Geoffrey West: The surprising math of cities and corporations

TED
26 Jul 201117:34

Summary

TLDRThis transcript discusses the exponential growth and impact of urbanization over the past 200 years, emphasizing the critical need for a scientific theory of cities. The speaker highlights how cities contribute to global problems like pollution and disease but also drive creativity, innovation, and economic growth. Using examples from biology, the speaker draws parallels between biological systems and cities, exploring scalability and growth. The talk concludes with a focus on the necessity of continuous innovation to sustain urban development and avoid collapse, comparing the lifecycle of cities to that of companies.

Takeaways

  • 🌆 Cities are crucial to civilization and have been expanding exponentially in the last 200 years.
  • 📈 Urbanization has reached a point where cities dominate the planet, impacting various global issues like global warming, health, pollution, and economies.
  • 🏙️ By 2050, it is expected that cities will continue to grow, with over a million people being added to urban areas weekly.
  • ⚖️ Despite their negative impacts, cities also drive creativity, innovation, and wealth, making them a dual-natured phenomenon.
  • 🔬 There is a need for a scientific theory of cities that relies on quantifiable, universal principles to predict urban growth and challenges.
  • 🌍 Urbanization rates have skyrocketed, with the US being over 82% urbanized and China planning to build 300 new cities in the next 20 years.
  • 📊 Cities exhibit scaling laws similar to biological systems, where socio-economic variables like wages and crime increase with city size, but with greater efficiency.
  • 💡 The concept of networks, especially social networks, is fundamental to understanding the growth and function of cities.
  • ⏩ Larger cities not only grow faster but also see an increase in the pace of life, driven by more interactions and innovations per capita.
  • 🔄 Sustaining urban growth and avoiding collapse requires continuous and accelerating innovation, posing a challenge for long-term sustainability.

Q & A

  • Why are cities considered the 'crucible of civilization'?

    -Cities are considered the 'crucible of civilization' because they have been the centers of human activity, culture, and innovation throughout history. They concentrate populations, which leads to increased creativity, economic activity, and technological advancements.

  • What has been the trend in urbanization over the last 200 years?

    -Urbanization has been expanding at an exponential rate over the last 200 years, leading to a significant increase in the number of people living in cities. This trend is expected to continue, with cities becoming even more dominant by the mid-21st century.

  • What are some of the major problems associated with urbanization?

    -Major problems associated with urbanization include global warming, environmental impact, health issues, pollution, disease, financial challenges, economic disparities, and energy consumption.

  • How has the urbanization rate changed in the United States over the past two centuries?

    -Two hundred years ago, the United States was less than a few percent urbanized. Today, more than 82 percent of the U.S. population lives in urban areas.

  • What is the projected rate of urban population growth until 2050?

    -It is projected that more than a million people will be added to cities every week until 2050, contributing to the rapid urbanization of the planet.

  • Despite their problems, why are cities also considered part of the solution?

    -Cities are considered part of the solution because they are hubs of creativity, innovation, and wealth generation. They attract talented individuals who drive economic growth and develop new ideas and technologies.

  • What is the speaker's provocative statement about cities?

    -The speaker's provocative statement is that there is an urgent need for a scientific theory of cities that relies on quantifiable and predictive principles to understand and address the challenges of urbanization.

  • How do cities compare to biological organisms in terms of resilience?

    -Cities are highly resilient, much like biological organisms. For example, even after significant destruction, such as a nuclear bomb, cities can recover and continue to thrive, whereas companies are more prone to failure and eventual collapse.

  • What role do networks play in the organization and function of cities?

    -Networks play a crucial role in the organization and function of cities, similar to biological systems. Social networks, infrastructure networks, and economic networks all contribute to the efficiency, creativity, and growth of cities.

  • What is the significance of the 15 percent rule mentioned in the script?

    -The 15 percent rule indicates that when the size of a city doubles, there is a 15 percent increase in various socio-economic factors, such as wages, wealth, and innovation, as well as a 15 percent savings on infrastructure. This rule highlights the benefits of urban scaling.

  • How does the pace of life change with city size according to the theory presented?

