The Competitiveness of Nations in a Global Knowledge-Based Economy

F. E. Emery and E. L. Trist

Towards A Social Ecology:

Contextual Appreciation of the Future in the Present

Plenum, London, 1972 


Western Societies as the Leading Part

The Strategy of Overall Characterization

Placid, Clustered Environment

Disturbed Reactive Environment

The Turbulent Environment

 to Chapter 3

Chapter 4

The General Characteristics of Social Fields - Environmental Levels

Western Societies as the Leading Part

It was argued in the first section of this paper that the future will be largely shaped by the choices men make, or fail to make, and it will not be moulded simply by technical forces; it was argued that processes existing in the present can reveal some of the basic choices that will confront men over the next thirty years; and, finally, it was argued that social science should consider not only the provision of tools (trained personnel, institutions, theories and methods) but also the more active role of helping men to extend their visions.

On this basis I shall seek to identify current developments which are changing the conditions within which men can make their future, and shall look at these both in terms of the challenges they pose and the opportunities they create for further human development.  This should reveal the areas within which growth in social scientific knowledge and capabilities can most help men to help themselves.

Following the conceptual scheme outlined in chapter 2, I shall move from consideration of the broader social systems to narrower ones.  Following my own judgement, I shall start from consideration of the total social field of entities such as the U.K. and U.S.A. i.e., modern Western nations.  I am assuming that within the inclusive social field constituted by the world population these currently constitute the leading part.  The


method of approach will be basically that of trying to answer the two basic questions of system-field relation posed in chapter 2.

Next, I shall assume that the current leading part in such systems is the productive system - the complex of interrelated socio-technical organizations concerned with the social (not household  production of material goods and service.  For reasons given in chapter 3, I think that this method of proceeding is preferable to abstracting common phenotypical characteristic aspects such as the political beliefs or values.  The next step follows the same procedure of identifying the information and communication industries as the leading part of the productive system.  Because this last step puts us at two removed from the social field of modern Western nations I will then go back to see what effect this elaboration of the production system has on the total system.

Lastly, I shall touch upon the major boundary conditions of our primary unit.  These appear to be (a) the relation of the modern Western nations to the more inclusive international field, (b) the biological inputs of these social fields, and (c) the natural resources upon which they rely.

Throughout, the concern will be with matters on which the development of the social sciences might have a bearing.

The Strategy of Overall Characterization

As pointed out in chapter 2, if there are predictions to be made about complex systems they are most likely to be valid if they are derived from analysis of the genotypical characteristics of broader social fields.  This is, of course, only a theoretical point: we might have little or no information on which to assess the larger systems.  This is, in fact, the reason for starting with the more limited strategy of choosing the Western nations as the leading part, although it is evident that they are part of a larger social field.  Nevertheless, I do not wish to be like the drunk in the story who knew he had lost his watch up the dark alley but searched under the street lamp because there he had lots of light.  There is a body of evidence accumulating about the growth characteristics of the Western type of society.  This evidence is not of the sort that readily permits of graphical or mathematical extrapolation but it seems to permit of


genotypical analysis.  I will devote most attention to this analysis because it provides the framework within which more detailed predictions of part processes can be made.  A simplified version of this analysis has been published (Emery and Trist, 1965), but so much weight is being placed upon drawing inferences that the argument should be spelt out more fully.

In trying to characterize large complex social systems, I am reminded that some behaviours of both organisms and organizations are a function of gross overall characteristics of their environment (Chein, 1954).  We can advance our knowledge of these behaviours if we can identify the properties that best characterize the overall environment and the system behaviours necessary for adapting to them.

