Movie makers and fiction writers have long depicted the disruption and fall of civilizations. But in a few works of fiction, like the classic “Foundation” series by Isaac Asimov, scientists develop models to help predict and avoid societal calamities.
SFI Professor Luis Bettencourt has been awarded $500,000 by the Army Research Office to do something akin to Asimov’s models, but as a very real technique to meet humankind’s contemporary challenges of environmental change, energy, infectious disease, and violence.
What brings such an idea out of science fiction and into the realm of genuine research, Bettencourt says, is the rapid expansion in the last decade of our ability to measure human and social behaviors across many levels of organizations.
“There has been relatively little progress in turning these increasing volumes of data into predictive scientific knowledge that can be used to intervene and avoid deeper problems,” he says. “Among the critical issues that can be studied relate to the robustness (or lack thereof) of large human social organizations, such as cities and nations, and to resource and environmental stress, and how these factors interact with internal dynamical and organizational structures, including the potential for decay and collapse.”
Although plenty of work has been done to try to capture the internal dynamics of organizations, such as firms or governments, and to model their decision structures, these models apply at best to a single level of organization and typically fail to predict accurately, or to be sensitive to, dynamics and inputs at different scales. Bettencourt wants to address these issues by building a theory based on empirical data about human social organizations across scales from firms to nations.
“It’s really about understanding the nature of these processes and learning how to interfere in them,” he says. “If you understand the nature of problems, specifically in terms of their potential for instability in positive or negative directions, you have a means to tilt the process to a benign outcome.”
The modeling effort draws on SFI's cities and urbanization research.
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