Introduction to critical complexity

In the previous sections, some of the movements that have had an influence on the development of critical complexity were briefly schematised, albeit not chronologically. Although critical complexity shares significant similarities with these movements (including the use and understanding of much of the terminology), there are also several ideological differences between critical complexity and these movements. As such, this section commences with a summary of the major insights derived from these various movements, followed by a discussion of how critical complexity differs from restricted complexity and systems theory specifically.

110 4.1. Summary of the influences on critical complexity

Below follows a list of the most important insights that emerged from the preceding discussion on cybernetics, restricted complexity, and systems theory. These insights have had a significant impact on our understanding of generalised or critical complexity:

• In focusing attention on the principles of entropy, information, and feedback, first-order cybernetics influenced the development of critical complexity theory through placing the emphasis on the interactions between objects (regardless of their nature), rather than on the objects themselves.

• Self-reflexivity (which characterises second-order cybernetics) brought forth a shift from observed systems to the observers of systems, which has impacted on our understanding of our ability to know complex systems (psychological complexity). Maturana and Varela’s emphasis on autopoiesis has also influenced critical complexity theory, by drawing attention to questions regarding the relations between systems and the environment, as well as to the constitutive nature of systems.

• Third-order cybernetics (which focuses on artificial life) has significantly influenced critical complexity in introducing the concepts of self-organisation and emergence – both of which are central to any understanding of complex systems.

• The field of restricted complexity further developed the above ideas, and contributed to our understanding of complex systems through making important advances in terms of formalising and modelling complex systems.

• General systems theory – like cybernetics and restricted complexity – has provided important challenges to the mechanistic conception of the universe, and has greatly enriched our knowledge on the organisation of systems (as a set of elements standing in interaction amongst themselves and with the environment).

Despite the positive influence that the above movements have had on the development of critical complexity, critical complexity also differs in important respects from these movements. Below, follows a brief discussion of the most important differences between critical complexity versus restricted complexity and general systems theory.

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4.2. Critical complexity vs. restricted complexity: the problem of reductionism

In section 2.2., it was argued that restricted complexity or a Theory of Everything still remains within the epistemology of the classical sciences. In this paradigm, the explanatory principle is the principle of reduction, which is supported by the principle of disjunction (that consists in separating cognitive difficulties from one another) and the principle of universal determinism (that is, the idea that deterministic principles govern the course of cosmic events, past and future) (Morin, 2007: 5). Although it is conceded that the world is a complicated affair, within this paradigm the phenomenon of complexity (10) is never seriously questioned. This is because – following the syllogism mentioned in section 2.2. – it is believed that, with a lot of hard work and computational power, we can expose a set of simple rules that underlie complex systems. On this understanding, complexity is related to original simplicity (Rasch, 1991: 69) and one, therefore, ‘recognizes complexity by decomplexifying it’ (Morin, 2007: 10).

In order to further support this argument, consider Holland’s (1998: 24-26) approach to complexity, which is based on formal models consisting of ‘atomistic building blocks... whose interactions are determined by a set of formal production rules’. Holland views these models as descriptions of reality, although he also talks of rule-governed models. This, according to Cilliers (2000: 43), suggests that formal rules are fundamental to complex systems. Cilliers (43) criticises Holland’s view of complexity, arguing that something which can be fully-understood in terms of a set of rules, can at best be understood as complicated. As explained in the introduction, the term critical complexity (Cilliers, 2010a) or generalised complexity (Morin, 2007) takes account of the nature of complexity itself45, which characterises systems that are ‘the result of countless, local nonlinear, non-algorithmic, dynamic interactions, [which]... cannot be described completely in terms of a set of rules’ (Cilliers, 2000: 46).

In this context, non-linearity means that systems cannot be compressed without discounting some of the complexity. Any model of a complex system, will, therefore, exclude a degree of complexity (43). Furthermore, one cannot determine in advance the significance of that which has been omitted

45 _{This broader understanding of complexity – which takes seriously the implications of non-linear, emergent} behaviour – is not new: indeed Weaver (in Morin, 2007: 11) already stated in 1948 that whereas the 19th century was the century of disorganised complexity (which refers to the eruption of the second law of thermodynamics and its consequences for our understanding of entropy), the twentieth century must be the century of organised complexity (which refers to the idea that systems are inherently complex due to their organising processes). Similarly, the biologist, Robert Rosen (who described evolution in terms of a complexifying process), is another early theorist who supports the idea of organised complexity, and who identifies – and asserts himself against traditional science – which he describes as having the goal of resolving ‘a given system into a spectrum of subsystems, and to reconstruct the properties of the entire system from those of the subsystems into which it has resolved’ (Rosen, 1985: 322).

