Sociocybernetics: Complexity, Autopoiesis, and Observation of Social Systems

When the opportunity arose to review this book, I
leapt at the chance. The title was inviting – relating to areas of
research that have held my attention for many years – in particular
the relevance of complexity and autopoiesis to social science.
Compiled from a selection of over 100 papers presented at the 1998
World Congress of Sociology, Montreal, this text brings together
examples of the application of second order cybernetics (the
cybernetics of observing systems) to the social sciences. According
to the authors, responding to the growing complexity of societies is
the major challenge that sociocybernetics is directed towards. In the
introduction, the editors argue that an explosion of points of social
differentiation and the development of technology and the knowledge
revolution present major challenges for the governability of society.
The theme of governability was therefore adopted to link the three
sections of the volume. These sections are Growing Societal
Complexity, Autopoiesis and Observation of Social
Systems. The aim of the first section is to establish and
describe the challenge or problematic, the second the theoretical
tools to tackle it and the final section to raise methodological
issues for the study of the phenomena of interest – complex social
interaction.

For those readers interested in social simulation
the book offers two opportunities. Firstly, the latter chapters
provide examples of approaches to simulation. Of these, the chapter
by Kluver and Smhmidt (chapter 11) addresses one of the more
challenging aspects of simulation work; how to define and specify the
relational dimensions of social actors in some space of interaction.
Chapter 12 by Dijkum, Lam and Ganzeboom provides an example that,
while interesting, pushes no boundaries in social modelling or
simulation method. The remaining chapters provide useful triggers to
thinking about alternative approaches to social modelling, covering a
range of conceptions within a wider systems discipline. In addition,
given the focus of sociocybernetics on second order phenomena, there
is a useful emphasis on the importance of the reflexive nature of
social organisation. This orientation is important as it is very easy
to conceive of simulations where the parameters are set by the
omnipotent system designer/researcher and far more difficult to close
them informationally – the equivalent of placing the observer inside
the system observed.

Some General Observations

In an earlier work Geyer traces the lineage of sociocybernetics to
General Systems Theory and first order cybernetics. He notes that the
advent of second order cybernetics represented a significant
transition, but the overall approach of sociocybernetics discussed
reveals that a broad net is cast and many diverse (and sometimes
inconsistent) systems concepts are appealed to. Geyer uses the term
cybernetics to include almost all systems theories, including
autopoiesis and complex systems approaches . Sociocybernetics therefore runs
the risk of suffering the same criticism earlier levelled at General
Systems Theory (GST) that it “…pays for its generality with a lack
of content.” (Jackson 2000). Similarly,
Checkland (1984, p. 93) cites Naughton
as suggesting that GST was a “…melange of insights, theorems,
tautologies and hunches…” Unfortunately this collection,
particularly some of the earlier contributions, suffers in just this
way.

I found the quality of the chapters quite varied.
Several contributions returned to debates that have haunted General
Systems since its inception – holism versus reductionism, naturalism
versus anti-naturalism, modernism versus postmodernism. These are
recurrent themes and as much as we might hope otherwise, they have
not yet been adequately laid to rest. The source of my frustration
was that, by and large, rather than developing and extending the
debate, the presentations simply echoed well established
dichotomies.

Despite the claim that sociocybernetics is founded
on second order concepts (and hence a constructivist epistemology)
the position within and between some contributions was inconsistent
with this claim. The contributors move curiously from modernist
assumptions to more post-modern ones and in some cases never quite
come to terms with the challenges many of the recent developments of
systems concepts (particularly complexity theory) pose to
cybernetics. Again, surprisingly, contributors take quite different
positions with respect to the ontological status of systems. Some
reify systems, others assert that they are distinctions made by
observers. Overall these more difficult aspects of systems approaches
are not consistently or well handled. It is accepted that this is a
collection of papers and so the offerings are made to stimulate
debate and cannot be expected to be consistent in all respects.
Nevertheless these are significant foundational issues and may point
to some underlying inconsistencies within the sub-discipline.

The theme of governability was a potentially
interesting one. It is relevant to contemporary debate about
post-Fordism in organisation science and disorganised capitalism and risk society in sociology.

The theme is however pursued only loosely and at times the thematic relevance
of contributions is not apparent. The issue of governability in the
context of systemic uncertainty is attracting considerable interest
within the wider systems sciences – in particular the recent rapid
development of complex systems theoretical positions applied to
sociology (see for example Eve et al.1997).

The approaches presented in this collection, however,
seldom stray far from a general systems/cybernetic framework and its
attendant focus on self-regulating/homeostatic systems. This may
suggest excessive adherence to a particular line of argument that may
hinder the development of valuable insights, at least with respect to
this chosen governability theme. Perhaps the choice of this theme
itself is evidence of a preoccupation with and pre-commitment to
predictability and understanding the order producing aspects of
social systems common to most social theory (Burrell and Morgan 1994) rather than the disordering processes.

The Contributions and Overall Themes

Given my personal interests, I found chapter 11
most interesting and it provided me with a good link to the remainder
of the content. Rather than address the content in a linear order,
chapter by chapter, and on the assumption that readers of JASSS would
have a similar interest in the content of this book as I, this
chapter is used as the entry point. It provides a way of structuring
my discussion of the perceived relevance of the overall book to the
simulation endeavour. I will return to the theme of governability
chosen by the editors at the end of the review.

