By Jean Boulton
What are the key ideas that define the science of complexity? How do they help us better understand our world so that we can engage more effectively?
The science of complexity conveys a view of the world as dynamic, richly interdependent and full of variety.
“A world – organic and emergent, shaped by history and context – naturally patterned, yet always in process” (Boulton 2024: 39).
Ilya Prigogine asked why classical physics and evolutionary biology seem to contradict each other. The word that brought these two sciences together and shaped the development of complexity theory, was ‘open’ (Prigogine 1977).
Situations that are open to their environments display emerging order in the form of patterns of relationships. For evolutionary processes at every level – from galaxies to amoeba – this ability to suck fuel from their surroundings is the source of complexification, evolution and adaptation.
Process complexity
Process complexity moves us from an image of concretely objective ‘things which interact’ towards an image of entities that are more akin to ripples on a river (Boulton 2021). It emphasises the processual nature of the complex world. It is a world of processes in process, a world always becoming (see Prigogine 1980).
Embracing this perspective can seem obvious or subtle, exciting or irritating, rich or overwhelming, depending on your point of view. But in that embracing is offered the promise of an understanding that can lead to discernment and judicious action.
Complexity raw and complexity cooked
To talk of complexity theory or complexity science is a complex thing in itself. Edgar Morin (2006) makes a distinction between a framing of complexity that sits within the ontology of classical science, which he calls ‘restricted complexity’; he contrasts this with the raw ‘general complexity’ of the ‘real world’.
Restricted complexity emanates from the world of models, maps and mathematics. The aim is to find ways to represent the complexity of the real world and find a good map.
General complexity, by contrast, starts further back into the primordial mud, and champions the attainment of knowledge through wandering the ‘territory’. General complexity is more paradoxical, more integrating, more challenging, ambiguous and uncertain – but also ripe with potential. It is complexity that is beyond (or before) mathematics. It often starts with experiment and observation – of forests, cells, swirls in chemical systems, galaxies, social groups or societies – rather than with conceptual abstractions.
“Instead of trying to analyse complex phenomena in terms of single or essential principles, [complexity] approaches acknowledge it is not possible to tell a single or exclusive story about something that is really complex. The acknowledgement of complexity, however, certainly does not lead to the conclusion that anything goes (Cilliers 1998).
Subjectivity
The complex world does not present itself as objectively existent entities interacting in measurable ways. There is a subjectivity as to what we perceive and how we interpret what we perceive.
I suggest that there are three aspects to subjectivity: one centred in the person who is perceiving, one centred in the nature of what is perceived and the third embedded in a rather different view of the nature of ‘reality’, a view that emerges from quantum physics.
“We experience more than quantities; we also experience qualities such as colour, texture, pain, health, beauty, coherence. Science tends to dismiss these as ‘subjective’… Subjectivity is getting squeezed out by science… I believe there is a whole scientific methodology that needs to be developed on the basis of what is called the intuitive way of knowing (Brian Goodwin in Brockman 1997).
In general, in order to engage fully with the complex open inter-relational social and natural world, we need to ensure we do not exclude that which is indefinite qualitative contextual, local and emerging. There is a difference between knowing smoking causes cancer and exploring what are the wider determinants that cause a particular group of people to continue to smoke nevertheless, or that makes them more vulnerable to the disease.
We need to resist the desire only to give phenomena salience when they become more settled, fixed and statistically significant. It is through engaging with situations in flux, with emerging patterns and with glimmers of newness, that we have a chance to explore the nature of change and becoming, and indeed the nature of relative stability. We need to be curious and open both in our perceiving, and in our thought processes and sense-making; we need both to respond to what seems concrete and not in dispute and pay attention to that which is more imprecise.
Essential characteristics of the complex world
Complexity theory suggests that organisations, markets, ecologies and communities are:
- Organic: They have more in common with ecosystems, with evolving organisms than with machines; they are not in general predictable or controllable.
- Self-organising and comprised of temporary patterns of relationships: They often display patterns of relationships (such as ways of working in organisations or buying patterns in markets) which can be relatively stable but still display some variation and fluctuation and may indeed evolve, eventually, into new patterns.
