Podcast appearances and mentions of luis bettencourt

What will the city of the future be like? To explore the future of our cities, we're joined once more by Luis Bettencourt, Professor at the University of Chicago and External Faculty at the Santa Fe Institute, as he explains how urban areas will need to evolve in terms of infrastructure and sustainability to match pace with growing populations around the world.   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 role do cities play in driving economic progress? In today's episode, we're joined by Luis Bettencourt, Professor at the University of Chicago and External Faculty at the Santa Fe Institute, who explains how cities allow us to do something magical - they allow us to specialise.   Resources: Luis Bettencourt on Simplifying Complexity - Cities as social reactors Geoffrey West on Simplifying Complexity - Scaling 3: Why companies die, but cities don't    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.

”TBD” / Rose and Luis Bettencourt / Omegaman Episode 10516 Recorded 10-13-2023 on OMEGAMAN  

”TBD” / Rose and Luis Bettencourt / Omegaman Episode 10516 Recorded 10-13-2023 on OMEGAMAN  

Today we're joined by Luis Bettencourt, Professor at the University of Chicago, and External Faculty at the Santa Fe Institute. Luis is going to pull apart how cities work, why they work the way they do, what's good about them, and what's bad about them. He's also going to talk specifically about slums, and the challenges that exist in raising people out of poverty.   Resources and links: 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   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.

One way of looking at the world reveals it as an interference pattern of dynamic, ever-changing links — relationships that grow and break in nested groups of multilayer networks. Identity can be defined by informational exchange between one cluster of relationships and any other. A kind of music starts to make itself apparent in the avalanche of data and new analytical approaches that a century of innovation has availed us. But just as with new music genres, it requires a trained ear to attune to unfamiliar order…what can we learn from network science and related general, abstract mathematical approaches to discovering this order in a flood of numbers?Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I'm your host, Michael Garfield, and in every episode we 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 we speak with SFI External Professor, UCLA mathematician Mason Porter (UCLA Website, Twitter, Google Scholar, Wikipedia), about his research on community detection in networks and the topology of data — going deep into a varied toolkit of approaches that help scientists disclose deep structures in the massive data-sets produced by modern life.If you value our research and communication efforts, please subscribe, rate and review us at Apple Podcasts or Spotify, and consider making a donation — or finding other ways to engage with us — at santafe.edu/engage.I know it comes as a surprise, but this is our penultimate episode.  Please stay tuned for one more show in May when SFI President David Krakauer and I will reflect on major themes and highlights from the last three-and-a-half years, and look forward to what I'll be doing next! It's been an honor and a pleasure to bring complex systems science to you in this way, and hope we stay in touch. I won't be hard to find.Thank you for listening.Podcast theme music by Mitch Mignano.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedInMentioned & Related Media:Bounded Confidence Models of Opinion Dynamics on NetworksSFI Seminar by Mason Porter (live Twitter coverage & YouTube stream recording)Communities in Networksby Mason Porter, Jukka-Pekka Onnela, & Peter MuchaSocial Structure of Facebook Networksby Amanda Traud, Peter Mucha, & Mason PorterCritical Truths About Power Lawsby Michael Stumpf & Mason PorterThe topology of databy Mason Porter, Michelle Feng, & Eleni KatiforiComplex networks with complex weightsby Lucas Böttcher & Mason A. PorterA Bounded-Confidence Model of Opinion Dynamics on Hypergraphsby Abigail Hicock, Yacoub Kureh, Heather Z. Brooks, Michelle Feng, & Mason PorterA multilayer network model of the coevolution of the spread of a disease and competing opinionsby Kaiyan Peng, Zheng Lu, Vanessa Lin, Michael Lindstrom, Christian Parkinson, Chuntian Wang, Andrea Bertozzi, & Mason PorterSocial network analysis for social neuroscientistsElisa C Baek, Mason A Porter, & Carolyn ParkinsonCommunity structure in social and biological networksby Michelle Girvan & Mark NewmanThe information theory of individualityby David Krakauer, Nils Bertschinger, Eckehard Olbrich, Jessica C Flack, Nihat AySocial capital I: measurement and associations with economic mobilityby Raj Chetty, Matthew O. Jackson, Theresa Kuchler, Johannes Stroebel, Nathaniel Hendren, Robert B. Fluegge, Sara Gong, Federico Gonzalez, Armelle Grondin, Matthew Jacob, Drew Johnston, Martin Koenen, Eduardo Laguna-Muggenburg, Florian Mudekereza, Tom Rutter, Nicolaj Thor, Wilbur Townsend, Ruby Zhang, Mike Bailey, Pablo Barberá, Monica Bhole & Nils Wernerfelt Hierarchical structure and the prediction of missing links in networksby Aaron Clauset, Cristopher Moore, M.E.J. NewmanGregory Bateson (Wikipedia)Complexity Ep. 99 - Alison Gopnik on Child Development, Elderhood, Caregiving, and A.I.“Why Do We Sleep?”by Van Savage & Geoffrey West at Aeon MagazineComplexity Ep. 4 - Luis Bettencourt on The Science of CitiesComplexity Ep. 12 - Matthew Jackson on Social & Economic NetworksComplexity Ep. 68 - W. Brian Arthur on Economics in Nouns and Verbs (Part 1)Complexity Ep. 100 - Dani Bassett & Perry Zurn on The Neuroscience & Philosophy of Curious Minds 

Luis Bettencourt is a respected theoretical physicist who serves as theInaugural Director of the Mansueto Institute for Urban Innovation with the University ofChicago and is an external professor at the Santa Fe Institute. Here, he tells Travis about hisinterest in cities and city development and his interest in social change.Host: Travis VaughnSponsor: coreMEDIA - http://www.coremediasource.comVoyager is a production of coreMEDIA.Audio editing and mixing: James Curtis and Kevin DuthuProducer: Kevin DuthuRecording and coordination: Beth GrabenkortSong Credits: "Like the Ocean" by The Big Let Down & "Could be Anyone" by Courses. Music provided by Epidemic Sound.https://vaughngroup.io/voyager/

COVID has exposed and possibly amplified the polarization of society. What can we learn from taking a multiscale approach to crisis response? There are latencies in economies of scale, inequality of access and supply chain problems. The virus evolves faster than peer review. Science is politicized. But thinking across scales offers answers, insights, better questions…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 conclude our conversation (recorded on December 9th last year) with SFI External Professors Kathy Powers, Associate Professor of Political Science at the University of New Mexico, and Melanie Moses, Director of the Moses Biological Computation Lab at the University of New Mexico.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. Please also be aware of our new SFI Press book, The Complex Alternative, which gathers over 60 complex systems research points of view on COVID-19 (including those from this show). Learn more at SFIPress.org. 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:“Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection”by Melanie E. Moses et al. incl. Stephanie Forrest“Sunsetting As An Adaptive Strategy”by Roberta Romano and Simon A. Levin“The Virus That Infected The World”by David Krakauer & Dan RockmoreA Model For A Just COVID-19 Vaccination ProgramLegacies of Harm, Social Mistrust & Political Blame Impede A Robust Societal Response to The Evolving COVID-19 PandemicHow To Fix The Vaccine RolloutModels That Protect The VulnerableComplexities in Repair for Harm (Kathy's SFI Seminar)"The inevitable shift towards science as crisis response is a call to arms for complexity science. How well we will be able to meet these challenges will determine the future path of humanity."- Miguel FuentesAlso Mentioned:Jessica Flack, James C. Scott, Sam Bowles, Wendy Carlin, Joseph Henrich, Luis Bettencourt, Matthew Jackson, David Kinney

Some people say we're all in the same boat; others say no, but we're all in the same storm. Wherever you choose to focus the granularity of your inquiry, one thing is certain: we are all embedded in, acting on, and being acted upon by the same nested networks. Our fates are intertwined, but our destinies diverge like weather forecasts, hingeing on small variations in contingency: the circumstances of our birth, the changing contexts of our lives. Seen through a complex systems science lens, the problem of unfairness — in economic opportunity, in health care access, in susceptibility to a pandemic — stays wicked. But the insights therein could steer society toward a much better future, or at least help mitigate the worst of what we're left to deal with now. This is where the rubber meets the road — where quantitative models of the lung could inform economic policy, and research into how we make decisions influences who survives the complex crises of this decade.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, in a conversation recorded on December 9th 2021, we speak with SFI External Professors Kathy Powers, Associate Professor of Political Science at the University of New Mexico, and Melanie Moses, Director of the Moses Biological Computation Lab at the University of New Mexico. In the first part of a conversation that — like COVID itself — will not be contained, and spends much of its time visiting the poor and under-represented, we discuss everything from how the network topology of cities shapes the outcome of an outbreak to how vaccine hesitancy is a path-dependent trust fail anchored in the history of oppression. Melanie and Kathy offer insights into how to fix the vaccine rollout, how better scientific models can protect the vulnerable, and how — with the help of complex systems thinking — we may finally be able to repair the structural inequities that threaten all of us, one boat or many.  Subscribe for Part Two in two weeks!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. Please also be aware of our new SFI Press book, The Complex Alternative, which gathers over 60 complex systems research points of view on COVID-19 (including those from this show) — and that PhD students are now welcome to apply for our tuitionless (!) Summer 2022 SFI GAINS residential program in Vienna. Learn more at SFIPress.org and SantaFe.edu/Gains, respectively. 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:A Model For A Just COVID-19 Vaccination ProgramLegacies of Harm, Social Mistrust & Political Blame Impede A Robust Societal Response to The Evolving COVID-19 PandemicHow To Fix The Vaccine RolloutModels That Protect The VulnerableComplexities in Repair for Harm (Kathy's SFI Seminar)How a coastline 100 million years ago influences modern election results in Alabama @ Reddit

It feels like our world has never faced so many crisis all at the same time, and trying to solve them at once seems impossible. But, in 2015, the United Nations came together to develop a list of 17 Sustainable Development Goals, a blueprint for addressing all of humanity's problems—from poverty to climate change to peace and justice. And, amazingly, every UN nation signed it. So, how is it going? On this episode, we talk with Chris Williams, the director of UN Habitat; and Prof. Luis Bettencourt, director of the Mansueto Institute for Urban Innovation at the University of Chicago, to get some insight on how they've been studying and working on these goals, as well as their perspective on the current state of our global crisis moving forward.