In chapter 11 (Social Differentiation as the
unfolding of dimensions of social systems) Jurgen Kluver and Jorn
Schmidt address issues relevant to social simulation, and in
particular the challenges in modelling social relations
topologically. They note that there are many ways to define social
experience and hence of specifying the relational dimension of any
model. They propose an approach that draws principally on the theory
of social differentiation to define the fundamental dimensions and
thus to classify different social forms (family, tribe, class).
Accordingly they argue that a feature of social evolution is an
increase in this dimensionality. They conclude that modern societies
can be represented using three dimensions as they are horizontally
segmented (as with families), vertically differentiated (as with
class) and functionally differentiated (as with role). They contrast
this with earlier social forms, which they argue, have fewer
dimensions.

They note that dynamic modelling of such systems
is difficult, as social systems are adaptive. In particular they note
that the notional ‘rules’ governing interaction are under the control
of the system itself. An approach for dealing with this, they
suggest, is to approach social systems as sets of social actors whose
interactions are determined by specific rules, which generate the
system dynamics. The trajectories the system describes in its state
space are “nothing else than the intended and unintended consequences
of social actions.” Here then social behaviour can be modelled as a
consequence of both rational actions by individuals (acting in
response to the rules) and the product of complex organisation of the
system. This captures a concern of interest to complexity researchers
- the fact that interactions between the rational and structural
aspects of social systems have not hitherto been well dealt with.
McKelvey for example (1997, p. 7)
identifies four sources of order in the natural and social world,
these are:

• physical order: reducible to the four forces of field theory
• organic order: the result of natural selection
• rational order: rational actor decision effects
• complexity

He argues that order in social systems has tended
to be seen as originating exclusively from rational order.

Kluver and Schmidt further note that the reflexive
closure or capacity for social systems to self-organise and adapt
their response capability as a part of that self-organisation,
implies that such systems have not one set of rules of interaction
but at least two – the second set comprising meta rules “by which the
rules of interaction – the base rules – are changed…” As a
consequence of these capabilities and of defining them in this way
they argue that “social evolution occurs by varying, eliminating, and
enlarging social rules”. They consider these rules to be the ‘gene’
equivalents of social evolution. The authors briefly outline an
approach to modelling such a system using Cellular Automata to
represent the ‘real system’ or base rule interactions and a Genetic
Algorithm to provide the meta level capability.

This model generates some very interesting
behaviour. The authors argue that while the model is very simple,
there is a mapping between the behaviour generated and observations
of real social systems. These include the fact that more
differentiated social structures are more sensitive to perturbation
(less intrinsically stable) or, looked at another way, have greater
requisite variety and hence greater adaptive and survival capability.
They note, however, that getting to this state is “difficult and
rare”. They argue that “modern societies obviously have to pay for
their adaptive efficiency with permanent unrest”. Further they
observe that in their model, increasing dimensionality – increases in
social stratification (class) or functional differentiation (role) -
disrupts cohesion at other levels (e.g. family). Hence traditional
social forms are disrupted as society increasingly differentiates in
the other dimensions. Importantly they suggest that such
characteristics are an emergent property of intrinsic social
organisation and not the result of first order mechanisms such as
human nature (biology) or social interests (politics). They conclude
also that any search for fundamental rules (i.e. laws) of social
interaction as with natural science will necessarily fail as social
rules are constantly changed. However, they consider that the current
search for higher order descriptive mechanisms such as rules of
self-referentiality may prove more fruitful. Here there is an
implicit link to other work in the volume and in particular the work
of those concerned with autopoiesis.

There is a significant divergence of opinion about
whether social systems constitute third order autopoietic systems or
whether they are systems simply comprised of autopoietic unities.
Stafford Beer in the preface of Maturana and Varela’s

Autopoiesis and Cognition: The Realisation of the Living

(Maturana and Varela 1980), suggests that
they meet the relevant criteria for autopoiesis although in this
reference (originally written in 1973) the authors appeared unclear
or uncertain. Subsequently there has been a divergence of view, with
Varela (1981) firming his opposition to
treating social systems as autopoietic in and of themselves. Bednarz
(1988, p. 61) summarises the overall problem as follows:

“The attempt to extend autopoiesis to the social domain
has failed so far precisely because it has one foot in each camp. The
process of an autopoietic system cannot belong to one domain while
its components belong to another. But this is what occurs when social
systems are regarded as being composed of human beings.”

His conclusion is that if we are to resolve the
conceptual difficulty, we need to cease considering human beings as
the components of social systems and instead view social systems as
constituted by interrelations between humans. This leads to the
approach to social autopoiesis adopted by Luhmann and it is the
Luhmannian approach that is most commonly appealed to by contributors
to this volume. For Luhmann (1990), it is
the linguistic domain (communicative acts) which gives rise to social
relations and which in turn are constituted in and through the social
domain. This domain is dependent on the pre-existence of the
biological and becomes possible only when sufficient complexity is
available at the biological level consistent with Maturana and
Varela’s views on the emergence of language. The ‘meaning structures’
which arise from communicative acts are referentially closed and
self-producing. All non-communicational things and processes belong
to the environment. Note that what is pointed to here is a
functional closure rather than a physical one, a point
which has a bearing on the concept of boundedness that is central to
autopoiesis. Significantly, when it is a functionally defined unity
that is self-produced, the distinction between autopoietic and
simply viable seems to break down. In other words, all
functionally autonomous unities are, by definition, self-producing:
the categorical distinction collapses for this class of system. This
is what Varela (1981, p. 38) clearly
identifies when he says of social systems:

“Such units are autonomous but with an organisational
closure that is characterisable in terms of relations such as
instructions or linguistic agreement.”

