与收集的数据一样，这些目标也非常“大”。毋庸置疑，商业渴望更好地认识社会。毕竟，与客户行为及文化相关的信息不仅是经营的关键；在知识经济时代，它们也逐渐成为一种货币，用来交换点击数、浏览量、广告费，或是更简单直接的——权力。在此过程中，倘若谷歌、facebook这类公司能帮助我们不断地增进对自己的认识，它们便将获得更大的权力。问题是声称电脑终将组织所有数据，或是向我们提供对流感、健康、社交联系或任何其他事情的全面认识，这彻底拉低了数据和认识的意义。
如果硅谷的大数据传教士们真想“了解世界”，那么他们不仅需要掌握数据的量，也要掌握数据的质。不幸的是，要实现后者，人们要将电脑放下，不仅“从谷歌眼镜中看世界”（或是从facebook中、从虚拟现实中），还要去体验真实的世界。这样做有两个重要原因。
要了解人，你就要了解他们所处的情境
如果你对一个领域高度熟悉，薄数据则是最有用的。你有能力填补信息的不足，设想到人们为什么这样做或为什么有这样的反应——当你能想象并重建行为发生的情境时，薄数据便是有意义的。如果不知道情境，想推断出任何因果关系或是了解人们的行为动机则是很难实现的。
这也是为什么在科学实验中，研究人员需要竭尽全力掌控实验室环境的方方面面，以求打造一个人为场所，使各种影响因素都在可计量范围内。不过，真实世界并不是一个实验室。能确保你对陌生情境有所了解的唯一途径即是置身其中地去观察、去内化并阐述正在发生的每一件事。
世上大部分是我们所不知道的隐性知识
如果说大数据擅长测量人们的行为，那么它在认识人们日常事物的隐性知识方面则是失败的。我怎么知道刷牙时该挤多少牙膏？什么时候该并入行车道?眨眼是表示“这东西真有趣”还是“我的眼睛进了东西”？这些都是内化的能力、无意识的行为，一种内隐的认识在控制着我们的行为。跟身边的事物一样，这些不可见的隐性知识只有主动去看，我们才能发现。不过，它们却对每个人的行为方式有着重要影响。它能够解释事物是怎样、以哪种意义与我们联系起来的。
人类及社会科学中有一系列俘获和解释人的方法，他们所处的情境，他们的隐性知识，而且这些都拥有一个特质：它们要求研究者进入杂乱而真实的生活。
没有哪一个工具可以成为认识人类的快捷方式。尽管硅谷有许多出色的发明，不过我们对数字技术的期望还是要有个限度。“谷歌流感趋势”真正教给我们的是：不能仅仅问这个数据有多“大”，还要问问这个数据有多“厚”。
有时，走进真实的生活将会得到更好的效果。有时，我们必须要离开电脑一会儿。
英语原文：
In a generation, the relationship between the “tech genius” and society has been transformed: from shut-in to savior, from antisocial to society’s best hope. Many now seem convinced that the best way to make sense of our world is by sitting behind a screen analyzing the vast troves of information we call “big data.”
Just look at Google Flu Trends. When it was launched in 2008 many in Silicon Valley touted it as yet another sign that big data would soon make conventional analytics obsolete.
But they were wrong.
IF THE BIG-DATA EVANGELISTS OF SILICON VALLEY REALLY WANT TO “UNDERSTAND THE WORLD” THEY NEED TO CAPTURE BOTH ITS (BIG) QUANTITIES AND ITS (THICK) QUALITIES.
Not only did Google Flu Trends largely fail to provide an accurate picture of the spread of influenza, it will never live up to the dreams of the big-data evangelists. Because big data is nothing without “thick data,” the rich and contextualized information you gather only by getting up from the computer and venturing out into the real world. Computer nerds were once ridiculed for their social ineptitude and told to “get out more.” The truth is, if big data’s biggest believers actually want to understand the world they are helping to shape, they really need to do just that.
It Is Not About Fixing the Algorithm
The dream of Google Flu Trends was that by identifying the words people tend to search for during flu season, and then tracking when those same words peaked in the real time, Google would be able alert us to new flu pandemics much faster than the official CDC statistics, which generally lag by about two weeks.
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For many, Google Flu Trends became the poster child for the power of big data. In their best-selling book Big data: A Revolution That Will Transform How We Live, Work and Think, Viktor Mayer-Sch?nberger and Kenneth Cukier claimed that Google Flu Trends was “a more useful and timely indicator [of flu] than government statistics with their natural reporting lags.” Why even bother checking the actual statistics of people getting sick, when we know what correlates to sickness? “Causality,” they wrote, “won’t be discarded, but it is being knocked off its pedestal as the primary fountain of meaning.”