This week we conclude our two-part discussion with ecologist Mark Ritchie of Syracuse University on how he and his SFI collaborators are starting to rethink the intersections of thermodynamics and biology to better fit our scientific models to the patterns we observe in nature. Most of what we know about the enzymatic processes of plant and animal metabolisms comes from test tube experiments, not studies in the context of a living organism. What changes when we zoom out and think about life's manufacturing and distribution in situ?Starting where we left off in in Episode 62, we tour the implications of Mark's biochemistry research and ask: What can studying the metabolism of cells tell us about economics? How does a better model of photosynthesis change the way we think about climate change and the future of agriculture? Why might a pattern in the failure of plant enzymes help biologists define where to direct the search for life in space?A better theory of the physics of biomolecules — and the networks in which they're embedded — provides a clearer understanding of the limits for all living systems, and how those limits shape effective strategies for navigating our complex world.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.If you value our research and communication efforts, please subscribe, rate, and review this show at Apple Podcasts, and/or consider making a donation at santafe.edu/give. You can find numerous other ways to engage with us at santafe.edu/engage. Thank you for listening!Join our Facebook discussion group to meet like minds and talk about each episode.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedInRelated Reading & Listening:Ritchie Lab at Syracuse University | Mark's Google Scholar Page | Mark's soil ecology startupReaction and diffusion thermodynamics explain optimal temperatures of biochemical reactionsby Mark Ritchie in Scientific ReportsThermodynamics Of Far From Equilibrium Systems, Biochemistry, And Life In A Warming World [Mark Ritchie's 2021 SFI Seminar + @SFIscience Twitter thread on Mark's talk]Scale and information-processing thresholds in Holocene social evolutionby Jaeweon Shin, Michael Holton Price, David H. Wolpert, Hajime Shimao, Brendan Tracey & Timothy A. KohlerGeneralized Stoichiometry and Biogeochemistry for Astrobiological Applicationsby Christopher P. Kempes, Michael J. Follows, Hillary Smith, Heather Graham, Christopher H. House & Simon A. Levin Complexity 4: Luis Bettencourt on The Science of CitiesComplexity 5: Jennifer Dunne on Food Webs & ArchaeoEcologyComplexity 17: Chris Kempes on The Physical Constraints on Life & EvolutionComplexity 35: Scaling Laws & Social Networks in The Time of COVID-19 with Geoffrey WestComplexity 41: Natalie Grefenstette on Agnostic Biosignature DetectionAlien Crash Site 15: Cole Mathis on Pathway Assembly and AstrobiologyPodcast theme music by Mitch Mignano.Cover artwork adapted from photos by Peter Nguyen and Torsten Wittmann (UCSF).

