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.
城市是文明的熔炉 它们一直在扩张 城市化的扩张速度 在过去的200年里变得越来越快 到了本世纪下半叶 整个地球都将被城市 所主宰 城市是全球变暖的源头 影响着环境 卫生 污染 疾病 金融 经济 能源-- 这些问题 都是由城市引起的 这是所有这些问题的源头 我们感觉可持续性方面的问题 正如海啸般扑面而来 而这些问题实际上 是与日俱增的 全球城市化进程所产生的效应
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.
我们来看几个数字 200年前 美国 城市化程度不到百分之几而已 而现在则超过了82% 全球的城市化程度在几年前就超过了百分之五十 中国在将来的20年内 建设300座新城市 请注意 在将来的每一周 一直到2050年 每一周 将有100万人 进入我们的城市 这将对一切产生影响 在座的各位 如果你一直活着 你就必定要受到 城市化所带来的 翻天覆地的影响 然而 城市 尽管存在负面效应 但城市也是问题解决的出路 这是因为城市是除尘器和吸铁石 吸纳了所有创意人才 创造着思想 革新 财富等等 我们具有这样的双面性 我们迫切需要运用 城市的科学原理
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.
这些是我全副武装的同志们 这群杰出的人士做了这些工作 都是他们的功劳 我只会胡吹海侃 做个总体介绍
(Laughter)
(众人笑)
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.
这里有个问题 这是我们希望的结果 到了2050年,地球上的10亿人 都想生活在这样的地方 拥有这些东西 进行这样的活动 在这样的经济增长情况下 而没有意识到 人口过剩会造成这样 这样 这样 和这样的情况 问题是 爱丁堡 伦敦和纽约 到了2050年会变成这样 还是这样 这是个问题 我不得不说 许多这样的参数 似乎更可能是它们将来的样子 我们来探讨一下
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.
我敢大胆地说 我们急需一个严谨的城市科学理论 科学理论意味着它是可量化的 依据基本的普遍原理 我们能够推导出一个可预见的结构 这是我们的目标 这可能吗 有这样的普遍定律吗 每当我思考这个问题 两个疑问一直在我脑子里打转 第一 城市是生物界的一部分吗 伦敦是一只大鲸鱼吗 爱丁堡是一匹马吗 微软是一座巨型蚁山吗 我们从中能得到什么启发 我们可以使用比喻 一个公司的DNA 一个城市的新陈代谢 等等 这些都是胡扯 乱七八糟的比喻 还是有严谨的依据 如果确有依据 为什么城市总是生生不息呢 你可以扔一个原子弹炸毁一个城市 而30年之后 它依然存在 消亡的城市寥寥无几 而所有公司都会关门 无一例外 如果你掌握了缜密的原理 你就应该可以预测 谷歌什么时候关门大吉
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.
这是不是 这个画面的翻版 我们对此非常清楚 如果你随便问一个常识问题 某已知体积的大树有多少棵 一颗体积已知的大树有多少分枝 多少树叶 每根树枝中流动的能量是什么 树冠有多大 它长势如何 寿命多长 我们有一套数学体系 建立在普遍原理的基础上 它能够解答那些问题 问题是 它是否适用于城市 首先我们要认识到 生命最奇妙之处 其中之一 就是它是会长大的 它能够长到非常之大 这只是很小的一个尺度 这是我们 哺乳动物 我们是其中之一 相同的原理 相同的活动 相同的组织 在所有这些动物中 发挥着作用 我们也包括在内 它能够长大到一亿个单位 生命如此周而复始 欣欣向荣 这就是原因之一 伸展性 我们一会再讨论这个
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.
从我们自身出发 你会长大 在座所有人的身体都长大了 这就是成长 你就是这么成长的 这是一只老鼠 也可以是你 我们之间非常相似 你们可以看到 你的情况与之十分相似 你长得很快 接着停止生长 上面的那条线 是同一理论推导出来的 所依据的原理 与描述森林的原理相同 这显示的是老鼠的生长情况 上面的点是数据点 即体重与年龄的比例 你看 它停止生长了 这对生物界非常有益 这也证明了其强大的伸展性 但对我们目前规划中的 经济 公司和城市而而言 这是非常糟糕的 我们就是这么认为的 这就是我们的经济 强加给我们的 左上角的图表凸显了这一点 冰球棍 它显示的是众多软件公司 收入与公司建立时间的比例 它们都平步青云 每家公司都大把大把地捞钱
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.
