In his Histories, Herodotus tells the story of Croesus, a wealthy king who ruled the region of Lydia some 2,500 years ago. One day, Croesus consulted the famous oracle at Delphi about his conflict with the neighboring Persians. The oracle responded that if Croesus went to war, he would destroy a great empire. Sure of victory, Croesus marched for battle. Much to his surprise, however, he lost. The great empire he destroyed was not his enemies’, but his own. A few centuries later, the Persians were in turn bested by Alexander the Great.
Civilizations rise and fall, sometimes at the stroke of a sword. Myriad explanations have been posited as to why this happens. Often, hypotheses of collapse say more about the preoccupations of contemporary society than they do about the past. It is no coincidence that Edward Gibbon’s The History of the Decline and Fall of the Roman Empire (01776), written during the anticlerical Age of Reason, blamed Christianity for Rome’s downfall, just as it is no coincidence that recent popular accounts of civilizational collapse such as Jared Diamond’s Collapse: How Societies Choose to Fail or Succeed (02005) point toward environmental damage and climate change as the main culprits.
I’ve been fascinated by the oscillations of human societies ever since the early days of my research for my Ph.D. in archaeology. Over the last 12,000 years, we’ve gone from small hunter-gatherer groups to highly urbanized communities and industrialized nation-states in a globally interconnected world. As societies grow, they expand in territory, produce economic growth, technological innovation, and social stratification. How does this happen, and why? And is collapse inevitable? The answers provided by archeology were unsatisfying. So I looked elsewhere.
Ultimately, I settled on a radically different framework to explore these questions: the field of complexity theory. Emerging from profound cross-disciplinary frustrations with reductionism, complexity theory aims to understand the properties and behavior of complex systems (including the human brain, ecosystems, cities and societies) through the exploration of their generative patterns, dynamics, and interactions.
In what follows, I’ll share some thoughts about what social complexity is, how it develops, and why it provides a more comprehensive account of societal change than the traditional evolutionary approaches that permeate archeology. By recasting the rise and fall of civilizations in terms of social complexity, we can better understand not only the past of human societies, but their possible futures as well.
In the 19th century, scholars like the sociologist Herbert Spencer and anthropologist Lewis Morgan became interested in the historical development of societies. They found a suitable explanatory framework in the principles of biological evolution as posited by Charles Darwin. Social evolution holds that human groups undergo directed processes of change driven by fitness adaptations to external circumstances, resulting in an inherent tendency to increase complexity over time. The phrase “survival of the fittest,” often attributed to Darwin, was coined by Herbert Spencer to describe the evolutionary struggles of societies. Social evolutionists conceptualized historical change as part of a teleological trajectory towards higher stages of social complexity. They believed complex societies to be the most successful. “Complex” entailed more developed rationality, philosophy, and morality. It meant, in short, more civilized. This notion of successful societies was appropriated and embedded in a wider framework of Eurocentrism and Western superiority to place Western nation-states at the pinnacle of human evolution and to provide a justification for colonialism (Morris, 02013, p.2).
During the second half of the 20th century, a neo-evolutionary resurgence resulted in the postulation of societal stages of development that are still in vogue today, such as Elman Service’s scheme of bands, tribes, chiefdoms, and states (Service, 01962). While these works abandoned teleological notions, the identification of distinct developmental stages implies that fundamental properties co-occur in societies across time and space. It also suggests that societies stay in equilibrium until they go through a sudden phase shift and rapidly adopt a new set of properties and characteristics.
These assumptions are problematic in two ways. First, societal properties do not necessarily co-evolve, even if societal trajectories can converge to varying degrees due to similar underlying drivers (Auban, Martin and Barton, 02013, p.34). Second, equilibrium-based approaches are inherently static because they assume that changes cancel each other out over the long term. As a result, they regard change as ‘‘noise’’ that must be filtered out to understand the system. These approaches frequently employ reductionist views. This means identifying distinct subsystems, figuring out how these subsystems work, and then aggregating them to understand the behavior of the overall system. In human societies, that could mean identifying a separate economic system, then setting forth to understand that economy, while doing the same for other subsystems like politics, religion, and so on. Finally, by combining the understanding of each subsystem, we come to an understanding of society as a whole. Such top-down, reductionist approaches have strong limitations, as system behavior is not the result of the aggregation of the properties of its components, but rather the result of entirely new properties emerging in a bottom-up fashion. In other words, we must realize that “the whole is more than the sum of its parts.”
Since the 01970s, scholars from a broad range of disciplines, including biology, chemistry, physics, mathematics, systems theory and cybernetics, have been grappling with non-linearity, feedback loops, and adaptation across many kinds of systems, giving rise to the new field of complexity theory. Complex systems thinking posits that the fundamental units of social systems are social interactions between people. These interactions generate complex behavior, information processing, adaptation, and non-linear emergence. This means that social complexity is an inherent characteristic of all human societies, not just complex ones.