02:13 - Michael’s Superpower: Being Able to Creatively Digest and Reconstruct Categories * Integral Theory (https://en.wikipedia.org/wiki/Integral_theory_(Ken_Wilber)) * Creative Deconstruction – Michael Schwartz (https://ideas.repec.org/f/psc306.html) * Creating Truly Novel Categories – Recognizing Novelty as Novelty 09:39 - Recognizing Economic Value of Talents & Abilities * Invisible Labor * Ecosystem Services * Biodiversity; The Diversity Bonus by Scott Page (https://www.amazon.com/Diversity-Bonus-Knowledge-Compelling-Interests/dp/0691176884) 18:49 - The Edge of Chaos; Chaos Theory (https://en.wikipedia.org/wiki/Chaos_theory) * “Life exists at the edge of chaos.” 23:23 - Reproducibility Crisis and Context-Dependent Insight 28:49 - What constitutes a scientific experiment? * Missed Externalities * Scholarly articles for Michelle Girvan "reservoir computing" (https://scholar.google.com/scholar?q=Michelle+Girvan+reservoir+computing&hl=en&as_sdt=0&as_vis=1&oi=scholart) * Non-conformity 38:03 - The Return of Civil Society and Community Relationships; Scale Theory * Legitimation Crisis by Juergen Habermas (https://www.amazon.com/Legitimation-Crisis-Juergen-Habermas/dp/0807015210) * Scale: The Universal Laws of Life and Death in Organisms, Cities and Companies by Geoffrey West (https://www.amazon.com/Scale-Universal-Organisms-Cities-Companies-ebook/dp/B010P7Z8J0) 49:28 - Fractal Geometry More amazing resources from Michael to check out: Michael Garfield: Improvising Out of Algorithmic Isolation (https://blog.usejournal.com/improvising-out-of-algorithmic-isolation-7ef1a5b94697?gi=e731ad1488b2) Michael Garfield: We Will Fight Diseases of Our Networks By Realizing We Are Networks (https://michaelgarfield.medium.com/we-will-fight-diseases-of-our-networks-by-realizing-we-are-networks-7fa1e1c24444) Reflections: Jacob: Some of the best ideas, tv shows, music, etc. are the kinds of things that there’s not going to be an established container. Rein: “Act always so as to increase the number of choices.” ~ Heinz von Foerster Jessica: Externality. Recognize that there’s going to be surprises and find them. Michael: Adaptability is efficiency aggregated over a longer timescale. This episode was brought to you by @therubyrep (https://twitter.com/therubyrep) of DevReps, LLC (http://www.devreps.com/). To pledge your support and to join our awesome Slack community, visit patreon.com/greaterthancode (https://www.patreon.com/greaterthancode) To make a one-time donation so that we can continue to bring you more content and transcripts like this, please do so at paypal.me/devreps (https://www.paypal.me/devreps). You will also get an invitation to our Slack community this way as well. Transcript: JACOB: Hello and welcome to Episode 234 of Greater Than Code. My name is Jacob Stoebel and I’m joined with my co-panelist, Rein Henrichs. REIN: Thanks, Jacob and I’m here with my friend and co-panelist, Jessica Kerr. JESSICA: Thanks, Rein and today, I’m excited to introduce our guest, Michael Garfield. He’s an artist and philosopher and he helps people navigate our age of accelerating weirdness and cultivate the curiosity and play we need to thrive. He hosts and produces two podcasts, The Future Fossils Podcast & The Santa Fe Institute's Complexity Podcast. Yay, complexity! Michael acts as interlocutor for a worldwide community of artists, scientists, and philosophers—a practice that feeds his synthetic and transdisciplinary “mind-jazz” performances in the form of essay, avant-guitar music, and painting! You can find him on Bandcamp, it’s pretty cool. Refusing to be enslaved by a single perspective, creative medium, or intellectual community, Michael walks through the walls between academia and festival culture, theory and practice. Michael, welcome to Greater Than Code! MICHAEL: Thanks! I’m glad to be here and I hope that I provide a refreshingly different guest experience for listeners being not a coder in any kind of traditional sense. JESSICA: Yet you’re definitely involved in technology. MICHAEL: Yeah, and I think the epistemic framing of programming and algorithms is something that can be applied with no understanding of programming languages as they are currently widely understood. It’s just like design is coding, design of the built environment, so. JESSICA: And coding is a design. MICHAEL: Indeed. JESSICA: Okay, before we go anywhere else, I did not prepare you for this, but we have one question that we ask all of our guests. What is your superpower and how did you acquire it? MICHAEL: I would like believe that I have a superpower in being able to creatively digest and reconstruct categories so as to drive new associations between them for people and I feel like I developed that studying integral theory in grad school. I did some work under Sean Esbjörn-Hargens at John F. Kennedy University looking at the work of and work adjacent to Ken Wilber, who was trying to come up with a metatheoretical framework to integrate all different domains of human knowledge. All different types of inquiry into a single framework that doesn't attempt to reduce any one of them to any other and then in that process, I learned what one of my professors, Michael Schwartz, called creative deconstruction. So showing how art can be science and science can be art and that these aren't ontologically fixed categories that exist external to us. Looking at the relationship between science as a practice and spiritual inquiry as a practice and that kind of thing. So it's an irreverent attitude toward the categories that we've constructed that takes in a way a cynical and pragmatic approach to the way that we define things in our world. You know. REIN: Kant was wrong. [laughs] MICHAEL: It's good to get out of the rut. Obviously, you’ve got to be careful because all of these ideas have histories and so you have to decide whether it's worth trying to redefine something for people in order to open up new possibilities in the way that these ideas can be understood and manipulated. It's not, for example, an easy task to try and get people to change their idea about what religion is. [laughs] JESSICA: Yeah. More than redefined. It's almost like undefined. MICHAEL: Hm. Like Paul Tillich, for example. Theologian Paul Tillich said that religion is ultimate concern. So someone can have a religion of money, or a religion of sex, but if you get into these, if you try to interpose that in a debate on intelligent design versus evolutionary theory, you'll get attacked by both sides. JESSICA: [chuckles] That’s cosmology. MICHAEL: Yeah. So it's like – [overtalk] JESSICA: Which is hard to [inaudible] of money, or sex. MICHAEL: Yeah, but people do it anyhow. JESSICA: [laughs] Yeah. So deconstructing categories and seeing in-between things that fits through your walking through walls, what categories are you deconstructing and seeing between lately? MICHAEL: Well, I don't know, lately I've been paying more attention to the not so much tilting after the windmills of this metamorphic attitude towards categories, but looking at the way that when the opportunity comes to create a truly novel category, what are the forces in play that prevent that, that prevent recognizing novelty as novelty that I just – JESSICA: Do you have any examples? MICHAEL: Yeah, well, I just saw a really excellent talk by UC Berkeley Professor Doug Guilbeault, I think is how you say his name. I am happy to link his work to you all in the chat here so that you can share it. JESSICA: Yeah, we’ll link that in the show notes. MICHAEL: He studies category formation and he was explaining how most of the research that's been done on convergent categorization is done on established categories. But what happens when you discover something truly new? What his research shows is that basically the larger the population, the more likely it is that these categories will converge on something that's an existing category and he compared it to island versus mainland population biogeography. So there's a known dynamic in evolutionary science where genetic drift, which is just this random component of the change in allele frequencies in a population, the larger the population, the less likely it is that a genetic mutation that is otherwise neutral is going to actually percolate out into the population. On an island, you might get these otherwise neutral mutations that actually take root and saturate an entire community, but on the mainland, they get lost in the noise. You can look at this in terms of how easy it is for an innovative, artistic, or musical act to actually find any purchase. Like Spotify bought the data analysis company, The Echo Nest, back in 2015 and they ran this study on where emergent musical talent comes from. It comes from places like Australia, the UK, and Iceland, because the networks are small enough. This is a finding that's repeated endlessly through studies of how to create a viral meme that basically, or another way – JESSICA: You mean a small enough pool to take hold? MICHAEL: Yeah. That basically big science and large social networks online and these other attempts, anywhere we look at this economies of scale, growing a given system, what happens is—and we were talking about this a little before we got on the call—as a system scales, it becomes less innovative. There's less energy is allocated to – JESSICA: In America? MICHAEL: Yeah. Bureaucratic overhead, latencies in the network that prevent the large networks from adapting, with the same agility to novel challenges. There's a lot of different ways to think about this and talk about this, but it basically amounts to, if you want to, you can't do it from the conservative core of an organization. You can't do it from the board of directors. JESSICA: Oh. MICHAEL: You have to go out onto – like why did they call it fringe physics? It's like, it is because it's on the fringe and so there's a kind of – JESSICA: So this would be like if you have like one remarkably lowercase agile team inside your enterprise, one team is innovating and development practices. They're going to get mushed out. Whereas, if you have one team innovating like that in a small company, it might spread and it might become dominant. MICHAEL: Yeah. I think it's certainly the case that this speaks to something I've been wondering about it in a broader sense, which is how do we recognize the economic value of talents and abilities that are like, how do we recognize a singular individual for their incompressible knowledge and expertise when they don't go through established systems of accreditation like getting a PhD? Because the academic system is such that basically, if you have an innovative contribution, but you don't have the credentials that are required to participate in the community of peer review, then people can't even – your contribution is just invisible. The same is true for how long it took, if you look at economic models, it took so long for economic models to even begin to start addressing the invisible labor of women in at home like domestic labor, or what we're now calling ecosystem services. So there's this question of – I should add that I'm ambivalent about this question because I'm afraid that answering it in an effective way, how do we make all of these things economically visible would just accelerate the rate at which the capitalist machine is capable of co-opting and exploiting all of these. [chuckles] REIN: Yeah. You also have this Scott Seeing Like a State thing where in order to be able to even perceive that that stuff is going on, it has to become standardized and you can't dissect the bird to observe its song, right? MICHAEL: Totally. So obviously, it took almost no time at all for consumer culture to commodify the psychedelic experience and start using to co-opt this psychedelic aesthetic and start using it in advertising campaigns for Levi's Jeans and Campbell Soup and that kind of thing. So it’s this question of a moving frontier that as soon as you have the language to talk about it, it's not the ineffable anymore. REIN: Yeah. MICHAEL: There's a value to the ineffable and there's a value to – it's related to this question of the exploitation of indigenous peoples by large pharmaceutical companies like, their ethnobotanical knowledge. How do you make the potential value of biodiversity, something that can be manufactured into medicine at scale, without destroying the rainforest and the people who live in it? Everywhere I look, I see this question. So for me, lately, it's been less about how do we creatively deconstruct the categories we have so much as it is, what is the utility of not knowing how to categorize something at all and then how do we fix the skewed incentive structures in society so as to value that which we currently do not know how to value. JESSICA: Because you don’t have a category for it. MICHAEL: Right. Like right now, maybe one of the best examples, even though this is the worst example in another way, is that a large fraction of the human genome has been patented by Monsanto, even though it has no known current biomedical utility. This is what Lewis Hyde in his book, Common as Air, called “the third enclosure” of the common. So you have the enclosure of the land that everyone used to be able to hunt on and then you have the enclosure of intellectual property in terms of patents for known utilities, known applications, and then over the last few decades, you're starting to see large companies buy their way into and defend patents for the things that actually don't – it's speculative. They're just gambling on the idea that eventually we'll have some use for this and that it's worth lawyering up to defend that potential future use. But it's akin to recognizing that we need to fund translational work. We need to fund synthesis. We need to fund blue sky interdisciplinary research for which we don't have an expected return on investment here because there's – JESSICA: It's one of those things that it’s going to help; you're going to get tremendous benefits out of it, but you can't say which ones. MICHAEL: Right. It's a shift perhaps akin to the move that I'm seeing conservation biology make right now from “let's preserve this charismatic species” to “let's do everything we can to restore biodiversity” rather than that biodiversity itself is generative and should be valued in its own regard so diverse research teams, diverse workplace teams. We know that there is what University of Michigan Professor Scott Page calls the diversity bonus and you don't need to know and in fact, you cannot know what the bonus is upfront. JESSICA: Yeah. You can't draw the line of causality forward to the benefit because the point of diversity is that you get benefits you never thought of. MICHAEL: Exactly. Again, this gets into this question of as a science communications staffer in a position where I'm constantly in this weird dissonant enters zone between the elite researchers at the Santa Fe Institute where I work and the community of complex systems enthusiasts that have grown up around this organization. It's a complete mismatch in scale between this org that has basically insulated itself so as to preserve the island of innovation that is required for really groundbreaking research, but then also, they have this reputation that far outstrips their ability to actually respond to people that are one step further out on the fringe from them. So I find myself asking, historically SFI was founded by Los Alamos National Laboratory physicists mostly that were disenchanted with the idea that they were going to have to research science, that their science was limited to that which could be basically argued as a national defense initiative and they just wanted to think about the deepest mysteries of the cosmos. So what is to SFI as SFI as to Los Alamos? Even in really radical organizations, there's a point at which they've matured and there are questions that are beyond the horizon of that which a particular community is willing to indulge. I find, in general, I'm really fascinated by questions about the nonlinearity of time, or about weird ontology. I'm currently talking to about a dozen other academics and para-academics about how to try and – I'm working, or helping to organize a working group of people that can apply rigorous academic approaches to asking questions that are completely taboo inside of academia. Questions that challenge some of the most fundamental assumptions of maternity, such as there being a distinction between self and other, or the idea that there are things that are fundamentally inaccessible to quantitative research. These kinds of things like, how do we make space for that kind of inquiry when there's absolutely no way to argue it in terms of you should fund this? And that's not just for money, that's also for attention because the demands on the time and attention of academics are so intense that even if they have interest in this stuff, they don't have the freedom to pursue it in their careers. That's just one of many areas where I find that this kind of line of inquiry manifesting right now. REIN: Reminds me a lot of this model of the edge of chaos that came from Packard and Langton back in the late 70s. Came out of chaos theory, this idea that there's this liminal transitionary zone between stability and chaos and that this is the boiling zone where self-organization happens and innovation happens. But also, that this zone is itself not static; it gets pushed around by other forces. MICHAEL: Yeah, and that's where life is and that was Langton's point, that life exists at the edge of chaos that it's right there at the phase transition boundary between what is it that separates a stone from a raging bonfire, or there’s the Goldilocks Zone kind of question. Yeah, totally. REIN: And these places that were at the edge of chaos that were innovative can ossify, they can move into the zone of stability. It's not so much that they move it's that, I don't know, maybe it's both. Where the frontier is, is constantly in motion. MICHAEL: Yeah, and to that point again, I tend to think about these things in a topographical, or geographical sense, where the island is growing, we're sitting on a volcano, and there's lots you can do with that metaphor. Obviously, it doesn't make sense. You can't build your house inside the volcano, right? [laughs] But you want to be close enough to be able to watch and describe as new land erupts, but at a safe distance. Where is that sweet spot where you have rigor and you have support, but you're not trapped within a bureaucracy, or an ossified set of institutional conventions? JESSICA: Or if the island is going up, if the earth is moving the island up until the coastline keeps expanding outward, and you built your house right on the beach. As in you’ve got into React when it was the new hotness and you learned all about it and you became the expert and then you had this great house on the beach, and now you have a great house in the middle of town because the frontier, the hotness has moved on as our massive technology has increased and the island raises up. I mean, you can't both identify as being on the edge and identify with any single category of knowledge. MICHAEL: Yeah. It's tricky. I saw Nora Bateson talking about this on Twitter recently. She's someone who I love for her subversiveness. Her father, Gregory Bateson, was a major player in the articulation of cybernetics and she's awesome in that sense of, I don't know, the minister's daughter kind of a way of being extremely well-versed in complex systems thinking and yet also aware that there's a subtle reductionism that comes in that misses – JESSICA: Misses from? MICHAEL: Well, that comes at like we think about systems thinking as it's not reductionist because it's not trying to explain biology in terms of the interactions of atoms. It acknowledges that there's genuine emergence that happens at each of these levels and yet, to articulate that, one of the things that happens is everything has to be squashed into numbers and so it’s like this issue of how do you quantify something. JESSICA: It's not real, if you can't measure it in numbers. MICHAEL: Right and that belies this bias towards thinking that because you can't quantify something now means it can't be quantified. JESSICA: You can’t predict which way the flame is going to go in the fire. That doesn't mean the fire doesn't burn. [chuckles] MICHAEL: Right. So she's interesting because she talks about warm data as this terrain, or this experience where we don't know how to talk about it yet, but that's actually what makes it so juicy and meaningful and instructive and – JESSICA: As opposed to taking it out of context. Leave it in context, even though we don't know how to do some magical analysis on it there. MICHAEL: Right, and I think this starts to generate some meaningful insights into the problem of the reproducibility crisis. Just as an example, I think science is generally moving towards context dependent insight and away from – even at the Santa Fe Institute, nobody's looking for a single unifying theory of everything anymore. It's far more illuminating, useful, and rigorous to look at how different models are practical given different applications. I remember in college there's half a dozen major different ways to define a biological species and I was supposed to get up in front of a class and argue for one over the other five. I was like, “This is preposterous.” Concretely, pun kind of intended, Biosphere 2, which was this project that I know the folks here at Synergia Ranch in Santa Fe at the Institute of Ecotechnics, who were responsible for creating this unbelievable historic effort to miniaturize the entire biosphere inside of a building. They had a coral reef and a rainforest and a Savannah and a cloud desert, like the Atacama, and there was one other, I forget. But it was intended as a kind of open-ended ecological experiment that was supposed to iterate a 100 times, or 50 times over a 100 years. They didn't know what they were looking for; they just wanted to gather data and then continue these 2-year enclosures where a team of people were living inside this building and trying to reproduce the entire earth biosphere in miniature. So that first enclosure is remembered historically as a failure because they miscalculated the rate at which they would be producing carbon dioxide and they ended up having to open the building and let in fresh air and import resource. JESSICA: So they learned something? MICHAEL: Right, they learned something. But that project was funded by Ed Bass, who in 1994, I think called in hostile corporate takeover expert, Steve Bannon to force to go in there with a federal team and basically issue a restraining order on these people and forcibly evict them from the experiment that they had created. Because it was seen as an embarrassment, because they had been spun in this way in international media as being uncredentialed artists, rather than scientists who really should not have the keys to this thing. It was one of these instances where people regard this as a scientific failure and yet when you look at the way so much of science is being practiced now, be it in the domains of complex systems, or in machine learning, what they were doing was easily like 20 or 30 years ahead of its time. JESSICA: Well, no wonder they didn’t appreciate it. MICHAEL: [chuckles] Exactly. So it's like, they went in not knowing what they were going to get out of it, but there was this tragic mismatch between the logic of Ed Bass’ billionaire family about what it means to have a return on an investment and the logic of ecological engineering where you're just poking at a system to see what will happen and you don't even know where to set the controls yet. So anyway. JESSICA: And it got too big. You talked about the media, it got too widely disseminated and became embarrassed because it wasn't on an island. It wasn't in a place where the genetic drift can become normal. MICHAEL: Right. It was suddenly subject to the constraints imposed upon it in terms of the way that people were being taught science in public school in the 1980s that this is what the scientific method is. You start with a hypothesis and it's like what if your – JESSICA: Which are not standards that are relevant to that situation. MICHAEL: Exactly. And honestly, the same thing applies to other computational forms of science. It took a long time for the techniques pioneered at the Santa Fe Institute to be regarded as legitimate. I'm thinking of cellular automata, agent-based modeling, and computer simulation generally. Steven Wolfram did a huge service, in some sense, to the normalization of those things in publishing A New Kind of Science, that massive book in whatever it was, 2004, or something where he said, “Look, we can run algorithmic experiments,” and that's different from the science that you're familiar with, but it's also setting aside for a moment, the attribution failure that that book is and acknowledging who actually pioneered A New Kind of Science. [chuckles] JESSICA: At least it got some information out. MICHAEL: Right. At least it managed to shift the goalpost in terms of what the expectations are; what constitutes a scientific experiment in the first place. JESSICA: So it shifted categories. MICHAEL: Yeah. So I think about, for example, a research that was done on plant growth in a basement. I forget who it was that did this. I think I heard this from, it was either Doug Rushkoff, or Charles Eisenstein that was talking about this, where you got two completely different results and they couldn't figure out what was going on. And then they realized that it was at different moments in the lunar cycle and that it didn't matter if you put your plant experiment in a basement and lit everything with artificial bulbs and all this stuff. Rather than sunlight, rather than clean air, if you could control for everything, but that there's always a context outside of your context. So this notion that no matter how cleverly you try to frame your model, that when it comes time to actually experiment on these things in the real world, that there's always going to be some extra analogy you've missed and that this has real serious and grave implications in terms of our economic models, because there will always be someone that's falling through the cracks. How do we actually account for all of the stakeholders in conversations about the ecological cost of dropping a new factory over here, for example? It's only recently that people, anywhere in the modern world, are starting to think about granting ecosystems legal protections as entities befitting of personhood and this kind of thing. JESSICA: Haven’t we copyrighted those yet? MICHAEL: [laughs] So all of that, there's plenty of places to go from there, I'm sure. REIN: Well, this does remind me of one of the things that Stafford Beer tried was he said, “Ponds are viable systems, they’re ecologies, they're adaptive, they're self-sustaining. Instead of trying to model how a pond works, what if we just hook the inputs of the business process into the pond and then hook the adaptions made by the pond as the output back into the business process and use the pond as the controlling system without trying to understand what makes a pond good at adapting?” That is so outside of the box and it blows my mind that he was doing this, well, I guess it was the 60s, or whatever, but this goes well beyond black boxing, right? MICHAEL: Yeah. So there's kind of a related insight that I saw Michelle Girvan gave at Santa Fe Institute community lecture a few years ago on reservoir computing, which maybe most of your audience is familiar with, but just for the sake of it, this is joining a machine learning system to a source of analog chaos, basically. So putting a computer on a bucket of water and then just kicking the bucket, every once in a while, to generate waves so that you're feeding chaos into the output of the machine learning algorithm to prevent overfitting. Again, and again, and again, you see this value where this is apparently the evolutionary value of play and possibly also, of dreaming. There's a lot of good research on both of these areas right now that learning systems are all basically hill climbing algorithms that need to be periodically disrupted from climbing the wrong local optimum. So in reservoir computing, by adding a source of natural chaos to their weather prediction algorithms, they were able to double the horizon at which they were able to forecast meteorological events past the mathematic limit that had been proven and established for this. That is like, we live in a noisy world. JESSICA: Oh, yeah. Just because it’s provably impossible doesn't mean we can't do something that's effectively the same thing, that's close enough. MICHAEL: Right. Actually, in that example, I think that there's a strong argument for the value of that which we can't understand. [laughs] It's like it's actually important. So much has been written about the value of Slack, of dreaming, of taking a long walk, of daydreaming, letting your mind wander to scientific discovery. So this is where great innovations come from is like, “I'm going to sleep on it,” or “I'm going to go on vacation.” Just getting stuck on an idea, getting fixated on a problem, we actually tend to foreclose on the possibility of answering that problem entirely. Actually, there's a good reason to – I think this is why Silicon Valley has recognized the instrumental value of microdosing, incidentally. [laughs] That this is that you actually want to inject a little noise into your algorithm and knock yourself off the false peak that you've stranded yourself on. JESSICA: Because if you aim for predictability and consistency, if you insist on reasonableness, you'll miss everything interesting. MICHAEL: Or another good way to put it is what is it, reasonable women don't make history. [laughs] There is actually a place for the – JESSICA: You don’t change the system by maximally conforming. MICHAEL: Right. JESSICA: If there is a place for… MICHAEL: It’s just, there is a place for non-conformity and it's a thing where it's like, I really hope and I have some optimism that what we'll see, by the time my daughter is old enough to join the workforce, is that we'll see a move in this direction where non-conformity has been integrated somehow into our understanding of how to run a business that we actively seek out people that are capable of doing this. For the same reason that we saw over the 20th century, we saw a movement from one size fits all manufacturing to design your own Nike shoes. There's this much more bespoke approach. JESSICA: Oh, I love those. MICHAEL: Yeah. So it's like we know that if we can tailor our systems so that they can adapt across multiple different scales, that they're not exploiting economies of scale that ultimately slash the redundancy that allows an organization to adapt to risk. That if we can find a way to actually generate a kind of a fractal structure in the governance of organizations in the way that we have reflexes. The body already does this, you don't have to sit there and think about everything you do and if you did, you’d die right away. JESSICA: [laughs] Yeah. REIN: Yeah. MICHAEL: If you had to pass every single twitch all the way up the chain to your frontal cortex JESSICA: If we had to put breathe on the list. [laughs] MICHAEL: Right. If you had to sit there and approve every single heartbeat, you'd be so dead. [overtalk] JESSICA: Oh my gosh, yeah. That's an energy allocation and it all needs to go through you so that you can have control. REIN: I just wanted to mention, that reminded me of a thing that Klaus Krippendorff, who's a cybernetics guy, said that there is virtue in the act of delegating one's agency to trustworthy systems. We're talking, but I don't need to care about how the packets get from my machine to yours and I don't want to care about that, but there's a trade-off here where people find that when they surrender their agency, that this can be oppressive. So how do we find this trade-off? MICHAEL: So just to anchor it again in something that I find really helpful. Thinking about the way that convenience draws people into these compacts, with the market and with the state. You look over the last several hundred years, or thousand years in the West and you see more and more of what used to be taken for granted as the extent in terms of the functions that are performed by the extended family, or by the neighborhood, life in a city, by your church congregations, or whatever. All of that stuff has been out boarded to commercial interests and to federal level oversight, because it's just more efficient to do it that way at the timescales that matter, that are visible to those systems. Yet, what COVID has shown us is that we actually need neighborhoods that suddenly, it doesn't – my wife and I, it was easy to make the decision to move across country to a place where we didn't know anybody to take a good job. But then suddenly when you're just alone in your house all the time and you've got nobody to help you raise your kids, that seems extremely dumb. So there's that question of just as I feel like modern science is coming back around to acknowledging that a lot of what was captured in old wives’ tales and in traditional indigenous knowledge, ecological knowledge systems that were regarded by the enlightenment as just rumor, or… JESSICA: Superstition. MICHAEL: Superstition, that it turns out that these things actually had, that they had merit, they were evolved. JESSICA: There was [inaudible] enough. MICHAEL: Right. Again, it wasn't rendered in the language that allowed it to be the subject of quantitative research until very recently and then, suddenly it was and suddenly, we had to circle back around. Science is basically in this position where they have to sort of canonize Galileo, they're like, “Ah, crap. We burned all these witches, but it turns out they were right.” There's that piece of it. So I think relatedly, one of the things that we're seeing in economist samples and Wendy Carlin have written about this is the return of the civil society, the return of mutual aid networks, and of gift economies, and of the extended family, and of buildings that are built around in courtyards rather than this Jeffersonian everyone on their own plot of land approach. That we're starting to realize that we had completely emptied out the topsoil basically of all of these community relationships in order to standardize things for a mass big agricultural approach, that on the short scale actually does generate greater yield. It's easier to have conversations with people who agree with you than it is – in a way, it's inexpedient to try and cross the aisle and have a conversation with someone with whom you deeply and profoundly disagree. But the more polarized we become as a civilization, the more unstable we become as a civilization. So over this larger timescale, we actually have to find ways to incentivize talking to people with whom you disagree, or we're screwed. We're kicking legs out from under the table. REIN: At this point, I have to name drop Habermas because he had this idea that there were two fundamental cognitive interests that humans have to direct their attempts to acquire knowledge. One is a technical interest in achieving goals through prediction and control and the other is a practical interest in ensuring mutual understanding. His analysis was that advanced capitalist societies, the technical interest dominates at the expense of the practical interest and that knowledge produced by empirical, scientific, analytic sciences becomes the prototype of all knowledge. I think that's what you're talking about here that we've lost touch with this other form of knowledge. It's not seen as valuable and the scientific method, the analytical approaches have come to dominate. MICHAEL: Yeah, precisely. [laughs] Again, I think in general, we've become impoverished in our imagination because again, the expectations, there's a shifting baseline. So what people expect to pull out of the ocean now is a fish that you might catch off just a commercial, or a recreational fishing expedition. It's a quarter of the size of the same species of fish you might've caught 50, 70 years ago and when people pull up this thing and they're like, “Oh, look at –” and they feel proud of themselves. I feel like that's what's going on with us in terms of our we no longer even recognize, or didn't until very recently recognize that we had been unwittingly colluding in the erosion of some very essential levels of organization and human society and that we had basically sold our souls to market efficiency and efficient state level governance. Now it's a huge mess to try and understand. You look at Occupy Wall Street and stuff like that and it just seems like such an enormous pain in the ass to try and process things in that way. But it's because we're having to relearn how to govern neighborhoods and govern small communities and make business decisions at the scale of a bioregion rather than a nation. JESSICA: Yeah. It's a scale thing. I love the phrase topsoil of community relationships, because when you talk about the purposive knowledge that whatever you call it, Rein, that is goal seeking. It's like the one tall tree that is like, “I am the tallest tree,” and it keeps growing taller and taller and taller, and it doesn't see that it's falling over because there's no trees next to it to protect it from the wind. It's that weaving together between all the trees and the different knowledge and the different people, our soul is there. Our resilience is there. REIN: Michael, you keep talking about scale. Are you talking about scale theory? MICHAEL: Yeah. Scaling laws, like Geoffrey West's stuff, Luis Bettencourt is another researcher at the University of Chicago who does really excellent work in urban scaling. I just saw a talk from him this morning that was really quite interesting about there being a sweet spot where a city can exist between how thinly it's distributed infrastructurally over a given area versus how congested it is. Because population and infrastructure scale differently, they scale at different rates than you get – REIN: If I remember my West correctly, just because I suspect that not all of our listeners are familiar with scale theory, there's this idea that there are certain things that grow super linearly as things scale and certain things that grow sub linearly. So for example, the larger a city gets, you get a 15% more restaurants, but you also get 15% more flu, but you also get 15% less traffic. MICHAEL: Yeah. So anything that depends on infrastructures scales sub linearly. A city of 2 million people has 185% the number of gas stations, but anything that scales anything having to do with the number of interactions between people scales super linearly. You get 115% of the – rather you get, what is it, 230%? Something like that. Anyway, it's 150%, it's 85% up versus 115% up. So patents, but also crime and also, just the general pace of life scale at 115% per capita. So like, disease transmission. So you get into these weird cases—and this links back to what we were talking about earlier—where people move into the city, because it's per unit. In a given day, you have so much more choice, you have so much more opportunity than you would in your agrarian Chinese community and that's why Shenzhen is basically two generations old. 20 million people and none of them have grandparents living in Shenzhen because they're all attracted to this thing. But at scale, what that means is that everyone is converging on the same answer. Everyone's moving into Shenzhen and away from their farming community. So you end up – in a way, it's not that that world is any more innovative. It's just, again, easier to capture that innovation and therefore, measure it. But then back to what we were saying about convergent categories and biogeography, it's like if somebody comes up with a brilliant idea in the farm, you're not necessarily going to see it. But if somebody comes up with the same brilliant idea in the city, you might also not see it for different reasons. So anyway, I'm in kind of a ramble, but. JESSICA: The optimal scale for innovation is not the individual and it's not 22 million, it's in between. MICHAEL: Well, I feel like at the level of a city, you're no longer talking about individuals almost in a way. At that point, you're talking about firms. A city is like a rainforest in which the fauna are companies. Whereas, a neighborhood as an ecosystem in which the fauna, or individual people and so, to equate one with the other is a potential point of confusion. Maybe an easier way to think about this would be multicellular life. My brain is capable of making all kinds of innovations that any cell, or organ in my body could not make on its own. There's a difference there. [overtalk] JESSICA: [inaudible]. MICHAEL: Right. It's easier, however, for a cell to mutate if it doesn't live inside of me. Because if it does, it's the cancer – [overtalk] JESSICA: The immune system will come attack it. MICHAEL: Right. My body will come and regulate that. JESSICA: Like, “You’re different, you are right out.” MICHAEL: Yeah. So it's not about innovation as some sort of whole category, again, it's about different kinds of innovation that are made that are emergent at different levels of organization. It's just the question of what kinds of innovation are made possible when you have something like the large Hadron Collider versus when you've got five people in a room around a pizza. You want to find the appropriate scale for the entity, for the system that's the actual level of granularity at which you're trying to look at the stuff, so. REIN: Can I try to put a few things together here in potentially a new way and see if it's anything? So we talked about the edge of chaos earlier and we're talking about scale theory now, and in both, there's this idea of fractal geometry. This idea that a coastline gets larger, the smaller your ruler is. In scale theory, there's this idea of space filling that you have to fill the space with things like capillaries, or roads and so on. But in the human lung, for example, if you unfurled all of the surface area, you'd fill up like a football field, I think. So maybe there's this idea that there's complexity that's possible, that’s made possible by the fractal shape of this liminal region that the edge of chaos. MICHAEL: Yeah. It's certainly, I think as basically what it is in maximizing surface area, like you do within a lung, then you're maximizing exposure. So if the scientific community were operating on the insights that it has generated in a deliberate way, then you would try to find a way to actually incorporate the fringe physics community. There's got to be a way to use that as the reservoir of chaos, rather than trying to shut that chaos out of your hill climbing algorithm and then at that point, it's just like, where's the threshold? How much can you invite before it becomes a distraction from getting anything done? When it's too noisy to be coherent. Arguably, what the internet has done for humankind has thrown it in completely the opposite direction where we've optimized entirely for surface area instead of for coherence. So now we have like, no two people seem to be able to agree on reality anymore. That's not useful either. REIN: Maybe there's also a connectivity thing here where if I want to get from one side of the city to the other, there are 50 different routes. But if I want to get from one city to another, there's a highway that does it. MICHAEL: Yeah, totally. So it's just a matter of rather than thinking about what allows for the most efficient decisions, in some sense, at one given timescale, it's how can we design hierarchical information, aggregation structures so as to create a wise balance between the demands on efficiency that are held at and maintained at different scales. SFI researcher, Jessica Flack talks about this in her work on collective computation and primate hierarchies where it’s a weird, awkward thing, but basically, there is an evolutionary argument for police, that it turns out that having a police system is preventing violence. This is mathematically demonstrable, but you also have to make sure that there's enough agency at the individual level, in the system that the police aren't in charge of everything going on. It's not just complex, it's complicated. [laughs] We've thrown out a ton of stuff on this call. I don't know, maybe this is just whetting people's appetite for something a little bit more focused and concise. JESSICA: This episode is going to have some extensive show notes. MICHAEL: Yeah. [chuckles] JESSICA: It's definitely time to move into reflections. JACOB: You were talking, at the very beginning, about Spotify. Like how, when unknown ideas are able to find their tribe and germinate. I was reading about how Netflix does business and it's very common for them to make some new content and then see how it goes for 30 days and then just kill it. Because they say, “Well, this isn't taking off. We're not going to make more of it,” and a lot of people can get really upset with that. There's definitely been some really great things out on Netflix that I'm like, for one on the one hand, “Why are you canceling this? I really wanted more,” and it seems like there's a lot of the people that do, too. What that's making me think about as well for one thing, I think it seems like Netflix from my experience, is not actually marketing some of their best stuff. You would never know it’s there, just in the way of people to find more unknown things. But also, I'm thinking about how just generally speaking some of the best ideas, TV shows, music, whatever are the kinds of things that there's not going to be an established container, group of people, that you can say, “We want to find white men ages 25 to 35 and we're going to dump it on their home screen because if anyone's going to like it, it's them and if they do, then we keep it and if they don't move, we don't.” I feel like the best things are we don't actually know who those groups are going to be and it's going to have a weird constellation of people that I couldn't actually classify. So I was just thinking about how that's an interesting challenge. JESSICA: Sweet. Rein, you have a thing? REIN: Yeah. I have another thing. I was just reminded of von Foerster, who was one of the founders of Second-order cybernetics. He has an ethical imperative, which is act always so as to increase the number of choices. I think about this actually a lot in my day-to-day work about maximizing the option value that I carry with me as I'm doing my work, like deferring certain decisions and so on. But I think it also makes sense in our discussion as well. JESSICA: True. Mine is about externalities. We talked about how, whatever you do, whatever your business does, whatever your technology does, there's always going to be effects on the world on the context and the context of the context that you couldn't predict. That doesn't mean don't do anything. It doesn't mean look for those. Recognize that there's going to be surprises and try to find them. It reminds me of sometimes, I think in interviewing, we’re like, “There are cognitive biases so in order to be fair, we must not use human judgment!” [laughter] Which is not helpful. I mean, yes, there are cognitive biases so look for them and try to compensate. Don't try to use only something predictable, like an algorithm. That's not helpful. That's it. MICHAEL: Yeah. Just to speak to a little bit of what each of you have said, I think for me, one of the key takeaways here is that if you're optimizing for future opportunity, if you're trying to—and I think I saw MIT defined intelligence in this way, that AI could be measured in terms of its ability to – AGI rather could be measured in terms of its ability to increase the number of games steps available to it, or options available to it in the next step of an unfolding puzzle, or whatever. Superhuman AGI is going to break out of any kind of jail we try to put it in just because it's doing better at this. But the thing is that that's useless if we take it in terms of one spaciotemporal scale. Evolutionary dynamics have found a way to do this in a rainforest that optimizes biodiversity and the richness of feeding relationships in a food web without this short-sighted quarterly return maximizing type of approach. So the question is are you trying to create more opportunities for yourself right now? Are you trying to create more opportunities for your kids, or are you trying to transcend the rivalrous dynamics? You've set yourself up for intergenerational warfare if you pick only one of those. The tension between feed yourself versus feed your kids is resolved in a number of different ways in different species that have different – yeah. It is exactly, Rein in the chat you said, it reminds you of the trade-off between efficiency and adaptability and it's like, arguably, adaptability is efficiency aggregated when you're looking at it over a longer timescale, because you don't want to have to rebuild civilization from scratch. So [chuckles] I think it's just important to add the dimension of time and to consider that this is something that's going on at multiple different levels of organization at the same time and that's a hugely important to how we actually think about these topics. JESSICA: Thinking of scales of time, you’ve thought about these interesting topics for an hour, or so now and I hope you'll continue thinking about them over weeks and consult the show notes. Michael, how can people find out more about you? MICHAEL: I'm on Twitter and Instagram if people prefer diving in social media first, I don't recommend it. I would prefer you go to patreon.com/michaelgarfield and find future fossils podcasts there. I have a lot of other stuff I do, the music and the art and everything feeds into everything else. So because I'm a parent and because I don't want all of my income coming from my day job, I guess Patreon is where I suggest people go first. [laughs] Thank you. JESSICA: Thank you. And of course, to support the podcast, you can also go to patrion.com/greaterthancode. If you donate even a dollar, you can join our Slack channel and join the conversation. It'll be fun. Special Guest: Michael Garfield.

