basis their justification (if any), always looking to improve the logical consistency, scientific efficiency and humanitarian richness of our behaviours, if at all possible.
Only if we are unhappy with some aspects of our lives, with the standards that we currently employ, does the question of judgement arise. This means that we must be considering going beyond the static, beyond the status-quo, into new territory. Thus judgement is the evaluation of the unknown, an attempt to assess one or more new options with respect to the existing situation. Note that this judgement need not appraise a new behaviour, it may equally concern the cessation of an existing one (e.g. pollution), thus is equally applicable to both old and new - all that is necessary is a suspicion, perhaps generated by new scientific data or world awareness, that the current state of affairs is sub-optimal with respect to our set of values. And note that in a changing world this 'current state of affairs' is already different than that of the world upon which our standard behaviours were based, so this should automatically trigger a re-evaluation - rather than the retreat into dogma and denial by 'experts' that we so often see today (in all fields !).
Improvements in value and fitness are possible along many dimensions or axes. Yet in complex systems our judgements must concentrate on overall effects and not focus solely on one targeted value. We can see the problems of inappropriate focus in the effects of 'profit' (as the only value business takes seriously) on all our other social values e.g. trust, honesty, fairness and cooperation. A 'cheat' culture proves highly fitness reducing overall... Avoiding such childish greed is one reason at least for adopting a wider and more balanced focus. But there are other benefits, our current systems waste vast resources, and due to a process of self-deceit do not even meet their own economic objectives. Additionally, by judging fitness effects, rather than abstract theories, we can better focus our decision making, realising that devolved responsibility, rather than centralised control (either governmental or company), is far more effective at maximising personal and social fitnesses, which surely should be our aim ?
Let us look finally at using the six stages we previously identified in a positive way, in order to improve the match between our knowledge and our needs.
6. Guesses
This relates to the important step of generating alternatives, new ideas to start the ball rolling. It can be structured, as in 'brainstorming', subconscious (dream ideas) or more deliberate (combinatorics). All that is important is that we realise that vast numbers of alternatives always exist. Situations are never as cut and dried (either/or) as many of the academic 'test cases' suggest. From a systems perspective, new associations can lead to new levels of structure (emergence and synergy) and here encouraging cooperation between humans rather than conflicts is a key factor - as the old saying goes, "two heads are better than one".
5. Fantasies
This second stage relates to recognising our personal biases, our propensity to filter information into certain channels, to twist and reinterpret data to correspond to what we would prefer to believe. It is important that we understand ourselves, perhaps this is even more important than understanding either the physical world or our societies ? Our worldview acts to shape our every action in far more crucial ways than these other two influences, so it is vital that we get it right, and don't accept uncritically anything we are told, however 'expert' the source... Methods such as Critical Systems Heuristics can help here.
4. Prejudice
Here we need to understand the notion of statistical probability, the likelihood that a certain sample is representative of the whole. From one case only, we can only generate a vague expectation (especially if we do not know anything of the other options possible). This is of course better than nothing, so it is perfectly valid to generalise as a first step. But we must expect most such notions to be false, and always be on the look out for data that can help confirm or deny the theory. Remember that theories are not people, they have no intrinsic value, only an extrinsic usefulness, and if they are actually wrong then we want to know (however much we 'love' them) - otherwise they are fitness negating both for ourselves and society.
3. Oops...
Even with the best will in the world we all make mistakes, none of us are infallible or even come close. Failure to recognise this, and a psychological aversion to criticism and apology, leads us often to cling to ideas that to an outsider are absurd; especially when these ignore details that are clearly important in the context and need to be incorporated into our actions. In complex systems, many values are simultaneously active and we cannot afford to fixate on one dimension to the exclusion of all the others.
2. Forced Fits
Good ideas are intoxicating, they fire our imagination and that is a good thing. But we often try to force all situations to fit that idea (e.g. in Marxist or feminist 'explanations' of everything that happens). Whilst some of our ideas do have an influence on many issues, it would be quite incorrect to assume that such explanations are always true or always the main factor. Context matters greatly in complex systems, and the full situation must be understood if we are to validly generalise from specialist experiments to the 'real world'. This specifically means that we must understand the system dynamics, i.e. what happens when all the other variables are not held constant and can interact freely. Behaviours in these situations often prove to be counter-intuitive.
1. Approximations
Nothing ever works like it should, or at least not for long ! Over enthusiastic belief in the accuracy of 'bottom lines' has been the downfall of 'number worshippers' throughout history. Mathematics does not generate accuracy, the result can never be more accurate than the initial data. Thus all these academic 'results', to many places of decimals, are pure fantasy if they are based upon uncertain experiential data, i.e. 'estimates' of initial facts derived in the usual way. Errors here of 10% or more are common (100% or greater discrepancies are not unknown !) and in complex systems trajectories diverge quickly with much smaller errors than this. "Long term prediction is useless" as the Borg may have said... We must reassess all plans and conclusions frequently in a fast changing world !
This essay has looked at various forms of knowledge and error and at how science can be made to relate to our values and needs. We have found that searching for knowledge is a human enterprise and that divorcing 'facts' from our purposes as humans is a futile exercise, which harms both our own fitness and that of our planet. What we believe is crucial in determining how we behave, and it is our actions which will determine the state of our world in the future. To ensure that that world is a positive one, and not a disaster area, we must integrate our science completely with our values, changing our priorities to target the real problems and not mythical or abstract ones. We must hold scientists responsible not only for what they do, but also for what they fail to do, e.g. by shirking their collective responsibility for the misuse of science by the ignorant masses and their leaders."Nothing to do with us" just WILL NOT do !
Science is not 'value-free', scientists are not 'responsibility-free'. From our viewpoint, science if correctly applied (with appropriate priorities) leaves no excuse for the current state of our world and for the suffering of our people. What is lacking, as is so often the case, is not knowledge, not money, not manpower but willpower, the desire of humans to rise above that level of 'animals' which characterises perhaps the highest level of most corporate and political behaviour. The creativity of the Renaissance and the social progress of the Enlightenment needs to be complemented today by the wisdom of the Millennium. Those deceitful 'out of sight, out of mind' approaches to tricky problems and complex decisions so evident today must be reversed, and we must now embrace (with honesty) the full complexity of our world and its many interactions. After all, we already have the holarchic tools...