COMPLEXITY: Physics of Life

Scaling Laws & Social Networks in The Time of COVID-19 with Geoffrey West (Part 1)

Episode Notes

We’re living through a unique moment in history. The interlocking crises of a global pandemic, widespread unemployment, social unrest, and climate change, show us just how far human civilization has traveled along a path that leads to collapse. It is more crucial than ever to seek a deeper understanding of the systems that sustain us, and the thin layer of life on the surface of our planet. What are the underlying laws that govern how we live together and as individuals? How do our economies and cities grow? How are the human and non-human worlds related? And can we solve the problems we’ve created when we’re quarantined from one another?

By identifying the basic cardiovascular and nervous systems of human societies, we may one day be able to cure some of the complex diseases of civilization and found a new, sustainable mode of existence.

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 episode is part one of a two-part conversation with Geoffrey West, a physicist,  Distinguished Shannan Professor, and former president of the Santa Fe Institute.

In it we set the stage for a deep, difficult examination of the existential threats we’re facing by reviewing some key revelations from his book, Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. In next week’s episode, we tackle the question of open-ended growth and whether complex systems science offers any insight into the design of a sustainable economy. 

Note that these episodes were taped before the murder of George Floyd, and now seem both strangely out-of-date and uncannily prophetic. Stay tuned in the weeks to come for conversations more directly touching on race, bias, inequality, polarization, counterspeech, and trauma, and follow us on social media for timely coverage of the science helping guide society toward fairer and saner outcomes.

If you value our research and communication efforts, please consider making a one-time or recurring monthly donation at … and/or consider rating and reviewing us at Apple Podcasts. Thank you for listening!

Further Listening & Reading:

Geoffrey West’s Wikipedia & Google Scholar Pages
Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies by Geoffrey West
COMPLEXITY 04: Luis Bettencourt on The Science of Cities
COMPLEXITY 10: Melanie Moses on Metabolic Scaling in Biology & Computation
COMPLEXITY 17: Chris Kempes on The Physical Constraints on Life & Evolution

Visit our website for more information or to support our science and communication efforts.

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Podcast Theme Music by Mitch Mignano.

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Episode Transcription

Michael Garfield: Geoffrey West. It is an honor to have you on Complexity Podcast, finally.

Geoffrey West: Well, Michael, it's a delight to be here and I'm delighted we've eventually found a mutually convenient time to make it work.

Michael Garfield: Well, so let's focus on this fabulous compression and consummation of your work, your book Scale: The Universal Laws of Life, Growth, and death in Organisms, Cities, and Computers. But within this book, there are so many different trajectories that we could take. And you've given so many different interviews about this topic already. It's my hope today that we can carve a refreshingly different path through this and touch on some things that we haven't heard from you before. I guess maybe the place to start is, how did you become a scientist? Let's go all the way back.

Geoffrey West: Oh my God, how did I become a scientist? Well, I suppose it's the confluence of many things, like everybody else, and a lot of serendipitous things that happened, but two pieces were central. One is, I was very good at mathematics when I was a kid. That was one thing. So, you know, it was in language I could adapt to without huge difficulties on the one hand. On the other, I was always sort of a curious kid, like most kids are, but I was always pondering, you know, the meaning of life, what of the stars and, you know, all the kinds of things you do when you're a young kid growing up and beginning to become more and more conscious. And I think also what was crucially important was a gradual, semi-conscious realization that, in answering some of the questions that popped up in my life, when it was a scientific answer, it seemed to have much more — a wealth of facts and knowledge and prediction and understanding behind it than the kind of explanations I was given, which mostly came from either folklore or the Bible, because I had a relatively religious upbringing. And even though I still . . . in kind of a strange way, I respect those narratives, I recognize them as something different, but they did play this role that they weren't satisfying in the same way that explanations with some grounding in what we now call science. And that began more and more to play an important role for me.

Michael Garfield: So, when this book picks up, you're working at Los Alamos in high-energy physics, and you're sort of taken by a bug to follow a particular path and apply some of this mathematical rigor beyond the domain that's normally thought of as the physical domain into life sciences. And then this brings you into a collaboration with Jim Brown and Brian Enquist, and that feels like a good place to start this.