Hello Interactors,More Microsoft history and it’s role in the growth of itself, other companies around the world, and our pervasive connections to each other and the internet. I was lucky to play a small part in this transformation. I did my best to understand the behavior of people using the software that fueled these expansions. It taught me lessons I’m now applying to understanding behavior of people interacting with place.As interactors, you’re special individuals self-selected to be a part of an evolutionary journey. You’re also members of an attentive community. I welcome your participation.Interplace is a place for people to interact so please leave your comments below or feel free to email me directly. Now let’s go…MICROSERFSIn my early days at Microsoft, the place felt more like a startup. I had come from a company of 120 people, so 11,000 people should have felt huge. But compared to the 168,000 of today, it was small. The culture was different too. People were there to make something – not to be somebody. This attitude is best ensconced in Douglas Coupland’s 1995 novel, Microserfs. Set on Microsoft’s forested campus, it gives a peek into ‘geek culture’ of the early 90s. It also exposes the heartfelt belief that we really were doing something meaningful.“What is the search for the next great compelling application but a search for the human identity?” “Maybe thinking you're supposed to 'have a life' is a stupid way of buying into an untenable 1950s narrative of what life *supposed* to be. How do we know that all of these people with 'no lives' aren't really on the new frontier of human sentience and preceptions?” – Douglas Coupland, MicroserfsWhen this book came out, Windows 95 was just starting up. PC sales were revving. Selling at the rate of 40 Million per year it’s success pushed Intel’s revenue growth to 41% in a single year. And the promise of the World Wide Web was taking hold. Bill’s book, The Road Ahead, had come out and he had a vision. That vision was expressed in a keynote at COMDEX, a popular technology conference. The concept was called, ‘Information at your Fingertips’ and he needed a murder mystery movie to tell the story. My team designed the PC desktop interactions in this video. We imagined what interactions would be like in 2005. At one point in the video, Bill jokingly refers to our work as a ‘rather cluttered desktop’. Soon after you’ll see Bill introducing long file names and video conferencing. But in 1995, that meant video conferencing with somebody in a public phone booth! People around the world were buying in to Bill’s vision — including major corporations and governments. Businesses multiplied PC growth. And so did connectivity. Bill’s vision of a PC on every desk was coming true. Connecting computers to the internet really did put information at your fingertips. Buying a PC in 1995 was the entry price to a new world of communication. Windows 95 made connecting to the internet easy, Office 95 simplified sending email, and the Internet Explorer let you, well, explore the internet. Information was not just gingerly touching the tips of fingers. Hands were cupped and people were scooping up tiny bits of addictive bytes and gorging themselves. We still are. In 1996 36 million people were on the internet. By 2000 it grew tenfold to 360 million. A decade later it jumped to two billion. Estimates now put that number at around four billion – over half of the world’s population. A reminder of the advantage and privilege half the world holds over the other half. GROW BABY GROWSatisfying this growing appetite for information required more than software. Cables needed to be run, server farms needed built, and somebody had to manage all this information and technology. Enter the IT Manager. IT had been around for some time already, but installing, managing, and controlling access to Windows, Office, and all these PCs and peripherals put real strains on IT departments. So did the need to control access to the exponential growth of documents, spreadsheets, and presentations. Other comparable modes of communication, like snail mail and telephones, only grew at a rate of around 10% over a much longer period of time. The expansion of IT departments mirrored this curve. Digital connection and communication between people inside companies fuels the same ingenuity that physical connections do in dense cities. The bigger the city, the more innovation occurs. Successful cities attract talented and conscientious people generating superlinear population growth and creativity. It’s why bigger cities and bigger companies have bigger stockpiles of patents. “Just as bounded growth in biology follows from the sublinear scaling of metabolic rate, the superlinear scaling of wealth creation and innovation (as measured by patent production, for example) leads to unbounded, often faster-than-exponential growth consistent with open-ended economies.”– Geoffrey West. Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies.To accommodate this growth, the infrastructure must scale accordingly. But whether it’s an ethernet cable plugged in to a PC, a copper pipe connected to a toilet, or the capillaries feeding those information seeking fingertips the endpoints all start small. Universally small. Be it Boston, Bamako, or Bangladesh, the clear plastic fitting at the end of that network cable is the same. The diameter of piping connected to the toilet is also roughly the same. So are the smallest blood vessels in every human’s freakishly flexible fingers all they way down to their tiny typing tips. All of which connect to progressively larger conduits that accommodate increasing amounts of data, water, or blood. All the way to massive data gateways, waterworks plants, and plasma pumping hearts. “The pipe that connects your house to the water line in the street and the electrical line that connects it to the main cable are analogs of capillaries, while your house can be thought of as an analog to cells. Similarly, all employees of a company, viewed as terminal units, have to be supplied by resources (wages, for example) and information through multiple networks connecting them with the CEO and the management.”– Geoffrey West. Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies.It’s the work of fractals and the power of sublinear scaling. It’s what makes an elephant live longer than mouse, and companies like Microsoft to live longer than most startups. But an elephant is also big and slow, and so are big companies. As the year 2000 approached, other growing companies suffered the same fate of growth. The burden of managing these layers of modern administration increased the total cost of ownership of assets. The cost of managing equipment, software, and data, exceeded the cost of the software used to create it. Office 97 was deemed ‘good enough’ by the industry. This meant every new feature we added only diminished the return on their investment. Microsoft Office faced the same fate natural organisms do – a growth plateau. POWER TO THE PEOPLEThis marked a notable shift in our approach to user research. Instead of focusing entirely on the tasks and activities of individual end users, we had new problems to consider: reducing the total cost of ownership and increasing the return on existing investments. Our infamous attempt at expanding menus in Office was one such example. Instead of a bottoms-up ‘geek culture’ approach to software development that was tied to individual needs and desires, we were looking through the lens of IT managers and business decision makers.Meanwhile, the kind of things people were doing in Office was expanding and diversifying. We discovered people used Excel for everything from poetry to programming. Word users made love letters and legal documents. We were constantly surprised by how people used Office. I recall a site visit where we observed an office manager at a car dealership using Word. She was making a flyer to post in the break room. We watched as she created a new document, typed and formatted some text, spent a few minutes laying it out, and then hit ‘Print’. What happened next surprised us. She closed Word, and was dutifully prompted to save her document. To our amazement, she declined. We politely interjected, “You just lost all your work!” She responded, “No I didn’t, it’s sitting right there on the printer.” As we observed more and more behavior we found ourselves looking across individual use cases in search of commonalities. We would cluster and clump collections of behaviors into buckets with names like, “Create”, “Communicate”, “Synthesize“, and “Collaborate”. Before long we distanced ourselves from those individual behaviors. The language became obtuse and abstract. The knowledge of how people were using the product on the ground became mediated through layers of corporate administration. There were decisions being made among the ‘corporate elite’ in corporation that had measurable impacts on how people were using Office. Decisions that impacted their satisfaction of our product and of their livelihood. But much of that became insulated from us. IT didn’t much like Microsoft researching their employees. Knowledge of how real people did real things in real ways was information just beyond our fingertips.STRIKING THE BALANCEThe same effects of scaling occur in cities as well.  Small towns are like startups. They have their own version of ‘geek culture’; transcendental motivators that rally a group around something bigger than themselves. As the city grows, it too attracts the best and brightest. And as the population grows, so does the infrastructure needed to sustain it. The close interactions of smart talented people yields new innovations that generate revenue and attract more talent. City growth seems to be impervious to scaling laws. Luis Bettencourt, a physicist and complexity scientist who studies cities, calls them ‘social reactors’. By his estimation, there’s only one thing in nature that behaves like cities. The sun. In a Santa Fe Institute interview by host Michael Garfield , Bettencourt says, “…the only system that has sort of these properties that I know of exist in nature that concentrates things, increases interaction rates and admits products at a rate that's higher, per unit of mass is the sun, is a star and that's a reactor, right?”Researchers have been observing and understanding the behavior of people and place for centuries. And they too have struggled with the same things I did trying to understand the behavior of people using complex systems like Office. Studying people on the ground indeed yields insights at a micro-level. But after collecting and amassing mounds of data patterns emerge, generalizations are made, and soon they’re looking at humans in the aggregate. Researching at the macro level-begins with agglomerated aggregate. But patterns also emerge. Moreover, it allows for the study of behavior of decision makers, policy writers, and power brokers. These decision makers work together to convive, concoct and sometimes conspire ways of influencing the outcomes of organizations. It’s important we study how planning and long term execution of coordinated strategies impact the world. Only then will hidden influences of our economic and political systems emerge. In synthesizing decades of human geography research by social scientists, researchers Reginald Golledge and Robert Stimson came to this conclusion:“It was found that the long-term plans and objectives of Western capitalist societies often benefited small, elite groups of capitalists more than they benefited people with low incomes and that planning for personal welfare diverged widely among capitalist and socialist and social-welfare economies. Decision making at the macro level was thus defined as a constrained process, undertaken and implemented by a powerful elite, often encompassing goals that differentially considered segments of society or economy.” – Reginald G. Golledge and Robert J. Stimson. Spatial Behavior: A Geographic PerspectiveUnderstanding human behavior is a challenging and dynamical undertaking. After all, in the words of Douglas Coupland, “What is human behavior, except trying to prove that we're not animals?”I’m not convinced we’re smart enough to fully understand or describe human behavior. It’s like looking through a telescope with one eye and a microscope with the other and then coherently explaining what you see. But it does involve a little bit of both of these techniques. It requires us to sit with people in their context to fully grasp the how their physical environment impacts their work, lives, attitudes, and beliefs. When you see someone, as I did, straight out of college sitting in a broom closet with a desk and a laptop using Excel for 10 hours a day, it’s hard to un-see. Somebody in ‘corporate’ decided it was a good idea to put a human in a closet to work. Like an animal. It’s essential we understand why people do these, and much, much worse things to other people. Every organization has a group, or two, of just a few people with a privileged view. They reckon and wrangle, poke and prod, and wager which message to tangle and skew. I’ve been there, I know, they impact me and they impact you.The same is true in the cities we live. And the regions and counties and countries, too. By trying to know all we can know and showing the world what we’re we willing to show, a bigger vessel of understanding can flow. In the words of Reg Golledge and Robert Stimson, “A paradigm for examining human-environment settings needs to encompass a complex set of relevant variables and their functional relationships. It includes the physical and the built aspects of environment; it allows for roles of culture and its related social and political systems and institutions; it identifies the evolution of culture over time through technology; and it recognizes intervening psychological processes as filtering mechanisms in how humanity perceives the environment and acts within it.”Our collective behavior has fueled a rate and pace of growth that we cannot survive. Microsoft, as a company, has survived longer than most. Looking at over 22,000 U.S. companies, from 1950 to 2009, only half made it past 10 years. I’m half way to 60 and many scientists would agree that I’m as old as the Anthropocene – a geological epoch marked by the negative impact our behavior is having on the planet. The majority of my life has been spent molding and understanding the behavior of people behind a computer screen – billions of finger tips making, taking, and shaping information through software. My one wish is that they, we, look at our reflection in that screen and ask, “Will my current behavior allow the next two generations to survive?” Subscribe at interplace.io

