Paul Ormerod

The literature on the fall of civilizations spans from the archaeology of early state societies to the history of the 20th century. Explanations for the fall of civilizations abound, from general extrinsic causes (drought, warfare) to general intrinsic causes (intergroup competition, socioeconomic inequality, collapse of trade networks) and combinations of these, to case-specific explanations for the specific demise of early state societies. Here, we focus on ancient civilizations, which archaeologists typically define by a set of characteristics including hierarchical organization, standardization of specialized knowledge, occupation and technologies, and hierarchical exchange networks and settlements. We take a general approach, with a model suggesting that state societies arise and dissolve through the same processes of innovation. Drawing on the field of cumulative cultural evolution, we demonstrate a model that replicates the essence of a civilization’s rise and fall, in which agents at various scales—individuals, households, specialist communities, polities—copy each other in an unbiased manner but with varying degrees of institutional memory, invention rate, and propensity to copy locally versus globally. The results, which produce an increasingly extreme hierarchy of success among agents, suggest that civilizations become increasingly vulnerable to even small increases in propensity to copy locally.

Economics is by no means an empty box. For example, it offers what is possibly the only general law of behaviour in the social sciences, namely that agents react to incentives. Over the past two decades or so, at the micro level, the level of individual agent decision making, the discipline has made progress. Developments in the econometric theory of the analysis of large longitudinal data bases and the rise of behavioural and experimental economics have made the discipline much more empirical. However, at the macro level, economics has, if anything, gone backwards. The main intellectual effort since the 1980s has been to import the concept of equilibrium into macroeconomics. It is no surprise that policymakers during the financial crisis of the late 2000s found the mainstream economic models to be of little or no help at all. In the 1950s, there was an active debate about the computational limits which agents faced when making decisions. The polymath Nobel Laureate Herbert Simon was prominent in arguing that the rational model of choice, the core model of economic theory, was not realistic in many situations because of these limits. Even after the event, it may not be possible to determine what the optimal decision would have been at any given time. The world is in general too complex. Mainstream economics gradually lost sight of this fundamental challenge to one of its key assumptions. The rise of cyber society and Big Data mean that Simon’s challenge is more relevant than ever. Looking to the future, new models of ‘rational’ agent behaviour are required which are better suited to the cyber society of the twenty-first century. Key areas of research include: agent decision making rules; heuristics to identify decision types in any given context; network percolation of imitation, incentives, ideas, beliefs, influence and sentiments; networks evolution; the policy implications of different modes of behaviour; fundamental theory and tools to operationalise narrative dynamics; computational theories of narratives, including Big Data; tools for processing narratives and sentiment; and predicting the emergence of narratives.