The Atlas of Social Complexity. Chapter 23: Governance, Politics and Technocracy

The first major content theme in The Atlas of Social Complexity is Cognition, Emotion and Consciousness. This first theme includes six chapters, which I have so far blogged on. Chapter 6 addresses autopoiesis. Chapter 7 turns to the role of bacteria in human consciousness. Chapter 8 explores how the immune system, just like bacteria and cells, is cognitive – and the implications this has for our wider brain-based consciousness. Chapter 9 explores a complexity framing of brain-based cognition, emotion and consciousness. Chapter 10 explores the complex multilevel dynamics of the Self. Chapter 11 is about human-machine intelligence.

 

The second major content theme in The Atlas of Social Complexity is The Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders ; Chapter 15: Healing and the therapeutic process; and Chapter 16: Mindfulness, imagination, and creativity.

 

The third major theme is living in social systems (Chapter 17). The first chapter in this section is Complex social psychology (Chapter 18). From there we move on to Collective behaviour, social movements and mass psychology (Chapter 19). Next is Configurational SocialScience (Chapter 20). From there we move to the Complexities of Place (Chapter 21); followed by Socio-technical Life (Chapter 22). 

 

The focus of the current post is CHAPTER 23: GOVERNANCE, POLITICS AND TECHNOCRACY

 

OVERVIEW OF CHAPTER

We are occasionally mystified that complexity scholars who understand their subject very well can at the same time come up with policy recommendations that are so wide off the mark that one should not be surprised that no one listens.

The term ‘wicked problems’ is never far away once the discussion turns to how the complexity sciences can inform government and public policy. Rittel and Webber’s[1] seminal 1973 paper[2] observed how scientists are good at developing recommendations for those instances where there is agreement about the goals to be reached, and that have a known problem structure. In such cases, science can identify what must happen in order to close the gap between the current situation and the desired system state. These are ’tame problems’. Somewhat unfortunately, most complex societal issues lack both aspects. Not only is the structure underneath the problem poorly understood, but there is also little agreement about what desirable future(s) should be pursued. These are the type of ‘wicked problems’ that challenge complexity scientists. They cannot be solved by throwing more (computational) science at it because the lack of consensus about the desired future means that the space of possibilities increases a manifold.

The reason why, some 50 years later, we draw this paper back into focus when it comes to the conjunction of societal problems, public policy and complexity is that there is a tendency for complexity scientists to do exactly what Rittel and Webber warned us for half a century ago: to throw more science at it.

 

Wicked problems are real, but their causal complexity is only one aspect of it. Normative ideas about what is good[3] cannot be settled through science.

 

Our comment in Chapter 3 that the complexity sciences can appear tone-deaf to the real-world stems from exactly this point. The complexity sciences have a veneer of technocracy, which is not very useful as a solution direction. It is one thing to get a better understanding of a seemingly intractable problem, it is quite another to believe that science can be the arbiter about what constitutes the best solution.

 

This does not imply that science has no role to play in societal issues, beyond the science itself. Most certainly, we are convinced that science must speak truth to power.

 

Our main argument for wicked problems is that politics are central to the equation in ways they are not in tame problems. In terms of the study of social complex, this means that any analysis of a real-world societal problem must include the complexities of politics and policy.[4] There is no use in analysing such problems and devising solutions for them if one treats government as a black-box-implementation-machine that will just carry out whatever scientists think is the best solution. Frustrating? Perhaps. But this is the reality, and the complexity sciences must deal with that reality. Hence our journey for this part of the tour. In Chapter 23, we discuss how governance and politics have become interwoven in societal networks and need to be understood as such. Ample attention goes to that one big blind spot in the study of social complexity: power. We discuss how power may be understood from a complexity perspective. Last but definitely not least, we demonstrate the need for dialogue instead of technocracy if one wishes to achieve real impact in today’s complex societies.

 

While certainly not everything in the chapter, we thought it useful to provide a list of things that need to be given focus or attention for those keen on using social complexity to study governance and policy. Here are the key takeaways from the chapter:

