Solving the Puzzle of the Supercooperators Means Studying Cooperation Cooperatively


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Until about 10,000 years ago, humans everywhere lived in small foraging groups with a simple material culture and a weak division of labour. These groups lacked professional militia, priesthoods, bureaucrats, lawyers, and academics. The ability to store information was limited, since writing had not yet been invented and the transmission of technological knowledge and tradition relied heavily on collective memory. And yet in the space of just a few millennia, human societies have grown to encompass millions of individuals, contributing to unfathomably complex systems of governance, production, and exchange that span the globe, regulated by highly elaborated political institutions, administrations, judiciaries, industries, financial regulators, scientific bodies, schools, universities, libraries, and much more.

Many efforts have been made to explain why the transformation took off when it did and why socio-political complexity continues to evolve. Unfortunately, most of the efforts using historical data have been difficult to evaluate because they are based on cherry picking evidence to fit the theory and are thus vulnerable to selection bias. An alternative way to establish what caused the rise of socio-political complexity in world history is to quantify variables of theoretical interest and establish the order in which they emerged or changed on a global canvas over thousands of years. After all, temporal order provides some insight into causality insofar as causes normally precede effects. This requires a vast amount of specialist knowledge, not only of history and prehistory, but also of various branches of computer science necessary to curate and organize large datasets, relevant fields of statistics needed to analyse the data, and knowledge in disciplines as diverse as evolutionary theory, anthropology, agent-based modelling, and many more. Even more dauntingly, this very diverse knowledge needs to be coordinated in quite specific ways to address the questions of interest here. Ironically, therefore, the challenge of explaining the scaling up of cooperation in world history actually requires a scaling up of cooperation within and across the academic fields that need to do the explaining. This is easier said than done, however.

It is often said that getting academics to cooperate, especially within and across disciplines where collaborative research is not the norm, is rather like herding cats. There are many reasons for this. Some boil down to terminological differences that can be overcome through painstaking translation but others are much more difficult to address, having to do with conceptual and even epistemological differences that can seem to be quite unbridgeable. Despite these problems, the past decade has witnessed the establishment of a massive global history databank that is enabling us to track the rise of socio-political complexity around the world over thousands of years. Seshat: Global History Databank is beginning to accomplish the previously unthinkable – establishing a common list of variables that can be compared across all time periods around a diverse sample of regions in five continents from the beginning of the Neolithic to the beginning of the industrial revolution. Thanks to this transdisciplinary effort, we can begin to evaluate the performance of various predictor variables in the face of quantitative evidence. Cue the drum roll…

Up first: the Big Gods hypothesis. Proponents argue that all-seeing punitive deities helped drive the rise of social complexity by providing a way of sanctioning cooperation between relative strangers. Earlier this year, the Seshat team published its first paper on this topic in Nature, showing that supernatural moral enforcement appeared after rather than before the sharpest initial rises in social complexity.

Building on this work, a second wave of analyses of Seshat data pertaining to the drivers of socio-political complexity in world history has just been completed. This includes new data from additional geographic regions and domains such as warfare and the environment, along with more sophisticated measures of moralizing religion and more nuanced treatment of missing/disputed data. The resulting new wave of analysis robustly confirms the main finding of the Nature paper but also points to additional factors driving the rise both of social complexity and moralizing religion, most notably intergroup warfare. In particular, cavalry warfare turns out to be a much stronger factor in the appearance of moralizing religion than other hypothesized drivers such as affluence, climate security, and reliance on pastoralism. Using Seshat to quantify patterns such as these in world history is necessarily an incremental process. But it is also one that pushes our capacity for cooperation in academia to the limit. One of the greatest challenges in this regard is to avoid a tragedy of the commons in which arguments over which approach is best become sufficiently adversarial that the fragile collaborative networks through which scientific advances can be built, are at risk of being damaged or fragmented into camps. In an effort to avoid these kinds of problems, the Seshat team has published online its latest paper on moralizing religions, as well as all the data, analytic narratives, and statistical analyses used to produce it, so that interested parties can engage critically with it in parallel with peer review and prior to publication. This way of studying cooperation is itself maximally cooperative. If we can all build on this and pull in the same direction, it may give rise to even more ambitious forms of academic collaboration, bridging the famously divided ‘two cultures’ of the sciences and the humanities, and allowing us eventually to solve the great puzzle of the supercooperators.

 

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