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So extraordinary variations, and surprising to some,
如此巨大的差異震驚了一些人，
but not surprising to people who have read the work of Daniel Kahneman, for example, the Nobel-winning economist.
但是對一些人來說并不驚訝，比如閱讀過諾貝爾經濟學獎獲得者丹尼爾·卡內曼的研究成果的人。
He and his colleague, Amos Tversky, spent years researching this disjoint between what people perceive and the reality,
他和他的同事，阿莫斯·特沃斯基，花費了數年的心血在這個人們的見解與現實脫節的問題上，
the fact that people are actually pretty poor intuitive statisticians.
實際上人們是直覺很差的統計學家。
And there are many reasons for this.
這背后有著很多原因。
Individual experiences, certainly, can influence our perceptions,
個人體驗，當然可以影響我們的見解，
but so, too, can things like the media reporting things by exception, rather than what's normal.
但也包括媒體帶有偏見而非全面客觀的報道。
Kahneman had a nice way of referring to that.
卡內曼對此有一個很好的描述。
He said, "We can be blind to the obvious" -- so we've got the numbers wrong -- "but we can be blind to our blindness about it."
他說，“我們對顯而易見的事情視而不見”--所以我們有了錯誤的數字--“但是我們可以對我們視而不見這個事實視而不見。”
And that has enormous repercussions for decision making.
而這對做決策來說有巨大的影響。
So at the statistics office while this was all going on, I thought this was really interesting.
那么在統計學辦公室，當這些事情在發生的時候，我覺得很有趣。
I said, this is clearly a global problem, but maybe geography is the issue here.
我認為顯然這是一個全球性的問題，但也許與地域差異有關。
These were questions that were all about, how well do you know your country?
這里的一些問題都是關于你對你的國家了解多少。
So in this case, it's how well do you know 64 million people?
在這個問題里，是在問關于你對6400萬人口了解多少？
Not very well, it turns out. I can't do that.
結果是，我并不是很了解。
So I had an idea, which was to think about this same sort of approach but to think about it in a very local sense.
所以我有了一個想法，是用相同的方法，但是以一種非常地方化的方式來思考。
Is this a local? If we reframe the questions and say, how well do you know your local area, would your answers be any more accurate?
這是因地制宜的嗎？如果我們重新思考問題然后說，你對你的當地狀況了解多少，你的答案會更準確嗎？