This is not a new strategy for the social sciences (see chapter 2).  Thus, in psychology the Lewinians were able to demonstrate the lawful behaviour of ‘human-beings-in-cognitively-unstructured-situations’ and of ‘human-beings-in-overlapping-situations’ (Barker, 1946).  A great deal of so-called learning theory is of the same kind, that is, the study of behaviour in overly simplified ‘conditioning’ situations, structured ‘meaningful’ situations, complexity structured or ‘problem’ situations, overly complex or ‘puzzle’ situations.  Similarly, Chein (1954) has pointed to the gain that may be had for psychology from the study of environments that in overall terms are relatively stimulating or stimulus lacking, relatively rich or poor in goals or noxiants, cues or goal paths, easy to move in or sticky, etc.

In the field of economic organization, a similar scientific strategy has yielded the characterization of markets as classical competitive, imperfectly competitive, oligopolic, monopolistic.  These again are attempts to define ideal types of overall environments and again have been relatively successful in showing the lawfulness of some of the behaviour of economic enterprises.

In the field of military organization, the great post-war disputes over optimum size of operating units, optimum weapon capabilities for size of unit, optimum organization of support facilities and command structures have all centred on the problem of the changes in the more general characteristics of the battlefield environment following the advent of tactical nuclear weapons.

The solution we sought appeared to be along these lines.  Therefore we concentrated on those dimensions of the


environment which constitute its causal texture (Emery and Trist, 1965).  By causal texture we meant, following Pepper, Tolman and Brunswick, the extent and manner in which the variables relevant to the constituent systems and their inter-relations are, independently of any particular system, causally related or interwoven with each other.

For simplicity of exposition we considered the relevant variables only as goal objects or noxiants for the constituent systems (i.e. having different relative values for the systems with the values ranging from positive to negative) and assumed that there is some sense in which these can be spoken of as more or less distant from or available to the organization and hence requiring more or less organizational effort to attain or avoid.  Already, it will be noted, something has to be known about the organization in order to delimit the environment in this way.  We have to know what is of potential value to it and what are possible courses of action.

For our purposes, we found it necessary to distinguish only four levels of organization of environments. 1


Placid Random Environment

The simplest form of environment is that in which goals and noxiants are distributed randomly and independent through the environment.  That is, a placid, random environment, placid because of heteronomous processes in the environment of the system. 2  This ideal corresponds to Simon’s ‘surface over which it (an organism) can locomote.  Most of the surface is perfectly

l. Any attempt to conceptualize a higher order of environmental complexity would probably involve us in notions similar to vortical processes.  We have not pursued this because we cannot conceive of adaptation occurring in such fields.  Edgar Allen Poe did go into this problem in his short story ‘Into the Vortex’.  He intuited that there was a survival tactic if drawn into a whirlpool - namely to emulate an inanimate object.  To strive in one’s own way was to perish.  Folklore and natural history are full of similar lessons about ‘playing possum’, ‘playing dead’.  For our purposes we are inclined to regard these as survival tactics rather than adaptive behaviour.  In case there may be something to the hunch that a type V environment has the dynamics of a vortex it is worthwhile noting that vortices develop at system boundaries when one system is moving or evolving very fast relative to the other - like a Watt County, L.A., and between the developed and underdeveloped countries.

2. We certainly do wish to convey the meanings associated, for example, with ‘placid tranquillity’.  An old-fashioned mad-house or a Nazi concentration camp could constitute the kind of environment we are defining.  Our choice of the term was largely dictated by our need for a contrast with the environmental disturbances that characterize some of the more textured environments.


bare, but at isolated, widely scattered points, there are little heaps of food’. ... ‘.. - the food heaps are distributed randomly’ (Simon, 1956, pp. 129-38).  It also corresponds to Ashby’s limiting case of ‘no connection between the environmental parts’ (1960, S,15/4); to Toda’s ‘Taros Crater’ (1962, p. 169); and Schutzenberger’s stochastic environment (1954, pp. 97-102).  The economists’ classical market comes close to this ideal environment.  Thus, although this represents an extreme type of environment, there has been wide recognition of the need to postulate it as a theoretical limit.  The relevance goes deeper than simply providing a theoretical bench-mark.  This low level of organization may frequently occur as the relevant environment for some secondary aspect of an organization and is also quite likely to occur in humanly designed environments for the reason that such simplified environments offer maximum probability of predicting and controlling human behaviour, e.g. Adler’s ‘Sociology of the Concentration Camps’ and the experimental environments of conditioning theory.