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from the model, because unlike linear phenomena (where the system is the additive result of its components), complex, nonlinear phenomena interact with the environment in intricate and complex ways, which results in novel and often surprising configurations of the system’s components. It is, therefore, not clear where the boundaries of the system are (Dyke & Dyke 2002: 72; Cilliers, 2000: 43). As such, Cilliers (46-47) is of the opinion that although we cannot avoid using rules, formal rule-based systems (such as described by Holland) cannot fully capture complexity. This point is supported by Rosen’s (1985: 424) work on ‘encodings’ (or representations/models), in which a system is defined as complex precisely ‘to the extent that it admits non-equivalent encodings; encodings which cannot be reduced to one another.’

Compounding the matter further, is the fact that complexity is also generated by the descriptions that we give to systems: in other words, complexity is generated by a reflexive mode of investigation, or ‘from the number of ways in which we are able to interact with a system’ (322). Therefore, following a reductive mode of investigation not only results in the negation of systemic complexity, but also obviates the difficulties associated with a process of observation. In this regard, Dyke (1988: 5) writes: ‘Not only are the phenomenon to be studied complex, but scientific practice itself is a phenomenon of organized complexity. The complexity of the investigation must be studied along with the complexities investigated.’ As such, the central insight to emerge from this discussion is that we need to account for the manner in which we generate models, as well as the status of these models (this point is elaborated upon in section 6.1).

4.3. Critical complexity vs. systems theory: the problem of holism

Morin (2008: 10) summarises the virtues of systems theory as: placing the notion of the system (construed not as an elementary discreet unity, but as a complex whole) at the centre of the theory; conceiving of the system in ‘ambiguous, ghostly’ terms, rather than real, formal terms; and, situating the study of systems at an interdisciplinary level, which allows for both the unity of science (under the general banner of systems theory) and the differentiation of sciences (according to the material nature of the objects under investigation, as well as the types and complexities of organisational phenomena). Despite these virtues, one finds that much of the work in this field is also characterised by the problem of reductionism. However, unlike the traditional scientific approach (in which the basic constituting elements are studied in order to gain knowledge of a composite (Morin, 2007: 5)), systems theorists tend to simplify and reduce the constituting elements to the composite. More specifically, systems theorists are often guilty of employing the principle of holism. Morin (1992: 372) offers the following description of holism:

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Holism is a partial, one-dimensional, and simplifying vision of the whole. It reduces all other systems-related ideas to the idea of the totality, whereas it should be a question of confluence. Holism thus arises from the paradigm of simplification (or reduction of the complex to a master-concept or master-category).

Instead of conceiving of systems in terms of a global unity, Morin (373) argues that we should view systems and their component parts in terms of a ‘unitas multiplex’ where ‘antagonistic terms are necessarily coupled’. The terms or parts remain antagonistic to the extent that they retain their own individual identities that cannot be reduced to one another or to the whole. At the same time, however, the coupling of the parts implies a common identity, which constitutes their citizenship in the system. In other words, the parts have a double-identity (373). Therefore, the ‘system is not only a composition of unity out of diversity, but also a composition of internal diversity out of unity’ (373). When thinking about systems, this double-identity needs to be accounted for, because – on the one hand – if we forego the diversity-principle, our thinking becomes increasingly homogenised (holism); and – on the other hand – if we forego the unity-principle, our ‘thinking becomes a mere catalogue and loses unity’ (373).

However, taking cognisance of this double-identity is not enough: Morin (374) states that we should also account for the complex character of these interrelations. This means not only respecting the age-old truism that ‘the whole is greater than the sum of the parts’, but also that ‘the whole is less than the sum of the parts’ (since some of the qualities of the parts are suppressed under the constraints that result from systems organisation); and, that ‘the whole is greater than the whole’. This last systemic feature is due to the dynamic organisation or emergence that takes place in systems where local interactions allow for global structure, which – in turn – feed back to constrain the behaviour of the parts through a process of downward causation (374) (see secs 5.2. & 6.2.). In summary: in contrast to reductionism and holism, critical complexity requires that one try to comprehend the relation between the whole and the parts. What is important here is the relation itself: knowledge of the whole is not enough, and knowledge of the parts is not enough. One must substitute the principle of reductionism with a principle that conceives of whole-part mutual interaction (Morin, 2007: 10).

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