From the motion of asteroids or weather patterns to pollution and climate change, science and technology provide us with ever-increasing abilities to understand our world through computer simulation.
But can we use this technology to understand how we are changing ourselves? Simulations allow us to predict things like traffic or epidemics, but when it comes to the small matter of the economy and society, we are not even making a serious effort. Why aren't we using simulations to understand the key problems facing society, such as the monopoly driven tendencies of the digital economy,the merits and perils of a basic income, or the way we measure growth? Is it feasible to simulate the economy? What could we achieve, and what are the challenges?
Academic, University of Oxford
J. Doyne Farmer is Director of the Complexity Economics program at the Institute for New Economic Thinking at the Oxford Martin School, Professor in the Mathematical Institute at the University of Oxford, and an External Professor at the Santa Fe Institute. His current research is in economics and finance, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology. During the eighties he was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student in the 70’s he build the first wearable digital computer, which was successfully used to predict the game of roulette.
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