The survival of an organization in a placid random environment is a fairly simple function of the availability these environmental relevancies and the approach-avoidance tactics available to the system (I.e. its response capabilities).  So long as the environment retains this random character, it does not make much difference if there is more than one need and it is not necessary to postulate any complex organizational capacity for identifying marginal utilities or substitution criteria.  ‘We can go further, and assert that a primitive choice mechanism is adequate to take advantage of important economies, if they exist, which are derivable from the interdependence of the activities involved in satisfying the different needs’ (Simon, 1956, p. 134).  We can go even further and assert that in the absence of differences in relative value - the nearest goal object being the best - system behaviour in those environments does not involve choice.

Given that some environments with which we are concerned may be judged to be ‘random, placid’ in their causal texturing we may still be concerned with the effects of different degrees of randomness on survival.

An indication of the importance of these differences is given by Simon’s consideration of the effects of ‘range of vision’.


Increased range of vision in a random environment is equivalent to increasing the area of non-random environment immediately surrounding the system.  From the computations he makes for his very clean model of the random environment ‘... we see that the organism’s modest capacity to perform purposive acts (sic) over a short planning horizon permits it to survive easily in an environment where random behaviour would lead to rapid extinction.  A simple computation shows that its perceptual powers multiply by a factor of 880 the average speed with which it discovers food’ (Simon, 1956).

It is not enough just to characterize an environment and postulate minimum survival characteristics for systems in those environments.  Environment and system do not just co-exist side by side.  They interact to the point of mutual inter-penetration.  Some aspects of the environment become ‘internalized’ by the system and some aspects of the system become externalized to become features of the environment.  There are three modes of inter-relation that we will consider for each level of environment:

(1) instrumentality;

(2) planning;

(3) learning.

The first two are forms of interpenetration of the system into its environment.  What Trist and I labelled as L12 relations; where L11 relations represent potentially lawful processes within a system, L22 lawful processes within the environment and L21, L12 the influences from environment to system and system to environment, respectively (Emery and Trist, 1965).  The third mode, learning, may and, hopefully, usually does manifest itself in the use of instruments and planning.  However, I think we come closer to the core of meaning if we look at learning as an interpenetration of the environment into the system (i.e., as an L21 relation).  Viewed in this way the main concerns of learning theory should be with (a) the informational structure of different environments, (b) the kinds of behaviour in these environments that justify the title of ‘learning behaviour’.

Again we turn to Simon, this time for a good consideration of the relevance of instrumentality in placid, random environments.  This appears in his treatment of ‘storage capacity’.  Storage capacity is not a response capability but it


may be instrumental in extending or restricting response capabilities.  In an example dealing with organisms it is natural to think of storage capacity as intrinsic, like a stomach or fatty tissue, but in thinking about systems this is an irrelevant assumption - parts of the environment may just as readily be used by the system for storage purposes.  Simon found that storage capacity was a highly relevant parameter of survival although not as much so as reduction of randomness.  One would expect therefore to find that systems exposed to these environments would tend to hoard, and to find that this was adaptive.

The appropriate planning mode in this environment has been stated very precisely by Schutzenberger, namely that under this condition of random distribution there is no distinction between tactics and strategy, and ‘we find that the optimal strategy is just the simple tactic of attempting to do ones best on a purely local basis’ (Schutzenberger, 1954).  This aptly describes the marketing approach of successful traders in Petticoat Lane and other such flea-markets.  They do not know where their next mark (customer) is coming from and when he shows up their only concern is with closing the sale to their maximum advantage, without thought to subsequent consumer satisfaction.