    -According to the theory, the pace of life increases with city size. As cities grow larger, activities and interactions happen at a faster rate, which contributes to the dynamic and innovative environment of large urban areas.

  • What challenge does continuous urban growth pose, and how can it be addressed?

    -Continuous urban growth poses the challenge of potential collapse due to resource depletion and other constraints. To address this, constant innovation is required to sustain growth and prevent collapse, necessitating a faster and more frequent introduction of new technologies and solutions.

  • How do companies differ from cities in terms of growth and scaling?

    -Companies differ from cities in that they scale sublinearly, similar to biological organisms, and are dominated by economies of scale and bureaucracy. This sublinear scaling leads to sigmoidal growth, meaning companies grow rapidly initially but eventually plateau and die, unlike cities which continue to grow and innovate.

Outlines

00:00

🏙️ The Role of Cities in Civilization and Their Exponential Growth

Cities have played a crucial role in the development of civilization and have seen exponential growth in the last 200 years. This urbanization is projected to dominate the planet by the second half of this century, posing challenges such as global warming, pollution, and economic issues. Despite these problems, cities are also hubs of creativity and innovation. A scientific theory of cities is urgently needed to understand and predict their development. The growth of urbanization is exemplified by the United States, now over 82% urbanized, and China's plan to build 300 new cities in 20 years. This rapid urbanization will significantly impact everyone, necessitating a scientific approach to urban planning.

05:01

📈 Biological Scalability and Its Implications for Urbanization

Scalability is a fundamental aspect of biological systems, contributing to their resilience and robustness. This principle also applies to urbanization. Just as organisms grow and then stop, economies and cities must contend with growth limits. While biology benefits from a slowed pace of life with increased size, cities face challenges if they continue to grow exponentially. This section compares the predictable growth patterns in biology with the dynamic, often unpredictable growth of cities and companies, emphasizing the need for understanding scalability in urban contexts.

10:03

🏢 The Scaling Laws of Cities and Their Universal Principles

Cities, like biological organisms, exhibit scaling laws. The number of petrol stations and other infrastructure components scale with the size of a city, demonstrating economies of scale. However, socio-economic factors such as wages and the number of creative people scale super-linearly, meaning larger cities have higher per capita rates of these variables. This universality across different cities and countries highlights the intrinsic nature of urban networks. The section argues that cities grow faster and life accelerates with size, contrasting the biological principle of slowed life pace with increased size.

15:05

🔄 Continuous Innovation to Sustain Urban Growth and Avoid Collapse

Sustaining urban growth requires continuous innovation to avoid collapse. Unlike biological systems that stabilize after growth, cities must innovate faster and faster to maintain their trajectory. This section outlines the cyclical nature of innovation needed to prevent collapse, likening it to a treadmill that constantly speeds up. The key question posed is whether socio-economic systems can sustain this accelerated pace without succumbing to catastrophic failure. The section also touches on the scalability of companies, which, unlike cities, often follow biological scaling laws and eventually decline.

Mindmap

Keywords

💡Urbanization

Urbanization refers to the process by which rural areas transform into urban areas, leading to the growth of cities. In the video, it is described as an exponential trend over the past 200 years, significantly impacting the planet by increasing the concentration of people in cities and posing sustainability challenges.

💡Sustainability

Sustainability involves meeting the needs of the present without compromising the ability of future generations to meet their own needs. The video highlights sustainability concerns as a reflection of rapid urbanization, indicating that cities must find ways to balance growth with environmental and resource limitations.

💡Scientific Theory of Cities

A scientific theory of cities aims to develop quantifiable, predictive models based on underlying principles that explain how cities grow and function. The speaker emphasizes the urgent need for such a theory to understand and manage the complex dynamics of urbanization and its effects.

💡Economy of Scale

Economy of scale refers to the cost advantages that entities obtain due to their size, output, or scale of operation. In cities, this means that larger cities can operate more efficiently, with fewer resources per capita, similar to biological organisms where larger size results in reduced energy consumption per unit.