Geoffrey West: Well, I actually in some ways already thought about this many years earlier in teaching, when I was still at Stanford. And one of the things I actually enjoyed was teaching sort of non-physics majors physics. I began to appreciate that because it was extremely challenging. And most of these were pre-meds, not all, but most. And you know, most of them were there just to get the grade and tick the box and so on, but I felt a real challenge to present a cause that I felt, you know, a cultivated, intelligent human being should really be interested in. You know, that is the kind of examples I would choose. So, in so doing that was the first time I started thinking seriously about applying the principles and techniques of physics to biological problems, because I wanted to choose examples that were not just from ordinary day life, but in particular, because there were so many pre-meds, something that might be of relevance to them.

And so, I would concoct all kinds of examples about our body, the physiology of our body and so on, and the world around us, ecosystems, very simple examples, some to do with thermodynamics, some to do with the flow of blood, and so on. And I had already at that time sort of come across the original scaling law of all scaling laws, the scaling law about metabolic rate. And we can come and talk about that in a minute, and it intrigued me that there was such a thing and I sort of worked it in to the course just to show them that, look, here's an interesting way of thinking about something that you'd normally think about in the medical world as eating food and digesting it and sending . . . you know, creating metabolic energy to keep you alive. But how interesting it is, that it has this kind of systematic behavior, and what might that mean?

And, you know, I sort of left it at that, but of course it planted a seed. Because I always, from the beginning, when I entered physics, I had sort of, because I'd been so impressed by the power of mathematics and the power of rational thinking and the power of — and this was extraordinary; it's something I had great difficulty with — of choosing the right variables in which to write the equations and therefore solve a problem. Because I'd always wanted to apply all of that to something beyond the so-called physical world, this sort of planted the seed, which propagated through. And although I spent the rest of my career at that time — the next 25, 30 years — focused on problems at exactly the other end of the spectrum, namely the elementary particles, fundamental forces of nature, and eventually dark matter and string theory and all these wonderful things, the origin of the universe, marvelous questions. Despite being enamored and passionate about that, I always felt that there was this other side that was, you know, having these extraordinary techniques at hand and this powerful way of thinking and formulating problems. Surely we can apply that to situations that are outside of the traditional physical regime. So that's what got me going. And that's why I was very open to it when the timing came along, even though the sequence of events was quite serendipitous.

Michael Garfield: So, this issue of metabolism, you know, it's funny to have you on at this point now that we've already spoken to Luís Bettencourt and Melanie Moses and Chris Kempes about extensions on your work.

Geoffrey West: They’ve all worked under me!

Michael Garfield: Yeah. So I feel like, you know, we've had such rich conversations about scaling already that I'm kind of torn between taking it even further past those or doubling back and doing some remedial work. But I think as far as history and tracing the development of these ideas is concerned, metabolism feels like a good place to start because metabolism seems like it's what provides the analogical framework that we can use to compare all of these different kinds of things — cities, companies, conventionally understood organisms. And so, could you talk a little bit more about how we understand metabolism in a general way and then how metabolism fits in with these properties that you identify, you know, space filling and terminal units and optimization?

Geoffrey West: Sure. Well, first of all, the focus on metabolism is, you know, when you come from a physics background, of course the most natural, the most central. Of course it's also central in biology, but it has been displaced of course, by the genome and the focus on both molecular properties in a very reductionistic way and on information exchange, all of which of course is powerful and important, but in so doing metabolism and the focus on energy has very much taken a back seat in biology. That's a shame because nothing happens without energy and energy is fundamental. And you can't have — at least from my viewpoint — you can't have information exchange, can’t have genes doing what they're doing unless you have energy first. So it's primary. And indeed I would say the evidence strongly points towards metabolism constraining what you can do with genomic networks and so on, and that's a whole other area, but that also relates to how it works in cities.

That is that metabolism of the city — that is, how energy and resources flow through the city — is a huge constraint on what the city and its citizens can accomplish in terms of their social networks. You can't have, obviously, information exchange, wealth creation, ideas generated, businesses flourish without energy and resources. So, it's primary. And it of course can be thought of in two different ways typically. One is the way it's traditionally thought of, I would say, in biology and, to some extent, I would say, in economics and therefore social systems, and that is again in a kind of reductionistic way, in biology, you know, it's a bunch of chemical processes, extraordinarily complex chemical processes that are truly remarkable because they take stuff and turn it into life. But that's what's going on inside us somehow — it's kind of amazing, but it's sophisticated chemical processes. That is usually summarized, somewhat glibly, that the currency of energy is this molecule ATP, which it is, one that is the cycle that allows you to function. It happens within cells inside what's called respiratory complexes. Chemical reactions take place within cells. And in one of your more active cells, there could be as many as even a million of such little engines doing these chemical processes, producing this molecule ATP, which is your sort of currency of energy.

