15 episodes

Far-reaching conversations with a worldwide network of scientists and mathematicians, philosophers and artists developing new frameworks to explain our universe's deepest mysteries. Join host Michael Garfield at the Santa Fe Institute each week to learn about your world and the people who have dedicated their lives to exploring its emergent order: their stories, research, and insights…

COMPLEXITY Santa Fe Institute

    • Life Sciences

Far-reaching conversations with a worldwide network of scientists and mathematicians, philosophers and artists developing new frameworks to explain our universe's deepest mysteries. Join host Michael Garfield at the Santa Fe Institute each week to learn about your world and the people who have dedicated their lives to exploring its emergent order: their stories, research, and insights…

    15 - R. Maria del-Rio Chanona on Modeling Labor Markets & Tech Unemployment

    15 - R. Maria del-Rio Chanona on Modeling Labor Markets & Tech Unemployment

    Since the first Industrial Revolution, most people have responded in one of two ways to the threat of technological unemployment: either a general blanket fear that the machines are coming for us all, or an equally uncritical dismissal of the issue. But history shows otherwise: the labor market changes over time in adaptation to the complex and nonlinear ways automation eats economies. Some jobs are easier to lose but teach skills that translate to other more secure jobs; other kinds of work elude mechanization but are comparably easier for humans, and thus don’t provide the kind of job security one might suppose. By analyzing labor networks — studying the landscapes of how skillsets intersect with labor markets and these systems mutate under pressure from a changing technological milieu — researchers can make deeper and more practical quantitative models for how our world will shift along with evolutions in robotics and AI. Dispelling Chicken Little fears and challenging the sanguine techno-optimists, these models start to tell a story of a future not unlike the past: one in which Big Changes will disrupt the world we know, arrive unevenly, reshape terrains of privilege and hardship, and reward those who can dedicate themselves to lifelong learning.
    This week’s guest is R. Maria del Rio-Chanona, a Mathematics PhD student supervised by SFI External Professor Doyne Farmer at the University of Oxford. Before starting her PhD, Maria did her BSc in Physics at Universidad Nacional Autónoma de México and was a research intern at the International Monetary Fund, where she studied global financial contagion in multilayer networks. We met at the 2019 New Complexity Economics Symposium to discuss the use of agent-based models in economics, how the labor market changes in response to technological disruption, and the future of work.
    If you enjoy this podcast, please help us reach a wider audience by leaving a review at Apple Podcasts, or by sharing the show on social media. Thank you for listening!
    Visit our website for more information or to support our science and communication efforts.
    Join our Facebook discussion group to meet like minds and talk about each episode.
    Maria’s Website & Links to Papers.
    Maria’s Google Scholar Page.
    Andrew McAfee & Erik Brynjolfsson on Technological Unemployment.
    Carl Benedikt Frey & Michael A. Osborne on Technological Unemployment.
    Podcast Theme Music by Mitch Mignano.
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    • 50 min
    W. Brian Arthur (Part 2) on The Future of The Economy

    W. Brian Arthur (Part 2) on The Future of The Economy

    If the economy is better understood as an evolving system, an out-of-equilibrium ecology composed of agents that adapt to one another’s strategies, how does this change the way we think about our future? By drawing new analogies between technology and life, and studying how tools evolve by building on and recombining what has come before, what does this tell us about economics as a sub-process of our self-organizing biosphere? Over the last forty years, previously siloed scientific disciplines have come together with new data-driven methods to trace the outlines of a unifying economic theory, and allow us to design new human systems that anticipate the planet-wide disruptions of our rapidly accelerating age. New stories need to be articulated, ones that start earlier than human history, and in which societies work better when engineered in service to the laws of physics and biology they ultimately follow…
    This week’s guest is W. Brian Arthur, External Professor at the Santa Fe Institute, Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford, and Visiting Researcher at Xerox PARC.  In this second part of our two-episode conversation, we discuss technology as seen through the lens of evolutionary biology, and how he foresees the future of the economy as our labor market and financial systems are increasingly devoured by artificial intelligence.
    If you enjoy this podcast, please help us reach a wider audience by leaving a review at Apple Podcasts, or by sharing the show on social media. Thank you for listening!
    Visit our website for more information or to support our science and communication efforts.
    Join our Facebook discussion group to meet like minds and talk about each episode.
    Podcast Theme Music by Mitch Mignano.
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    Twitter • YouTube • Facebook • Instagram • LinkedIn
    Brian’s Website.
    Brian’s Google Scholar page.
    “Where is technology taking the economy?” in McKinsey, 2017.
    The Nature of Technology: What It Is and How It Evolves.
    “Punctuated equilibria: the tempo and mode of evolution reconsidered” by Gould & Eldredge.
    "A natural bias for simplicity" by Mark Buchanan in Nature Physics.
    "Economic Possibilities for our Grandchildren" by John Maynard Keynes.