💡Super-linear Scaling

Super-linear scaling describes the phenomenon where socio-economic outputs in cities increase disproportionately with size. For example, as cities grow, they generate more wealth, innovation, and social interactions per capita than smaller cities, leading to increased productivity and creativity.

💡Networks

Networks in the context of cities refer to the interconnected systems and interactions among individuals, businesses, and infrastructure. The video explains that cities are physical manifestations of these networks, which drive urban growth, innovation, and socio-economic development.

💡Innovation

Innovation is the process of creating new ideas, products, or methods. In the video, it is presented as a crucial element for sustaining urban growth and preventing collapse. Cities are seen as hubs of innovation, attracting creative individuals and fostering economic development.

💡Resilience

Resilience is the capacity of a system to absorb disturbance and still retain its basic function and structure. The video discusses how cities, like biological organisms, exhibit resilience through scalability and adaptability, allowing them to survive and thrive despite challenges.

💡Exponential Growth

Exponential growth refers to the increasing rate of growth as a function of the growing total number or size. The video highlights how urbanization and the growth of cities have followed an exponential trajectory, leading to rapid increases in urban populations and associated challenges.

💡Predictive Framework

A predictive framework is a structured approach to forecasting future trends based on current data and underlying principles. The speaker calls for the development of such a framework for cities to better anticipate and manage the impacts of urban growth and its socio-economic and environmental consequences.

Highlights

Cities are the crucible of civilization and have been expanding exponentially in the last 200 years.

By the mid-21st century, the planet is expected to be completely dominated by urban areas.

Cities are the origins of global warming and numerous environmental, health, and economic challenges.

The exponential increase in urbanization is a reflection of the sustainability questions we face today.

Two hundred years ago, the United States was less than a few percent urbanized, now it's over 82 percent.

China plans to build 300 new cities in the next 20 years.

Every week until 2050, over a million people will be added to cities globally.

Cities are not only the source of problems but also the solution, attracting creative people and innovation.

There's an urgent need for a scientific theory of cities that is quantifiable and predictive.

Are cities part of biology, and do they share similar principles with living organisms?

Cities, unlike companies, are hard to kill and often survive even after catastrophic events.

The theory suggests that if cities were part of biology, we should be able to predict the lifespan of companies like Google.

Biology exhibits scalability and economies of scale, which contribute to its resilience.

The growth patterns of organisms, including humans, can be predicted using the same principles.

Economic growth, as exemplified by software companies, often follows an unsustainable 'hockey stick' pattern.

Metabolic rates of organisms scale sublinearly with mass, indicating an economy of scale in biology.

Cities and companies may scale differently than biological organisms, with potential super-linear scaling in socio-economic quantities.

Infrastructure and socio-economic quantities in cities exhibit a consistent scaling pattern across different countries.

The size of cities is directly proportional to wages, wealth, and innovation, with a 15% increase per capita as cities grow.

The pace of life in cities increases with their size, suggesting a faster pace due to social networks.

Growth patterns in cities and companies may follow an exponential curve, necessitating continuous innovation to avoid collapse.

Companies scale sublinearly, similar to biology, indicating a shift from innovation to economies of scale and bureaucracy.

The growth of companies, as exemplified by Walmart, eventually follows a sigmoidal pattern, suggesting a limit to growth.

Transcripts

play00:16

Cities are the crucible of civilization.

play00:19

They have been expanding,

play00:21

urbanization has been expanding,

play00:23

at an exponential rate in the last 200 years

play00:25

so that by the second part of this century,

play00:28

the planet will be completely dominated

play00:30

by cities.

play00:33

Cities are the origins of global warming,

play00:36

impact on the environment,

play00:38

health, pollution, disease,

play00:41

finance,

play00:43

economies, energy --

play00:46

they're all problems

play00:48

that are confronted by having cities.

play00:50

That's where all these problems come from.

play00:52

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

play00:55

in terms of sustainability questions

play00:57

are actually a reflection

play00:59

of the exponential increase

play01:01

in urbanization across the planet.

play01:04

Here's some numbers.

play01:06

Two hundred years ago, the United States

play01:08

was less than a few percent urbanized.

play01:10

It's now more than 82 percent.

play01:12

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

play01:15

China's building 300 new cities

play01:17

in the next 20 years.

play01:19

Now listen to this:

play01:21

Every week for the foreseeable future,

play01:24

until 2050,

play01:26

every week more than a million people

play01:28

are being added to our cities.

play01:30

This is going to affect everything.

play01:32

Everybody in this room, if you stay alive,

play01:34

is going to be affected

play01:36

by what's happening in cities

play01:38

in this extraordinary phenomenon.

play01:40

However, cities,

play01:43

despite having this negative aspect to them,

play01:46

are also the solution.

play01:48

Because cities are the vacuum cleaners and the magnets

play01:52

that have sucked up creative people,

play01:54

creating ideas, innovation,

play01:56

wealth and so on.

play01:58

So we have this kind of dual nature.

play02:00

And so there's an urgent need

play02:03

for a scientific theory of cities.

play02:07

Now these are my comrades in arms.

play02:10

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

play02:12

and they've done all the work,

play02:14

and I'm the great bullshitter

play02:16

that tries to bring it all together.

play02:18

(Laughter)

play02:20

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

play02:22

The 10 billion people on the planet in 2050

play02:25

want to live in places like this,

play02:27

having things like this,

play02:29

doing things like this,

play02:31

with economies that are growing like this,

play02:34

not realizing that entropy

play02:36

produces things like this,

play02:38

this, this

play02:42

and this.

play02:44

And the question is:

play02:46

Is that what Edinburgh and London and New York

play02:48

are going to look like in 2050,

play02:50

or is it going to be this?

play02:52

That's the question.

play02:54

I must say, many of the indicators

play02:56

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

play02:59

but let's talk about it.

play03:02

So my provocative statement

play03:05

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

play03:08

And scientific theory means quantifiable --

play03:11

relying on underlying generic principles

play03:14

that can be made into a predictive framework.

play03:16

That's the quest.

play03:18

Is that conceivable?

play03:20

Are there universal laws?

play03:22

So here's two questions

play03:24

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

play03:26

The first is:

play03:28

Are cities part of biology?

play03:30

Is London a great big whale?

play03:32

Is Edinburgh a horse?

play03:34

Is Microsoft a great big anthill?

play03:36

What do we learn from that?

play03:38

We use them metaphorically --

play03:40

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

play03:42

is that just bullshit, metaphorical bullshit,

play03:45

or is there serious substance to it?

play03:48

And if that is the case,

play03:50

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

play03:52

You could drop an atom bomb on a city,

play03:54

and 30 years later it's surviving.

play03:56

Very few cities fail.

play03:59

All companies die, all companies.

play04:02

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

play04:04

when Google is going to go bust.

play04:07

So is that just another version

play04:10

of this?

play04:12

Well we understand this very well.

play04:14

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

play04:16

how many trees of a given size,

play04:18

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

play04:20

how many leaves,

play04:22

what is the energy flowing through each branch,

play04:24

what is the size of the canopy,

play04:26

what is its growth, what is its mortality?

play04:28

We have a mathematical framework

play04:30

based on generic universal principles

play04:33

that can answer those questions.

play04:35

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

play04:40

So the route in is recognizing

play04:43

one of the most extraordinary things about life,

play04:45

is that it is scalable,

play04:47

it works over an extraordinary range.

play04:49

This is just a tiny range actually:

play04:51

It's us mammals;

play04:53

we're one of these.

play04:55

The same principles, the same dynamics,

play04:57

the same organization is at work

play04:59

in all of these, including us,

play05:01

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

play05:04

And that is one of the main reasons

play05:07

life is so resilient and robust --

play05:09

scalability.

play05:11

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

play05:14

But you know, at a local level,

play05:16

you scale; everybody in this room is scaled.

play05:18

That's called growth.

play05:20

Here's how you grew.

play05:22

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

play05:24

We're all pretty much the same.

play05:27

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

play05:29

You grow very quickly and then you stop.

play05:31

And that line there

play05:33

is a prediction from the same theory,

play05:35

based on the same principles,

play05:37

that describes that forest.

