Social Complexity and Complex Systems in Archaeology

Dries Daems

• Publisher: Routledge
• Year: 2021
• eBook ISBN: 9781000344738
• Topic: Social Sciences
• Subtopic: Anthropology
• Index: Social Sciences

Social Complexity and Complex Systems in Archaeology turns to complex systems thinking in search of a suitable framework to explore social complexity in Archaeology.

Social complexity in archaeology is commonly related to properties of complex societies such as states, as opposed to so-called simple societies such as tribes or chiefdoms. These conceptualisations of complexity are ultimately rooted in Eurocentric perspectives with problematic implications for the field of archaeology. This book provides an in-depth conceptualisation of social complexity as the core concept in archaeological and interdisciplinary studies of the past, integrating approaches from complex systems thinking, archaeological theory, social practice theory, and sustainability and resilience science. The book covers a long-term perspective of social change and stability, tracing the full cycle of complexity trajectories, from emergence and development to collapse, regeneration and transformation of communities and societies. It offers a broad vision on social complexity as a core concept for the present and future development of archaeology.

This book is intended to be a valuable resource for students and scholars in the field of archaeology and related disciplines such as history, anthropology, sociology, as well as the natural sciences studying human-environment interactions in the past.

1Introduction

The aim of this book is to champion complex systems thinking as a major conceptual approach to study social complexity in archaeology. At the beginning of the new millennium, Stephen Hawking famously claimed that the 21st century would be the ‘century of complexity’. In the first two decades of that century, complexity science has started to gain ground as a core theoretical and methodological approach. Studying complexity entails trying to understand the underlying patterns and common mechanisms in physical, biological, social, and technological systems. It is about uncovering how and why the adaptive interactions of agents within these systems produce evolution and change expressed in – oftentimes surprising – emergent behaviour. Over the last few decades, archaeology has also increasingly come to realise the enormous potential of this approach. Summarising some of the trends and evolutions of the use of complex systems in archaeology is one of the goals of this book. Yet, it is not a retrospection. There is still much left to be done to develop complex systems thinking as a major research framework in archaeology.

It is not my intention here to advance complex systems thinking as a new paradigm for archaeological theory and practice. The days of the ‘paradigm wars’ in archaeology are long gone and good riddance to them. Paradigmatic modes of thinking result in overly simplified characterisations of research traditions that “reduce ‘the other’ to a fixed point which provides leverage against the current dynamic” (McGlade and van der Leeuw, 1997, p. 1). Archaeologists today prefer to stress the plurality of theoretical approaches to construct interdisciplinary, integrative, and synthesising research frameworks (Altschul et al., 2018). Instead, I aim to integrate complex systems thinking as part of a set of conceptual and methodological tools derived from archaeological theory, social practice theory, and resilience science to build a multi-faceted conceptual framework for the study of social complexity.

Social complexity

Over the last 12,000 years, human societies have changed in dramatic ways. We have gone from small hunter-gatherer groups to highly urbanised communities and industrialised nation-states in a globally interconnected world. These changes are typically considered indicative of a massive increase in social complexity. Yet, what exactly constitutes social complexity and how it changes over time is not altogether clear and not always made explicit. Social complexity is often used as a catch-all concept for a variety of different processes and characteristics. It has been noted that “Inequality, large-scale networks of cooperation, institutionalized leadership, and hierarchical forms of governance all are central elements of the human career, often lumped under the rubric of social complexity” (Feinman, 2017, p. 459). Archaeological definitions of social complexity commonly involve aspects of scale, functional differentiation, and hierarchical power structures. To illustrate the point, I refer to a definition by Gary Feinman, who stated that social complexity is:

“The extent of functional differentiation among social units, [which] may be vertical or horizontal; vertical complexity is hierarchical governance with a degree of concentration in decision making and power, [whereas] horizontal complexity is the differentiation of a population into various roles or subgroups.”

(Feinman, 2012, p. 36)

The emergence of social complexity has been ascribed to a variety of drivers, including environmental pressures, population growth, innovation and technology transfers, warfare, peer-polity interaction, surplus production, and redistribution and individual agency. Trends of increasing complexity have been mostly noted in: (1) Agriculture (Boserup, 1965; Clark and Haswell, 1964; Minnis, 1996; Nelson, 1996; Wilkinson, 1973); (2) Technology (Arthur, 2015; Nelson, 1996; Wilkinson, 1973); (3) Competition and warfare (Carneiro, 1970); and (4) Socio-political control and specialisation (Carballo et al., 2014; Feinman, 2011; Spencer, 2014; Tainter, 1988).

Traditionally, archaeologists consider social complexity as a defining property of ‘complex societies’, as opposed to ‘simple societies’, with the former evolving out of the latter. This is the premise of social evolutionary approaches which will be discussed in the next chapter. While such perspectives have been rightfully criticised and largely abandoned in contemporary archaeology, the moniker of ‘complex societies’ is still fully in vogue. Complex societies can be generally defined as those human societies consisting of large numbers of people, many social and economic roles and large permanent settlements (Barton, 2014).

