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