Simplifying Complexity

A key part of complexity science is understanding the behaviour of networks. Networks are groups of interacting agents, and they're all around us; our friendship groups, our colleagues, and even interactions online are all examples of networks. But what role does influence and power play in these networks?  In today's episode, we're joined by Matthew Jackson, William D. Eberle Professor of Economics at Stanford University, and External Faculty of the Santa Fe Institute. Matthew is going to break down the key factors of a network, with an example from all the way back in the 1400s, featuring the Medici family. He'll explain how Cosimo de’ Medici used his network to wield power, and what about his network made it so successful.    Connect: Simplifying Complexity on Twitter Sean Brady on Twitter Sean Brady on LinkedIn Brady Heywood website This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.

In our last episode with Tyler Marghetis, we learnt about how a complex system can tip from one state into another. But what happens when systems don't tip or fail? What makes a system robust? In today's episode, we're talking with Karoline Wiesner, a Professor of Complexity Science in the Department of Physics and Astronomy at the University of Potsdam, Germany. She breaks down the characteristics of a robust system, through the context of an incredibly robust complex system — the ant colony.   Connect: Simplifying Complexity on Twitter Sean Brady on Twitter Sean Brady on LinkedIn Brady Heywood website This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.

A fascinating property of a system's behaviour is its ability to change, and change quickly. For example, how does an economy go from boom to bust so suddenly and unpredictably? That is to say, how does it 'tip' from one behaviour to another? What are these tipping points, and are they really as unpredictable as they seem? In today's episode, we speak to Tyler Marghetis, Assistant Professor of Cognitive and Information Sciences at the University of California Merced. He pulls apart the underlying reasons why the behaviour of a complex system can radically change. He also poses the question, can you tell when a system is about to tip?   Connect: Simplifying Complexity on Twitter Sean Brady on Twitter Sean Brady on LinkedIn Brady Heywood website This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.

What is complexity science, and why should you care about it? Well, complexity science is all about understanding the systems that are all around us — systems like the economy, your body, cities, companies, and the environment. To properly understand how these systems work, and how they fail, you need to understand complexity science. Because complexity science provides us with the underlying principles that govern these systems. In today's episode, we speak to David Krakauer, President and William H. Miller Professor of Complex Systems at the Santa Fe Institute. He explains the underlying principles of complex systems and what they have in common — even if they all seem completely unrelated. He also talks through the history of complexity science and provides his top three takeaways on how you can start to think about complex systems.   Connect: Simplifying Complexity on Twitter Sean Brady on Twitter Sean Brady on LinkedIn Brady Heywood website This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.