So that's kind of the fundamental viewpoint of it, the reductionistic, but there's another view, which is the more holistic, integrated view. Because obviously there's a million of those inside your cell, and you have a hundred trillion cells in your body, how you actually function, doesn't know anything. You know, you're not at all conscious that any of that is going on, but you use energy all the time. Here I am waving my hands and talking passionately about this and that! Of course, it may have its origins in those ATP molecules, but something else obviously is going on to be able to translate that into action.

And that's the more top-down holistic view, which I took when I started thinking about metabolism. And because one of the things that you recognize about metabolism — about energy in general — is that if you have a system, a highly complex system, like a human body with a hundred trillion cells, you have to supply those with energy in an efficient, roughly democratic fashion. And the way of course we do that is that we have evolved to be a bunch of networks that do that. The most obvious one we’re all familiar with is our circulatory system. Well, we pump blood through our arterial system to take oxygen and other nutrients to the cells which go through this chemical process to produce energy, but they feed the cells and the cells feed the system and so on. It's a continuous feedback loop. What I focused on — and what I became fascinated by — was this other end of the spectrum, macroscopic systemic part of the system in which the network itself is constraining what metabolism can do.

And it turns out that is an extremely fruitful way of looking at the system, because it turns out that gives rise to these extraordinary systematic scaling laws, because those scaling laws actually reflect the scaling of the network — or, more generally, of the multiple networks that control your body. And so, from that viewpoint, the fact that even though we are evolved creatures and all creatures evolved by natural selection, and that implies that there is a huge level of historical contingency in, you know, who we are, meaning that all kinds of frozen accidents took place. There were all kinds of special environmental niches we were in, all kinds of survival-of-the-fittest phenomena going on.

So, all of these things were going on in this messy, extraordinary, apparently random process, in which case you would think almost nothing systematic would evolve from it. It would all be sort of, not exactly arbitrary, but it would have huge variances across different organisms, which is the way we actually see it because we focus on diversity.

We do look very different than an elephant, and we do behave somewhat differently than a mouse. Nevertheless, in terms of anything that you could measure about us, we're actually scaled versions of both an elephant and a mouse, which is about anything we can measure, both our physiology and our life history. And this view, this kind of holistic, top-down view, is that it's not such a surprise because we are all controlled by the same kinds of networks. And it is the mathematics and physics engendered by those networks that are constraining things to behave in similar ways in a predictable scaled fashion, as you go from one small size to a very large size. And so that provided the template for much of the later work.

And I'm so delighted; I hadn't realized you talked to — I knew you’d done Luís. I didn't realize you’d also done Melanie and Chris, but of course they all came a little bit later, but they were all . . . I had extremely fruitful collaborations with all of them.

Michael Garfield: Well, to the episode that we did with Chris, we spent a lot of time talking about his work with you on this particular issue — you know, the biophysical constraints that are lying behind natural selection.

Geoffrey West: Yeah.

Michael Garfield: We talked a lot about the emergence of multicellularity and the break points, major evolutionary transitions, that get into some of these issues about the pace at which a cell divides up against the pace at which it's capable of copying its genetic material and so on.

One of the questions from our audience that seems relevant to this is about cell types. This is one of those areas where I think your work starts to answer questions about the relationship between metabolism and energy and then also regulation and informational structure. So, Caleb Meredith on Twitter wanted to know why is it that the number of cells in multicellular organisms scale with an exponent of roughly 0.88 to the number of genes. Just to append to that his question, it seems like there is an inference that we can draw from that, and you touch on this in your book, about the number of jobs in a city of a given size and so on. And so, what is going on there? Why would the size of a genetic code constrain or determine the number of cell types?