• Empirical Engagement Over Abstraction: Complexity science should prioritize empirical grounding by engaging directly with governance and policy challenges rather than relying solely on abstract modelling.
• Integrate Complexity with Political Science & Policy Studies: Bridging insights from complexity science with political science, public administration, and policy studies can improve real-world applicability.
• Recognize the Role of Power in Complexity: Complexity-informed governance studies must incorporate power dynamics, including issues of dominance, inequality, and structural constraints on decision-making.
• Use Complexity Science to Navigate Policy Uncertainty: Policy-making occurs in a dynamic and uncertain environment; complexity tools can help identify emergent risks, feedback loops, and unintended consequences.
• Develop Configurational Approaches to Policy Analysis: Recognizing that governance outcomes depend on specific contextual configurations, case-based complexity and conjunctural causation should be integrated into policy studies.
• Adopt Fitness Landscape Models for Governance Networks: Policy actors navigate governance networks like fitness landscapes, where positioning, negotiation, and adaptability shape policy effectiveness.
• Enhance Policy Adaptability & Responsiveness: Policies should be designed to be flexible enough to respond to local conditions while maintaining coherence at broader levels.
• Engage in Cross-Disciplinary Dialogue: Scholars from complexity science and governance studies should collaborate to refine methodologies, ensuring complexity models reflect real-world governance processes.
• Leverage Complexity for Policy Implementation Insights: Complexity science can help explain why policies succeed or fail based on local contingencies, feedback loops, and adaptive learning mechanisms.
• Use Complexity as a Sense-Making Tool: Instead of focusing solely on predictive modelling, complexity science should be applied as a framework for sense-making and scenario analysis in governance.
• Incorporate Metaphors & Narrative Framing: Complexity concepts should be communicated using accessible metaphors and narratives to bridge the gap between academia and policymakers.
• Move Beyond Technocratic Approaches: Complexity science should not reinforce technocracy but engage meaningfully with political realities, democratic processes, and stakeholder participation.
• Prioritize Real-World Engagement Over Theoretical Purity: Complexity scholars should engage directly with policymakers, governance networks, and stakeholders to refine their models based on practical governance challenges.
• Improve Policy Resilience through Complexity-Informed Strategies: Recognizing that policies function within dynamic, interconnected systems, complexity science can help policymakers design more resilient and adaptive strategies.
• Encourage Translational Research & Knowledge Brokerage: Complexity scholars should work with policy practitioners to translate complex concepts into actionable governance insights.
• Reconceptualize Power as Emergent & Relational: Instead of viewing power as an individual attribute, complexity science should analyse how power emerges from networked interactions and structural conditions.
• Balance Between Modelling & Empirical Research: While formal models are useful, they should be informed by and tested against real-world governance cases to ensure relevance and impact.

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[1] Unsurprisingly, Rittel was a professor in the science of design, and Webber a planner and planning scholar. As we noted in Chapter 24, planners are among the people acutely confronted with real-world complexity.

[2] Horst W. J. Rittel and Melvin M. Webber, ‘Dilemmas in a General Theory of Planning’, Policy Sciences 4, no. 2 (1 June 1973): 155–69.

[3] A central tenet in political science, public administration, and other related strands, is that there is no such thing as the ‘common good’. The term is often used to justify a certain goal, but such is society that the goal will always be contested.

[4] David Colander and Roland Kupers, Complexity and the Art of Public Policy: Solving Society’s Problems from the Bottom Up (Princeton University Press, 2014).

The Atlas of Social Complexity. Chapter 21: The Local and the Global: The Complexities of Place

As I stated in my previous posts, The Atlas of Social Complexity is comprised of several content themes.

The first major content theme in The Atlas of Social Complexity is Cognition, Emotion and Consciousness. This first theme includes six chapters, which I have so far blogged on. Chapter 6 addresses autopoiesis. Chapter 7 turns to the role of bacteria in human consciousness. Chapter 8 explores how the immune system, just like bacteria and cells, is cognitive – and the implications this has for our wider brain-based consciousness. Chapter 9 explores a complexity framing of brain-based cognition, emotion and consciousness. Chapter 10 explores the complex multilevel dynamics of the Self. Chapter 11 is about human-machine intelligence.

The second major content theme in The Atlas of Social Complexity is The Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders ; Chapter 15: Healing and the therapeutic process; and Chapter 16: Mindfulness, imagination, and creativity.

The third major theme is living in social systems (Chapter 17). The first chapter in this section is Complex social psychology (Chapter 18). From there we move on to Collective behaviour, social movements and mass psychology (Chapter 19). Next is Configurational Social Science (Chapter 20).

The focus of the current post is CHAPTER 21: THE LOCAL AND THE GLOBAL: COMPLEXITIES OF PLACE

 

OVERVIEW OF CHAPTERS 21

The Information Age, Castells 1996. C.E. Up to this point on our tour we have made significant progress in understanding the social psychology and collective behaviour of living in social systems. We have also made substantial progress in positioning people (be they individuals, groups, communities) in terms of the intersecting social structures and the configurations of factors that drive their system-based experiences. As a next step on our tour, we will bring in the socio-geographical to explore people and their social systems in (geographical) time and space, ranging from the local to the global. Our chapter is organised as follows. We begin with a few preliminaries, most of which involve us narrowing in on our primary target: the complexities of cities and the global urban. 