It is for this reason also that Hejl (1984) distinguished between self-maintaining
systems and self-referential systems. Functionally autonomous unities
are abstract (observer defined), they can be approached as
self-referential but as they do not ’self-produce’ in a physical
domain they should not be regarded as autopoietic. Thus both Varela
and Hejl identify social systems as belonging to the broader class of
autonomous, operationally closed and self-organising/self-referential
systems but not as autopoietic. Further, if this argument holds the
concept of autopoiesis only offers new insight into systems that do
self-produce in a physical domain, i.e. biological systems as per the
genesis of the concept. In relation to other classes of system the
concept of operational closure and self-organisation are sufficient
and equivalent. Along with Robert Kay, I have argued elsewhere that
autopoiesis provides a foundation for understanding how human social
action is constrained by our intrinsic biological character (Goldspink and Kay 2002).

 

In chapter 6 (Information, meaning and communication: An autopoietic approach) Mingers further adds to the debate about the possibility for and legitimacy of social autopoiesis. This is a debate to which he has been a significant
contributor over some years (Mingers 1991 and 1995). In this chapter, Mingers
reaffirms his earlier concerns about treating social systems as
autopoietic but argues that the conception has some relevance because
it compels us to reconsider the role and nature of communication. In
this Mingers appears to be attempting to reconcile alternative
approaches to social autopoiesis. Despite pointing out that Luhmann’s
concept invokes quite different social agents (communicative acts
rather than people) he tries to work with this concept. This involves
him in working under two alternative (and in my view incompatible)
ontologies and leads to a presentation which I find somewhat less
clear and satisfying than much of his earlier work. Here his
attention is on the relationship between ‘information’ and ‘meaning’.
He begins by rearticulating a proposed typology of organisationally
closed or self-referential systems. This typology terminates at level
seven with a consideration of the relational characteristic of what
Mingers calls self-conscious systems or the ‘embodied individual’.
This distinguishes human agents and hence acts as a starting point
for the examination into social systems and communication that
follows. The main contribution of this chapter involves introducing
three additional levels of social organisational closure, The Social
Individual, Social Networks and Society/Organisations. These are
discussed in terms of their components, structural relations, mode of
closure and emergent properties.

Focusing on the first level (that of the individual) Mingers reinforces the argument presented by Maturana and Varela that information can only act as a trigger for any individual and hence cannot determine the state of their nervous system. He
introduces a distinction between ‘information’ and ‘meaning’ arguing
that a sign constitutes a “complex analogue stimulus” to the nervous
system which is then “progressively transformed through a process of
digitalisation” generating meaning for a particular individual. It is
not clear why the terms “analogue” and “digitalise” are introduced
here nor how they are to be interpreted – does the process of
digitalisation refer to the neurological process? Information,
Mingers argues, is ever present while “human consciousness only ever
exists in a domain of meaning”. This meaning is embodied i.e.
captured in the physical structures of the body and nervous system.
It does not exist as “pure thought”. While trying to stay clear of
the minefield of self-referential systems concepts, Mingers draws on
Luhmann’s concepts of society as communicative action to discuss the
social individual. This discussion is rather convoluted and in my
view this level is better dealt with, as Varela does, through the
studious avoidance of concepts of communication, information and
meaning. Invoking these concepts invariably leads to a potential for
confusion between the subject and object of the discussion. To
discuss ‘meaning’ in this context, for example, immediately risks
reification or leaves unclear who or what is making the attribution
of ‘meaning’ – meaningful for whom. It seems to me that Mingers does
not entirely succeed in disentangling these issues.

At level two – social networks – Mingers observes
that with recurrent interaction between individuals, structural
coupling occurs and there arises a circular co-determinacy between
the emergent structures of interaction and the structures of the
individuals which give rise to them through their networks of
interaction. Mingers makes the important observation that individuals
participate in many such networks and that these networks notionally
intersect in and through their common members. This is a theme dealt
with by Hejl earlier (1993) and as I have
argued elsewhere, has very important implications for thinking about
the dynamics of social systems (Goldspink 2000 and Goldspink and Kay 2002).
Mingers argues for attending to ‘membership’ determined by the
emotion of acceptance and rejection as a basis for the bounding of
social interaction.

The focus of this chapter is an important one,
trying to tease apart and understand the relationship between the
physical (biological) phenomena and the non-physical (emergent
social), and to deal with the linkages between levels of phenomena.
For me the treatment offered here is not ultimately successful or
lacks sufficient development and refinement to be convincing.

