Abstract

Human survival depends on our ability to predict future outcomes so that we can make informed decisions. Human cognition and perception are optimized for local, short-term decision-making, such as deciding when to fight or flight, whom to mate, or what to eat. For more elaborate decisions (e.g., when to harvest, when to go to war or not, and whom to marry), people used to consult oracles—prophetic predictions of the future inspired by the gods. Over time, oracles were replaced by models of the structure and dynamics of natural, technological, and social systems. In the 21st century, computational models and visualizations of model results inform much of our decision-making: near real-time weather forecasts help us decide when to take an umbrella, plant, or harvest; where to ground airplanes; or when to evacuate inhabitants in the path of a hurricane, tornado, or flood (1). Long-term weather and climate forecasts predict a future with increasing torrential rains, stronger winds, and more frequent drought, landslides, and forest fires as well as rising sea levels, enabling decision makers to prepare for these changes by building dikes, moving cities and roads, and building larger water reservoirs and better storm sewers (2). Computational models are particularly useful if they are combined with high-quality data and if they are widely used and understood. As early as 1960, Buckminster Fuller proposed the “World Game” to address the world’s problems through a holistic and anticipatory systems approach (3, 4). The game used Fuller's Dymaxion Map to visualize resources, trends, and scenarios. It was meant to be accessible to everyone (not just experts); therefore, decisions could be made collectively, and results could be used by anyone. In the 1970s, “The limits to growth: A report to the club of Rome” (5) used simulations to forecast future states of the … [↵][1]1To whom correspondence should be addressed. Email: katy{at}indiana.edu. [1]: #xref-corresp-1-1

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