play05:39

And here it is for the growth of a rat,

play05:41

and those points on there are data points.

play05:43

This is just the weight versus the age.

play05:45

And you see, it stops growing.

play05:47

Very, very good for biology --

play05:49

also one of the reasons for its great resilience.

play05:51

Very, very bad

play05:53

for economies and companies and cities

play05:55

in our present paradigm.

play05:57

This is what we believe.

play05:59

This is what our whole economy

play06:01

is thrusting upon us,

play06:03

particularly illustrated in that left-hand corner:

play06:06

hockey sticks.

play06:08

This is a bunch of software companies --

play06:10

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

play06:12

all zooming away,

play06:14

and everybody making millions and billions of dollars.

play06:16

Okay, so how do we understand this?

play06:19

So let's first talk about biology.

play06:22

This is explicitly showing you

play06:24

how things scale,

play06:26

and this is a truly remarkable graph.

play06:28

What is plotted here is metabolic rate --

play06:31

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

play06:34

versus your weight, your mass,

play06:36

for all of us bunch of organisms.

play06:39

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

play06:42

otherwise you couldn't get everything on the graph.

play06:44

And what you see if you plot it

play06:46

in this slightly curious way

play06:48

is that everybody lies on the same line.

play06:51

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

play06:54

in the universe,

play06:57

there's an extraordinary simplicity

play06:59

being expressed by this.

play07:01

It's particularly astonishing

play07:04

because each one of these organisms,

play07:06

each subsystem, each cell type, each gene,

play07:08

has evolved in its own unique environmental niche

play07:12

with its own unique history.

play07:15

And yet, despite all of that Darwinian evolution

play07:18

and natural selection,

play07:20

they've been constrained to lie on a line.

play07:22

Something else is going on.

play07:24

Before I talk about that,

play07:26

I've written down at the bottom there

play07:28

the slope of this curve, this straight line.

play07:30

It's three-quarters, roughly,

play07:32

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

play07:35

And here's the point of that.

play07:37

It says that, if it were linear,

play07:40

the steepest slope,

play07:42

then doubling the size

play07:44

you would require double the amount of energy.

play07:46

But it's sublinear, and what that translates into

play07:49

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

play07:51

you actually only need 75 percent more energy.

play07:54

So a wonderful thing about all of biology

play07:56

is that it expresses an extraordinary economy of scale.

play07:59

The bigger you are systematically,

play08:01

according to very well-defined rules,

play08:03

less energy per capita.

play08:06

Now any physiological variable you can think of,

play08:09

any life history event you can think of,

play08:11

if you plot it this way, looks like this.

play08:14

There is an extraordinary regularity.

play08:16

So you tell me the size of a mammal,

play08:18

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

play08:21

in terms of its physiology, life history, etc.

play08:25

And the reason for this is because of networks.

play08:28

All of life is controlled by networks --

play08:31

from the intracellular through the multicellular

play08:33

through the ecosystem level.

play08:35

And you're very familiar with these networks.

play08:39

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

play08:42

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

play08:45

If you take those networks,

play08:47

this idea of networks,

play08:49

and you apply universal principles,

play08:51

mathematizable, universal principles,

play08:53

all of these scalings

play08:55

and all of these constraints follow,

play08:58

including the description of the forest,

play09:00

the description of your circulatory system,

play09:02

the description within cells.

play09:04

One of the things I did not stress in that introduction

play09:07

was that, systematically, the pace of life

play09:10

decreases as you get bigger.

play09:12

Heart rates are slower; you live longer;

play09:15

diffusion of oxygen and resources

play09:17

across membranes is slower, etc.

play09:19

The question is: Is any of this true

play09:21

for cities and companies?

play09:24

So is London a scaled up Birmingham,

play09:27

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

play09:30

Is New York a scaled up San Francisco,

play09:32

which is a scaled up Santa Fe?

play09:34

Don't know. We will discuss that.

play09:36

But they are networks,

play09:38

and the most important network of cities

play09:40

is you.

play09:42

Cities are just a physical manifestation

play09:45

of your interactions,

play09:47

our interactions,

play09:49

and the clustering and grouping of individuals.

play09:51

Here's just a symbolic picture of that.

play09:54

And here's scaling of cities.

play09:56

This shows that in this very simple example,

play09:59

which happens to be a mundane example

play10:01

of number of petrol stations

play10:03

as a function of size --

play10:05

plotted in the same way as the biology --

play10:07

you see exactly the same kind of thing.

play10:09

There is a scaling.

play10:11

That is that the number of petrol stations in the city

play10:15

is now given to you

play10:17

when you tell me its size.

play10:19

The slope of that is less than linear.

play10:22

There is an economy of scale.

play10:24

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

play10:27

But here's what's surprising.

play10:29

It scales in the same way everywhere.

play10:31

This is just European countries,

play10:33

but you do it in Japan or China or Colombia,

play10:36

always the same

play10:38

with the same kind of economy of scale

play10:40

to the same degree.

play10:42

And any infrastructure you look at --

play10:45

whether it's the length of roads, length of electrical lines --

play10:48

anything you look at

play10:50

has the same economy of scale scaling in the same way.

play10:53

It's an integrated system

play10:55

that has evolved despite all the planning and so on.

play10:58

But even more surprising

play11:00

is if you look at socio-economic quantities,

play11:02

quantities that have no analog in biology,

play11:05

that have evolved when we started forming communities

play11:08

eight to 10,000 years ago.

play11:10

The top one is wages as a function of size

play11:12

plotted in the same way.

play11:14

And the bottom one is you lot --

play11:16

super-creatives plotted in the same way.

play11:19

And what you see

play11:21

is a scaling phenomenon.

play11:23

But most important in this,

play11:25

the exponent, the analog to that three-quarters

play11:27

for the metabolic rate,

play11:29

is bigger than one -- it's about 1.15 to 1.2.

play11:31

Here it is,

play11:33

which says that the bigger you are

play11:36

the more you have per capita, unlike biology --

play11:39

higher wages, more super-creative people per capita as you get bigger,

play11:43

more patents per capita, more crime per capita.

play11:46

And we've looked at everything:

play11:48

more AIDS cases, flu, etc.

play11:51

And here, they're all plotted together.

play11:53

Just to show you what we plotted,

play11:55

here is income, GDP --

play11:58

GDP of the city --

play12:00

crime and patents all on one graph.

play12:02

And you can see, they all follow the same line.

play12:04

And here's the statement.

play12:06

If you double the size of a city from 100,000 to 200,000,

play12:09

from a million to two million, 10 to 20 million,

play12:11

it doesn't matter,

play12:13

then systematically

play12:15

you get a 15 percent increase

play12:17

in wages, wealth, number of AIDS cases,

play12:19

number of police,

play12:21

anything you can think of.

play12:23

It goes up by 15 percent,

play12:25

and you have a 15 percent savings

play12:28

on the infrastructure.

play12:31

This, no doubt, is the reason

play12:34

why a million people a week are gathering in cities.

play12:37

Because they think that all those wonderful things --

play12:40

like creative people, wealth, income --

play12:42

is what attracts them,

play12:44

forgetting about the ugly and the bad.

play12:46

What is the reason for this?

play12:48

Well I don't have time to tell you about all the mathematics,

play12:51

but underlying this is the social networks,

play12:54

because this is a universal phenomenon.

play12:57

This 15 percent rule

play13:00

is true

play13:02

no matter where you are on the planet --

play13:04

Japan, Chile,

play13:06

Portugal, Scotland, doesn't matter.

play13:09

Always, all the data shows it's the same,

play13:12

despite the fact that these cities have evolved independently.

play13:15

Something universal is going on.

play13:17

The universality, to repeat, is us --

play13:20

that we are the city.

play13:22

And it is our interactions and the clustering of those interactions.

play13:25

So there it is, I've said it again.

play13:27

So if it is those networks and their mathematical structure,

play13:30

unlike biology, which had sublinear scaling,

play13:33

economies of scale,

play13:35

you had the slowing of the pace of life

play13:37

as you get bigger.

play13:39

If it's social networks with super-linear scaling --

play13:41

more per capita --

play13:43

then the theory says

play13:45

that you increase the pace of life.

