Available via license: CC BY 4.0
Content may be subject to copyright.
A preview of the PDF is not available
A Note on the Difference Between Complicated and Complex Social Systems
Abstract
The distinction between complicated and complex systems is of immense importance, yet it is often overlooked. Decision-makers commonly mistake complex systems for simply complicated ones and look for solutions without realizing that ‘learning to dance’ with a complex system is definitely different from ‘solving’ the problems arising from it. The situation becomes even worse as far as modern social systems are concerned. This article analyzes the difference between complicated and complex systems to show that (1) what is at stake is a difference of type, not of degree; (2) the difference is based on two different ways of understanding systems, namely through decomposition into smaller parts and through functional analysis; (3) complex systems are the generic, normal case, while complicated systems are highly distinctive, special, and therefore rare.
... Given regional uncertainties of how climate will affect ecosystems, their complex adaptive nature and their management, for instance freshwater bodies (Vlieg & Zandvoort, 2013), governance entities cannot rely on predictive models alone for long-term planning, as such models 'often acknowledges an easing of uncertainty' (Foley et al., 2018, 227). This might very well lead to self-defeating policies since uncertainties might never be fully resolved, and furthermore, new uncertainties might emerge from the co-evolutionary path which is unfolding for complex adaptive SES (Haider et al., 2021;Poli, 2013;Preiser et al., 2018). While adaptive governance for ecosystem management already recognizes how multiscale, diverse actor networks create a capacity to respond to ecosystem change and new challenges (Schultz et al., 2015), this approach can be insufficient facing long-term, catastrophic change and remains reactive (Vlieg & Zandvoort, 2013). ...
... Considering them together, as an ensemble, and exploring the mutually reinforcing connections among these dimensions is particularly important'. Fuerth (2009) andPoli (2017) discuss the importance of an open-minded institutional culture within a governance system, hence of enabling institutional settings which can support ensemble-ization. Our results support the arguments of those authors by going a step further and demonstrating how low ensemble-ization created barriers to anticipatory governance in our case studies. ...
Climate change effects are already being felt around the globe, and governance systems need to adapt to this new reality to foster greater resilience in social–ecological systems (SES). Anticipatory governance is a concept proposed for such a purpose. However, its definition remains rather vague in the literature, as is its practical use for decision makers. In this paper, we contribute to filling these two shortcomings.
First, we conducted a systematic literature review of the concept and derived the following main criteria: foresight, networked engagement, integration and feedback. Second, we use the identified criteria to analyse two social–ecological systems around lakes in Lower Saxony, Germany and in Quebec, Canada.
In both cases, data were generated using a participatory approach (interviews and workshops) with local stakeholders. We examined these data, identifying opportunities and barriers to anticipatory governance. Our findings support, with empirical data for the first time, the claim in the literature that ensemble‐ization—the fact that all anticipatory governance criteria must be put forward jointly and not in isolation—is a facilitator for the emergence of anticipation.
Furthermore, by highlighting opportunities and barriers to anticipatory governance within two temperate lake SES cases, we illustrate how to understand a given system's limitations with respect to anticipatory governance, as well as how to engage with the concept through concrete, already existing opportunities. The proposed course of actions could help design more anticipatory governance systems to support decision‐making processes that could enhance SES resilience.
Read the free Plain Language Summary for this article on the Journal blog.
... Complicated systems, on the one hand, are closed; they are isolatable and therefore formally tractable. Complex systems, on the other hand, are open to their environment, including other complex systems; they are not formally tractable [11; pp.9-10] (see also [6,10]). Importantly, proponents of CCD further consider the difference between closed and open systemsi.e. between complicated and complex systemsto be one of type and not of degree. ...
... Preiser and Woermann [18] list various texts that "very convincingly" defend the idea that CCD is ontologically sharp. These include [10,11,[19][20][21][22] (see also [6; pp.5-7]). What these texts have in common, according to Preiser and Woermann, is that they dispel the notion that the distinction is superficial (i.e. ...
Several complexity theorists draw a sharp and ontologically robust distinction between (merely) complicated systems and (genuinely) complex systems. I argue that this distinction does not hold. Upon fine-grained analysis, ostensibly complicated systems turn out to be complex systems. The purported boundary between the complicated and the complex appears to be vague rather than sharp. Systems are complex by degrees.
... Every system is unique, and must be understood as an individual. Hence, all living systems, psychological systems, and social systems are defined as complex (Poli;. ...
... The distinction between a complicated system and a complex system lies in knowing what we can expect of the outcomes of the two systems. Whereas in complicated systems the problems can be (permanently) solved, in complex systems they can be modified but not solved, since intervention generates new problems (Poli;. Therefore, when dealing with complex systems, Meadows' advice is that the best approach is to 'learn dancing with them' 2009, p. 170). ...