Geoffrey West: So, well, let's see, this is a great question, of course, because it relates to something that is part of my present, ongoing work. Although I must say I'm not making huge progress. And that is, this very general question, which lies at the heart of many complex systems, which complex adaptive systems. And that is the interrelationship between the networks of energy, the physical networks, the infrastructure, the physiology on the one hand and the informational networks. And this question of course relates to it because cells — you know, when you think of a cell you think of its physicality and you certainly think of the physicality of genes, but you normally associate them with encoding information. And so their currency is rather different. Cells, you know, are the centers at a fundamental level of metabolism, of creating metabolic energy. But within those cells, of course, are also genomes that carry information and carry the code. So, one of the things that I've — I was almost going to say railed against, but that's too strong — I've just talked about is that I think it's very misleading only to think of the genome and genomic networks as independent of metabolism, because necessarily they're intertwined.

So, I'm going to now generalize the problem because that's the one I'm most interested in. And that is, if you think of the brain, which is even more extreme than just in terms of ordinary tissue, because the brain clearly is designed to exchange and process information and the emphasis on the brain in terms of research and understanding, is almost entirely in terms of its neural networks, both in terms of how information is exchanged, how it's stored, what are the modularities in that network and so on. However, none of that works, as I said earlier, without the fact that you have an artery that goes out of your heart, goes straight up to your brain to give it all that energy so that it can do that. And those two networks, the neural network and the circulatory system to the brain, are necessarily intertwined and integrated. They're not arbitrarily there. They're carefully tuned to one another. And as just a side comment to that, you know, when people do FMRI studies or just ordinary MRI studies, they don't measure, of course, the neural aspect of your brain. What they actually are measuring is the physical part — the flow of blood. You know, and they’re assuming that that's a proxy for the neural network. And the question is, well, yes, obviously they're into it, but there's very, very little work, if any, on the interface between them.

Going to the language of the scaling laws, and the question of numbers of cells that is raised, the brain is unusual in several respects. First, as an organ within the body, it is almost unique in that it does not scale linearly with the size of the body. So, put slightly differently, elephant's brain is as a proportion of its body mass, much smaller than that of ours, which is much smaller as a proportion than that of a mouse. So you need proportionately less brain, the bigger you are. So that's one curious fact about the brain and you know that, you know, when you see babies. If you actually look at them, you know, as grown-ups, they have enormous heads relative to their bodies. And, indeed, effectively stops growing, well, certainly by about five years old — done. And that's it. And then you sort of sit with this little head on top of this big body. Of course, we don't see it that way, but that's effectively what it is. So the other thing about the brain is that the white matter and the gray matter often scale superlinearly, that is, you have more of it per capita. It's one of the few places in biology where you get such scaling, whereas the regular number of cells in the brain or body decreases with size as you get bigger than the proportion does. And that is reminiscent of a system which we've also studied, and you've heard about it. That is of course of cities, because cities are also a very close integration of, on the one hand, its physicality, the various buildings, roads, and all the various networks of supply, the transport networks, the roads, the gas lines and electric lines — on the one hand its physicality, with, of course, its information exchanges, neural networks, which we call social networks. That is the exchange of information between people. And in that image, one can think of the city as the stage and the infrastructure that is there to facilitate social interaction, to facilitate, to increase information exchange so that, you know, when you look at the scaling of a city with size, in terms of its infrastructure, the part that you sort of naively think of as the city, that scales like biology, sublinearly, meaning the bigger the city, the less infrastructure, whatever it is you need per capita in a systematic way.

However, that facilitates information exchange and you get more of that — more social attraction, therefore more innovation, more wealth creation, more disease, more COVID-19 the bigger the city, because the city is doing what it should be doing. It's increasing interactions, the bigger you are. So, if you live in New York, you're going to get, you know, more buzz, more excitement, more activity. You're going to get higher wages. You're going to be in a more innovative environment, but you're going to get more disease and your liable to get more COVID-19 than you are if you live in little old Santa Fe.

Michael Garfield: Yeah. So for folks that are familiar with your work, you frequently bring up this 15% increase — the dividend comes with per capita doubling of innovation with scale in cities, which you mention in your book. It can be interpreted as a 15% savings in the physical infrastructure of the energy usage.

I think we're getting closer to the heart, if you will, of this issue I wanted to raise with you today, which is that the brain and the heart are not scaling in the same way. So that's like part A. Part B is that the 15% savings doesn't just stay saved. It's fed back into the system. The way we think about it in companies is, oh, that's 15% more I can spend on increasing my productivity. So, the demands for information processing and the metabolic demands seem to be tugging at each other. And this sort of opens up this whole question about the hypothetical cap on city size. You know, you talk about why don't we have mammals the size of Godzilla, and it has to do with the networks of distribution and the difficulty of being able to push resources through them. And I remember when we had Brian Arthur on the show, you know, he was making a case that we have scaled the economy to a point where the resource allocation needs to move from productivity. Like you were talking about earlier about the growth of an individual human, that it moves at some point from productivity to distribution or maintenance costs. And that we're at a point now where the economic system is large enough that we may have to start pushing resources through these networks actively through stuff like basic income.

