In Making Sense of Chaos: A better economics for a better world, J. Doyne Farmer challenges traditional economic models, which rely on simplistic assumptions and fail to provide accurate predictions. Farmer, a complex systems scientist at the University of Oxford and the Santa Fe Institute, argues that with technological advances in data science and computing, we are now able to apply complex systems thinking to build models that more accurately capture reality and enable us to make better predictions about the economy. Together with Martin Reeves, Chairman of the BCG Henderson Institute, Farmer discusses the limitations of standard models of economics as well as the consequences of such limitations. He proposes an alternative based on complex systems thinking and agent-based modeling—and describes how it can be applied in various fields, including business. Key topics discussed:  01:42 | Limitations of the standard model of economics 04:44 | How complex systems thinking works 09:01 | Consequences of using inadequate economic models 12:44 | Agent-based modeling as a powerful alternative 19:02 | Leveraging alternative modeling techniques in business 24:59 | How CEOs can start embracing complexity thinking This podcast uses the following third-party services for analysis: Chartable - https://chartable.com/privacy