Ashby has suggested that the best tactic in the circumstances can be learnt only on a trial and error basis and only for a particular class of local environmental variances (Ashby, 1960, p. 1 7).  I agree that the circumstances place peculiar restrictions on learning but not with the suggestion that the appropriate learning behaviour is trial-and-error.  The experimental environments in which trial-and-error has been observed to be adaptive have been complexly joined environments - puzzle situations for the organisms concerned (Thorndike, 1911, Hamilton, 1967).  The classical learning situation most closely corresponding to the placid, random environment is that devised by Pavlov and his followers.  In this situation sound-proofing, restrictive harness for the animal etc. are used to create a blank unvarying environment and the animal is exposed to random encounters (that is, random for the animal) with some goal objects and some other specific stimuli which are unrelated to the goal objects, except for co-occurrence in space and time (Pavlov, 1928).  It would be difficult to devise a


better reproduction of a random, placid environment.  The learning ‘behaviour’ observed is conditioning not trial-and-error.  Strictly speaking there is no behaviour involved as there is no element of goal-seeking, the system is just conditioned.  Theoretically the probability of survival should improve as the system is conditioned to take advantage of any departures from randomness in its environment.

A final point is that higher order systems must accept the degrading of their learning to simple conditioning, their strategies to simply following their noses etc., if they are to survive in these placid environments.  However, as Zener found with his dogs (Zener, 1937) and Alder found in reviewing human behaviour in concentration camps, higher order systems will strive to utilize any elements of non-randomness to create more order and permit themselves to perform closer to their level.


Placid Clustered Environment

More textured, but still essentially a placid environment is that which can be characterized in terms of clustering of the goals and noxiants.  The goals and noxiants occur together in space and time with varying probabilities that are potentially knowable for the system.  This level of environmental texturing was introduced by our discussion of the significance for placid random environments of any reduction of randomness.  It happens to be the kind of environment with which Tolman and Brunswick were concerned and corresponds to Ashby’s serial environment and the non-stochastic environment within which Schutzenberger could identify the minimal characteristics of goal-directed behaviour.

The structuring that exists at this level of texturing enables some parts of it to act as signs (local representatives) of other parts or as means-objects (manipulanda, paths) with respect to approaching or avoiding.  However, as Ashby has shown, survival is almost impossible if a system attempts to deal tactically with each environmental variance as it occurs or as it is signalled (signalling having the effect of multiplying greatly the density of confrontation) (1960, p. 199).  Survival in environments of this kind requires a second-order of feedback involving some sort of threshold mechanism so that reaction is evoked less


readily and only to the more general aspects of the environment - to the clustering which will reveal itself only through a manifold of particular occurrences.

This is the critical feature of adaptation to this kind of environment, namely that choice of strategies emerges as distinctively more adaptive than choice of tactics.  It no longer follows that ‘a bird in the hand is worth two in the bush’.  To pursue the goal object that it can see, the goal object with which it is immediately confronted, may lead the system into parts of the field which are fraught with unforeseen difficulties.  Similarly, avoiding a present difficulty may lead the system away from parts of the environment that are potentially rewarding.  Adaptation of these environments therefore requires as a minimum that a system be goal-directed (Sommerhoff, 1969) - that for each of a number of different concrete situations it has a course of action that is determined more by the goal it pursues than by the immediate presenting of goals and noxiants.

In this sort of environment, it becomes possible to seek a best strategy where optimality is limited only by restrictions upon knowledge.  Survival of a system becomes conditional upon its knowledge of its environment.  In the extreme case, if enough is known of the structure of the environment so that ‘the map’s projection has been changed to that of the really optimal matrix, the distinction between strategy and tactic (again) disappears’ (Schutzenberger, 1954).  This differs from the randomized environment in that here strategy tends to absorb tactics.  Given the omnipotence of a Laplace the tactics could be derivable from the strategy.