Contar com bons dados sempre foi central para o decisor de marketing – mas ter os dados não basta. Numa era em que, graças à tecnologia, nunca foi tão fácil ter todo o tipo de métricas, não é por isso que tomar decisões fica mais fácil. É preciso separar os dados que importam dos que nem tanto, e saber o que fazer com eles. Por isso fomos falar o Luis Bettencourt Moniz: uma autoridade em data science que junta à sua intensa atividade académica uma longa experiência de profissional de marketing. Curiosamente, a conversa levou-nos para caminhos que podem surpreender quem tiver uma visão fria e mecanicista da decisão baseada em dados. Falámos dos limites da abordagem analítica ao marketing. Do papel da intuição nas decisões de marketing. E até da importância de integrar uma atitude “artística” no processo de decisão. Foi um episódio surpreendente - com pequenos problemas no som, mas nada que impeça de ouvir e descobrir: · As 3 funções básicas a que podemos reduzir o marketing · Como data science e intuição humana têm de se combinar na tomada de decisões · Por onde começar quando há muitos dados e não se sabe quais são os importantes e os menos importantes · O que fazer com as descobertas que fazemos a partir dos dados e que não têm aplicação imediata · O que é a navalha de Ockham e por que, passados tantos séculos, continua a ser importante na tomada de decisões · Como tomar decisões quando não há dados suficientes que as sustentem · Qual é a dimensão “artística” do marketing e por que acaba por ser tão importante como ter bons dados NOTAS DESTE EPISÓDIO Sobre o convidado Luis Bettencourt Moniz no Linkedin E no instagram Livros do Luis Bettencourt Moniz citados no episódio: · Marketing Performance – 80 métricas de marketing e vendas · 52 métricas de marketing e vendas FoxP2– Empresa fundada pelo Luis Bettencourt Moniz Livros sugeridos pelo convidado: Manuel Lima: The book of trees; The book of Circles; Visual Complexity Sobre marketing e comunicação business-to-business: Visite a Hamlet em hamlet.pt Subscreva a newsletter da Universidade B2B, da Hamlet; Fique em dia com a comunicação de marketing B2B no nosso blog; Siga-nos também no Linkedin, no Facebook, e no Youtube;