Social complexity takes place in spaces. These can be geographical – think cities – but also abstract and imaginary, such as virtual networks and attractor spaces through which cases move. The spatial dimension of social complexity is extremely important because it shapes said complexity and provides the space where this complexity plays out. As some scholars discussed here stress: there is no pressing reason to separate time, space and geographical location. We follow their recommendation and survey all of this in this chapter. We discuss the many types of spaces that provide the stage for social complexity: cities, networks, time-space continuums, and more. Along the way, we discuss urban complexity and the modelling and simulation of spaces, and – importantly – the planning of spaces.

HERE ARE SOME (BUT CERTAINLY NOT ALL) OF THE HIGHLIGHTS FROM THIS CHAPTER:

• Social complexity plays out in spaces: in villages and in cities, in buildings and on the road, in hospitals and in schools.
• The globalizing world has added more dimensions to the role of space in social complexity, as places became entangled in worldwide digital and transportation networks and increasing social mobilities.[1]
• Globalisation has also brought about a highly mobile world, both physically and digitally.[2]
• For a short time, some scholars thought that the space of flows and global mobilities would render physical locations less important. The opposite has happened. It reinforced cities and metropolitan areas as central nodes to create clusters and networks of megacities or super-cities[3] and enhanced spatial inequalities.[4]
  
• The traditional analytical distinction between city and countryside has become thoroughly obsolete in an age of the sprawling megapolis and megaregions, which have absorbed individual towns and suburbs into one continuous fabric.[5]^,[6]
• As our opening argument elucidates, a thorough revision of how we understand the (globalized) urban is needed.[7]
• Importantly, the notion of ‘space’ is multifaceted. Not only is this about networks and temporal attunement, but it is also about the differences between the physical space, the experienced space at the level of individual urban dwellers, and abstract symbolic spaces.[8]
• Complex spaces immediately conjure up images of contemporary cities. And yes, cities are important expressions of complex spaces. However, there is another aspect that is equally important: the spatial dimension of complexity sciences itself, such as attractor spaces and fitness landscapes.
• The surprising thing about time, and its relationship with space, in the complexity sciences is that it plays a key role in understanding complexity; yet it is usually captured in a fashion that prohibits true exploration. Complexity plays out over time. Without the time dimension, we wouldn’t observe emergence, non-linearity, hysteresis and path-dependence, to name a few key notions from the first chapters of this Atlas.
• The biggest hurdle in unpacking time is not how we understand emergence but rather how it is projected upon time units. Indeed, time in the complexity sciences is usually treated as sui generis and as a uniform measure.[9] Thus, emergence is distributed across uniform units such as ticks in a simulation or clock time (minutes, days, years, etc.).
• This convention is deeply ingrained in research, not in the least because it is a workable and understandable proxy for social processes. The main problem with all this is that it imposes a regimentation on any observation.[10]
• Time is a social institution that, by extension, varies from one space to another.[11] Arguably, contemporary time and its regimentation are hallmarks of industrialization and the emergence of the big city[12], creating what Adam[13] calls a ‘time-grid’ that characterizes contemporary society.
• An important step in understanding how else we could capture time in the study of social complexity, we should also highlight the intricate relationships between time and space. Time-space dualities have been criticized for creating false dichotomies.[14]
• From a system’s perspective, one might argue that clock time would capture movements more accurately. From the perspective of within-case variation, it is the experience of time that is more important. It points to the importance of pace or velocity.
  

 Again, lots more on the topic, but you need to read the chapter to find out! :)

 

KEY WORDS: space; urban; cities; time-space; space of flows; local; global; time; planning; time; urban simulation; geospatial modelling

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[1] In addition to Castells, see John Urry, The Tourist Gaze (Sage, 2002); John Urry, Sociology beyond Societies: Mobilities for the Twenty-First Century (Routledge, 2012).

[2] Mimi Sheller and John Urry, ‘Mobilizing the New Mobilities Paradigm’, Applied Mobilities 1, no. 1 (2016): 10–25; Jonas Larsen and John Urry, Mobilities, Networks, Geographies (Routledge, 2016).

[3] Jonathan V. Beaverstock, Richard G. Smith, and Peter J. Taylor, ‘World-City Network: A New Metageography?’, Annals of the Association of American Geographers 90, no. 1 (2000): 123–34.

[4] Ali Madanipour, ‘“Social Exclusion, Space, and Time”’, in The City Reader, 7th ed. (Routledge, 2020).