In chapter 5 (On the interpenetration of social
subsystems) Michael Rempel examines the social differentiation
theories of Parsons and Luhmann. Rempel opens by arguing that “In
general, deliberations in one institution [he gives the examples of
politics and law] seem increasingly to incorporate social and
technical influences rooted historically in others” (p 89). He argues
that there is therefore a need for a better theoretical approach that
deals with such interpenetration in the context of social
differentiation theory. This further develops the arguments about
interpenetration of social domains mentioned above. Rempel summarises
the difference between Parsons’ and Luhmann’s approach to
understanding structuration as follows: “Whereas Parsons defines a
social system to consist of socially structured actions, Luhmann
defines it to consist of conceptually structured meanings” (p. 91).
These two approaches (Rempel argues) have complementary weaknesses
and on this basis he proposes a synthesis of the two. The problem is
that the classificatory formalisms of both theories make it difficult
to examine the implications when agents of functionally
differentiated units increasingly participate in networks of
processes which are not functionally differentiated but rather which
bring together functional specialisation to produce outputs. The
proposed dual focus which analyses both action systems (as with
Parsons) and communication systems (as with Luhmann) will increase
the likelihood of appreciating processes of interpenetration in any
social structuration research.

In chapter 7 Lucio Biggiero asks Are Firms
Autopoietic? Biggero opens this chapter by noting that interest
in autopoiesis has been greatest outside biology (its field of
origin). He argues that the debate about autopoiesis has distracted
attention from the relevance of many of the underpinning cybernetic
concepts such as self-organisation and autonomy which lie at the core
of autopoiesis but are not restricted to application within it. This
again reflects the earlier observation by Hejl, that the concept of
autopoiesis and operational closure collapse when applied to
non-physical phenomena. Biggiero goes on to illustrate, drawing on a
diverse range of organisational theory, many areas that lead to a
need to question the legitimacy of seeing firms or organisations as
autopoietic. This is done, not as Mingers does in his earlier work,
by comparing the foundational concepts of autopoiesis with the
intrinsic nature of social systems, but rather by a looser comparison
between the implications of extant organisation theory and the
implications of a notional social autopoiesis. It serves to highlight
the contradictions and difficulties of reconciling autopoiesis with
most contemporary theory but is less effective than alternative
arguments at clearly disqualifying autopoiesis for such an
application.

Again, as with Mingers, Biggiero several times
notes the significance of social actors (i.e. people) belonging to
more than one social system at the same time. This suggests (he
argues) that social systems are not closed as suggested by the theory
of autopoiesis. He further argues that given that social systems are
not substantive (but are brought forth through acts of distinction)
their closure and boundaries are notional or matters of degree rather
than being absolute. He goes on to argue that second order
cybernetics furnishes the necessary analytical tools for dealing with
such systems and has no need for social autopoiesis.

In chapter 8 (The autopoiesis of social
systems: An Aristotelian interpretation) Colin Dougall further
contributes to the autopoiesis theme by engaging with the
controversial issue of social autopoiesis. Seeking a resolution he
proposes what he calls the M-A model as a basis for generalising the
concept of autopoiesis and disconnecting it from its biological roots
or tie to life. He notes that social models of autopoiesis commonly
fail “because social systems do not meet the formal requirements of
the theory”. Dougall usefully reconnects autopoiesis to related
ideas, both in contemporary sociology and earlier metaphysics. In so
doing he surfaces issues and weaknesses in alternative conceptions.
His M-A model is a more abstract rendering of the defining
characteristics of systems that are self-producing and is constructed
drawing on both Aristotlean and Maturanean influences. Dougall then
argues that Maturana and Varela’s biological theory is an instance of
this more abstract model and that what is sought by social scientists
is a derivative suited to social systems – a role the organic variant
cannot fill. He hints at the form such a model may take but does not
go on to describe the specific characteristics nor to compare it with
the organic except by way of the common root characteristics captured
in the M-A model.

In chapter 9 (Autopoiesis and governance:
Societal steering and control in democratic societies) John
Little discusses the relevance of autopoiesis concepts to the theme
of governability. He notes that we have increasingly had to confront
the limited efficacy of government as a basis for social control,
observing that “In complex networks governance is a matter of
autonomous self control and not top down steering from a central
position” (p. 160).

He expresses the opinion that as well as needing
to address the influence potential of government on society there is
growing concern about the influence potential of citizens over the
government which claims to represent them. In developing this theme
he explores the alternative implications of Luhmann’s theory and that
of Peter Hejl. Luhmann’s ideas, he concludes, lead to a pessimistic
prediction for the possibility of improved democratic governance. He
argues that this theory suggests that top down structural change will
not make administration more democratic. He argues further that as
complexity grows through, for example, greater social plurality,
governmental systems must respond by increasing their organisational
complexity thus further reducing the possibility for responsiveness
and control from and by citizens. By contrast, Little argues that
Hejl’s theory does suggest the possibility for influence over complex
systems and suggest that such influence requires an intimate
knowledge of system possibilities, and that this may best come from
within. This, he argues, is at odds with recent reforms influenced by
the so-called New Public Management (Pollitt
and Bouckaert 2000) or managerialism which, drawing on management
practices from commercial enterprises, tends to reduce citizens to
‘customers’ belonging to some general category rather than engaging
with them as individuals. He concludes by arguing that the
implication of adopting the perspective of either Hejl or Luhmann is
that small units of government interacting directly with citizens are
the best way forward.

Little suggests that Luhmann’s and Hejl’s
perspectives are potentially complementary focusing on different
levels of analysis (macro for Luhmann and micro for Hejl). This
micro-macro issue is taken up in chapter 4 by Robert Artigiani as he
discusses The emergence of societal information.

