Mitchell Waldrop's 'Complexity' brought complexity science into the limelight with an account of the early days of the Santa Fe Institute. One of the people who appear in this book is W. Brian Arthur, the engineer turned economist who found economics unsatisfactory — because it treated the economy purely as a system in equilibrium when he knew it very obviously wasn't. In this episode, you'll hear from W. Brian Arthur, External Professor at the Santa Fe Institute, and Researcher at Palo Alto Research Center, as he explains his journey to understanding the economy as a non-equilibrium system, and his work on increasing returns. But what are increasing returns? Well in complexity terms, it's how positive feedback affects the economy.   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.

Can you write a novel using only nouns? Well, maybe…but it won’t be very good, nor easy, nor will it tell a story. Verbs link events, allow for narrative, communicate becoming. So why, in telling stories of our economic lives, have people settled into using algebraic theory ill-suited to the task of capturing the fundamentally uncertain, open and evolving processes of innovation and exchange?Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.This week on Complexity, we bring our two-part conversation with SFI External Professor W. Brian Arthur to a climax — a visionary exploration of multiple scientific methodologies that takes us from the I Ching to AlphaGo, Henri Bergson to Claude Shannon, artificial life to a forgotten mathematics with the power to (just maybe) save the future from inadequate and totalizing axioms…We pick up by revisiting the end of Part 1 in Episode 68 — if you’re just tuning in, you’ll want to double back for vital context.If you value our research and communication efforts, please subscribe to Complexity Podcast wherever you prefer to listen, rate and review us at Apple Podcasts, and/or consider making a donation at santafe.edu/give. You can find numerous other ways to engage with us — including job openings for both SFI staff and postdoctoral researchers, as well as open online courses — at santafe.edu/engage.Thank you for listening!Join our Facebook discussion group to meet like minds and talk about each episode.Podcast theme music by Mitch Mignano.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedInRelated Reading & Listening:W. Brian Arthur on Complexity episodes 13, 14, & 68.“Economics in Nouns and Verbs” by W. Brian Arthur (+ @sfiscience Twitter thread excerpting the essay“Mathematical languages shape our understanding of time in physics” by Nicolas Gisin for Nature Physics“Quantum mechanical complementarity probed in a closed-loop Aharonov–Bohm interferometer” by Chang et al. in Nature Physics“Quantum interference experiments, modular variables and weak measurements” by Tollaksen et al. in New Journal of Physics

W. Brian Arthur, a leading economist and complexity theorist, delves into the intricate ties between technology and the economy. He discusses how technological innovations are often driven by functional needs, not just creative sparks. The conversation also highlights how geographic concentration can boost creativity and collaboration, as seen in places like Silicon Valley. Arthur explores the future of economies shaped by automation and the pressing need to address wealth concentration and collective responsibility. His insights bridge complexity with real-world implications.

W. Brian Arthur joins the show to explore how economic policies are gamed. They discuss gaming systems, manipulation in the 2008 financial crash, and the vulnerability of economic systems. They also delve into the consequences of private control over financial systems and the need for understanding and addressing these issues.

W. Brian Arthur, a pioneer in complexity economics, dives into the intricate dance of modern economies, emphasizing that traditional models often fall short. He explores how individual behaviors disrupt equilibrium and advocates for adaptable forecasting methods amidst chaotic interactions. The conversation compares insights from physics and biology to enhance our understanding of economic systems. Arthur also highlights the unpredictable nature of markets and the significance of embracing complexity to inform better policies and charitable giving.