[5] Jennifer Robinson, Comparative Urbanism (Sussex: John Wiley & Sons Ltd., 2022).

[6] To some, the level of urbanization has become so vast that one should accept that all forms of human settlement are urban, i.e., planetary urbanism, see e.g., Henri Lefebvre, Rhythmanalysis: Space, Time and Everyday Life, trans. Gerald Moore and Stuart Elden (London ; New York: Bloomsbury Academic, 2013). And while the process of urbanization is just as complex as the actual places itself, Robinson rightly points out that this concepts must be treated with some caution. The similarities and dissimilarities of places matter.

[7] Neil Brenner and Roger Keil, ‘From Global Cities to Globalized Urbanization’, Glocalism: Journal of Culture, Politics and Innovation, no. 3 (2014).

[8] David Harvey, ‘Space as a Keyword’, in David Harvey (John Wiley & Sons, Ltd, 2006), 70–93.

[9] Lasse Gerrits, Robin A. Chang, and Sofia Pagliarin, ‘Case-Based Complexity: Within-Case Time Variation and Temporal Casing’, Complexity, Governance & Networks 7, no. 1 (2 May 2022): 29.

[10] Gerrits, Chang, and Pagliarin.

[11] E. Durkheim, The Elementary Forms of Religious Life, trans. J. Swain (London: Allen & Unwin, 1968).

[12] G. Simmel, Le Metropoli e La Vita Dello Spirito (Rome: Armando Editore, 1903).

[13] B. Adam, Timewatch: The Social Analysis of Time (Cambridge: Polity Press, 1995).

[14] N. Thrift, ‘Torsten Hägerstrand and Social Theory’, Progress in Human Geography 29, no. 3 (2005): 337–40; N. Thrift, ‘Space, Place, and Time: Chapter 29’, in The Oxford Handbook of Contextual Political Analysis, ed. Robert E. Goodin and Charles Tilly, Oxford Handbooks of Political Science (Oxford: New York and Oxford University Press, 2006), 547–63.

[15] Gieryn, Thomas F. "A space for place in sociology." Annual review of sociology 26, no. 1 (2000): 463-496. Urry, John. "The sociology of space and place." The Blackwell companion to sociology (2001): 3-15.

[16] Thomas Weber, Jorge Louçã, and Lasse Gerrits, ‘Dissipative Structures and the Relation between Individual and Collective Aspects of Social Behavior’, Systems Research and Behavioral Science 39, no. 2 (March 2022): 274–86, https://doi.org/10.1002/sres.2777.

[17] See, as a few key examples, P. Allen, ‘Self-Organization and Evolution in Urban Systems’, Cities and Regions as Non-Linear Decision Systems, 1 January 1984, 29–62; Gert de Roo and Ward S. Rauws, ‘Positioning Planning in the World of Order, Chaos and Complexity: On Perspectives, Behaviour and Interventions in a Non-Linear Environment’, in Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design, ed. Juval Portugali et al. (Berlin, Heidelberg: Springer, 2012), 207–20; Gert de Roo and Elisabete A. Silva, A Planner’s Encounter with Complexity (London: Routledge, 2010); Ward Rauws and Gert De Roo, ‘Adaptive Planning: Generating Conditions for Urban Adaptability. Lessons from Dutch Organic Development Strategies’, Environment and Planning B: Planning and Design 43, no. 6 (1 November 2016): 1052–74; Juval Portugali, ‘Complexity Theory as a Link between Space and Place’, Environment and Planning A: Economy and Space 38, no. 4 (1 April 2006): 647–64.

[18] Beyond the general observation that cities are complicated, that is.

[19] Antonio Isalgue, Helena Coch, and Rafael Serra, ‘Scaling Laws and the Modern City’, Physica A: Statistical Mechanics and Its Applications 382, no. 2 (15 August 2007): 643–49.

[20] Big data analysis about cities runs into the same issues that plague big data analysis everywhere.

[21] Michael Batty, ‘Big Data, Smart Cities and City Planning’, Dialogues in Human Geography 3, no. 3 (November 2013): 274–79.

The Atlas of Social Complexity. Chapter 22: Socio-technological life

As I stated in my previous posts, The Atlas of Social Complexity is comprised of several content themes.

The first major content theme in The Atlas of Social Complexity is Cognition, Emotion and Consciousness. This first theme includes six chapters, which I have so far blogged on. Chapter 6 addresses autopoiesis. Chapter 7 turns to the role of bacteria in human consciousness. Chapter 8 explores how the immune system, just like bacteria and cells, is cognitive – and the implications this has for our wider brain-based consciousness. Chapter 9 explores a complexity framing of brain-based cognition, emotion and consciousness. Chapter 10 explores the complex multilevel dynamics of the Self. Chapter 11 is about human-machine intelligence.