That's a sort of a multidimensional question, but I'm curious, based on the tension between the demands of the power laws governing information processing and the power laws governing metabolic rate, what you think is the cap on the size of a city or on the size of a global economy before it has to go through a kind of a phase transition into a different kind of architecture in order to persist.

Geoffrey West: Well, that's a big question, you know, the whole thing. I’ll try to dance around it and then try to answer your question.

So, first, the essentials. We didn't quite clarify this, but the essential difference between biological organisms and cities — let's take cities and, by implication, economies — is that in biology, the networks, the ones associated with metabolism, associated with distributing energy and resources, are dominated a simplistic idea of efficiency. That is, how our circulatory system has evolved such that if we make any change in it, you know, you double the size of the fifth branch of your arterial system, or you halve the size of the eighth branch, whatever. If you make any change, your heart will have to work harder. That's sort of the idea — well, that's averaged of course across all mammals. And if you do that, that's a fundamental input into the derivation of the equations that give rise to the scaling laws and to the quantitative form of the scaling laws.

So, that gives rise — that's economy of scale: bigger you are, the less you need, in that case, per cell per capita to stay alive, gives rise to two major things. One is it gives rise to the concept of the pace of life decreasing with size. So elephants sort of walk slower — they don't actually walk slower. They just look like they walked slower. Their heart certainly beats slower. The whole metabolism is slower than a mouse. All in a systematic way. That's one thing: so the pace of life decreases.

The other is that this sublinear behavior, the bigger you are the less per capita, gives rise to a cessation of growth. When you feed that into the growth equations, that gives rise to the idea that you grow faster at the beginning, and then gradually you stop and you reach a stable kind of asymptotic size, and you live most of your life at that size. So that's sort of the idea. And then you die, by the way — that's built into these equations, unfortunately. And that stable configuration of course plays a fundamental role in the generic stability and sustainability of life itself, that there is a stable configuration that the mature organism lives in, okay. There's exceptions to this and so on, but that's sort of the general features.

Now, contrast that with social behavior — socioeconomic behavior and cities. There, we of course do have economies of scale in terms of the infrastructure, the buildings and roads and so on. But we have this new thing, which is the dynamics of social networks, which cities have actually evolved without. As I said earlier, cities are the engine that drives, if you like, social networks, or facilitates social networks; a great city increases social connectivity. And that social connectivity has a characteristic, which is quite different than biological networks, because built into it is positive feedback, A talks to B, B talks to C, C talks to D, D talks back to A . . . there's this conversation goes on and that has positive feedback in it. It produces ideas, produces innovation, almost all of which, even though it's going on all the time, are useless and pointless, even probably to the people involved in them, but that's part of it. But what is remarkable is, every once in a while, it produces the theory of relativity or quantum mechanics or a Google or a Microsoft or whatever.

And that's the wonder of it, but it is the sort of fundamental source of innovation and cities are the engine we have evolved to facilitate that. That positive feedback mechanism gives rise to something quite different than we see in biology. It gives rise to this superlinear scaling. The bigger you are, the more you have per capita: more social interactions per capita, therefore the greater wealth per capita, the greater ideas, more ideas per capita, the more disease per capita, etc.

And that superlinear behavior, if you now feed it into the same growth equations that gave rise to the stability of biological organisms, has a remarkable effect. It gives rise to the open-ended growth of socioeconomic organisms like cities. And so we have a distinct difference, two different categories coming from the same basic mathematics, one giving rise to a kind of highly stable situation, the other giving rise to an open-ended growth situation, which of course is the paradigm under which, especially in the last couple of hundred years, modern society operates. We operate in the paradigm that we need to have open-ended growth to sustain the economy. So that's the structure. And one of the nice things about this work is that it gives very succinct, well-defined mathematical underpinnings for all that, including many, many predictions that all agree with data.