The objective of a system in this type of environment also has certain characteristics.  In the placid, random it could have none, apart from tactical improvement and hoarding against a rainy day.  In this second type the relevant objective is that of ‘optimal location’.  Given that the environment is non-randomly arranged, some positions can be discerned as potentially richer than others, and the survival probability will be critically dependent upon getting to those positions.  So much of management of organizations is concerned with planning, that it is worth considering some of the approximations that are appropriate in this type of environment:

(i) Domain selection.  The recognition of clustering itself so


that, at the level of strategic planning, one is concerned with relatively few clusters which can be approximately characterized as units instead of with a multitude of individual objects.  This lowers the cost of information gathering and processing;

(ii) the development of a hierarchy of strategies as in the rules for trouble-shooting in complex equipment; in this way the off-putting effects of the unexpected occurring may be buffered by modifying lower order strategies but retaining intact higher order ones.

(iii) the assignment of step functions to the values of goals and noxiants instead of trying to act on a continuous range of value; the average human being, for instance, tends to break a continuum into five steps (Jordan, 1968, p. 137).

(iv) the backward determination of the strategic path.  This is by far the least demanding procedure once the strategic objective is selected (Schutzenberger, 1954).  This, however, does require subsequent adjustments of the strategic objective to fit the available paths.

‘Planning by approximation’ may represent only that lowest level of planning which Ackoff calls ‘satisficing’ (Ackoff, 1970).  Nevertheless it represents what is possible and adaptive, given the information structure of a placid clustered environment.  By definition an environment is only of this type when the system is limited to information about the relative probabilities of co-occurrence of goals and noxiants.

Naturally the planning behaviour reflects the learning behaviour that is possible.  Systems are no longer limited to mere conditioning.  This was clearly demonstrated by Zener (1937) when he duplicated the classical conditioning experiments with one modification: he freed the dogs of much of the restraining harness so that they could react to textural characteristics of the experimental setting, other than just the conditioned and unconditioned stimuli.  The learning behaviour he observed, and filmed, was not conditioned behaviour but goal directed meaningful behaviour.  The major characteristics of this type of learning have been studied and formulated by Tolman:

(1) The organism brings to a problematic situation various


systematic modes of attack, based largely on prior experiences.

(2) The cognitive field is provisionally organized according to the hypotheses of the learner, the hypotheses that survive being those which best correspond with reality, that is, with the causal texture of the environment.  These hypotheses or expectancies are confirmed by successes in goal achievement.

(3) A clearly established cognitive structure is available for use under altered conditions, as when a frequently used path is blocked.

The third relation we have been considering, instrumentality, is also different in this environment.  In the placid random environment the instrumental relation seems to be limited to variety-reducing forms such as hoarding and hiding (reducing the effects of environmental variation in goals and noxiants respectively).  In the placid. clustered environment there is evidence that systems can use parts of the environment to increase the variety of courses of action open to them, i.e. to use them as tools.  The classical experimental demonstration of this is Kohler’s work with apes (Kohier, 1927).  As originally reported these studies suggested that the experimental situation presented such a richly textured environment for the apes that their successful learning to use tools must manifest a higher order than just meaningful learning.  It seemed that apes were capable of purposeful problem solving with the insights into causal structures that that implies.  However, the knowledge that has now accumulated about the innate response capabilities of apes makes it fairly certain that their tool using was in response to an environment which was for them only placid and clustered (Chance, 1960).


Disturbed Reactive Environment

The next distinguishable level of causal texturing is one that we have called the disturbed-reactive environment.  It approximates to Ashby’s ultrastable system and the economists’ oligopolic market.  In this we simply postulate a placid clustered environment in which there is more than one system of the same kind, and hence the environment that is relevant to the