As cultural heritage institutions, libraries and archives are responsible for managing collections in order to ensure access for present and future generations, and sustainable preservation. In pursuing these two goals, institutions face the challenge of determining to what extent preservation actions are beneficial in the context of their own collections. This project contributes to the complex decision-making processes of collections management by developing a mathematical model that shows, quantitatively, the effects of different preservation decisions during a collection’s lifetime. The novelty of this research lies in its approach to preservation management not as single, independent measures, but as a process that is part of a complex system: preservation management is not seen in isolation, but in relation to the other archival and library functions in the broader context of collections management. To meet this aim, complex systems modelling and simulation paradigms, such as system dynamics (SD) and agentbased modelling (ABM), are applied. Applying simulation to model preservation management decisions has the potential to develop into an integrated approach for evaluating and comparing the potential benefits of different preservation measures, which, so far, is lacking. This model will support collection keepers in the complex decision-making process of collection management by comparing different strategies, and therefore finding potential synergies as well as counter-intuitive decision outcomes which otherwise might not have been identified.
... Human understanding of the world we inhabit is both complex and complicated. Human logic and thinking based on seeking laws and principles in the natural world have come up short mainly because their review does not include or factor into the dynamics or the complexity of relationships between and among entities (Poli, 2013). ...
ABSTRACT
This dissertation presents an exploratory study of leadership dimensions using the theoretical lens of Complex Adaptive Systems (CAS) to evaluate the change challenges of the green energy transition. Adaptive Leadership principles are derived from Complexity Science and Leadership Theories and applied to Complex Adaptive Leadership Theory using a Complex Adaptive Systems framework. Complexity is a change process of simultaneous iterative cycles of adapting, coping, learning, surviving, and evolving consciousness. Complexity is a probabilistic existence of reality explained as the sense-making of the observer. Complex Adaptive Systems are a metaphor for this reality, allowing the observer to understand the nature of the complexity and the complex systems operating together and alone. Leadership encourages others in their personal development, stage development via adaptive challenges, and learning while evaluating competencies through occupational standards in the performance of their tasks.
This research design addresses deficiencies in the knowledge and understanding of leadership theories in the green energy transition by using a Complex Adaptive Systems framework. The Complex Adaptive Leadership Theory framework proposes that leadership dimensions are within iterative cycles measured through learnings and experiences. This theory situates leadership in complexity, becoming leading in complexity. The research question was: “Given a Complex Adaptive System, how could Complex Adaptive Leadership Theory apply to the green energy transition?” This study used the theoretical lens of Complex Adaptive Systems, allowing systems thinking applied to Complex Adaptive Leadership. This theory produces a better theoretical approach to resolving complex problems with its systems designs and sub-systems thinking in a proposed Complex Adaptive Systems Leadership Theory. The researcher interviewed a purposively selected sample of ten energy experts in Trinidad and Tobago using
2
qualitative inquiry as the research methodology. This research study may provide leadership guidance and real-world value to organizations operating in dynamic business environments of the green energy transition. Leadership judgment, decision-making, and choice were indicative of sense-making and thought processes in the green energy transition. The research study recommends leadership development for the green energy transition via three themes: Environment, Social, and Governance (ESG). The increasing complexity of the business environment requires leaders to be intellectual thought leaders who think differently, using adaptive and holistic decision-making patterns. The leader in thinking fast and slow (Kahneman, 2013) starts with a Complex Adaptive Systems Thinking approach to the complex problem to cause change and produce solutions. Creation occurs first in the mental world and then in the physical world. This study supports the Complex Adaptive Systems Leadership Theory to resolve complex issues. Leaders understand complexity as systems interacting with one another.
Key Words: Complexity, Complex Adaptive Leadership Theory, Complex Adaptive Systems, Leadership, and Green Energy Transition.
... Törnberg, , 2017. Exhibiting intertwined and mutually reinforcing properties of complex (possibility of functional analysis) and complicated (possibility of structural analysis) systems (Poli, 2013), WS are problematic for both mathematical and behavioral modeling, and neither discipline has yielded theoretical or methodological tools to address WS fully (Manhire, 2015). Besides climate change, other examples of WS are migration, development investment, ICT innovation, poverty management, crime management, genetic modification, and healthcare, among many of the most pressing, controversial, and persistent societal issues. ...
... Complicated systems, such as a car's gearbox, do not possess adaptive and interactive capabilities and, as a result, can be studied by decomposing their component parts. Complex system, because of higher order dependencies, are far less amenable to decomposition (Poli 2013). ...
Sustainability transition is not new for higher education. Universities around the world have discussed about the topic since the 1970s, publishing series of reports and declarations of intentions. These documents kept calling for transdisciplinary approaches and the implementation of Education for Sustainable Development competences. However, a few decades after, HEIs struggle with the operationalization of an educational vision on sustainable development into the practicality of a faculty program or curricula. This chapter calls the academic community to explore new learning contexts that facilitate moving to higher orders of learning that can sustain the integration sustainability approaches. Moving to deeper levels of learning means the transition from educating about sustainability towards educating for sustainability and the final destination: educating as sustainability.