Artigiani reminds us that the modernist venture
was atomistic – attempting to reduce explanation of macro phenomena
to micro order. Here he begins to tap into the longstanding
micro-macro problem that bedevils social science (Coleman 1994 and Smith
1997). He argues that “to make progress towards answering Big
Questions, a new paradigm respecting the integrity of qualitatively
different levels of being is needed.” This seems to be an appeal to
move from a dichotomous ontology (real/not real) to one based on
levels (Broad 1925, Newman 1996, Emmeche et al. 1997 and Schroder 1998)
and recognising that emergent phenomena have ontological status. This
possible theme is not developed, however. Artigiani reveals that his
concern is not so much for the development of an explanatory
framework that can deal adequately with level transition but rather
but for emergent phenomena “to be treated according to rules
appropriate to their level of reality, rather than analysed in terms
of material atoms”. Sociology already arguably adopts this
(inadequate) solution to the micro-macro problem – positing
perspectives and concepts which describe some chosen behaviour but
failing to develop an adequate response for explaining how phenomena
at one level generate those at another.

Artigiani draws on Prigogine’s thinking and makes
appeals for insights from thermodynamics. This is somewhat
problematic as thermodynamic systems are a very limited class that
are closed with respect to energy transfer. Social systems are
manifestly not of this class. They can and have been argued to be
informational closed. Artigiani does not flag this distinction nor
address the implications of different forms of closure and this is
unfortunate, as it would seem fundamental to thinking about the basis
of and mechanisms for self-organisation in social systems. Drawing on
natural (thermodynamic) systems can at best be relevant as loose
metaphor.

According to Artigiani “In societies, human
behavioural choices depend on rules appropriate to their emergent
level of reality, and these rules are moral rather than biological”
(p. 79). These rules, he argues, are stored in the systems themselves
i.e. in the interrelationships between people. This idea is important
- that social structure captures ‘information’ relevant to social
viability and thus the survival of the individuals that comprise it.
There are some concerning aspects of his application of selectionist
ideas here however. The author argues thats selection “acts on social
systems” but the mechanism is unspecified. I found the handling of
these matters is too simplistic and not sufficiently based in a
knowledge of the other disciplines drawn on.

In chapter 2, Walter Buckley takes on the issue of
the relationship between mind and brain and sets out to establish a
A Dynamic Systems Model. This is another hot topic that is
relevant to the micro-macro theme. It is critical to developments in
AI and in computer simulation of social processes (
href=”#kennedy2001″>Kennedy and Eberhart 2001). In the
introduction to this chapter Buckley proposes to set out a model of
“mind brain interaction and the continuous real-time generation and
maintenance of consciousness and mental events in terms of the
organism-environment interaction.” He proposes to set out the main
features, provide some empirical evidence to support it and deal with
some of the philosophical issues. Essentially Buckley is arguing for
a view of mind as emergent phenomenon – a phenomenon that arises from
the dynamic between the nervous system and the environment.
Accordingly he argues against the value of locating mind in the brain
or rather of reductionist attempts to argue that the two are the
same. This is a reasonably well established line of argument and it
is surprising that the author does not locate his own position in the
context of others who have mounted the same or similar arguments.
Given the focus of the volume, Maturana and Varela’s constructivism
(Maturana and Varela 1980) and the more
recent enactive position of Varela

(Varela et al. 1991) spring immediately to mind. Also,
connectionist approaches to cognition link strongly to complex
systems approaches such as those of Paul Cilliers (
href=”#cilliers1998″>1998) and it would have been useful to see
these links established and explored. Buckley draws attention to the
tendency for many of his contemporaries to assign lesser ontological
status to dynamic processes and this insight could also be extended
to emergent processes which I am sure was his intention. These two
classes of process are not the same – the latter being phenomena of a
different logical type which results from non-linear interactions.
The former includes linear interactions and results in phenomena at
the same logical level (i.e. motion) albeit of a different class.

In the end the author recapitulates some of the
observations from recent neurological studies and discusses the
veracity of viewing mind as emergent. He notes that “it is not clear
why this is problematic for some since it seems intuitively
obvious…” The promise of a model is not forthcoming; rather there
is a wide-ranging and somewhat superficial recapitulation of
fragments of the argument for this perspective. The author often
seems to be ranging into the work of disciplines with which he is
only marginally familiar – drawing on reports that support his
general argument. It is unfortunate that he does not focus on
developing and articulating a model with some prospect for testing
and advancing the development of this approach rather than another
loose recapitulation of the need for it. The reason that there is
concern about viewing ‘mind’ as emergent is again that there is
inadequate treatment of how micro-level (neurological) activity gives
rise to the range and type of macro phenomena we may classify as
‘mind’. In other words, as with the micro-macro problem in social
theory generally, claiming something as emergent means that we can
describe it but not explain how it is generated from the interaction
of the micro agents which give rise to it. That said, the principal
conclusion is fair enough – Buckley asserts that adequate analysis
(of mind) must focus on the total system of organism and environment
as a complex and on-going dynamic whole.

Methodology

In the final chapter titled Towards a
methodology for the empirical testing of complex social cybernetic
models van der Zouwen and van Dijkum argue that social
applications of cybernetic systems methods have become more
sophisticated. As a consequence the complexity of the models has
become such that it has become increasingly difficult to test them
empirically. It is this that has led to a growing interest in
computer simulation as a means for exploring the behaviour of models
and as a basis for comparing that behaviour with real world
phenomena. In addressing the question of how researchers might
approach evaluation of complex sociocybernetic models they set out
what they argue are the defining characteristics of social
systems.