All human societies need energy and resources to sustain themselves. Beyond these so-called endosomatic needs, societies also have exosomatic needs, that is, energy requirements for material and technological maintenance and development. The social structures necessary for the exploitation of energy and resources can only emerge through the exchange and processing of information for communication, maintaining social connections, sharing knowledge, enabling innovation, and coordinating activities.
I assess social complexity through three main flows:
I define social complexity as the extent to which a social entity can exploit, process and consume flows of energy, resources and information (Daems, 02021). A society is not more complex because it is more civilized, but because it extracts more energy and resources from its environment or transmits information more efficiently. With this definition, complexity is dissociated from both social and environmental sustainability. Societies that manage to extract more energy and resources are not necessarily sustainable. Nor does enhanced information transmission always benefit society, as is so clearly illustrated in today’s struggles with misinformation.
This approach provides a clear answer to what social complexity is, but does not yet explain how it develops. Authors such as Joseph Tainter have posited social complexity as a problem-solving tool (Tainter, 01996). Societies are continuously faced with selection pressures – e.g. subsistence, cooperation, competition, production, demography, etc. – that act as input information for decision-making strategies driving societal development on two levels (Cioffi-Revilla, 02005):
- An episodic process of opportunistic decision-making; which feeds
- A gradual process of socio-political development or decline
Let us take the example of a society faced with a bad harvest. Such a society needs to assess the causes of this situation and define its strategies accordingly. Did the failed harvest stem from bad luck? Crop disease? The wrath of the gods?
Once the situation is assessed, a proper strategy needs to be devised. Do they try again and hope for the best? Experiment with new types of crops? Perform the necessary rituals to appease the wronged gods? Or perhaps they appoint officials to monitor agricultural production. Some strategies can be one-offs, such as a sacrifice or an official inspection. Or they can persist and become entrenched in the social fabric, such as when divine favor becomes indispensable for ensuring successful harvests, or a central government extends its control through a new bureaucratic system. Social structures do not spring forth fully-fledged from one day to the next, but are the result of incremental expansion, addition, and recombination of the outcomes of day-to-day decision-making processes.
As a system grows more complex, it self-organizes into nested groups that can take shape as horizontal networks or vertical hierarchies. When nested units across multiple scales become integrated within the same system, non-linear emergence and feedback loops across scales can generate some of the most powerful outcomes of complex system dynamics. A good example can be found in the process of energized crowding (Bettencourt, 02013; Smith, 02019). Drawn from the field of urban studies, energized crowding is what turns cities into “social reactors.” This is the idea that as more people live together in higher densities, more social interactions and exchange of information produces more social outcomes, both positive and negative. Bigger communities tend to proportionally display higher levels of innovation, income, and productivity, but also higher crime and scalar stress. All of the things drawing us towards the buzz of city life are ultimately born from the interactions between people.
Complexity formation is not without risk. Larger cities or polities tend to draw in population from a larger area. This requires a larger catchment, fulfilled through self-subsistence production, by importing goods, or both. As capital of the Roman empire, Rome grew to a population of over 1,000,000 people. Such a massive concentration of people was unthinkable without the structures of empire such as the ‘Annona’, state-sponsored grain subsidies relying on large-scale grain imports from Egypt, North Africa, and Sicily. Larger societies have a proportionally larger environmental footprint due to higher exosomatic needs. Rome needed not only food to sustain its population, but also resources to maintain its buildings, institutions, artisans, and cultural amenities. Moreover, as societies continue to implement changes over the long term, past measures could trigger future challenges which, in turn, need to be dealt with. Over time, a society builds an “ever denser scaffolding structure of related and interacting institutions” (van der Leeuw, 02016, p.168). The risks of this continued problem-solving process are twofold:
- Institutional structures grow more rigid, reducing the capacity of societies to adequately respond to new situational events
- Societies tend to focus on frequently occurring challenges, increasing the dangers of unknown challenges
Societies generally tend to first use simple and cost-effective efforts with high returns on investment. As iterations continue, solutions to maintain societal structures become more complicated and costly, with diminishing proportionate marginal returns. Beyond some of the more spectacular causes of the fall of Rome proposed by Gibbon and others, such as large-scale invasions or civil strife, this slow “rigidification” is far less visible, but no less impactful. It is likely no coincidence that waves of administrative reorganizations followed in ever-quickening succession during the Late Roman period. Societies that do not have the expertise or flexibility to deal with new challenges could undergo a “tipping point” leading to drastic societal transformations generally associated with societal collapse. However, collapse only makes sense from a top-down perspective. During the Late Bronze Age (around 1200 BCE), a widespread disintegration of polities across the eastern Mediterranean and Near East occurred, including the Hittites of Anatolia (modern Turkey), Mycenaean Greece, the Egyptian New Kingdom, and the Middle Assyrian Empire (modern Iraq). Recent archaeological research, however, has found abundant evidence for local communities that continued to be inhabited and even thrive.
An explanation can be found in another property of complex systems called “near decomposability” (Simon, 01962). This refers to stronger connectivity between units of a similar type and the ability of units to operate semi-independently from others in the system. For example, households share stronger ties and interact more frequently with other households in the same community than with those of another community. Units that make up nested systems can often continue to function even when links to other units break down. If a larger polity, say the Hittite state, were to disintegrate, local or regional levels may have continued largely unaffected. Scalar divisions can therefore act as “fault lines” along which polities can be broken up, apparently collapsed when seen from a top-down perspective, but maintaining a bottom-up continuity.
Social complexity formation is a complicated process drawing on the exploitation, processing, and consumption of interrelated flows of energy, resources, and information. It is neither intrinsically good as was the belief of social evolutionists, nor does it inevitably lead to societal collapse. It is a phenomenon with both positive and negative consequences.
Earlier I outlined how direct parallels with biological evolution resulted in social evolutionism and a problematic conceptualization of teleological trajectories of social complexity. Nevertheless, evolution can offer fruitful metaphors to generate deeper insight into social complexity formation. The evolutionary taxonomic space is composed of a near-infinite number of dimensions, each corresponding to a particular characteristic of an organism (Hutchinson, 01978). Yet, organisms are part of nested clusters (species, genus, family, order, etc.) taking up specific portions of this space. This means that even though biological evolution has been at work for millions of years, only a very limited area of the potential space has been actualized (Lewontin, 02019). Exploring the full potential taxonomic space would take millions upon millions of years.
Human societies likewise are clustered within the taxonomic space of all possible societal configurations. Current states are built from past configurations, in combination with the contingent opening of new pathways of development. At its current pace, humankind will not have sufficient time to explore the potential configuration space of societal organizations that will allow us to balance increasing social complexity with a sustainable dynamic within our natural environment. Yet, this should not discourage us from using the necessary long-term perspective to look beyond the edges of the current, toward what might be possible in the future. One thing is clear: Any foray into the future would do well to also have an eye on the past.
Auban, J., Martin, A. and Barton, C., 02013. Complex Systems, Social Networks, and the evolution of Social Complexity in the East of Spain from the Neolithic to Pre-Roman Times. In: M. Berrocal, L. Sanjuán and A. Gilman, eds. The Prehistory of Iberia: Debating Early Social Stratification and the State. New York: Routledge.
Bettencourt, L., 02013. The Origins of Scaling in Cities. Science, 340(6139), pp.1438–1441. https://doi.org/10.1126/science.1235823
Cioffi-Revilla, C., 02005. A Canonical Theory of Origins and Development of Social Complexity. The Journal of Mathematical Sociology, 29(2), pp.133–153. https://doi.org/10.1080/00222500590920860
Daems, D., 02021. Social Complexity and Complex Systems in Archaeology. London: Routledge.
Hutchinson, G.E., 01978. An Introduction to Population Ecology. New Haven: Yale University Press.
van der Leeuw, S., 02016. Uncertainties. In: M. Brouwer Burg, H. Peeters and W.A. Lovis, eds. Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling, Interdisciplinary Contributions to Archaeology. [online] Cham: Springer International Publishing. pp.157–169. https://doi.org/10.1007/978-3-319-27833-9_9
Lewontin, R., 02019. Four Complications in Understanding the Evolutionary Process. In: D.C. Krakauer, ed. Worlds Hidden in Plain Sight. SFI Press. pp.97–113.
Morris, I., 02013. The Measure of Civilization: How Social Development Decides the Fate of Nations. Princeton: Princeton University Press.
Service, E.R., 01962. Primitive social organization: an evolutionary perspective. New York: Random House.
Simon, H.A., 01962. The Architecture of Complexity. Proceedings of the American Philosophical Society, 106(6), pp.467–482.
Smith, M., 02019. Energized Crowding and the Generative Role of Settlement Aggregation and Urbanization. In: A. Gyucha, ed. Coming Together: Comparative Approaches to Population Aggregation and Early Urbanization. New York: State University of New York Press. pp.37–58.
Tainter, J., 01996. Complexity, Problem Solving and Sustainable Societies. In: R. Costanza, O. Segura and J. Martinez-Alier, eds. Getting Down To Earth: Practical Applications of Ecological Economics. Washington DC: Island Press. pp.61–76.
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