The modern world has a way of distancing itself from everything that came before it…and yet the evidence from archaeology supports a different story. While industrial societies tend to praise markets and advanced technologies as the main drivers of the last few centuries of change, a careful study of civilizations as distinct as Ancient Rome, Peru, and Central Mexico reveals an underlying uniformity. Consistent patterns have played out in human settlements across millennia and continents, regardless of the economic systems we’ve employed or the inventions on which we’ve relied. These patterns, furthermore, look just like those that govern and delimit evolutionary change; the scaling laws determining the growth of cities are, apparently, the same that led to cities in the first place, or to human social groups, or complex animals. Human settlements act as social reactors, by facilitating interactions — in other words, the functional relationships within communities drive history, and this century has more in common with the distant past than commonly believed.These revelations, though, might have remained invisible to us if archaeology itself had not transformed over the last few decades, evolving new approaches to cross-disciplinary synthesis. It’s time to update both our notions of the ancient world and our popular conception of the archaeologist…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 we talk to Former SFI Omidyar Fellow Scott Ortman, Associate Professor of Anthropology at The University of Colorado Boulder, about his work on settlement scaling theory and fostering synthesis in archaeology to advance science and benefit society.If you value our research and communication efforts, please consider making a donation at santafe.edu/give — and/or rating and reviewing us at Apple Podcasts. You can find numerous other ways to engage with us at santafe.edu/engage. Thank you for listening!Check out Scott’s CU Boulder Website and Google Scholar Page for more information and links to the research papers and opinion pieces we discuss in this episode.For more on universal scaling laws and the science of cities, revisit these earlier episodes of COMPLEXITY:4 — Luis Bettencourt10 — Melanie Moses17 — Chris Kempes33 — Tim Kohler & Marten Scheffer35 — Geoffrey West36 — Geoffrey WestJoin 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