The working definition proposed is that a social
system is “a system in which actors, their actions and/or their
communications” form the elements. These elements interact and the
resulting system is separated from its environment by a boundary. My
first observation about this definition is that it hides a great deal
that is important. Real (biological) actors are very different types
of things than ‘actions’ or ‘communications’. The latter are
distinctions made by observers. In suggesting that a social system
can be comprised of one or more of these different types of things,
the definition simply papers over some of the most important debates
about the constitutive nature of social phenomena. Similarly, the
assertion of the necessary existence of a boundary leaves open or
fails to address the fundamental question – what form of boundary? As
Mingers argues in his critique of those who advocate social
autopoiesis, social system boundaries are observer relative and lack
the ontological standing of physical boundaries found in, for
example, biological autopoietic systems. Hejl also has had quite a
bit to say about this notion of boundedness in social systems.

Moving on from the base definition, van der Zouwen
and van Dijkum identify the first defining characteristics of social
systems as their ‘openness’. This reflects the longstanding assertion
of general systems theorists, that social systems are open. In this
context it is a remarkable assertion given that, in failing to
specify open with respect to what, they potentially take a line at
odds with autopoietic theory that is clearly embraced within
sociocybernetics. A defining characteristic of an autopoietic system
is its informational closure.

The second defining characteristic is that delays
in input/output transformation may occur. This they note is a source
of non-linearity. Strange then that the rapidly advancing field of
non-linear systems research, which has a great deal of relevance to
understanding how such systems may as a consequence behave is almost
entirely absent from all work presented in this book. This is further
evidence that many working in sociocybernetics are reluctant to
venture far from traditional cybernetic concepts. This is reflected
in the third defining characteristic – homeostatic/goal-seeking
behaviour. In asserting this defining characteristic, there is no
treatment of the important distinction between teleonomic and
teleological goal seeking. A failure to adequately distinguish
between whether implicit or explicit goal directedness is being
implied is all too common in social applications of systems theory
and is vital if the issue of the ‘observer’ is to be adequately
handled. The fourth characteristic is the possibility for positive
feedback loops and this is also noted as a source of non-linearity
but no reference to the wider implications of this assertion is
made.

The fifth characteristic is the presence of
reflexivity and anticipation via feed forward loops. This is a vital
aspect and its recognition is to be commended as it is arguably an
aspect of social systems inadequately dealt with by the models being
derived from complex systems approaches as well as those being used
by many simulations. Simulating the implications of reflexivity in
social agents is rare. The sixth and final characteristic is that of
‘goal adaptation and morphogenesis’ – the capacity of social systems
to change theory, goals and/or structure. There is not a great deal
of discussion of this characteristic but there is apparently implicit
acceptance of a definition of social systems as goal seeking systems
without again clarifying if this is teleonomic or teleological or
both. The observation (raised by autopoietic approaches and complex
systems theoretical approaches) that order may arise without any
explicit, rational or goal directed behaviour but as a consequence of
recurrent interaction is left unexplored. All in all a great deal
that is important is left unexamined both within the definition and
in setting out the defining characteristics.

There then ensues a discussion of the problems
with empirical validation for social hypotheses using the
hypothetico-deductive method. More usefully, the authors propose a
methodology (based on what they refer to as a sophisticated
interpretation of Popper’s falsification principle) for the
validation of models. Here it is argued that a useful approach to
model testing is to test two models against the real world data and
to establish which best explains the data. They argue further that
there is a need to consider and test for fit – i.e. where there is a
match between the real world data and that generated by the model and
the absence of falsifiers – i.e. states that would be forbidden given
the theory. Most of the subsequent elaboration is for the use of
linear models. Only brief account is taken of issues for non-linear
modes and this mainly involves observing that tests for such models
are in their infancy. This is true but not particularly helpful.
Given that two defining characteristics that the authors present are
potent sources of non-linearity and that a premise of the chapter is
that the greatest challenge to validation comes from increasing model
complexity, the development of methodologies which can deal with this
aspect of social system research are particularly important. The
theme has been developed elsewhere by McKelvey (
href=”#mckelvey1999″>McKelvey 1999) and by myself (
href=”#goldspink2002″>Goldspink 2002).

Chapter 10 (Implications of autopoiesis and
cognitive mapping for a methodology of comparative cross-cultural
research) by Bernd Hornung and Charo Hornung addresses the
possibility for cross-cultural social research. The authors briefly
discuss a range of conceptions that alternatively suggest the
impossibility of such research (due for example to cultural
relativism and the lack of a common grounding point) or the
suggestion that it should be feasible. The problem centres on the
possibility for ontological claims that are not culturally specific.
While they introduce concepts (including autopoiesis) which they
believe have some conceptual relevance to this topic, the nature of
the relevance is addressed only sketchily and it is unclear what
their central argument is. In some cases it is also unclear why the
concepts were introduced as few clear conclusions about their
relevance are drawn. In the end, they draw rather eclectically on
these alternative conceptions to propose a methodology for
cross-cultural research. This is unsatisfactory as it is not
presented as a synthesis and the inherent philosophical compatibility
issues between the approaches drawn on are not addressed. Their
proposed ‘hermeneutic circles’ are supposed to allow identification
of conceptual and functional equivalence between cultural contexts.
They argue quite reasonably that only once such equivalence has been
established can more conventional research methods be applied to
compare evidence from the two or more cultural contexts. Clearly they
have derived a general heuristic for attempting to isolate such
equivalence from a variety of systems related approaches. These may
form practical tools for any researcher wanting to work in
cross-cultural research. To call this heuristic a methodology seems,
however, to be going too far in that the conceptual tools drawn upon
(while derived from systems ideas) are not necessarily theoretically
compatible.

