Making Sense of Chaos: A Better Economics for a Better World

We live in an age of increasing complexity, where accelerating technology and global interconnection hold more promise – and more peril – than any other time in human history. Financial crises, as well as issues around climate change, automation, growing inequality, and polarization are all rooted in the economy, yet standard economic predictions fail us. Using big data and ever more powerful computers, we can, for the first time, apply complex-systems science to economic activity, building realistic models of the global economy. The resulting simulations and the emergent behaviour we observe form the cornerstone of complexity economics. This new science, which grew in part from research conducted at the Santa Fe Institute, will allow us to test ideas and make significantly better economic predictions — and, ultimately, create a better world. This lecture is a tale of scientific discovery and adventure, an account of how these ideas came about and the people who made them happen. Doyne Farmer fuses his profound knowledge with stories from his life to explain how we are in the early stages of a scientific revolution that could address the economic conundrums facing society. Doyne Farmer is Director of Complexity Economics at the Institute for New Economic Thinking at the Oxford Martin School and is the Baillie Gifford Professor of Complex Systems Science at the University of Oxford’s Smith School of Enterprise and the Environment, as well as an External Professor at the Santa Fe Institute. His current research is in economics, including financial stability, sustainability, technological change, and economic simulation. Doyne is Chief Scientist at Macrocosm, his new Oxford spin-out company, which applies complexity economics to problems relating to climate change and the green energy transition. 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 spans complex systems, dynamical systems, time series analysis, and theoretical biology. He founded the Complex Systems Group at Los Alamos National Laboratory, and while a graduate student in the 1970s he built the first wearable digital computer, which was successfully used to predict the game of roulette. John Geanakoplos is the James Tobin Professor of Economics at Yale University. At Yale he has been Chair of the Yale Faculty of Arts and Sciences Senate, Director of the Cowles Foundation for Research in Economics for 9 years, and Chair of Hellenic Studies for 22 years. He was twice Director of the Economics Program at the Santa Fe Institute and later Chair of the Science Steering Committee for the Santa Fe Institute. He was Managing Director of Fixed Income Research at the investment bank Kidder Peabody and one of the founders in 1994 of the hedge fund Ellington Capital Management, where he remains a partner. He is a Fellow of the American Academy of Arts and Sciences and the Econometric Society, and a recipient of the Samuelson Prize and the Ross Prize. He has testified several times in Congress about mortgage debt forgiveness. He graduated summa cum laude from Yale University with a BA in Mathematics in 1975, and received his MA in Mathematics and his PhD in Economics at Harvard under Ken Arrow and Jerry Green in 1980. He won the 1970 United States Junior (under 21) Open Chess Championship. Learn more, follow us on social media and check out our podcasts: