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  • Cities are the crucible of civilization.

  • They have been expanding,

  • urbanization has been expanding,

  • at an exponential rate in the last 200 years

  • so that by the second part of this century,

  • the planet will be completely dominated

  • by cities.

  • Cities are the origins of global warming,

  • impact on the environment,

  • health, pollution, disease,

  • finance,

  • economies, energy --

  • they're all problems

  • that are confronted by having cities.

  • That's where all these problems come from.

  • And the tsunami of problems that we feel we're facing

  • in terms of sustainability questions

  • are actually a reflection

  • of the exponential increase

  • in urbanization across the planet.

  • Here's some numbers.

  • Two hundred years ago, the United States

  • was less than a few percent urbanized.

  • It's now more than 82 percent.

  • The planet has crossed the halfway mark a few years ago.

  • China's building 300 new cities

  • in the next 20 years.

  • Now listen to this:

  • Every week for the foreseeable future,

  • until 2050,

  • every week more than a million people

  • are being added to our cities.

  • This is going to affect everything.

  • Everybody in this room, if you stay alive,

  • is going to be affected

  • by what's happening in cities

  • in this extraordinary phenomenon.

  • However, cities,

  • despite having this negative aspect to them,

  • are also the solution.

  • Because cities are the vacuum cleaners and the magnets

  • that have sucked up creative people,

  • creating ideas, innovation,

  • wealth and so on.

  • So we have this kind of dual nature.

  • And so there's an urgent need

  • for a scientific theory of cities.

  • Now these are my comrades in arms.

  • This work has been done with an extraordinary group of people,

  • and they've done all the work,

  • and I'm the great bullshitter

  • that tries to bring it all together.

  • (Laughter)

  • So here's the problem: This is what we all want.

  • The 10 billion people on the planet in 2050

  • want to live in places like this,

  • having things like this,

  • doing things like this,

  • with economies that are growing like this,

  • not realizing that entropy

  • produces things like this,

  • this, this

  • and this.

  • And the question is:

  • Is that what Edinburgh and London and New York

  • are going to look like in 2050,

  • or is it going to be this?

  • That's the question.

  • I must say, many of the indicators

  • look like this is what it's going to look like,

  • but let's talk about it.

  • So my provocative statement

  • is that we desperately need a serious scientific theory of cities.

  • And scientific theory means quantifiable --

  • relying on underlying generic principles

  • that can be made into a predictive framework.

  • That's the quest.

  • Is that conceivable?

  • Are there universal laws?

  • So here's two questions

  • that I have in my head when I think about this problem.

  • The first is:

  • Are cities part of biology?

  • Is London a great big whale?

  • Is Edinburgh a horse?

  • Is Microsoft a great big anthill?

  • What do we learn from that?

  • We use them metaphorically --

  • the DNA of a company, the metabolism of a city, and so on --

  • is that just bullshit, metaphorical bullshit,

  • or is there serious substance to it?

  • And if that is the case,

  • how come that it's very hard to kill a city?

  • You could drop an atom bomb on a city,

  • and 30 years later it's surviving.

  • Very few cities fail.

  • All companies die, all companies.

  • And if you have a serious theory, you should be able to predict

  • when Google is going to go bust.

  • So is that just another version

  • of this?

  • Well we understand this very well.

  • That is, you ask any generic question about this --

  • how many trees of a given size,

  • how many branches of a given size does a tree have,

  • how many leaves,

  • what is the energy flowing through each branch,

  • what is the size of the canopy,

  • what is its growth, what is its mortality?

  • We have a mathematical framework

  • based on generic universal principles

  • that can answer those questions.

  • And the idea is can we do the same for this?

  • So the route in is recognizing

  • one of the most extraordinary things about life,

  • is that it is scalable,

  • it works over an extraordinary range.

  • This is just a tiny range actually:

  • It's us mammals;

  • we're one of these.

  • The same principles, the same dynamics,

  • the same organization is at work

  • in all of these, including us,

  • and it can scale over a range of 100 million in size.

  • And that is one of the main reasons

  • life is so resilient and robust --

  • scalability.

  • We're going to discuss that in a moment more.

  • But you know, at a local level,

  • you scale; everybody in this room is scaled.

  • That's called growth.

  • Here's how you grew.

  • Rat, that's a rat -- could have been you.

  • We're all pretty much the same.

  • And you see, you're very familiar with this.

  • You grow very quickly and then you stop.

  • And that line there

  • is a prediction from the same theory,

  • based on the same principles,

  • that describes that forest.

  • And here it is for the growth of a rat,

  • and those points on there are data points.

  • This is just the weight versus the age.

  • And you see, it stops growing.

  • Very, very good for biology --

  • also one of the reasons for its great resilience.

  • Very, very bad

  • for economies and companies and cities

  • in our present paradigm.

  • This is what we believe.

  • This is what our whole economy

  • is thrusting upon us,

  • particularly illustrated in that left-hand corner:

  • hockey sticks.

  • This is a bunch of software companies --

  • and what it is is their revenue versus their age --

  • all zooming away,

  • and everybody making millions and billions of dollars.

  • Okay, so how do we understand this?

  • So let's first talk about biology.

  • This is explicitly showing you

  • how things scale,

  • and this is a truly remarkable graph.

  • What is plotted here is metabolic rate --

  • how much energy you need per day to stay alive --

  • versus your weight, your mass,

  • for all of us bunch of organisms.

  • And it's plotted in this funny way by going up by factors of 10,

  • otherwise you couldn't get everything on the graph.

  • And what you see if you plot it

  • in this slightly curious way

  • is that everybody lies on the same line.

  • Despite the fact that this is the most complex and diverse system

  • in the universe,

  • there's an extraordinary simplicity

  • being expressed by this.

  • It's particularly astonishing

  • because each one of these organisms,

  • each subsystem, each cell type, each gene,

  • has evolved in its own unique environmental niche

  • with its own unique history.

  • And yet, despite all of that Darwinian evolution

  • and natural selection,

  • they've been constrained to lie on a line.

  • Something else is going on.

  • Before I talk about that,

  • I've written down at the bottom there

  • the slope of this curve, this straight line.

  • It's three-quarters, roughly,

  • which is less than one -- and we call that sublinear.

  • And here's the point of that.

  • It says that, if it were linear,

  • the steepest slope,

  • then doubling the size

  • you would require double the amount of energy.

  • But it's sublinear, and what that translates into

  • is that, if you double the size of the organism,

  • you actually only need 75 percent more energy.

  • So a wonderful thing about all of biology

  • is that it expresses an extraordinary economy of scale.

  • The bigger you are systematically,

  • according to very well-defined rules,

  • less energy per capita.

  • Now any physiological variable you can think of,

  • any life history event you can think of,

  • if you plot it this way, looks like this.

  • There is an extraordinary regularity.

  • So you tell me the size of a mammal,

  • I can tell you at the 90 percent level everything about it

  • in terms of its physiology, life history, etc.

  • And the reason for this is because of networks.

  • All of life is controlled by networks --

  • from the intracellular through the multicellular

  • through the ecosystem level.

  • And you're very familiar with these networks.

  • That's a little thing that lives inside an elephant.

  • And here's the summary of what I'm saying.

  • If you take those networks,

  • this idea of networks,

  • and you apply universal principles,

  • mathematizable, universal principles,

  • all of these scalings

  • and all of these constraints follow,

  • including the description of the forest,

  • the description of your circulatory system,

  • the description within cells.

  • One of the things I did not stress in that introduction

  • was that, systematically, the pace of life

  • decreases as you get bigger.

  • Heart rates are slower; you live longer;

  • diffusion of oxygen and resources

  • across membranes is slower, etc.

  • The question is: Is any of this true

  • for cities and companies?

  • So is London a scaled up Birmingham,

  • which is a scaled up Brighton, etc., etc.?

  • Is New York a scaled up San Francisco,

  • which is a scaled up Santa Fe?

  • Don't know. We will discuss that.

  • But they are networks,

  • and the most important network of cities

  • is you.

  • Cities are just a physical manifestation

  • of your interactions,

  • our interactions,

  • and the clustering and grouping of individuals.

  • Here's just a symbolic picture of that.

  • And here's scaling of cities.

  • This shows that in this very simple example,

  • which happens to be a mundane example

  • of number of petrol stations

  • as a function of size --

  • plotted in the same way as the biology --

  • you see exactly the same kind of thing.

  • There is a scaling.

  • That is that the number of petrol stations in the city

  • is now given to you

  • when you tell me its size.

  • The slope of that is less than linear.

  • There is an economy of scale.

  • Less petrol stations per capita the bigger you are -- not surprising.

  • But here's what's surprising.

  • It scales in the same way everywhere.