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.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

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.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedInBrian’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.

W. Brian Arthur, an economics pioneer and complexity theory expert, discusses the shift from traditional economics to complexity economics, where markets are seen as systems out of balance. They talk about how complex systems evolve, the impact of technology on the economy, and the need to understand non-equilibrium conditions for dynamic strategies and innovations.

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.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

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:Twitter • YouTube • Facebook • Instagram • LinkedIn

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:Twitter • YouTube • Facebook • Instagram • LinkedIn

The podcast explores social learning and decision-making, including the influence of social networks and political ideologies on our understanding of climate change. It delves into biases in social judgments and the impact of biased social networks on accurate estimates of the general population. The trade-off between computational cost and efficiency in understanding social networks is discussed, as well as contradictory findings in problem-solving networks. The podcast also explores the influence of social and semantic networks on scientific beliefs, and techniques to respond to hate speech online.

It’s easy to take modern Earth for granted — our breathable atmosphere, the delicately balanced ecosystems we depend on — but this world is nothing like the planet on which life first found its foothold. In fact it may be more appropriate to think of life in terms of verbs than nouns, of processes instead of finished products. This is the evolutionary turn that science started taking in the 19th Century…but only in the last few decades has biology begun to see this planet’s soil, air, and oceans as the work-in-progress of our biosphere. The story of our planet can’t be adequately told without some understanding of how life itself depends on opportunities that life creates, based on the energy and mineral resources made as byproducts of our metabolisms. A new, revelatory narrative of the last 3.8 billion years refigures living systems in terms of thermodynamic flows and the ever-growing range of possibilities created by our ever-more-complex ecologies. And in the telling, this new history sheds light on some of the biggest puzzles of the fossil record: why complex animals took so long to appear, why humans are the way we are, and maybe even why the sky is blue.This week’s guest is evolutionary biologist and science journalist Olivia Judson, an honorary research fellow at The Imperial College of London who received her PhD from the University of Oxford and whose writing has appeared in The Economist, The New York Times, The Guardian, and National Geographic. She is also the author of the internationally best-selling popular science book, Dr. Tatiana’s Sex Advice to All Creation. In this episode, we discuss her work on major energy transitions in evolution (the subject of her next book), and what we can learn by studying the intimate dance of biology and geology over the last 4 billion years.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.Olivia’s Website.“The energy expansions of evolution” in Nature.The Atlantic on Olivia’s essay.Music by Mitch Mignano.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

Whether or not you think you hold them, stereotypes shape the lives of everyone on Earth. As human beings, we lack the ability to judge each situation as unique and different…and how we group novel experiences by our past conditioning, as helpful as it often is, creates extraordinary complications in society. As modern life exposes us to an increasing number of encounters with the other in which we do not have time to form accurate models of someone   or some place’s true identity, we find ourselves in a downward spiral of self-reinforcing biases — transforming how we practice law enforcement, justice, and life online. Our polarized, irrational world calls for an intense look at what it will take to humanize each other — at traffic stops, in court, on social media, and anywhere our doubt about an unfamiliar face can lead to tragic consequences.This week’s guest is Rajiv Sethi, Professor of Economics at Columbia University and External Professor at the Santa Fe Institute. In this episode, we discuss how biases in our attention and cognition lead to unfair outcomes on the streets and on the Web, and where we can look for hope in countervailing strategies.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.Shadows of Doubt: Stereotypes, Crime, and the Pursuit of Justice by Brendan O’Flaherty & Rajiv Sethi (Harvard University Press).Rajiv’s Website.Albert Kao & Iain Couzin on collective intelligence and modular societies.Aumann’s agreement theorem.“We can’t disagree forever” (Geanakopolos & Polemarchakis).Raissa D’Souza on the Collapse of Networks.Geoffrey West on scaling laws and cities.Music by Mitch Mignano.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

Looking back through time, the fossil record shows a remarkable diversity of forms, creatures unfamiliar to today’s Earth, suggesting ecosystems alien enough to challenge any sense of continuity. But reconstructed trophic networks — maps of who’s eating whom — reveal a hidden order that has been conserved since the first complex animals of half a billion years ago. These network models offer scientists an armature on which to hang new unifying theories of ecology, a way to answer questions about how energy moves through living systems, how evolution keeps producing creatures to refill specific niches, how mass extinctions happen, what minimal viable ecosystems are and why.  Untangling this deep structure of food webs may also shed light on technology and economics, and guide interventions to ensure sustainability in agriculture, conservation efforts, even venture capital investment.This week’s guest is Jennifer Dunne, SFI’s Vice President for Science and Fellow at the Ecological Society of America. Dunne got her PhD in Energy and Resources from UC Berkeley, joined SFI’s faculty in 2007, and sits on the advisory board for Nautilus Magazine.  In this second half of a two-part conversation, we discuss her work on reconstructing ancient food webs, and the implications of this research for our understanding of ecologies, extinctions, sustainability, and technological innovation.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.Jennifer Dunne’s Website.Related Reading:Modern Lessons from Ancient Food WebsParasites Affect Food Web Structure Primarily through Increased Diversity and ComplexityHighly resolved early Eocene food webs show development of modern trophic structure after the end-Cretaceous extinctionThe roles and impacts of human hunter-gatherers in North Pacific marine food websA primer on the history of food web ecology: Fundamental contributions of fourteen researchersQuanta Magazine features Dunne on humans in food webs.Jennifer on This Week in Science at InterPlanetary Festival 2019.Learn more about The ArchaeoEcology Project.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn