by Muhammad Aurangzeb Ahmad

Science Fiction literature is fraught with examples of what-ifs of history which speculate on how the would have looked like if certain events had happened a different way e.g., if the Confederates had won the American Civil War, if the Western Roman Empire had not fallen, if Islam had made inroads in the imperial household in China etc. At best these are speculations that we can entertain to shed light on our own world but imagine if there was a way to gauge how societies react under certain environmental constraints, social structures and stress. Simulation is often described as the Third Paradigm in Science and the field of Social Simulation seeks to model social phenomenon that cannot otherwise be studied because of practical and ethical constraints. Isaac Asimov envisions the science of predicting future with the psychohistory in the foundation series of science fiction novels.

The history of social simulation can be traced back to the idea of Cellular Automata by Stainlaw Ulam and John von Neumann: A cellular automata is a system of cell objects that can interact with its neighbors given a set of rules. The most famous example of this phenomenon being Conway’s Game of Life, which is a very simple simulation, that generates self-organizing patterns, which one could not really have predicted by just knowing the rules. To illustrate the concept of Social Simulation consider Schilling’s model of how racial segregation happens. Consider a two dimensional grid where each cell represents an individual. The cells are divided into two groups represented by different colors. Initially the cells are randomly seeded in the grid representing an integrated neighborhood. The cells however have preference with respect to what percentage of cells that are their neighbors should belong to the same group (color). The simulation is run for a large number of steps. At each step a person (cell) checks if the number of such neighbors is less than a pre-defined threshold then the person can move by a single cell. If the number of such neighbors meets the threshold then the person (cell) remains at its current position. Even with such a simple setup we observe that the integrated neighborhood slowly becomes segregated so that after some iterations the neighborhood is completed segregated. The evolution of the simulation can be observed in Figure 1. The main lesson to be learned here is that even without overt racism and just having a preference about one’s neighbors can lead to a segregated neighborhood.

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