Since the 1940s, scientists have puzzled over a curious finding: armed conflict data reveals that human battles obey a power-law distribution, like avalanches and epidemics.  Just like the fractal surfaces of mountains and cauliflowers, the shape of violence looks the same at any level of magnification. Beyond the particulars of why we fight, this pattern suggests a deep hidden order in the physical laws governing society.  And, digging into new analyses of data from both armed conflicts and voting patterns, complex systems researchers have started to identify the so-called “pivotal components” — the straw that breaks the camel’s back, the spark that sets a forest fire, the influential (but not always famous) figures that shape history.  Can science find a universal theory that predicts the size of conflicts from their initial conditions, or identifies key players whose “knobs” turn society in one direction or another?Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and each 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’s guest is SFI Program Postdoctoral Fellow Eddie Lee, whose work into “conflict avalanches” and swing voters gives a glimpse of the mysterious forces that determine why we fight — and how we may be able to prevent the next conflagration. In this episode, we talk about armed conflict as a fractal and a form of computation, swing voters in the justice system and influencers in pop culture, and what these studies have to say about the deep constraints that guide the currents of society.Just a note that this will be our last episode before a short summer break, to give our scientists uninterrupted time to work on a torrent of new research. We have some exciting episodes scheduled for our return in mid-August…in the meantime, please be sure to subscribe to Complexity Podcast on your favorite podcast provider to make sure you stay in the know! And if you value our research and communication efforts, please consider making a donation at santafe.edu/podcastgive, or join our Applied Complexity Network at santafe.edu/action.Lastly, we are excited to announce that submissions are open for this fall’s inaugural Complexity Interactive, a three-week online, project-based immersive course where you get a rare opportunity for mentorship by a large faculty of SFI professors — including Cris Moore, Melanie Mitchell, Simon DeDeo, Danielle Bassett, Luis Bettencourt, Melanie Moses, Ricard Solé, and many more. For more info and to apply, please visit https://santafe.edu/sfi-ciThank you for listening!Eddie Lee’s SFI Webpage & Google Scholar PagePapers we discuss in this episode:A scaling theory of armed conflict avalanchesSensitivity of collective outcomes identifies pivotal componentsEmergent regularities and scaling in armed conflict dataCollective memory in primate conflict implied by temporal scaling collapseGo further:Time Scales & Tradeoffs, an SFI Flash Workshop [video]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 • LinkedInTranscript coming soon!  Thanks for your patience...

