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Why is the Mona Lisa the most famous painting in the world? Why did Facebook succeed when other social networking sites failed? Did the surge in Iraq really lead to less violence? How much can CEO’s impact the performance of their companies? And does higher pay incentivize people to work hard?

If you think the answers to these questions are a matter of common sense, think again. As sociologist and network science pioneer Duncan Watts explains in this provocative book, the explanations that we give for the outcomes that we observe in life—explanation that seem obvious once we know the answer—are less useful than they seem.

Drawing on the latest scientific research, along with a wealth of historical and contemporary examples, Watts shows how common sense reasoning and history conspire to mislead us into believing that we understand more about the world of human behavior than we do; and in turn, why attempts to predict, manage, or manipulate social and economic systems so often go awry.

It seems obvious, for example, that people respond to incentives; yet policy makers and managers alike frequently fail to anticipate how people will respond to the incentives they create. Social trends often seem to have been driven by certain influential people; yet marketers have been unable to identify these “influencers” in advance. And although successful products or companies always seem in retrospect to have succeeded because of their unique qualities, predicting the qualities of the next hit product or hot company is notoriously difficult even for experienced professionals.

Only by understanding how and when common sense fails, Watts argues, can we improve how we plan for the future, as well as understand the present—an argument that has important implications in politics, business, and marketing, as well as in science and everyday life.

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Duncan J. Watts (born 1971) is an Australian researcher and a principal research scientist at Yahoo! Research, where he directs the Human Social Dynamics group. He is also a past external faculty member of the Santa Fe Institute and a former professor of sociology at Columbia University, where he headed the Collective Dynamics Group. He is author of the book Six Degrees: The Science of a Connected Age and Everything is Obvious Once You Know the Answer.

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拉普拉斯妖

Demon de Laplace

拉普拉斯妖又被成为“智者”，它知道宇宙中的一切知识，包括每个原子确切的位置和动量，能够使用牛顿定律来展现宇宙事件的整个过程、过去以及未来。

然而，在这个过程中，拉普拉斯妖的概念模糊了两个不同过程的关键区别，为了便于论述，我将这两个过程分别称为“简单系统”和“复杂系统”。简单系统指的是，用一个模型就可以描述我们观察到的所有或大部分变化的系统。

......

复杂系统完全是另外一种系统。虽然目前人们对于复杂系统“复杂”的原因还没有达成一致看法，但大家普遍认为，其复杂性来源于众多互相依赖且以非线性方式相互作用的组成部分。

......

因此，拉普拉斯的观点有一个致命的缺陷，它只适用于简单系统。然而在现代社会中，无论是营销活动的影响、经济政策的效果，还是公司计划的结果，几乎所有的事物都属于复杂系统的范畴。

Historical explanations, in other words, are neither causal

explanations nor even really descriptions—at least not in the sense

that we imagine them to be. Rather, they are stories. As the

historian John Lewis Gaddis points out, they are stories that are

constrained by certain historical facts and other observable

evidence.12 Nevertheless, like a good story, historical explanations

concentrate on what’s interesting, downplaying multiple causes and

omitting all the things that might have happened but didn’t. As

with a good story, they enhance drama by focusing the action

around a few events and actors, thereby imbuing them with special

significance or meaning. And like good stories, good historical

explanations are also coherent, which means they tend to

emphasize simple, linear determinism...

Making the right prediction is just as important as getting the prediction right.

A Planner thinks he already knows the answer; he thinks of poverty as a technical engineering problem that his anwers will solve.

A Searcher admits he doesn't know the answers in advance; he believes that poverty is a complicated tangle of political, social, historical, institutional, and technological factors... and hopes to find answers to individual problems by trial and error...

A Planner believes outsiders know enough to impose solutions. A Searcher believes only insiders have enough knowledge to find solutions, and that most solutions must be homegrown.

几年后，回顾帕森斯理论的“败局”，社会学家罗伯特·默顿得出结论说，社会学家太急于模仿物理学家的理论性成功了。

......

相比之下，默顿描述的社会学家确实反其道而行之，他们先提出了整个思想体系，然后才开始考虑自己需要对什么进行探究。

......

默顿所言极是，社会科学还没有找到自己的开普勒。

了世界著名的私立研究型大学康奈尔大学攻读理论与

应用力学博士学位。也就是在那里，他遇见了成就他传奇人生的博士生导师

史蒂夫·斯托加茨

（Steven Strogatz）

斯托加茨是一位世界级的应用数学家，主要从事非线性动力学和网络科学研究。在当时的社会学研

究领域，有一个备受关注的理论名叫“六度分隔”理

论，由美国社会心理学家、哈佛太学心理学教授斯

坦利·米尔格拉姆（ Stanley Milgram）于1967年提

出。该理论指出，在人际交往的脉络中，任意两个陌

生人都可以通过“亲友的亲友”建立联系，这中间最

多需要通过5位朋友就能达到目的。不过，这个看似简单，却又很玄妙的社会学理论不仅引起了数学家

物理学家的兴趣，更是得到了计算机科学家的极大关注，致力于复杂网络研究的瓦茨与斯托加茨也不例外。1997年，瓦茨博士毕业，博士论文的标题为《小世界系统的结构与动力》（ The Structure andDynamic of Small- Worid Systems）；1998年，瓦茨和斯托加茨在《自然》杂志上合作发表的一篇名为《小世界网络的集体动力学》（ Collective Dynamics ofSmal- World' Networks）的文章中，他们提出了小世界网络模型，解释了小世界效应，也就是米尔格拉姆提出的“六度分隔”理论背后的必然性。

后来，瓦茨去往以研究复杂系统科学而知名的圣

书籍介绍

Why is the Mona Lisa the most famous painting in the world? Why did Facebook succeed when other social networking sites failed? Did the surge in Iraq really lead to less violence? How much can CEO’s impact the performance of their companies? And does higher pay incentivize people to work hard?

If you think the answers to these questions are a matter of common sense, think again. As sociologist and network science pioneer Duncan Watts explains in this provocative book, the explanations that we give for the outcomes that we observe in life—explanation that seem obvious once we know the answer—are less useful than they seem.

Drawing on the latest scientific research, along with a wealth of historical and contemporary examples, Watts shows how common sense reasoning and history conspire to mislead us into believing that we understand more about the world of human behavior than we do; and in turn, why attempts to predict, manage, or manipulate social and economic systems so often go awry.

It seems obvious, for example, that people respond to incentives; yet policy makers and managers alike frequently fail to anticipate how people will respond to the incentives they create. Social trends often seem to have been driven by certain influential people; yet marketers have been unable to identify these “influencers” in advance. And although successful products or companies always seem in retrospect to have succeeded because of their unique qualities, predicting the qualities of the next hit product or hot company is notoriously difficult even for experienced professionals.

Only by understanding how and when common sense fails, Watts argues, can we improve how we plan for the future, as well as understand the present—an argument that has important implications in politics, business, and marketing, as well as in science and everyday life.