survival of one is relevant to the survival of the other.  Formally, one could postulate a placid random environment with more than one system present, but I do not think that co-presence makes any difference to the concepts one needs to explain what differences in randomness would occur in that environment (which might be why the social sciences have such difficulties in linking up with so called reinforcement theories of learning).  Co-presence makes a real difference in a placid, clustered environment because the survival of the individual systems requires some strategy as well as tactics.  In this environment, each system does not simply have to take account of the other when they meet at random, but it has to consider that, what it knows about the environment can be known by another.  That part of the environment to which it wishes to move is probably, for the same reason, the part to which the other wants to move.  Knowing this, they will wish to improve their own chances to do likewise, but will know that they know this.  In a word, the presence of others will imbricate some of the causal strands in the environment.  The causal texture of the environment will, through the reactions of others, be partly determined by the intentions of the acting organization.  However, the environment at large still provides a relatively stable ground for the arenas of system conflict.  Because of this, conflicting systems ‘regarded as a unit, will form a whole which is ultrastable’ (Ashby, 1960, p. 209).

How can competing systems constitute a stable unit in a disturbed, reactive environment?  Given the relatively static nature of the environment within which the competition occurs, then it is possible (as it was for the individual organization in placid clustered environment) for strategies to evolve that limit the disruptive effects of competitive strategies or competitive tactics.  One would expect these strategies to be broader and take longer to emerge than those needed in a placid, clustered environment.  They would not, however, differ in principle.

By starting from consideration of the causal texture of the environment and the way information flows from this, we avoid the dilemma of the economists’ models of imperfect competition, duopoly etc.  As Ferguson and Pfoutts point out (1962), those models yield predictions of inherent instability


despite the observable fact that stability is commonly achieved.  Ferguson and Pfoutts show that stability can be deduced, however, if information flow and learning are taken into account.  By taking into account environmental properties, we find, as Simon found with the simplest environment, that we have less need to inject into our systems models (or models of man) a host of special ad hoc mechanisms, and we are less likely to come to false predictions.

One could maintain that this sort of disturbed reactive environment makes no difference to the distinction between strategy and tactics that we made for placid, clustered environments.  I am inclined to think that it does.  If strategy is selecting the ‘strategic objectives’ - where one wishes to be at a future time – and tactics is selecting an immediate action from one’s available repertoire then  there appears in these environment to be an intermediate level.  One has not simply to make sequential choices of actions (tactical decisions) such that each handles the immediate situation and yet they hang together by each bringing one closer to the strategic objective; instead one has to choose actions that will draw off the other organizations in order that one may proceed.  The new element is that of choosing not only your own best tactic, but also of choosing which of someone else’s tactics you wish to invoke.  Movement towards a strategic objective in these environments seems therefore to necessitate choice at an intermediate level - choice of an operation 3 of campaign in which are involved a planned series of tactical initiatives, predicted reactions by others and counteraction.  At this level the adoptive system is not just the one that can produce the right tactic for the right occasion (i.e. the goal directed system) but one that can choose the appropriate tactic.

If one tries to identify the level of system that is adaptive to disturbed reactive environments the critical criteria is that a system must be able, in at least some situations, to choose between two or more tactical moves either of which could further its ends, i.e. it must be a purposeful system.

There seems little doubt that even the formulation of strategic objectives is influenced by this kind of environment.  It is much less appropriate to define the objective in terms of

3. Cf. the use by German and Soviet military theorists of the three levels – tactics-operations-strategy


location in some relatively static and persisting environment.  It is much more necessary to define the objective in terms of developing the capacity or power needed to be ab1e to move more or less at will in the face of competitive challenge.  In business this would probably make it necessary to define objectives in terms of profitability, not profit.  This formulation has an advantage in this kind of environment, in that there can be a day-to-day feedback of information relevant to this objective.  In the former case, the day-to-day feedback about approach to a given location (e.g. percentage of market) may be extremely misleading.  It may conceal the fact that the competitor has made the going easy by conserving his strength for a later stage (e.g. preparing to introduce an improved product).

The factors in this kind of environment that make it desirable to formulate strategic objectives in power terms also give particular relevance to strategies of absorption and parasitism.  It is one thing in a placid random environment if other things can be characterized as goals or noxiants - they are either absorbed for the temporary sustenance they afford, or else avoided because noxious.  It is another thing in a disturbed, reactive environment when the other, itself a system, has to be absorbed or be absorbed into because it is potentially noxious - because it is a source of important but unpredictable variance.