Prima facie, we make successful decisions as we act on and intervene in the world day-today. Epistemologists are often concerned with whether rationality is involved in such decision-making practices, and, if so, to what degree. Some, particularly in the post-structuralist tradition, argue that successful decision-making occurs via an existential leap into the unknown rather than via any determinant or criterion such as rationality. I call this view radical voluntarism (RV). Proponents of RV include those who subscribe to a view they call Critical Complexity (CC). In this paper, I argue that CC presents a false dichotomy when it conceives of rationality in Cartesian-i.e. ideal and transcendental-terms, and then concludes that RV is the proper alternative. I then outline a pragmatist rationality informed by recent work in psychology on bounded rationality, ecological rationality, and specifically embodied rationality. Such a pragmatist rationality seems to be compatible with the tenets of post-structuralism, and can therefore replace RV in CC.
Anticipatory governance is a system of prescriptions explicitly addressing the interplay among complexity, acceleration, and policy. Specifically, anticipatory governance provides a way to use foresight, networks, feedback and hierarchical links for the purpose of reducing risk and increasing the capacity to respond to events at their initial stages of development. In order to deal with acceleration, organizations must acquire a much greater sensitivity to weak signals concerning alternative futures and learn to respond them with increased flexibility and speed. The idea of anticipatory governance is expounded against a network of concepts and tools, including the difference between strong and weak signals, anticipatory systems, regulation, resilience, and the Foresight Maturity Model.
Purpose
The purpose of this paper is to explain why finding a theory for futures studies is such a demanding task. In particular, the paper paves the way towards a theoretical framework that goes beyond both positivism and anti‐positivism.
Design/methodology/approach
The paper discusses a network of mutually interlinked concepts, including: levels of reality; parts and wholes; causation; the multiplicity of times; anticipation; the thick present; and latents.
Findings
The paper presents the two main obstructions blocking the way towards a theory for futures studies (namely, the belief that the opposition between positivists and anti‐positivists is exhaustive, and the need for better connections with other sciences such as biology, cognitive science and the social sciences.
Research limitations/implications
The paper discusses only one of the different threads in the elaboration of a theoretical basis for futures studies, namely the components closer to science.
Social implications
A proper theory for futures studies will contribute to making them more robust and efficient.
Originality/value
The general framework presented by the paper extends well beyond the somewhat restricted field of futures studies and includes social and psychological sciences, together with biology.
Ethics and futures studies interact in at least three ways: 1) through the values present within a foresight exercise; 2) through the understanding that values require the dimension of the future; 3) through the problem of the deontological code of the futurist. (1) and (3) characterise the work of the futurist; (2) instead proceeds in reverse: the need to address the question of the future arises from within ethics itself.
The paper introduces the idea of anticipatory systems, i.e. of systems that take their decisions in the present according to forecasts about something that may eventually happen. The best-known definition of anticipation is still Rosen's: “An anticipatory system is a system containing a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model's predictions pertaining to a later instant.”The most obvious mistake committed by almost everyone when first confronted with the idea of anticipation is to think that anticipation is a feature that we possess because we are such highly complex and wonderfully sophisticated cognitive agents. This is not what the theory of anticipation claims. Indeed, the major surprise embedded in the theory of anticipation is that anticipation is a widespread phenomenon present in and characterizing all types of realities.The paper presents some of Rosen's early works on anticipation and spells out in some details a few of its subtleties.
Purpose
After summarizing the theories of anticipation proposed over the past century, the paper aims to distinguish between anticipation as an empirical phenomenon and the conditions that make anticipation possible. The paper's first part seeks to show that many scholars from various research fields worked on the many nuances of anticipation. The paper's second part seeks to discuss the difference between the capacity of anticipation and the nature of systems able to exhibit anticipatory behavior. The former endeavor adopts a descriptive attitude, whilst the latter seeks to understand what it is that makes anticipation possible.
Design/methodology/approach
The paper presents a theoretical and experimental analysis of anticipation and anticipatory systems.
Findings
Anticipation is a widely studied phenomenon within a number of different disciplines, including biology and brain studies, cognitive and social sciences, engineering and artificial intelligence. There is a need for relying on at least two different levels of analysis, namely anticipation as an empirical phenomenon and the idea of an anticipatory system or the study of the internal structure that a system should possess so that it can behave in an anticipatory fashion.
Research limitations/implications
The literature summarized by the paper is only part of a substantially larger body of documents. More extensive analyses are needed to firmly establish the conclusions suggested.
Practical implications
The paper allows better understanding of the complexity of anticipation and the differences between types of anticipation (e.g. between explicit versus implicit anticipation).
Originality/value
For the first time, the distinction implicitly present in the surveyed literature between anticipation as an empirical phenomenon and the idea of anticipatory system as the study of the conditions that make anticipation possible is raised explicitly.
We propose a relational method to study impredicative systems, which are natural
systems that have models containing hierarchical cycles. The method is formulated in
category theory in terms of alternate descriptions and their functorial connections. This
general theory of impredicative systems has implications in the biological,
psychological, and social realms, from which we offer many exemplifications.