    • 1 hr
    W. Brian Arthur (Part 1) on The History of Complexity Economics

    W. Brian Arthur (Part 1) on The History of Complexity Economics

    From its beginnings as a discipline nearly 150 years ago, economics rested on assumptions that don’t hold up when studied in the present day. The notion that our economic systems are in equilibrium, that they’re made of actors making simple rational and self-interested decisions with perfect knowledge of society— these ideas prove about as useful in the Information Age as Newton’s laws of motion are to quantum physicists. A novel paradigm for economics, borrowing insights from ecology and evolutionary biology, started to emerge at SFI in the late 1980s — one that treats our markets and technologies as systems out of balance, serving metabolic forces, made of agents with imperfect information and acting on fundamental uncertainty. This new complexity economics uses new tools and data sets to shed light on puzzles standard economics couldn’t answer — like why the economy grows, how sudden and cascading crashes happen, why some companies and cities lock in permanent competitive advantages, and how technology evolves. And complexity economics offers insights back to biology, providing a new lens through which to understand the vastly intricate exchanges on which human life depends.
    This week’s guest is W. Brian Arthur, External Professor at the Santa Fe Institute, Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford, and Visiting Researcher at Xerox PARC.  In this first part of a two-episode conversation, we discuss the heady early days when complex systems science took on economics, and how biology provided a new paradigm for understanding our financial and technological systems.  Tune in next week for part two...
    If you enjoy this podcast, please help us reach a wider audience by leaving a five-star review at Apple Podcasts, or by sharing the show on social media. Thank you for listening!
    Visit our website for more information or to support our science and communication efforts.
    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 • LinkedIn
    For more information:
    Brian’s Website.
    Brian’s Google Scholar page.
    “Where is technology taking the economy?” in McKinsey, 2017.
    The Nature of Technology: What It Is and How It Evolves.
    “Punctuated equilibria: the tempo and mode of evolution reconsidered” by Gould & Eldredge.

    • 57 min
    Matthew Jackson on Social & Economic Networks

    Matthew Jackson on Social & Economic Networks

    It may be a cliché, but it’s a timeless truth regardless: who you know matters. The connectedness of actors in a network tells us not just who wields the power in societies and markets, but also how new information spreads through a community and how resilient economic systems are to major shocks. One of the pillars of a complex systems understanding is the network science that reveals how structural differences lead to (or help counter) inequality and why a good idea alone can’t change the world. As human beings, who we are is shaped by those around us — not just our relationships to them but their relationships to one another. And the topology of human networks governs everything from the diffusion of fake news to cascading bank failures to the popularity of social influencers and their habits to the potency of economic interventions. To learn about your place amidst the networks of your life is to awaken to the hidden seams of human culture and the flows of energy that organize our world.
    This week’s guest is SFI External Professor Matthew O. Jackson, William D. Eberle Professor of Economics at Stanford University and senior fellow of CIFAR, also a Member of the National Academy of Sciences, and a Fellow of the American Academy of Arts and Sciences. In this episode, we discuss key insights from his book, The Human Network: How Your Social Position Determines Your Power, Beliefs, and Behaviors.
    For transcripts, show notes, research links, and more, please visit complexity.simplecast.com.
    And note that we’re taking a short break over the winter holiday. COMPLEXITY will be back with new episodes in January 2020.
    If you enjoy this show, please help us reach a wider audience by leaving a review at Apple Podcasts, or by telling your friends on social media…after this episode’s discussion, we know you’ll understand how crucial this can be. Thank you for listening!
    Visit our website for more information or to support our science and communication efforts.
    Join our Facebook discussion group to meet like minds and talk about each episode.
    Matthew Jackson’s Stanford Homepage.
    WSJ reviews The Human Network.
    Jackson’s Coursera MOOCs on Game Theory I, Game Theory II, and Social & Economic Networks.
    Podcast Theme Music by Mitch Mignano.
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    • 1 hr 5 min
    Ray Monk on The Lives of Extraordinary Individuals: Wittgenstein, Russell, Oppenheimer

    Ray Monk on The Lives of Extraordinary Individuals: Wittgenstein, Russell, Oppenheimer

