Debates over the causes and consequences of the “Axial Age” – and its relevance for understanding and explaining “modernity” – continue to rage within and across a wide variety of academic disciplines, including anthropology, sociology, archaeology, history, social theory, and cognitive science. We present a computational model that synthesizes three leading theories about the emergence of axial civilizations. Although these theories are often treated as competitors, our computational model shows how their most important conceptual insights and empirically based causal claims (...) can be integrated within a single computational architecture. The plausibility of the latter is supported by the results of our simulation experiments, which were able to simulate the emergence and growth of an axial civilization. The model shows how the relevant theories can be rendered consistent, while challenging the claims of any one to comprehensiveness. (shrink)

From one of the most influential scientists of our time, a dazzling exploration of the hidden laws that govern the life cycle of everything from plants and animals to the cities we live in. The former head of the Sante Fe Institute, visionary physicist Geoffrey West is a pioneer in the field of complexity science, the science of emergent systems and networks. The term "complexity" can be misleading, however, because what makes West's discoveries so beautiful is that he has found (...) an underlying simplicity that unites the seemingly complex and diverse phenomena of living systems, including our bodies, our cities and our businesses. Fascinated by issues of aging and mortality, West applied the rigor of a physicist to the biological question of why we live as long as we do and no longer. The result was astonishing, and changed science, creating a new understanding of energy use and metabolism: West found that despite the riotous diversity in the sizes of mammals, they are all, to a large degree, scaled versions of each other. If you know the size of a mammal, you can use scaling laws to learn everything from how much food it eats per day, what its heart-rate is, how long it will take to mature, its lifespan, and so on. Furthermore, the efficiency of the mammal's circulatory systems scales up precisely based on weight: if you compare a mouse, a human and an elephant on a logarithmic graph, you find with every doubling of average weight, a species gets 25% more efficient--and lives 25% longer. This speaks to everything from how long we can expect to live to how many hours of sleep we need. Fundamentally, he has proven, the issue has to do with the fractal geometry of the networks that supply energy and remove waste from the organism's body. (shrink)

Since the Industrial Revolution, human societies have experienced high and sustained rates of economic growth. Recent explanations of this sudden and massive change in economic history have held that modern growth results from an acceleration of innovation. But it is unclear why the rate of innovation drastically accelerated in England in the eighteenth century. An important factor might be the alteration of individual preferences with regard to innovation resulting from the unprecedented living standards of the English during that period, for (...) two reasons. First, recent developments in economic history challenge the standard Malthusian view according to which living standards were stagnant until the Industrial Revolution. Pre-industrial England enjoyed a level of affluence that was unprecedented in history. Second, behavioral sciences have demonstrated that the human brain is designed to respond adaptively to variations in resources in the local environment. In particular, Life History Theory, a branch of evolutionary biology, suggests that a more favorable environment should trigger the expression of future-oriented preferences. In this paper, I argue that some of these psychological traits – a lower level of time discounting, a higher level of optimism, decreased materialistic orientation, and a higher level of trust in others – are likely to increase the rate of innovation. I review the evidence regarding the impact of affluence on preferences in contemporary as well as past populations, and conclude that the impact of affluence on neurocognitive systems may partly explain the modern acceleration of technological innovations and the associated economic growth. (shrink)