那么 我们如何解读 我们先来讨论一下生物学 这让你清清楚楚地看到 事物的规模是如何增大的 这幅图表意义非凡 上面显示的是新陈代谢率 为维持生命你每天需要摄入的能量 比上你的体重 这适用于人类以及许多其它生物 它的结构很有意思 以10倍递进 否则你无法看到全局 在这样一个有意思的图标中 你可以看到 每个人都落在了同一条线上 尽管这是宇宙中 最为纷繁复杂的系统 但它显示了一个 极为简单现象 这令人震惊 这上面的每个物种 每个子系统 每个细胞种类 每个基因 都在其独特的生态位和历史中 得到进化发展 然而 即使经过了达尔文派支持的进化论 和自然选择 它们最终还是集中到了一条线上
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.
还有其它力量在发挥作用 谈到这之前 我在底下标出了 这条曲线的斜率 即这条直线 大约为3比4 小于1 呈“次线性” 这里有一点值得注意 当最大斜率 呈线性 那么当体型翻倍 所需能量也随之翻倍 而若呈次线性 情况则是 当生物的体型翻倍 它实际只需增加75%的能量 生物的奇妙之处就在于 它巧妙地展现了经济的伸展能力 根据准确定义的规律 一个系统越大 其所需的平均能力越少 你能够想到的任何变量 任何历史事件 只要你照着这样制表 都会得到相似的图形 其一致性非常惊人 只要你说出一种哺乳动物的体型 我就能告诉你关于其生理和生命周期等情况 正确率90%
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.
原因就在于网络 所有生命都由网络所控制 不论是单细胞还是多细胞生物 整个生态系统都是如此 你对这些网络并不陌生 这是生长在大象体内的一种小生物 这是我讲话内容的总结 你有了这些网络 网络的概念 再用上普遍原理 数学化的普遍原理 所有规模增长 所有限制因素 包括森林的情况 你循环系统的情况 细胞内部情况等 我在介绍中没有提及的一点是 生长的节奏会随着你体型的增大 而系统性地减缓 心率会减缓 你活得更久 通过细胞膜的氧气 和物质的流动减缓
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.
问题是 这是否 也适用于城市和企业 伦敦是否是长大了的伯明翰 而伯明翰是否是长大了的布莱顿 等等 纽约是否是长大了的旧金山 而旧金山是否是长大了的圣达菲 不知道 我们稍候再讨论 但它们都是网络 而城市最重要的网络 就是你 城市只是 你我社会活动 以及个体相互聚拢集合的 物质表现 这只是一张简易图表 这是城市规模的扩大 这幅图显示出了一个非常简单的例子 这例子很寻常 加油站的数量 作为规模 按照同于生物的方法制表 你能够观察到一模一样的结果
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. This is just European countries, but you do it in Japan or China or Colombia, always the same with the same kind of economy of scale to the same degree. And any infrastructure you look at -- whether it's the length of roads, length of electrical lines -- anything you look at has the same economy of scale scaling in the same way. It's an integrated system that has evolved despite all the planning and so on. But even more surprising is if you look at socio-economic quantities, quantities that have no analog in biology, that have evolved when we started forming communities eight to 10,000 years ago. The top one is wages as a function of size plotted in the same way. And the bottom one is you lot -- super-creatives plotted in the same way. And what you see is a scaling phenomenon. But most important in this, the exponent, the analog to that three-quarters for the metabolic rate, is bigger than one -- it's about 1.15 to 1.2. Here it is, which says that the bigger you are the more you have per capita, unlike biology -- higher wages, more super-creative people per capita as you get bigger, more patents per capita, more crime per capita.
上面显示了增长的趋势 你告诉我城市的规模 我就能够说出 这座城市有多少个加油站 斜率呈次线性 这是规模经济 城市越大 人均加油站数量就越小 并不稀奇 稀奇的在这里 增长的规律在哪里都适用 这反映的只是欧洲国家的情况 但如果你用同样的方法观察日本 中国或哥伦比亚 结果都是一样的 同样的规模经济 同样的水平 而且 你看到的所有基础设施 不论是道路还是电线的长度 不论是什么 都存在增长模式相同的规模经济 这个综合体系 不停演进 无论如何规划都是如此 而当你看到 社会经济数量 即八千到一万年前 我们开始建立社区时的社会经济数量 你们会感到更加意外 上图以工资作为规模参数 同理制表 而下面的是“你” 也就是超级智能人 同理制表 上面显示出 一个规模增长的现象 但图上最重要的是 新陈代谢率的幂 近似于三分之四 大于1 大约在1.15和1.2之间 意思是 规模越大 人均数就越多 与生物学的情况相反 工资越高 就有越多的超级智能人出现 人均专利和犯罪率越高
And we've looked at everything: more AIDS cases, flu, etc. And here, they're all plotted together. Just to show you what we plotted, here is income, GDP -- GDP of the city -- crime and patents all on one graph. And you can see, they all follow the same line. And here's the statement. If you double the size of a city from 100,000 to 200,000, from a million to two million, 10 to 20 million, it doesn't matter, then systematically you get a 15 percent increase in wages, wealth, number of AIDS cases, number of police, anything you can think of. It goes up by 15 percent, and you have a 15 percent savings on the infrastructure. This, no doubt, is the reason why a million people a week are gathering in cities. Because they think that all those wonderful things -- like creative people, wealth, income -- is what attracts them, forgetting about the ugly and the bad.
我们研究了所有事物 艾滋病病例 流感等等 把这些都放在一起制成表 让你们看到 我们把收入 GDP 城市的GDP 犯罪和专利都放在一张图上 你们可以看到 下面是图的表述 如果一个城市的规模从10万增长至20万 从一百万到两百万 从一千万到两千万 都一样 在这个城市中 工资 财富 艾滋病病例 警察人数 任何你能想到的事物 都会系统地增加15% 对于所有事物都是如此 你还能节省 15%的基础设施经费 这无疑就是 城市每周新增一百万人口的原因 他们觉得那些美好的事物 包括创新人才 财富 收入 对他们有吸引力 而忘记了城市丑恶的一面
What is the reason for this? Well I don't have time to tell you about all the mathematics, but underlying this is the social networks, because this is a universal phenomenon. This 15 percent rule is true no matter where you are on the planet -- Japan, Chile, Portugal, Scotland, doesn't matter. Always, all the data shows it's the same, despite the fact that these cities have evolved independently. Something universal is going on. The universality, to repeat, is us -- that we are the city. And it is our interactions and the clustering of those interactions. So there it is, I've said it again. So if it is those networks and their mathematical structure, unlike biology, which had sublinear scaling, economies of scale, you had the slowing of the pace of life as you get bigger. If it's social networks with super-linear scaling -- more per capita -- then the theory says that you increase the pace of life. The bigger you are, life gets faster. On the left is the heart rate showing biology. On the right is the speed of walking in a bunch of European cities, showing that increase.
原因何在 我没有时间跟大家解释其中的数学 社会网络是其基础 因为这是个普遍现象 这个15%的规律 是真的 无论你在地球上哪个角落 日本 智利 葡萄牙 苏格兰 都一样 尽管城市的发展是各自独立的 然而所有数据显示的结果都是一样的 这里蕴藏着一个普遍的规律 普遍性在于我们 我们就是城市 城市是我们相互活动以及这些活动的汇集 我刚才说过了 那些网络和它们的数学结构 与呈次线性的生物界不同 生物是规模经济 会随着规模的增大 而减缓生长的速度 如果城市的社会网络呈现超线性 人均数值越高 那么依照原理 生长速度便会增加 你长得越大 生长速度就越快 左边是心率 右边是行走的速度 在许多欧洲城市 显示这样的增长情况
Lastly, I want to talk about growth. This is what we had in biology, just to repeat. Economies of scale gave rise to this sigmoidal behavior. You grow fast and then stop -- part of our resilience. That would be bad for economies and cities. And indeed, one of the wonderful things about the theory is that if you have super-linear scaling from wealth creation and innovation, then indeed you get, from the same theory, a beautiful rising exponential curve -- lovely. And in fact, if you compare it to data, it fits very well with the development of cities and economies. But it has a terrible catch, and the catch is that this system is destined to collapse. And it's destined to collapse for many reasons -- kind of Malthusian reasons -- that you run out of resources. And how do you avoid that? Well we've done it before.
