Simplifying Complexity

When a system fails, how do you think about cause and effect? One way to consider this in complex systems is to imagine a pile of sand, and dropping one grain of sand at a time in random positions onto the pile. As time passes, you'll start to form little hills. Eventually, a grain of sand will hit one of these hills, and you get an avalanche. Do you believe that the avalanche was caused by the last grain of sand falling onto it, or do you believe that the avalanche happened due to the shape of the hill itself? To explore this sand pile model, we are joined today by Neil Johnson, Professor of Physics and Head of the Dynamic Online Networks Lab at George Washington University.   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.

When most of us think about information, we think of it as something we can possess or ‘know’. But what if it’s so much more than that? In this episode, we’re joined by Sara Walker, Deputy Director of the Beyond Center for Fundamental Concepts in Science, Associate Professor in Earth and Space Exploration and Complex Adaptive Systems at Arizona State University, and External Faculty at the Santa Fe Institute. Sara is going to examine information and the critical role it plays in 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.

Imagine you have a bar that comfortably seats 60 people, but every week, 100 people have to decide whether or not they're going to go to the bar on any given night. If too many people go, then the bar is too crowded, and everyone has a miserable night. But if not enough people go, then that's a missed opportunity to go out. This is the basis of the El Farol problem, which asks us to consider how people make this decision. It's a beautifully simple problem that not only makes you think but also has profound implications. To help us through this problem, we're joined again by its inventor, W. Brian Arthur, External Professor at the Santa Fe Institute and Researcher at Palo Alto Research Center. Brian's going to help us understand how this problem is more than just the story of a bar, but a problem that gives us an incredible insight into how the economy works.   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, we talked about the four conditions of complex systems: numerosity, disorder and diversity, feedback, and non-equilibrium — and we also talked about the concept of emergence. In this episode, which is part two of our two-part series on the features of complex systems, we're joined again by Karoline Wiesner, Professor of Complexity Science in the Department of Physics and Astronomy at the University of Potsdam in Germany. In this episode, Karoline explains the six emergent features of complex systems:  Spontaneous order and self-organisation Non-linearity Robustness Nested structure and modularity History and memory Adaptive behaviour  By the time you've finished this episode, you'll understand the underlying principles of complex systems that hold together the wide variety of topics we talk about in this series.   Resources and links: Karoline’s book ‘What Is a Complex System?’ Simplifying Complexity - What makes ant colonies robust?  Simplifying Complexity - The Economy and Complexity Science: Part 2    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 most of our episodes so far, we've taken a single concept and looked at it through the context of a single example. But in this episode and the next, we're going to pull back the camera to get a bird's-eye view of complexity science, by exploring the features common to all complex systems. We're joined again by Karoline Wiesner, Professor of Complexity Science in the Department of Physics and Astronomy at the University of Potsdam in Germany. In this episode, Karoline is going to explain four conditions that we see in complexity science: numerosity, disorder and diversity, feedback, and non-equilibrium. At the end of the episode, she's going to bring them all together to explain a central concept of complex systems: emergence.   Resources and links: Karoline’s book ‘What Is a Complex System?’   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 we talked all about intelligence, specifically about what made us intelligent. In this episode we jump into artificial intelligence, and we're joined again by David Krakauer, President and William H. Miller Professor of Complex Systems at the Santa Fe Institute.  This episode was recorded before the release of GPT-4, so David doesn't mention it specifically, but he does take us through the history of artificial intelligence, from Alan Turing, all the way to machine learning and neural networks. And he's going to ask the question: Are we really building something that's intelligent, or are we just building mimics and parrots?    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.

With the recent release of GPT-4, now seemed like a good time for our episodes on intelligence. And not just artificial intelligence, but intelligence in general. To help us on this journey, we're joined again by David Krakauer, President and William H. Miller Professor of Complex Systems at the Santa Fe Institute. This episode is part one of our two-part conversation with David about intelligence. In part 2, David is going to cover artificial intelligence. But in this episode, we're going back to basics and David asks, what is it that makes us intelligent?   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.

If there's one type of music that goes particularly well with complexity science, it's free jazz. The sort of jazz that you get when you put a group of musicians together without a conductor or any written music. But despite this, they still produce incredible music. So how does this group of musicians play so tightly together, whilst creating such dramatic changes to their music? In this episode, we're joined again by Tyler Marghetis, Assistant Professor of Cognitive and Information Sciences at the University of California, Merced. Tyler is going to return to the concept of tipping points, but this time, he's going to explore tipping points through the context of jazz music. To understand how they occur, he's going to go to one of the most unlikely places for help: the study of ecologies.   Resources and links: 'Zadok the Priest' by Handel - Classical (composed) - This piece tips at 01:22 Listen on Spotify Listen on YouTube 'Implosion' by Alex Levine Quartet - Free jazz (improvised) - This piece tips between 00:10 to 00:30, and again between 02:20 to 02:40. Listen on Spotify Listen on YouTube   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.

Imagine you were going to Mars with a swarm of robots, and you needed to send those robots out foraging. How would you program them? A traditional top-down approach to programming would mean programming what every single robot is going to do, and that's going to get complicated fast.  So in this episode, we're joined by Melanie Moses, Professor of Computer Science at the University of New Mexico, and External Faculty at the Santa Fe Institute. Melanie is going to explain how you can take lessons from complexity science, and utilise a bottom-up approach to programming a swarm. In other words, she's going to explain how you can program the robots to interact with one another. And if you thought you'd heard the end of scaling or power laws, then you're in for a surprise, because Melanie is going to share how scaling fits in with her work on getting robots to work as a team.    Resources and links: Simplifying Complexity - How do bees self organise? Simplifying Complexity - Scaling 1: Why do we live longer than mice? Simplifying Complexity - Scaling 2: You and I are fractals Simplifying Complexity - Scaling 3: Why companies die, but cities don’t Complexity - Melanie Moses on Metabolic Scaling in Biology & Computation   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 the last few episodes, we learnt all about scaling laws or power laws and how they apply to mammals. In this episode, the final part of our discussion of scaling and complex systems, for now, we're looking even bigger.  We're joined again by Geoffrey West, Shannan Distinguished Professor and Former President of the Santa Fe Institute, who in this episode will be leaving mammals behind to look at other complex systems. In particular, Geoffrey is going to explain how scaling laws apply to cities or companies.    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.