In this book, I will explore social complexity from the perspective of complex systems thinking, focusing particularly on the properties and effects of social interaction and information transmission in human societies. A related definition states that “complex social systems are those in which individuals frequently interact in many different contexts with many different individuals, and often repeatedly interact with many of the same individuals over time” (Freeberg et al., 2012, p. 1787). This approach transcends qualitative dichotomies between simple and complex societies, and emphasises instead the (quantitative) differences in scale of flows of energy, resources, and information in societies as the defining aspects of social complexity trajectories. Traditional complexity characteristics such as monumental architecture, political institutions, and economic specialisation are seen as emergent phenomena produced by these underlying flows.

Social complexity is a topical subject in archaeology. An interesting debate that has been raging in the last few years involves the so-called ‘moralising gods’ hypothesis or ‘Big Gods’ theory (Norenzayan et al., 2016; Whitehouse et al., 2019b). This theory states that religious beliefs emerged as evolutionary by-products of human cognitive development and were repurposed as moralising tendencies upheld by supernatural surveillance and punishment. It is also claimed that supernatural beliefs reinforce social coordination as a prerequisite for the development of social complexity. The main point of contention is whether the belief in supernatural beings imposing a moral order preceded the development of ‘complex’ societies or not. In case of the former, it is suggested that the moral order imposed by supernatural beings provided a prosocial mechanism to overcome the classic free-rider problem and facilitate social cooperation among non-king members of society, thus allowing group sizes to grow beyond the limits of direct, face-to-face relations, and social complexity to increase (Whitehouse et al., 2019b). Others have disputed such a direct, causal relationship (Norenzayan et al., 2016) and argue instead that a more general standardisation of ritual practices among a large population precedes the emergence of moralising gods and is a far more important factor in the emergence of large social groups and social complexity (Whitehouse et al., 2015).

In an attempt to settle this debate – and advance the study of social complexity in general – the Seshat: Global History Databank project is building perhaps the most ambitious comparative research project in archaeology to date, compiling an online database currently containing data from 414 societies covering 30 regions across the world from the past 10,000 years.¹ By conducting time series analysis on this dataset, the Seshat project argued that moralising gods only emerged once the rise of social complexity had crossed a certain size threshold (Whitehouse et al., 2019b).

In a scathing response, a group of scholars produced heavy criticism regarding the methods, data quality, and biases unaccounted for in the study (Beheim et al., 2019). Other research groups such as the Database of Religious History project² have also questioned the coding practices and reliability of data collection by the Seshat project (Slingerland et al., 2019). This criticism prompted a string of responses by the Seshat team, in which they defend and uphold their original analysis and results (Savage et al., 2019; Turchin et al., 2019; Whitehouse et al., 2019b).

While the importance of this debate – including the original claims as well as the concerns raised against them – must be acknowledged, I will not dwell on the detail of the argument. Instead, I want to use this debate to illustrate the importance of proper data collection, coding practices, and methods, as well as stress how working in a transparent framework geared towards openness and reproducibility can stimulate the development of ideas and the future advancement of our discipline. The creation of openly accessible databases such as the Seshat Databank is an essential part of the development of archaeology as a scientific discipline. Even though the process is still showing some growth pains, I believe that efforts such as these constitute an important way forward for our discipline by facilitating quantitative analysis and synthetic research on topics such as social complexity. Recently, it has increasingly been argued that we are on the brink of a new era of ‘big data’ in archaeology which will reshape our discipline (Gattiglia, 2015; Graham et al., 2016; Huggett, 2020; White, 2016). More data allows us to distil patterns we could not possibly gather from small datasets. The potential of big data analysis to lift archaeological debates to a higher level is exciting indeed. However, to unlock this potential it is essential to provide both bottom-up and top-down embedding of data-based approaches:

“… initiatives seeking to marry quantitative and qualitative historical research must work from the ground up … and thereby amassing more granular, accurate and meaningful data on each.”

(Slingerland et al., 2019, p. 14)

This quote captures the idea that big data analysis in archaeology can only be pursued when supported by a foundation of in-depth expert knowledge and fine-grained data collection, that is, by adding a dimension of contextualisation and embedding. At the same time, it is essential to complement big data analysis with proper theory, conceptual knowledge, and hypotheses to guide our analysis and move beyond ‘blind’ interpretations driven by radical empiricism (Coveney et al., 2016; Huggett, 2020). This book aims to contribute to such an enriched approach by building a general conceptual framework to describe and explain social complexity trajectories. Such a framework needs to be able to deal with the messiness and limitations of archaeological data, while also allowing to draw out wider patterns of interpretation. The theoretical starting point for this approach is situated in complex systems thinking.