最后 我想谈谈增长 在重复一下 这是生物学的情况 规模经济 使之呈现反曲现象 你快速生长接着停止生长 这是我们回复力的表现 这对经济和城市都不利 说实在的 这个原理奇妙之处之一在于 如果财富创造和创新的 规模增长呈超线性 那么根据同一理论 你必定会得到 一条美妙的正态曲线 漂亮极了 实际上 如果你把它与数据进行对比 它非常符合 城市与经济的发展情况 然而 它存在着一个致命局限 这个局限就是 这个系统注定会崩溃 它之所以注定会崩溃 原因有很多 多少出于此消彼长的原因 资源枯竭了 如何避免这种情况呢 我们曾尝试过
What we do is, as we grow and we approach the collapse, a major innovation takes place and we start over again, and we start over again as we approach the next one, and so on. So there's this continuous cycle of innovation that is necessary in order to sustain growth and avoid collapse. The catch, however, to this is that you have to innovate faster and faster and faster. So the image is that we're not only on a treadmill that's going faster, but we have to change the treadmill faster and faster. We have to accelerate on a continuous basis. And the question is: Can we, as socio-economic beings, avoid a heart attack?
我们所做的是 当我们发展到接近崩溃的阶段 一项重大的创新出现了 我们又从新开始 向下一个目标靠近 以此类推 所以这个周而复始的创新周期 对于维系发展 避免崩溃 是十分必要的 然而 这一局限 要求你必须 不断加速创新 所以 情况就是 我们不仅坐在一架高速运转的机器上 我们还必须加速对机器的更新 我们必须不停地加速 问题是 作为社会经济的存在 我们能够避免心脏病发作吗
So lastly, I'm going to finish up in this last minute or two asking about companies. See companies, they scale. The top one, in fact, is Walmart on the right. It's the same plot. This happens to be income and assets versus the size of the company as denoted by its number of employees. We could use sales, anything you like. There it is: after some little fluctuations at the beginning, when companies are innovating, they scale beautifully. And we've looked at 23,000 companies in the United States, may I say. And I'm only showing you a little bit of this.
最后 我会花一两分钟 看看公司的情况 公司的规模不断增大 上面右边的是沃尔玛 同样的图表 这张图显示的是收入和资产 比上公司规模 即员工人数 我们还可以用销售量 什么都行 看 当公司进行革新 一开始出现轻微浮动 它们长势良好 我们观察了23000家 美国境内的企业 我今天展示给大家的只是冰山一角
What is astonishing about companies is that they scale sublinearly like biology, indicating that they're dominated, not by super-linear innovation and ideas; they become dominated by economies of scale. In that interpretation, by bureaucracy and administration, and they do it beautifully, may I say. So if you tell me the size of some company, some small company, I could have predicted the size of Walmart. If it has this sublinear scaling, the theory says we should have sigmoidal growth. There's Walmart. Doesn't look very sigmoidal. That's what we like, hockey sticks. But you notice, I've cheated, because I've only gone up to '94. Let's go up to 2008. That red line is from the theory. So if I'd have done this in 1994, I could have predicted what Walmart would be now. And then this is repeated across the entire spectrum of companies. There they are. That's 23,000 companies. They all start looking like hockey sticks, they all bend over, and they all die like you and me.
企业令人意想不到的地方是 是它们的规模增长呈次线性 就像生物学的情况一样 这表明主导它们的 并不是超线性的 创新活动和思想 主导它们的 是规模经济 具体说来 就是官僚主义和行政部门 可以说 它们干得很棒 所以 如果你告诉我某个小企业的规模 我就可以估摸出沃尔玛的规模 如果其规模的增长呈次线性 依照原理 我们应该会得到一个S型的增长 这是沃尔玛 看起来并不十分像个S 我们喜欢这个形状 冰球棍 但如果你仔细看 我其实做了手脚 因为我展示的部分只到94年 我们看看到了2008年情况如何 红线表示的是理论上的预测 如果我1994年开始制表 我就能够预测到沃尔玛现在的情况 这个情况 在所有公司的生命周期中不断重复 这些就是所有23000家公司 它们一开始都呈现冰球棍的形状 接着都弯下来了 最后它们就像你我一样难逃一死
Thank you.
谢谢大家
(Applause)
(众人鼓掌)