The second major content theme in The Atlas of Social Complexity is The Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Human psychology as dynamical system (Chapter 13). From there I reviewed Chapter 14: Psychopathology of mental disorders ; Chapter 15: Healing and the therapeutic process; and Chapter 16: Mindfulness, imagination, and creativity.

The third major theme is living in social systems (Chapter 17). The first chapter in this section is Complex social psychology (Chapter 18). From there we move on to Collective behaviour, social movements and mass psychology (Chapter 19). Next is Configurational Social Science (Chapter 20).

The focus of the current post is CHAPTER 22: SOCIO-TECHNICAL LIFE

 

OVERVIEW OF CHAPTER 

Chapter 22 invites readers on a journey through the intricate web of socio-technological systems that define our world in the Digital Anthropocene. At its heart, it explores the interplay of technology, agency, and social complexity, while grappling with questions about how these elements intertwine to shape human life, knowledge production, and societal transitions.

Technology as Both Sculptor and Subject

The narrative begins by acknowledging the dual role of technology. On the one hand, it is a tool for understanding complexity; on the other, it is a dynamic actor shaping social systems. The chapter highlights how digital technologies, particularly algorithms, weave themselves into the very fabric of human existence—becoming co-creators of social norms, practices, and even behaviours. Through examples ranging from train traffic control to predictive policing, the chapter underscores the distributed nature of agency in socio-technological systems, where humans and algorithms mutually influence and reconfigure one another.

 

Posthuman Perspectives and New Cartographies of Agency

Posthumanism offers a provocative lens through which to view these developments. Rejecting the humanist ideal of rational, hierarchical dominance, this framework asks: What does it mean to be human in a world where digital technologies blur the lines between human and non-human actors? The chapter answers with a call for "complex cartographies" of agency, shifting our focus from individual actors to the networks and assemblages that generate collective outcomes. It encourages readers to look beyond simplistic binaries, understanding agency as the emergent property of these intricate configurations.

 

The Role of Technology in Complexity Sciences

While the complexity sciences have long been tools for deciphering social systems, this chapter critiques their limited engagement with the deeper implications of technological agency. By focusing on algorithms as "performative, contingent, and ontogenetic," the chapter calls for a more nuanced exploration of how technology not only reflects but also reshapes the systems it inhabits. This insight is not just theoretical – it offers a blueprint for developing methods that account for the recursive feedback loops between human actions, algorithmic processes, and social outcomes.

 

Societal Transitions: Navigating the Unknown

Societal transitions, particularly those driven by technological innovation, emerge as a focal point. The chapter captures the complexity of these shifts, using examples like Germany's energy transition to illustrate the non-linear, path-dependent, and context-sensitive nature of change. It critiques overly deterministic views of technology, emphasizing instead the need to study how configurations of social, cultural, and technological factors align -- or fail to align -- to enable transitions.

 

Importantly, the chapter warns against techno-utopianism. The belief that technology alone can resolve societal challenges, from climate change to inequality, is deeply flawed. Instead, it advocates for a critical and reflexive approach that considers the unintended consequences, residual causality, and ethical dimensions of technological transitions.

 

Management and Operations: The Challenge of Complexity

Finally, the chapter examines the management and operation of socio-technological systems. Drawing on principles like Ashby’s Law of Requisite Variety, it highlights the challenges of navigating complexity in real-world contexts. The discussion critiques simplistic applications of complexity science to management, urging instead a deeper integration of insights from sociology, technology studies, and systems thinking.

 

The chapter also underscores the importance of critical reflection in management practices, particularly in resisting the allure of simplistic solutions or the rebranding of old ideas as novel insights. It suggests that the real value of complexity lies not in offering prescriptive frameworks but in fostering a more profound understanding of the dynamic interplay between systems, technologies, and human actors.

 

Conclusion: Towards a Reflexive Complexity

This chapter is not just an academic exploration; it is a call to action. It challenges readers to rethink the boundaries of agency, the role of technology, and the nature of complexity itself. It asks us to approach the Digital Anthropocene with a critical eye and a willingness to embrace uncertainty, complexity, and nuance.

 

In doing so, this chapter reminds us that the study of socio-technological systems is not just about mapping the present but also about imagining and shaping the future. Through its insights, it offers a roadmap for navigating the complexities of our hyperconnected world – one that is as intellectually rigorous as it is profoundly human.