也是一只自由泳的小鸟
在读 #ThinkingFastAndSlow，读到 10%，感觉跟我之前读的 #HowEmotionsAreMade 和 #TheWillpowerInstinct 重叠还蛮多的。
#读书
美国作者真的特别喜欢写一些只对在美国的人才有意义的话，比如”How many murders occur in the state of Michigan in one year?””Think of the last time you took a driving test.”
The event of a lost wallet could evoke many different causes: the wallet slipped out of a pocket, was left in the restaurant, etc. However, when the ideas of lost wallet, New York, and crowds are juxtaposed, they jointly evoke the explanation that a pickpocket caused the loss.
我又让作者失望了，我完全没联想到钱包是被偷的。
evidence accumulates gradually and the interpretation is shaped by the emotion attached to the first impression. In an enduring classic of psychology, Solomon Asch presented descriptions of two people and asked for comments on their personality. What do you think of Alan and Ben?
Alan: intelligent—industrious— impulsive—critical—stubborn—envious
Ben: envious—stubborn—critical—impulsive—industrious—intelligent
If you are like most of us, you viewed Alan much more favorably than Ben.
真的耶！第一印象好重要！不过随着了解的加深最后应该都会收敛的
If you examine Tom W again, you will see that he is a good fit to stereotypes of some small groups of students (computer scientists, …
这本书是不是过时了，CS 现在是大热门诶！不过我很好奇基数大了之后的现在计算机专业的学生在大家眼里还有没有 nerdy 的那种刻板印象…
you see a person reading The New York Times on the New York subway. Which of the following is a better bet about the reading stranger?
She has a PhD.
She does not have a college degree.
Representativeness would tell you to bet on the PhD, but this is not necessarily wise. You should seriously consider the second alternative, because many more nongraduates than PhDs ride in New York subways.
这书里面好多逻辑都好怪啊，比如他凭什么认为 PhD 会更少地坐地铁？他要是说没有大学文凭的人比 PhD 多那含义还明确一点，虽然如果没有大学文凭的人比 PhD 多的话那在地铁里的比例估计也如此，但他加上“坐地铁”的话就让我搞不清楚他到底是哪个意思…
还是觉得好怪啊，他说做估计的时候要结合人口基数和特征描述（是否符合刻板印象），问题是刻板印象完全是一个 heuristic，不存在“人群中 50% 的人符合这个刻板印象”这样的 knowledge，所以到底能怎么结合？而且结合了之后完全有可能结果还是更偏向于刻板印象指示的，为什么要说做出这样的选择是错误的？除非刻板印象完全不靠谱，但作者并不是这个观点..
所以勉强能 get 到的 moral 就是 base rate matters…如果有额外信息的话也要考虑 base rate。总感觉作者的例子举得不大好。