So far, with respect to this level of environment, we have discussed neither learning nor instrumentality.  In our discussion of planning it seemed clear that the strategic objective of maximizing power dictates a corresponding mode of ‘planning for the best solution’ (what Ackoff calls ‘optimizing’ - to do as well as possible’, Ackoff, 1970).  We can now ask, what kind of learning behaviour in this environment enables a system to do this sort of planning?

The first part of the answer lies, as might be expected, in the changed informational structure of the environment.  A placid clustered environment yields only information of concomitance (probable co-occurrence of goals and of noxiants).  In a disturbed-reactive environment, with its independent causal agents, it becomes possible to distinguish between what is system action and environmental response and what is environmental pressure and system response.  In other words, it


becomes possible for a system to ‘learn’ the causal patterning of its environment.  One further step in learning seems critical in this environment.  Given that the other systems can also learn the underlying causal patterning, and direct their behaviour accordingly, it is necessary to learn the possible and probable recombinations of the causal pattern. This I suggest is the sort of learning that is involved in chess and other such genuine exercises in problem-solving (De Groot, 1965; Wertheimer, 1959).

As regards instrumentality, it is enough to note that the adaptive distinctions between strategy, operations and tactics enable a system to use parts of the environment to change other parts to the status of too1s: in other words, to act as tool makers.  There seems to be no inherent restriction in these environments to elaborating such tools to the point where they are fully adaptive to placid clustered environments.


The Turbulent Environment

The most complexly textured environments in which adaptive behaviour is possible, as distinct from sheer survival tactics, are ‘turbulent fields’.  These are environments in which there are dynamic processes arising from the field itself which create significant variances for the component systems.  Like the disturbed reactive and unlike the placid random and placid clustered, they are dynamic environments.  Unlike the disturbed reactive, we are postulating dynamic properties that arise not simply from the interaction of the systems, but also from the field itself.

There are undoubtedly important instances in which these dynamic field properties arise quite independently of the systems in the social field (as with some of the earth and water movements in mining).  However, in the conceptual series we are here elaborating, most significance attaches to the case where the dynamic field processes emerge as an unplanned consequence of the actions of the constituent systems; that is, those environments that represent a transformation disturbed reactive environments.  Fairly simple examples of this may be seen in fishing and lumbering where competitive strategies, based on an assumption that the environment is static, may, by over-fishing and over-cutting, set off disastrous dynamic


processes in the fish and plant populations with the consequent destruction of all the competing social systems.  We have recently become more aware of these processes through the intervention of the ecologists in problems of environmental pollution.  It is not difficult to see that even more complex dynamic processes are triggered off in human populations.

There are four trends that have particularly contributed to the emergence of these turbulent environments.  Before stating these, however, let me briefly state that these fields are so complex, so richly textured, that it is difficult to see how individual systems can, by their own efforts, successfully adapt to them.  Strategic planning and collusion can no more ensure stability in these turbulent fields than can tactics in the clustered and reactive environments.  If there are solutions, they lie elsewhere.

The four trends that have together contributed most to the emergence of dynamic field forces are:

(i) The growth, to meet disturbed reactive conditions of organizations and linked sets of organizations that are so large that their actions are persistent enough and strong enough to induce autochthonous processes in the environment (I am here postulating an effect similar to that of a company of soldiers marching in step over a bridge or the pulsating budgetary requirements of the U.S., Soviet military establishments).