And so, it's a good starting point to ask this question about are there maximum sizes to these things. You know, can you go on making organisms as big as you like? You go from elephants and dinosaurs to blue whales, the biggest organism that has ever existed on the planet — could you make something ten or a hundred times bigger, so to speak? Could something like that evolve? Well, you sort of intimated earlier, the answer is, if you look at all the equations, it turns out highly unlikely. Um, you couldn't have a Godzilla because it turns out that the way those scaling laws work, you simply . . . The whole point of the networks is to supply cells. And, as the system grows, the distance between the capillaries, which feed cells, it gets further and further apart. So that at some stage you simply can't give enough energy to the cells and the system can’t survive. So, whales come pretty near that maximum limit. I would say it's extremely unlikely that there could be larger organisms, with one caveat: given the kinds of body designs that have evolved, and the kind of chemistry that has evolved. So obviously there are always caveats like that.

Now go to the other side of this mathematics, which is the positive feedback loops giving rise to superlinear behavior, which I say gives rise to open-ended growth. Well, turns out if you look at all that, and you just take cities as an example, and you ask the question, could you imagine Tokyo, which is 35 million people, being 70 or a hundred million people? Could you imagine Los Angeles, which is whatever it is, 10 or 12 million people, being 50 million people? Let's take Los Angeles. Well, there's nothing in the equations that stops it. It just could go on just adding on and adding on. That's the first sort of initial, superficial reaction, but then you realize something that is not in the equations, actually. It could be put it in principle. And that is, Los Angeles already has a problem supplying all of its selves, so to speak. It has already 12-lane freeways or whatever it is, something humungous, and they’re clogged. So if you are to supply all of the cells, meaning all of the individual buildings, all the individual people, in one unified network — this is very important — in one, all connected to the same network, which we call Los Angeles, then, if you kept adding and adding and adding, the only way to do it, of course, is to build freeways that are not 12 lanes, but are 25 lanes, and to have rail lines that are not four rail lines, but are ten rail lines, or to completely change the whole transport system in some magical way. Even with electric cars, I'm not sure we could do it, but . . .

Michael Garfield: Or in tunnels underground.

Geoffrey West: You know, so that's the point. If you change — that's why I put the caveat about organisms. If, in some science-fiction world, which may or may not be science fiction, you might be able to invent different physicalities, different solutions, in terms of not necessarily the transport of people, but the communication between people, because the point of a city is, and the definition in this way of thinking of a city is, people in the city have to be connected to the same network. So one of the ways you could define it, just to make that a little clearer, is, you would have to define you would be part of a city. If you interact with someone else in that city, say, at least once a week, it could be someone, it could be anyone. Do I go to the store once a week? You have to interact socioeconomically once a day, once a week; you could define the rate, but you have to have a cutoff.

By the way, it's an interesting definition because you could imagine that you live in Los Angeles and commute to Santa Fe once a week. And you would interact once a week with people in Santa Fe and Los Angeles. And there's no reason you couldn't be citizens of both. But anyway, the point is what you could imagine. So one of the things you could imagine is you completely redesign the city in some way, or you make some extraordinary new inventions in terms of communication and transportation, or you continue to build the city. And what happens, and which we already see happening, is the city alchemizes, it breaks off. That is, even though it is physically contiguous — it just goes on and on and on — it's actually not one city, it's two cities or three cities, four cities. Each one, which is effectively semi-autonomous. And the social networks of one are only very loosely connected to the social networks of the other, even though their infrastructure is continuous. And of course we see developing examples of that.

Michael Garfield: So that is linked to, when we were talking to Melanie Moses, the ant hive as an adaptation to the constraints on the size of insects . . .

Geoffrey West: Yes.

Michael Garfield: . . . and this idea that, you know, the social organism is it kind of balkanization of insect processes in a sense that rather than one big thing, you know, you get the equivalent amount of mass, you know, Ricard Solé would call a liquid brain.

And so this kind of question begs in relation to comments that you made later on I think it's page 406 in the paperback version of Scale, if readers are listening . . .

Geoffrey West: Ah, yes, I remember. Of course!

Michael Garfield: In the paperback version, page 406, you're talking about the longest-lived companies.

Geoffrey West: Oh yes.

Michael Garfield: And how all of these companies are a relatively modest size operating in highly specialized, niche markets, that they look very different from Fortune 500 companies. There's this question. Due to the fragmentation of the social network that we've experienced during this pandemic, and you're seeing a lots of people citing your book on both sides of the argument for the future of mega cities. Does this suggest that, rather than a sort of megalopolis, that we get sort of smaller polycentric coordinated networks of cities? I guess that's the question, or: how does polycentrism fit into an understanding of the way that this is going to scale?

