The fact that multiple, perhaps even conflicting conceptualizations of complex systems are inevitable (see Intro “Complex Systems” | Valonqua) challenges a basic assumption of many complexity researchers [for example, Cilliers 2010; Mitleton-Kelly 2003; Sporns 2007]. Namely, the assumption that a(n) (open-ended) list of general complexity features is applicable to complex systems on different scales and across various scientific disciplines.
Why is this assumption problematic? There are two main problems involved with this assumption:
Problem 1 – The essentialist relationship between the abstract and its concrete manifestations
When we assume that an abstract complex system consisting of some key characteristics (such as rich interactions, nonlinearity, unpredictability, etc) forms the basis of discipline-specific realizations of complex systems, we follow an essentialist conceptual strategy.
Essentialist often refers to the (traditional) attempt to determine stable identities (that is, the truth, the real meaning, or the essence of something). But, it can refer to the relationship between the transcendental conditions of possiblity of something (here: the features of an abstract complex system) and its empirical realizations (here: the concrete complex systems in the natural, technical, and social sciences), too.
Underlying the essentialist relationship between the transcendental and the empirical is a deterministic view. This means that the transcendental conditions of possibility are able to determine all their empirical (concrete) realizations. Consequently, new concrete phenomena aren´t really new, but just controlled variations of what is already known by the transcendental determinations.
This means further that the concrete realizations don´t affect the transcendental conditions of possibility. In short: The transcendental affects the empirical, but not vice versa – at least in a traditional perspective.
Such essentialist conceptual strategies [for more details see, for instance, Bormann 2012, 2003c; Hofstadter 1985] aren´t plausible any more and have been widely criticized since the 1950s. Instead, alternate non-essentialist strategies have been proposed. Examples:
- Ludwig Wittgenstein´s concept of family resemblance:
It argues that things which could be thought to be connected by one essential common feature may in fact be connected by a series of overlapping similarities, where no one feature is common to all. [Wikipedia 2016e]
This could mean in our context:
First, we have to deal with an open-ended series of complexity features which may be characteristic for some concrete complex systems, but not for others.
Second, we always compare concrete complex systems with each other, but not some abstract entity (the transcendental) with its concrete actualizations (the empirical phenomena).
Example: Instead of presupposing a proto-form (the essence) of character k, we only compare concrete variations of this character, as illustrated by the following figure from [Hofstadter 1985, 275]:
As you can see, these variations are similiar in some, but not in other regards. And there isn´t a single feature that is common to all variations of character k.
- Jacques Derrida´s open-ended series of interrelated quasi-transcendental infrastructures [see Gasché 1986] such as différance [Wikipedia 2016f] or itérabilité where the relationship between the transcendental and the empirical is intertwined.
That is: The transcendental underlies the empirical, but is, at the same time, affected by the latter. Therefore, this non-essentialist relationship becomes unstable, complex, and circular.
This means further: In such an open-ended series of quasi-transcendentalities (différance, itérabilité, etc.), we don´t have to deal with essentialist conditions of possiblity (simple origins, essences, etc.) any more. Rather, each of these non-concepts can play the role of an empirico-transcendental indecidability – in certain contexts [see Gasché 1986].
This could mean for complexity research: We can deconstruct some texts on complex systems and see if such empirico-transcendental indecidabilities emerge.
- Similar to Derrida´s deconstructive approach, sociological systems theory (Luhmann et al.) would give the (traditional) guiding distinction transcendental / empirical a selfreferential twist.
That is: Instead of assuming a simple and linear founding principle (here: the transcendental conditions of possibility), the distinction transcendental / empirical is interpreted as re-entering on either side of the distinction: transcendental (transcendental / empirical) or empirical (transcendental / empirical). And this leads to a similar empirico-transcendental indecidability (a paradox for observers using binary logic) as in the deconstructive case.
In more general terms: Paradoxes are the non-essentia-list (non-)beginnings of current universalist approaches. And these indecidabilities have to be unfolded by using various strategies of deparadoxation.