Chapter 12 by van Dijkum, Lam and Ganzeboom
provides an example of a simulation to investigate the dynamics of
educational expansion. Based on an assertion that very few aspects of
social evolution demonstrate pattern, with the exception of the
upward expansion of educational levels, the authors set out to
explain this phenomena. They suggest that existing arguments in which
educational expansion is driven by demand for more educated labour do
not stand up to critical scrutiny and posit an independent mechanism.
They argue that micro decision making (by rational actors) on grounds
of job competition and/or status seeking can explain the phenomena.
In this sense, educational expansion is an unintended consequence
rather than a direct effect. They present a simulation to model this
relationship and compare the results with data on actual expansion in
the Netherlands over the past century. The simulation uses first
order cybernetics concepts to model the relationships and dynamics.
The model comprises three sub-systems, a population sub-model, a
choice sub-model and an education sub-model.

This model provides a useful example of the way in
which simulation can be used for theory testing where there are good
sources of data for both calibration and testing. The model allows
for active experimentation, allowing modifications of the theory
derived rules to test their potential for explaining the real world
data. That said the model pushes no technical boundaries and doesn’t
serve to advance knowledge about the more challenging aspects of
social system modelling.

Governability

In chapter 1, Paris Arnopoulos sets out his
central thesis which is that some social control is “necessary,
possible and desirable”. He points in particular to the difficulties
of controlling natural and cultural systems given their intrinsic
complexity. He suggests as guiding principles the need to act
“humbly, carefully and responsibly”. Post modern sociocybernetic
strategies, he argues, are appropriate as they balance the
“libertarian and totalitarian extremes”. But this is about as far as
he goes with addressing this central issue. Instead of developing a
well-focused argument we are confronted with an eclectic
mélange – a string of bold assertions almost all of which
would warrant some defence but none of which are afforded one. The
issue of the desirability, necessity and possibility for social
control is not taken up with any rigour – indeed there is little
argument presented in any form on any topic. The author claims to
take a realist line, asserting natural and cultural systems as
‘isometric’. What ensues is an example of what Khalil and Boulding
(1996) call identificational slips -
associating or seeing as related, disparate phenomena on the grounds
of a superficial resemblance. In this case it takes the form of
suggesting a homologous relationship between a (long) list of natural
science concepts and social phenomena where even metaphorical
association would be stretching a point. Hence we have the suggestion
of ’sociomass’ and ’social inertia’ and later even ’socio-sclerosis’.
There is no attempt to justify the suggested homology or to argue for
it. The concepts spanned include those derived from various
positions, both Newtonian and complex systemic, with no recognition
that these may not be incremental developments but rather are founded
on incompatible assumptions. In short all grist to the
anti-naturalists mill.

Arnopoulos shows little awareness of the debates
and sensitivities of the many disciplines through whose which he
wanders. For example, he appears to take a progressionist position
about evolution on several occasions e.g. “man [sic] is the paragon
of animals and the highest stage of organic evolution.” There are few
references in the chapter – suggesting an ignorance of (or a
disregard for) the contributions of others – or perhaps a desire not
to be confused by the many competing and alternative arguments that
populate the areas where he so blithely strolls. Concepts and ideas
are thrown almost at random into a pot and stirred resulting in a
thick cloud of assertions. For example “Societies are complex
self-organising adaptive systems which value creation and
propagation. Since they are precariously balanced on the cosmos-chaos
boundary, autopoietic systems evolve by selection and mutation,
convergence and divergence. Thereby order can emerge spontaneously by
homeostatic convergence of various factors.” Well I am glad that’s
settled then! Although that ‘various factors’ looks a little under
specified.

It is not that there are no issues to be addressed
here and many interesting ideas are approached but unfortunately only
briefly and tangentially. For example, Arnopoulos points to the
problem of increasing global complexity (like Beck et al.
href=”#beck1994″>1994) remarking on the rapid increase in
transnational issues such as pollution and social dislocation and
observing that they are beyond the control of national policy. He
highlights global moves to establish frameworks of fundamental human
values that allow scope for local adaptation but provide a core set
of backdrop principles thus hinting at a possible response to the
problem. But on the whole opportunities for effective argument are
lost or passed up.

Heinrich W. Ahlemeyer approaches the issue of
governability from the perspective of organisations rather than wider
social systems. The author opens chapter 3 (Management by
complexity: Redundancy and variety in organisations) by noting
that complexity has generally been seen as a problem to be addressed
rather than as a potential solution. He sets himself the task of
looking at how organisations can use complexity. To accomplish this
he adopts an alternative focuses on organisational redundancy and
variety. The author takes a second order cybernetics perspective in
asserting that the complexity of systems rests on a distinction made
by an observer. He then outlines a set of criteria an observer may
use to make this distinction.