- Contingent on history and context: The future depends on the detail of what happens, does not smoothly follow from the past.
- Affected by multiple causes: In general in the social and natural world, there are no simple cause-and-effect chains; outcomes are influenced by several factors acting together, combined with the effects of chance, history and the wider environment.
- Co-evolutionary: Organisations are shaped by their environments and vice versa; there is interaction and reflexive change between scales, between actors.
- Episodic, non-linear change: Sometimes current patterns are resilient but flexible, sometimes locked-in and rigid, sometimes change can be fast and radical.
- Emergent: Change can lead to the emergence of features qualitatively different from the past.
Key takeaways
Key takeaways are to:
- diagnose situations systemically and historically – look for the “simplicity on the other side of complexity” (Boulton 2024: 239-40)
- stay alert to subtle signs of change – by the time there is objective evidence it is often too late
- create shared intentions but plan shorter term; review often and expect the unexpected
- allow some leeway to experiment
- develop good practice by sharing learning, not diktat
- ask questions – to uncover what is, surface new ideas, shape thinking.
How have you been informed by complexity science when tackling complex problems? Are there other perspectives that have influenced you? Do you have success stories about ‘embracing complexity’ that you can share?
To find out more:
Boulton, J. (2024). The dao of complexity: Making sense and making waves in turbulent times. De Gruyter: Berlin, Germany.
Jean Boulton’s website: https://www.embracingcomplexity.com/ also provides more information and excerpts from the book. This i2Insights contribution is taken, largely verbatim, from: https://www.embracingcomplexity.com/complexity/
References
Boulton, J. (2021). Process complexity. Complexity, governance and networks, 7, 1: 5-14.
Brockman, M. (1997). A new science of qualities: A talk with Brian Goodwin. Edge.org (‘Reality Club’) website. (Online): https://www.edge.org/conversation/brian_goodwin-a-new-science-of-qualities
Cilliers, P. (1998). Complexity and postmodernism: Understanding complex systems. Routledge: London, United Kingdom.
Morin, E. (2006). Restricted complexity, general complexity. In; C. Gershenson, D. Aerts and B. Edmonds. (eds.), Worldviews, science and us: Philosophy and complexity, University of Liverpool, UK. World Scientific: Singapore.
Prigogine, I. (1977). Ilya Prigogine – Biographical. NobelPrize.org website. Nobel Prize Outreach AB 2024. (Online): https://www.nobelprize.org/prizes/chemistry/1977/prigogine/biographical/. (From Nobel Lectures, Chemistry 1971-1980, Editor-in-Charge Tore Frängsmyr, Editor Sture Forsén, World Scientific Publishing Co., Singapore, 1993).
Prigogine, I. (1980). From being to becoming: Time and complexity in the physical sciences. W. H. Freeman and Company: New York, United States of America.
Recommended reading:
Boulton, J., Allen, P. and Bowman, C. (2015). Embracing complexity: Strategic perspectives for an age of turbulence. Oxford University Press: Oxford, United Kingdom.
Mowles, C. (2015). Managing in uncertainty: Complexity and the paradoxes of everyday organizational life. Routledge: London, United Kingdom.
Preiser, R. (Ed.). (2016). Critical complexity: Collected essays. De Gruyter: Berlin, Germany.
Varney, S. (2021). Leadership in complexity and change: For a world in constant motion. De Gruyter: Berlin, Germany.
Use of Generative Artificial Intelligence (AI) Statement: Generative artificial intelligence was not used in the development of this i2Insights contribution. (For i2Insights policy on generative artificial intelligence please see https://i2insights.org/contributing-to-i2insights/guidelines-for-authors/#artificial-intelligence.)
Biography: Jean Boulton PhD is a Fellow of the Institute of Physics and a visiting academic with the universities of Cranfield and Bath, in the United Kingdom. She has been deeply involved in the science and philosophy of complexity since the mid-1990s and the honing of these ideas continues to inform her research, consultancy work and personal practice.