    In this show’s first episode, David Krakauer explained how art and science live along an axis of explanatory depth: science strives to find the simplest adequate abstractions to explain the world we observe, where art’s devotion is to the incompressible — the one-offs that resist abstraction and attempts to write a unifying framework. Between the random and the regular, amidst the ligaments that bind our scientific and artistic inquiries, we find a huge swath of the world that we struggle to articulate in formal quantitative terms, but that rewards our curiosity and offers us profound insights regardless. Here lives the open question of what we can learn from history — specifically, the histories of other people’s lives.  Why do we love biographies?  What can the stories of the lives of others teach us about both situational and common truths of being?  This is a different kind of episode and conversation, one living at the intersection of philosophy and history and science…
    This week’s episode features guest interviewer, SFI President David Krakauer, in conversation with philosopher and biographer Ray Monk.  Monk teaches at the University of Southhampton and was SFI’s 2017 Miller Scholar, a position that he earned for his biographies of Ludwig Wittgenstein, Bertrand Russell, and J. Robert Oppenheimer — three mavericks whose legacies are lessons for contemporary leaders.
    If you enjoy this podcast, please help us reach a wider audience by leaving a five-star review at Apple Podcasts, or by sharing the show on social media. Thank you for listening!
    Visit our website for more information or to support our science and communication efforts.
    Join our Facebook discussion group to meet like minds and talk about each episode.
    Ray Monk on Twitter.
    Ray Monk’s SFI Miller Scholar Profile Page.
    Ray Monk on Hidden Forces Podcast.
    Podcast Theme Music by Mitch Mignano.
    Follow us on social media:
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    • 50 min
    Melanie Moses on Metabolic Scaling in Biology & Computation

    Melanie Moses on Metabolic Scaling in Biology & Computation

    What is the difference between 100 kilograms of human being and 100 kilograms of algae? One answer to this question is the veins and arteries that carry nutrients throughout the human body, allowing for the intricate coordination needed in a complex organism. Energy requirements determine how the evolutionary process settles on the body plans appropriate to an environment — one way to tell the story of life’s major innovations is in terms of how a living system solves the problems of increasing body size with internal transport networks and more extensive regulation. And the same is true in our invented information systems, every bit as subject to the laws of physics as we are. Computers, just like living tissue, seek effective tradeoffs between their scale and energy efficiency. A physics of metabolic scaling — one that finds deep commonalities and crucial differences between ant hives and robot swarms, between the physiology of elephants and server farms — can help explain some of the biggest puzzles of the fossil record and sketch out the likely future evolution of technology. It is already revolutionizing how we understand search algorithms and the genius of eusocial organisms. And just maybe, it can also help us solve the challenge of sustainability for planetary culture.
    This week’s guest is Melanie Moses, External Professor at the Santa Fe Institute, Professor of Computer Science and Biology at the University of New Mexico, and Principal Investigator for the NASA Swarmathon. In this episode, we talk about her highly interdisciplinary work on metabolic scaling in biology and computer information-processing, and how complex systems made and born alike have found ingenious ways to balance the demands of growth and maintenance — with implications for space exploration, economics, computer chip design, and more.
    If you enjoy this podcast, please help us reach a wider audience by leaving a five-star review at Apple Podcasts, or by sharing the show on social media. Thank you for listening!
    Visit our website for more information or to support our science and communication efforts.
    Join our Facebook discussion group to meet like minds and talk about each episode.
    Melanie’s UNM Webpage & full list of publications.
    “Beyond pheromones: evolving error-tolerant, flexible, and scalable ant-inspired robot swarms” by Joshua Hecker & Melanie Moses.
    “Energy and time determine scaling in biological and computer designs” by Moses, et al.
    “Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life” by DeLong, Moses, et al.
    “Distributed adaptive search in T cells: lessons from ants” by Melanie Moses, et al.
    “Curvature in metabolic scaling” by Kolokotrones, et al.
    The NASA Swarmathon.
    Podcast Theme Music by Mitch Mignano.
    Follow us on social media:
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    • 1 hr 6 min

Customer Reviews

GMOneyyYyy69 ,

Fascinating

This podcast fills a gaping hole in the podcast market. Super interesting stuff, helpful for learning about new and exciting research in complex systems. Off to a great start!

A. Non E. Mouse ,

Very interesting!

Very interesting material, and a great window into the world of complex systems and how experts think about them.

MissSlimskys ,

Fascinating stuff!

Important stuff presented in a way that even this non-scientist can understand. Highly recommended!

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