Complex systems thinking

This book centres on elucidating the potential of complex systems thinking for the study of social complexity in archaeology. I already outlined some archaeological definitions of social complexity earlier. The first question to consider is whether this conceptualisation matches that of complexity as a property of complex systems. The answer is generally no. Only few archaeologists have been considering complexity from the perspective of complex systems thinking. This field originated during the 1970s and 1980s out of developments in various disciplines – including physics, biology, chemistry, mathematics, general systems theory, and cybernetics – and has since been applied to a wide range of disciplines. ‘Complexity’ is a general term that has been defined in many different ways. To quote eminent sociologist and network scientist Duncan Watts: “Nobody really agrees on what makes a complex system ‘complex’ but it's generally accepted that complexity arises out of many interdependent components interacting in nonlinear ways” (Watts, 2011, p. 141). It is, however, a misconception that complexity is inevitably difficult to understand. It may be, well…complex, but that does not mean it remains irreversibly elusive from our understanding. So, what exactly do we mean when we say a system is complex?

It is of course tautological to state that complexity is that what defines a complex system. A complex system can be generally defined as “a system whose properties are not fully explained by an understanding of its component parts” (Lewin, 1992, p. x). Frequently cited examples include cities, economies, societies, the brain, the internet, and ecosystems. Obviously, complexity must be something very general if it can be considered a property of such a wide variety of systems. It is indeed telling that textbooks and general introductions to complexity science rarely offer a direct definition of what exactly complexity is. Instead, they tend to focus on a number of key properties of complexity, such as emergence, non-linearity, self-organisation, adaptation, and information processing.

The behaviour of a system that displays properties which cannot be explained by the dynamics and properties of its components is called ‘emergent’. Emergence derives from the non-linear aggregation of behaviour, properties and processes on a higher level that transcend mere summation of lower level effects. Human societies, for example, are emergent phenomena, arising from the multitude of interactions between people. Without people or their interactions, societies cannot exist. Yet, it is also impossible to assess how every individual interaction contributes to society and what its effects are. This is what we mean when we say that societies emerge in a non-linear fashion from its constituent interactions. Complex systems are also self-organised. This means that they have no central system of control governing behaviour. Individual components within a complex systems interact and make decisions based on locally-defined information that give rise to global patterns. Complex systems are dynamic because their components continuously adapt through an autocatalytic (i.e. self-­sustaining) loop of information transmission, information processing, and decision-making.

Throughout this book, I will use two terms when discussing the scientific framing of complexity. These are ‘complex systems thinking’ and ‘complex systems science’. With the former, I address the epistemic tenets of complexity, whereas the latter refers to its theoretical and methodological operationalisation. I prefer to talk in terms of complex systems thinking as, to me, it provides a more comprehensive approach to complexity. I am, however, aware that others might consider complex systems science to be a more comprehensive term than I have defined it here and would consider it to cover both sides of the spectrum that I paint here.

One might be tempted to take this explanation of complex systems and conclude that it is all about trying to look at the bigger picture of macro-level systems. This conclusion, however, does not fully capture what complex systems thinking is. Merely focusing on the big picture inevitably leads to loss of information at higher resolution. You could compare it with someone standing on top of a mountain. From this vantage point, you would have a great view over the surrounding landscape. However, without binoculars you will not be able to make out animals on the plains below. Complex systems thinking would be like bringing binoculars to the summit. It provides a way to direct attention and focus across scales within the system, and manipulate between what is currently foreground and background (Kepler, 2019).

One more thing to address is the convergence (or lack thereof) of complex systems and complex societies as defined earlier. If anything, only a weak parallel can be drawn. Complex societies often consist of differentiated structures such as social groups, classes, specialized labour, etc. Evaluations of the emergence of new political actors, levels of organisation, and hierarchical social relations are all aspects of interest from a complexity perspective, yet they do not match the full scope of a complex system. No inherent equivalence exists between complex societies in an archaeological sense and the more general phenomenon of complex systems (Auban et al., 2013, p. 53). All human societies, be they classified as socially complex or simple, are intrinsically complex systems in the sense of open systems requiring energy input, regardless of their size or organisational structure.

The crucial question remains how to interpret the unmistakable changes in social complexity in human societies from the Pleistocene until today. I argue that, from a complex systems perspective, the traditional characteristics of complex societies should not be considered as direct expressions of social complexity as such, but rather as emergent phenomena arising from social complexity trajectories. The latter are driven by transformations in energy capture, information processing, and the transmission of information and resources.

Complex systems thinking in archaeology

This book is not ground-breaking (that might seem like a self-deprecating statement but that does not mean it is not valuable) and it is definitely not the first application of complex systems thinking in archaeology. Over the last few decades, several important works have already paved the way. So far, however, we have not yet seen a comprehensive overview of complex systems thinking in archaeology or an attempt to propose a synthesising conceptual framework to study social complexity in a long-term historical perspective. This book aims to contribute towards addressing these gaps.

One might raise the question why we even need complex systems thinking as a framework to study the past. I am well aware that for many archaeologists, the introduction of a ‘f...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Contents
• List of figures
• List of tables
• Acknowledgements
• 1 Introduction
• 2 The history of complexity in archaeology
• 3 Conceptualising social complexity
• 4 Social complexity trajectories in Anatolia
• 5 Conclusions
• Bibliography
• Index