Geoffrey West: Yes, of course. Pandemic is extremely interesting in regards to the future of cities because it is an urban phenomenon predominantly, obviously, because that's where most of the people live. And, as I said earlier, it spreads faster and there are many more cases in cities that are larger. So cities play a predominant role. And, by the way, again, a side comment, cities of course are the determinant of the future of the planet anyway. You know, one of the things that has intrigued me about getting involved in trying to understand cities and why I've been so passionate about it is I believe very strongly that it is the key, the absolute key to global sustainability in the future of the planet. And I'm still disappointed how few people recognize that the city is the key.

And not only that. It plays a special role because one of the things that we've learned and seems to be sort of in our DNA is that we are social creatures and that has been hugely enhanced by our discovery or invention of language and our communication skills that, again, leads to those positive feedback mechanisms and the huge benefits that we have got from that, which has given us the kind of quality and standard alive to which many of us are privileged to have. But it's also so . . . it's almost diabolical, or maybe you could think of it also as poetic justice, but the very mechanisms of social networks that give rise to our huge success — in material terms, anyway — is the very source of our weakness.

And that's what we see in COVID-19 and the pandemic, because the same dynamic — indeed, the same mathematics — that governs the spread of ideas and the growth of innovation and the growth of cities and social systems and economies, that same dynamic is the dynamic, at least, that the spread of disease and in particular of the COVID-19. And we have to come to terms with that, but it's not just COVID-19; it's also spread of other negative aspects of human behavior, antisocial behavior, of crime, of other disease, of corruption, and so on.

So, coming to terms with that, and understanding that balance between the good, bad, and ugly that are inherent in the dynamic and social networks, is crucial. And in terms of the future of the city, I would say that if there are no changes in the way we do business, which is a big question mark and we can return to that momentarily, we've seen this: if you decrease social connectivity in order to limit antisocial behavior, everything from the transmission of disease to crime, then of course you decrease social entrepreneurship, ideas, and so forth.

Now, the thing that has saved us during this pandemic, we all know, is sort of what you and I are doing now, when we could have done this. Maybe I don't know if we would've done. We probably wouldn't because podcasts are by their very nature through the internet, but we could have done this face to face in principle. And I would argue that the vast majority of our meaningful social interactions are in what I call four-dimensional space, namely, the real space of being able to be near, have up, down, and sideways, so to speak, but also be able to smell you and touch you and feel you, I mean, metaphorically, maybe, but to be there with you, you know, and see the nuances of what's happening and what's happening around you. And this is the very essence of and the soul of human interaction. We need that.

And of course that is one reason cities have been so successful, is it engenders that. So, going to this question, that what we need to keep acting and, in fact, to enhance social interaction, but how do we do it by social distancing? And of course we've learned how to do it. We have Zoom and Skype and all the other mechanisms and they serve a purpose. And they've done remarkably well, I must say, I'm amazed how well they've done, but they are two-dimensional. They’re soulless, they're not four-dimensional, and unless we invent — which we may well — much more sophisticated versions, we're kind of stuck with having to agglomerate together in physical, three-dimensional space and be with one another. And there's nothing more satisfying then having an exciting get-together, have a group of people creating new ideas, having discussions, watching a football game together, watching a film together, going to the theater, having sex together, and so on.

This is what life is, and I speak with no expertise, but I feel that's in our DNA. That is who we are. And so it's very hard for me to see that, despite, you know, an aversion at the moment by some to urban living because of the pandemic, but when the new, better, stable configuration evolves in the next year or two, cities will gradually go back to the same trajectory they were on. I mean, there may be changes. I'm not denying that there certainly will be changes. You know, there may be some very positive changes. There may be limitations on transport and limitations on transport, you know, in this picture I saw this morning, I think in The New York Times, pictures of cities where, you know, they're closing roads and the restaurants bring more tables out onto the sidewalk and onto the road. Fantastic. And of course, actually in some ways that increases social conduct. That's why you're in the city — you want that!

So I must say I don't — you know, after all, it's kind of weird. I don't live in a big city, but I recognize the criticality of having big cities. And, as I said earlier, more importantly, really, perhaps more importantly is, that the future of the planet is completely dependent upon the future of our cities.