I´ll talk more about this subject in some of the subsequent blog posts on sociological systems theory.
- Another option is an equivalence functionalist approach, which uses the observational schema of problem and several solutions being functionally equivalent [see Knudsen 2011; Luhmann 1995]. This means:
If one wants to check the fruitfulness of generalizations, one must position the concepts used at the most general level of analysis, not as concepts describing possibilities but as concepts formulating problems. Thus general systems theory does not fix the essential features to be found in all systems. Instead, it is formulated in the language of problems and their solutions and at the same time makes clear that there can be different, functionally equivalent solutions for specific problems. Thus a functional abstraction is built into the abstraction of generic forms that guides comparison of different system types [Luhmann 1995, 15, my emphasis]
This is the non-essentialist strategy I´d like to follow when discussing the open-ended list of (key) features of complex systems.
To be more precise: If we connect this equivalence functionalist schema with a difference-based way of asking questions (What-questions are replaced by how-questions, that is: how – by means of which differences – is feature XY constituted?) then the list of key features (previously seen as essential) is transformed into a list of difference- and problem-based questions (see next blog post).
Problem 2 – The narrowing of the solution space
This means in our context that a specific solution is overgeneralized or represented as the only solution. Examples:
- A bottom-up perspective of system formation (that is, a system emerges from the interplay of its elements) seems to dominate in complexity, esp. complex adaptive systems (CAS) research. But, at least, for the emergence of social systems, a top-down perspective is plausible, too [see Luhmann 1995].
- Complex (adaptive) systems that are interpreted as open systems interacting with their environment [see, for instance, various authors in Allen / Maguire / McKelvey 2011; Cilliers 1998, 4; Wikipedia 2016g].
The problem isn´t simply that this perspective belongs to an older tradition of systems theoretical research. The problem is rather that there might be different solutions to the problem of openness / closure of a (complex) system:
– Within the same scientific domain: It depends on the ingenuity of the scientific observers to come up with plausible explanation mechanisms of how disciplin-specific complex systems might regulate their openness and closure.
– Between different scientific domains: Different complex systems (chemico-physical dissipative structures, biological cells, swarms of biological or artificial agents, human organizations, etc.) might have developed different solutions to the openness-closure-problem.
In short: There might be more than one mode of boundary (as system) maintenance for complex (adaptive) systems!
- Mechanisms for coordinating behavior and actions: Coordination mechanisms are necessary for evolved complex (adaptive) systems such as collections of cells, biological and artificial swarms, animal and human interactions, human organizations, etc.
But, it´s a mistake to believe that exchange- or transmission-based information models (esp. variations of the sender-receiver-model of communication) are the only relevant approaches in this context. These approaches are well suited for modeling technical communication processes (i.e., data and signal exchanges). They might be less suited for conceptualizing biological communication processes. And these technical approaches are probably not at all suited for the conceptualization of human communication [see Baecker 2013; Derrida 1971; Luhmann 1992a].
Again: For different types of complex systems, we have to expect various mechanisms that are able to solve the problem of behavioral coordination.
With these two problems at the back of our minds, we can formulate a(n open-ended) list of (complexity-features related) questions that are based on two perspectives:
- A perspective that focuses on which differences are used to conceptualize a feature XY (How-questions)
- The equivalence functionalist problem-solutions-schema mentioned above.
And this list of questions is the subject of the subsequent blog posts.
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[Mitleton-Kelly 2003] Mitleton-Kelly, E.(2003), Ten principles of complexity and enabling infrastructures, in: id. (ed.) Complex Systems and Evolutionary Perspectives on Organisations: the Application of Complexity Theory to Organisations, Oxford, UK: Elsevier, 3-20.
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[Wikipedia 2016e] Wikipedia (2016e), Family resemblance,
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[Wikipedia 2016f] – (2016f), Différance,
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[Wikipedia 2016g] – (2016g), Complex adaptive systems,
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