(ii) The deepening interdependence between the economic and the other facets of the society.  The growing size and relative importance of the individual units not only creates interdependence within their economic environment; it also produces interdependence between what consumers want and what they think can be produced, between the citizen as consumer, as producer, as inhabitant, and as a social and political entity.  This greater interdependence, when matched with the independent increase in the power of other citizen roles means that economic organizations are increasingly enmeshed in public reaction and in legislation and public regulation of what they do or might think of doing.  The consequences that flow from the actions of organizations lead off in ways that are unpredictable.  In particular the emergence of active field forces (forces other than those stemming from the individual organizations or the similar organizations competing with it) means that the effects will not tend to fall off ‘with the square


of the distance from the source’ but may at any point be amplified or attenuated beyond all expectation. As a case in point, thalidomide as a simple cure for morning sickness created a major crisis for the international pharmaceutical industry and initiated a radical redefinition of responsibilities in one of the relations between science and the society.  Similarly, lines of action that are strongly pursued may find themselves unexpectedly attenuated by emergent field forces, e.g. the U.S. ‘War against Poverty’.

For organizations, these changes mean primarily a gross increase in their area of relevant uncertainty.

(iii) The increasing reliance upon scientific research and development to achieve the capacity to meet competitive challenge (which capacity, we suggested, tends to become the strategic objective in disturbed reactive environments).  This has the effect not only of increasing the rate of change, but of deepening the interdependence between organizations and their environments.  Choices that once appeared to arise from the marketplace are now seen as being taken by the organization on behalf of the customer - they are seen as manipulators of desire or, as with thalidomide, sorcerers’ apprentices.  It is not hard to imagine an organization finishing up in the dock of public opinion because it chose a line of technical development that appeared to suit its own needs but eventually left the economy in the lurch.  The same trend appears in fields of public policy-making where competition over the allocation of resources is increasingly conducted by means of scientific research and analysis.

(iv) The radical increase in the speed, scope and capacity of intra-species communication.  Telegraph, telephone, radio, radar, television, gramophone, typewriter, linotype, camera, duplicator, Xerox, calculator, Hollerith, computer: these names register a century of change that continues in an explosive fashion.  Parallel with these has been a very great increase in speed and ease of travel, so that recorded communications flow in greater bulk at greater speed, and even the recording of communications becomes short circuited as it becomes easier for managers, scientists and politicians etc. to fly to each other than to correspond. We may recall that Trotter (1916) in searching for the conditions underlying social reactivity in living populations, postulated only two critical conditions: (a) some


special sensitivity to their own kind; (b) some intra-species communication system.  The change that has taken place in intra-species communication is a greater mutation than if man had grown a second head.  The consequences are a great increase in the information burden and a radical reduction in response time in the system - a reduction which is unaffected by distance.  Reaction takes place almost before action is formed.  Even simple servo-systems with these properties readily get entangled in erratic ‘hunting’ behaviours.  As the information burden approaches ‘overload’ it invites, in fact demands, radical counter-measures which tend to be maladaptive and increasingly unpredictable.

We will probably find that these trends are only part of the picture.  However, they are in themselves real enough and may explain why we feel that consideration of the turbulent fields is a matter of central importance and not just a theoretical exercise.

What is less clear is how our society can adapt to these conditions.  Ashby very wisely counsels that there may not be a solution to this problem:

As the system is made larger (and is richly joined), so does the time of adaptation tend to increase beyond all bounds of what is practical; in other words, the ultrastable system probably fails.  But this failure does not discredit the ultrastable system, as a model of the brain for such an environment is one that is also likely to defeat the living brain (1960, p.207).

However, as a biologist, Ashby offers us the consolation that: ‘Examples of environments that are both rich, large and richly connected are not common, for our terrestrial environment is widely characterized by being highly subdivided’ (1960, p. 205).  It is my belief that this sort of environment is, in fact, characteristic of the human condition: that in some areas of his living man has always had to contend with turbulent environments.  What is true is that just as the central matching process of consciousness has evolved to help protect the human organisms from information overload (Tomkins, Vol.11, p. 14), so has man evolved his symbolic cultures to provide a man-made environment of tolerable complexity.  What is significant of our present era is the emergence of a degree of social organizational complexity and a rate of coalescence of previously segregated populations that


defy our current efforts at symbolic reductionism.  Larger and larger parts of the lives of more and more people are being lived in conditions of environmental turbulence.