Luis Bettencourt, Pritzker Director of the Mansueto Institute for Urban Innovation at the University of Chicago, creates in his research new urban theories explaining how cities thrive and the challenges they face. He focuses on understanding the role of innovation and technological change as a driver of economic growth and human development in cities around the world and throughout history. In this podcast, Luis Bettencourt highlights the social essence of cities, looking at space as a platform. Bettencourt perceives slums as a result of fast-growing cities, at the center of research for better understanding cities and human development. Luis Bettencourt describes the city of the future as even bigger than the big cities of today, more complex, more interconnected, more diverse, with an even greater excitement and harnessing change for the benefit of people and of the environment. He advises not to look at cities or urban environments as problems but to look at what they do well. #NFFStories is a series of podcasts produced by the Norman Foster Foundation that aims to empower our community to make positive change. A new platform for people around the world to share and hear inspirational stories and ideas that are going to shape the future. www.normanfosterfoundation.org

If COVID-19 has made anything obvious to everyone, it might be how the very small can force the transformation of the very large. Disrupt the right place in a network and exponential changes ripple outward: a virus causes a disease that leads to economic shocks and other social impacts that, in turn, re-open urban spaces to nonhuman animals and change the course of evolution.Adapting to these changes will require a different kind of understanding: one of nonlinear dynamics, feedback loops, extended selves, and the tiered and interwoven ecological and economic systems of our planet. By studying the processes and structures that this change exposes, we’re offered a new way of seeing individuality-in-context…and, perhaps, new mechanisms for aligning individual and public good, the human and the wild.Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and each 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.In Transmission, SFI’s new essay series on COVID-19, our community of scientists shares a myriad of complex systems insights on this unprecedented situation. This special supplementary mini-series with SFI President David Krakauer finds the links between these articles—on everything from evolutionary theory to economics, epistemology to epidemiology—to trace the patterns of a deeper order that, until this year, was largely hidden in plain sight.If you value our research and communication efforts, please consider making a one-time or recurring monthly donation at santafe.edu/podcastgive … and/or consider rating and reviewing us at Apple Podcasts. Thank you for listening!Further Reading:Chris Kempes and Geoffrey West on understanding cities to respond to pandemicsEric Maskin on mechanism design for the marketPamela Yeh and Ian MacGregor-Fors on studying wildlife in empty citiesSidney Redner on exponential growth processesDavid Wolpert on SARS-CoV-2 and Landauer's boundWhat is an individual? Information Theory may provide an answerVisit 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 • LinkedInMentioned in this episode:David Wolpert, Alan Turing, Rolf Landauer, Timothy Morton, Buckminster Fuller, Sidney Redner, Chris Kempes, Geoffrey West, Bill Gates, Ann Pendleton-Jullian, Luis Bettencourt, Cris Moore, Eric Maskin, Wendy Carlin, Sam Bowles, Kenneth Arrow, John Von Neumann, Eric Morgenstern, John Nash, Pamela Yeh, Ian MacGregor-Fors, Alan Weisman, Doug Erwin

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

In the last decade, there has been a mass migration of people into urban areas across the globe. This rapid urbanization has been increasingly unsustainable for our cities and it’s projected to get worse in the next decade.  University of Chicago scholar Luis Bettencourt is tackling this global crisis by researching the underlying processes that dictate our cities. If you can understand the numbers, you can create models for the sustainable cities our planet needs. He’s starting by mapping a million neighborhoods. Subscribe to Big Brains on Apple Podcasts, Stitcher and Spotify.

If you’re a human in this century, the odds are overwhelming that you are a city-dweller. These hubs of human cultural activity exert a powerful allure – and most people understand that this appeal is due to some deep link between the density, pace, wealth, and opportunity of cities. But what is a city, really? And why have the vast majority of human beings migrated to these intense and often difficult locations? Cities breed not just ideas but also crime, disease, and inequality. We live amidst a shift in what a normal human life looks and feels like, akin to the transition from our lives as nomadic hunter-gatherers to sedentary farmers — only this time, it is happening before our eyes. How can we cultivate the best that cities offer and minimize the predicaments they pose? A powerful new science of the city has emerged in just the last few years, connecting the metropolis through physics to the properties that govern animal metabolisms, ecological diversity, and economics.This week’s guest is Luis Bettencourt, External Professor at the Santa Fe Institute and Director of the Mansueto Institute for Urban Innovation at the University of Chicago. We spoke while he was visiting Santa Fe to lead SFI’s Global Sustainability Summer School to talk about what makes a city such a fertile zone for innovation of all kinds, and how to help ensure the future of the city is one human beings want to live in.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.Visit The Mansueto Institute's Website.Watch a short video on Bettencourt’s work to eliminate slums.Here are the three papers we discussed in this episode:"Toward cities without slums: Topology and the spatial evolution of neighborhoods" in Science Advances."The Origins of Scaling in Cities" in Science.“Towards a statistical mechanics of cities” in Science Advances.Learn more about SFI's Global Sustainability Summer School.Follow us on social media:Twitter • YouTube • Facebook • Instagram • LinkedIn

Cities are complex and dynamic environments, which present many opportunities for new uses of merging technologies and data. In this episode, Luis Bettencourt will address many features that are common to all cities as complex ecosystems of people interacting over the built environment. In this light, he will presesnt opportunities to make cities smarter in terms of the efficiency and quality of underlying infrastructure, as well as the creation of informational signals and better markets that can reduce transaction costs and promote connectivity and exchange. Finally, he will highlight the need for smarter cities to integrate engineering solutions with a new logic of design that incorporates open-ended human development and synergies with evolving natural environments.

Luis Bettencourt is a theoretical physicist by training, but rather than study black holes or string theory, he uses data to better understand cities in new and predictive ways.  Bettencourt has spent his career studying complex systems—first as a researcher at the prestigious Santa Fe Institute and now as the inaugural director of the Mansueto Institute for Urban Innovation. Those systems encompass any linked group of things, from ant hills to financial systems, and Bettencourt said cities are some of the most interested complex systems of change, the likes of which have rarely been seen in nature.   “Cities are really the places where people come together and change is generated,” Bettencourt said. “Cities are really these nexus, these inventions by which humans can amplify their capabilities and create a lot of changes.” On this episode of Knowledge Applied, we talk with Bettencourt on how he’s combining science and policy and using data to capture “the magic of cities for the common good.”   Subscribe to Knowledge Applied on iTunes, Stitcher, and Google Play, and learn more at news.uchicago.edu

As cities continue to grow, scientists are trying to define the “Urban Equation” – a mathematical expression that defines not just a group of buildings, but a complex network of physical and social interactions. Why? Because our cities control previously elusive aspects of human evolution. To understand our cities is to understand us. In this episode, Luis Bettencourt and Tyler Nordgren discuss various elements of the urban equation. We see how complex networks give rise to creativity; how to break an urban metropolis down into a series of mathematical symbols; and how our cities are dramatically affecting a cultural connection reaching back nearly 400 years. Season 7, Episode 2 – June 4, 2015

Supercomputers at LANL that simulate a human's visualization process may soon boost technology to automate driving and making life generally easier and safer.