play13:47

The bigger you are, life gets faster.

play13:49

On the left is the heart rate showing biology.

play13:51

On the right is the speed of walking

play13:53

in a bunch of European cities,

play13:55

showing that increase.

play13:57

Lastly, I want to talk about growth.

play14:00

This is what we had in biology, just to repeat.

play14:03

Economies of scale

play14:06

gave rise to this sigmoidal behavior.

play14:09

You grow fast and then stop --

play14:12

part of our resilience.

play14:14

That would be bad for economies and cities.

play14:17

And indeed, one of the wonderful things about the theory

play14:19

is that if you have super-linear scaling

play14:22

from wealth creation and innovation,

play14:24

then indeed you get, from the same theory,

play14:27

a beautiful rising exponential curve -- lovely.

play14:29

And in fact, if you compare it to data,

play14:31

it fits very well

play14:33

with the development of cities and economies.

play14:35

But it has a terrible catch,

play14:37

and the catch

play14:39

is that this system is destined to collapse.

play14:42

And it's destined to collapse for many reasons --

play14:44

kind of Malthusian reasons -- that you run out of resources.

play14:47

And how do you avoid that? Well we've done it before.

play14:50

What we do is,

play14:52

as we grow and we approach the collapse,

play14:55

a major innovation takes place

play14:58

and we start over again,

play15:00

and we start over again as we approach the next one, and so on.

play15:03

So there's this continuous cycle of innovation

play15:05

that is necessary

play15:07

in order to sustain growth and avoid collapse.

play15:10

The catch, however, to this

play15:12

is that you have to innovate

play15:14

faster and faster and faster.

play15:17

So the image

play15:19

is that we're not only on a treadmill that's going faster,

play15:22

but we have to change the treadmill faster and faster.

play15:25

We have to accelerate on a continuous basis.

play15:28

And the question is: Can we, as socio-economic beings,

play15:31

avoid a heart attack?

play15:34

So lastly, I'm going to finish up in this last minute or two

play15:37

asking about companies.

play15:39

See companies, they scale.

play15:41

The top one, in fact, is Walmart on the right.

play15:43

It's the same plot.

play15:45

This happens to be income and assets

play15:47

versus the size of the company as denoted by its number of employees.

play15:49

We could use sales, anything you like.

play15:52

There it is: after some little fluctuations at the beginning,

play15:55

when companies are innovating,

play15:57

they scale beautifully.

play15:59

And we've looked at 23,000 companies

play16:02

in the United States, may I say.

play16:04

And I'm only showing you a little bit of this.

play16:07

What is astonishing about companies

play16:09

is that they scale sublinearly

play16:12

like biology,

play16:14

indicating that they're dominated,

play16:16

not by super-linear

play16:18

innovation and ideas;

play16:21

they become dominated

play16:23

by economies of scale.

play16:25

In that interpretation,

play16:27

by bureaucracy and administration,

play16:29

and they do it beautifully, may I say.

play16:31

So if you tell me the size of some company, some small company,

play16:34

I could have predicted the size of Walmart.

play16:37

If it has this sublinear scaling,

play16:39

the theory says

play16:41

we should have sigmoidal growth.

play16:44

There's Walmart. Doesn't look very sigmoidal.

play16:46

That's what we like, hockey sticks.

play16:49

But you notice, I've cheated,

play16:51

because I've only gone up to '94.

play16:53

Let's go up to 2008.

play16:55

That red line is from the theory.

play16:58

So if I'd have done this in 1994,

play17:00

I could have predicted what Walmart would be now.

play17:03

And then this is repeated

play17:05

across the entire spectrum of companies.

play17:07

There they are. That's 23,000 companies.

play17:10

They all start looking like hockey sticks,

play17:12

they all bend over,

play17:14

and they all die like you and me.

play17:16

Thank you.

play17:18

(Applause)

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Related Tags
UrbanizationSustainabilityInnovationEconomic GrowthEnvironmental ImpactGlobal WarmingCitiesTheory of CitiesSocial NetworksEconomic Theory