According to Ahlemeyer, when approaching an
organisation as a system, the observer notes that the system is
neither completely ordered or disordered but contains both redundancy
(order) and variety (disorder). Ahlemeyer observes that variety in
organisations “grows by increasing the range and heterogeneity of
decisions”. Here he draws primarily on Luhmann in positing social
systems as systems of communication. Hence the dimensionality
(heterogeneity) refers to communicative acts rather than individuals.
He further states that a system can be observed as complex “when it
contains more elements than can be connected completely”. This may be
a pragmatic definition rather than a technical one as it is not
consistent with definitions proposed by others. For example, Kauffman
(1993) describes systems where K=N (every
element is connected to every other) as maximally complex in his
experiments with Boolean networks. Using this definition, a
incompletely connected network is less complex than a completely
connected one with the same value of N. This problem may arise due to
a confusion between structural complexity (i.e. a constitutive
characteristic of the observed system) and the uncertainty associated
with incomplete information about the system on the part of the
observer. In other words the author may be arguing (consistent with
his stated epistemology) that an observer will perceive a system as
complex when he or she has an incomplete description of it. To say
something about the constitutive nature of such a system would be to
make ontological claims of a type with which Ahlemeyer may be
uncomfortable. He argues that “complexity enforces a selective
connection” and that “There is always a selection from a range of
possibilities and this selection is made by decision”. This suggests
that the constraint on governability is the bounded rationality of
the observer. Incompleteness and patchy connectivity arise as
managers make ‘boundedly rational’ choices in the face of a wide
range of possibilities and limited information that constrains their
capacity to choose. From this perspective Ahlemeyer seems to be
arguing that complexity arises from limits to rationality. This is a
very different position than that taken by many complexity
researchers who assert intrinsic unknowability as an aspect of
ontology rather than epistemology. Given the position that Ahlemeyer
takes one can ask whether complexity would cease to be complex from
the perspective of a hyper-rational being. If so this position is
suggestive of reductionism in disguise. It suggests that the universe
is in principal knowable and predictable. In other words this is a
restatement of the position that emergence is a product of limited
knowledge. (See Gilbert 1995 for a
discussion of this point.)

The author sums up as follows and raises some
interesting issues:

“If complexity enforces a decision by taking a selection,
organised social systems themselves are a solution of the problem of
complexity as both their existence and their elementary operations
are based on decision making. Only by drastically limiting the range
of alternative possibilities, can organisations come into existence.
Their continued operation demands the recursive production of
decisions with an ongoing reference to former decisions.”

This is an argument that organisations operate so
as to reduce complexity. This makes sense in that the patterns of
recurrent interactions which allow us to distinguish an organisation
are a reduction of complexity compared to completely unordered
interactions we may encounter with the same individuals in another
context – complexity is collapsed as behaviours become correlated.
The reduction is however internal i.e. experienced by those who
participate. This can also impact on the environment as systems with
which the organisation interacts are changed by the encounter. This
may disrupt the patterned dynamics of either or both or it may lead
to another order of coupling and hence complexity reduction. If the
coupling becomes too close (high co-adaptation) then as with over
evolved biological systems their vulnerability to contingency
increases – it can be absorbed only within limits. When such limits
are exceeded the contingent event may trigger failure of the
organisation. This is essentially the argument endorsing the need for
requisite variety, a debate that complexity research approaches in
the form of the edge of chaos argument (Bak
1996). With respect to most organisations, Ahlemeyer notes that
the market is the environment that tests the validity of the
complexity reduction choices (decisions). Markets involve
uncontrollable complexity from the perspective of the firm. The
approach to managing this complexity is to treat it as risk. The
strategies the author notes as having been adopted to increase
organisational complexity include the following:

• Structure: More small units with greater autonomy
• Hierarchy: Change in depth and function. The latter change is
  achieved by replacing the concept of hierarchy with leadership -
  based on negotiation and encouraging organisation members to be
  ’self-responsible’
• Teams: project based work
• Networks: virtual organisations

These are all consistent with the theoretical work
of Kauffman and Macready (1995) on the
need for ‘patching’ and link strongly to post-Fordist advocacy of the
need for greater organisational flexibility. As a check on the
advocacy of such change Ahlemeyer notes that “Many organisation
members – management and employees alike – feel overrun by rash and
radical changes. They feel they cannot cope and they feel rendered
superfluous. They are vulnerable and distraught; many have lost their
orientation.” In other words he cautions us to attend to the effects
of alternative approaches to achieving such changes in configuration
as they invariably create winners and losers.

Conclusion

While this book revisits many recent and long
standing themes in social research and there are some chapters which
make a useful offering, the overall reach of its contribution as a
whole is not great. There is certainly much more substantial and
deeper material readily available in the journal literature. The
convenience of combining several contributions in one book is
somewhat nullified by their variable quality. The book lacks a
well-integrated theme and the disparate (and often contradictory)
positions taken by contributors (along with some who fail to locate
themselves in the wider debate) limit the value of the collection to
anyone new to the area and wanting to gain a good overview. The lack
of depth and failure to push the boundaries or contribute significant
new thinking similarly limits the value of the book to established
researchers in these areas. It is therefore difficult to locate a
clear audience for it.

---

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