Early research in anthropology and geography focused on the diversity of societies and cultures. Semple considered the land basis of societies, from hunter-gatherers to modern nation states. As against this environmental determinism, Boas argued that geography can modify and constrain culture but not create it. Rappaport showed how ritual can regulate, through feedback, the balance of broader ecosystems. Reflecting on work in the Amazon, Moran argued that socio-environmental debates reflect different levels of analysis. Humans altered human–environment relationships by domesticating plants and animals during the Neolithic revolution, as described by Childe. Mumford explores the evolution of cities and suburbs, including the separation of people from resources and urban pollution. We assume modern life affords leisure, but Sahlins shows the affluence of hunter-gatherers given lower environmental demands. How society adapts to natural hazards is explored by White, while Blaikie and Brookfield pioneer political ecology by showcasing the cycle of poverty and land degradation. Sustainable livelihoods require emphasis on equity and capabilities, argue Chambers and Conway.

Chapter 15 concludes by describe two radically different future visions of the intelligent society. On one hand, instrumentarian intelligence assumes that algorithms tracking human behavior can predict human behavior more accurately than ever before. In western countries, this intelligence manifests itself in a new surveillance capitalism with companies like Google and Facebook constantly searching for behavioral surplus in both online and offline settings. In the political domain, instrumentarian intelligence seeks a reputation state built on a neobehavioristic governing model. The most prominent example is the nationwide social credit system in China that makes it possible to grade citizens on different behavioral indicators. In stark contrast, civic intelligence highlights a use of technology still controlled by the community and citizens in contrast to the dehumanizing aspects of instrumentarian intelligence. While machine intelligence also craves for informational diversity in its hunt for behavioral surplus, civic intelligence seeks a broader diversity that includes not only information, but also multicultural, cognitive, biological, and participatory diversity. The “fuel” of CI is people who are different from each other, with different interests and unique perspectives. Civic intelligence also builds on a strong knowledge commons and an open shared collective memory. It does not hide information to produce the best predictions, but it promotes complete transparency and individual empowerment. In contrast to instrumentarian intelligence, CI still lets human-to-human intelligence, and not the algorithms, be at the core of the human collective problem solving.