A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence
“Correlation is not causation.” This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality–the study of cause and effect–on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl’s work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
Judea Pearl is a professor of computer science at UCLA and winner of the 2011 Turing Award and the author of three classic technical books on causality. He lives in Los Angeles, California.
Dana Mackenzie is an award-winning science writer and the author of The Big Splat, or How Our Moon Came to Be. He lives in Santa Cruz, California.
作为一名学习经管类专业的学生,这本书给了我许多更深入的思考。作者作为人工智能领域的专家,对于因果关系的理解鞭辟入里,使人茅塞顿开。例如开篇提及,在统计学课程上,学生们经常被教导“相关性不代表因果”,但往往很多的教导都止步于此——学生们知道了什么不是因果,却...
评分 评分 评分2016年,在大数据的帮助下,人工智能(AI)围棋软件AlphaGo在系列赛中以4:1战胜了世界围棋顶尖高手李世石,震惊了全人类。 当时网络上有人戏谑道:“人工智能赢了不可怕,至少说明它还不懂得韬光隐晦,如果它假装输给人类,那才更加可怕。”这句看似戏言的话,却暗藏了人工智能...
评分图灵奖得主关于causality的科普读物。中心主题就是causality,correlation不等价于causality,因果的概念对于人来说也非常自然,这也许是因为我们的大脑是基于这样的基本概念来运作的。但是有点意外的是,根据书里描述的历史来看,人们是在最近一二十年才真正把 causality 相关的概念严格地定义出来并发展出了相关的数学工具进行演算和推理,并且这个过程似乎由于受到传统统计学“数据为王”,“correlation 为根本”的思想的无情打压和排挤,显得异常艰辛和漫长。我觉得强 AI 如果要实现的话肯定缺少不了 causality 这一环,不过要学习目前 causality 相关的理论和技术是得去看专业的书籍和论文,这本书更多的是科普,故事,和历史,当然,是很不错的一本科普
评分科普,好看,推荐。(时隔好多年又重新学习学校里讲过的东西我的心情可以用沮丧来形容)(第一次读评分10的书,激动)(背景音pulp)
评分老爷爷的书刷第二遍了,怀着无比崇敬的心情。我想我的新年愿望就是把这书再刷几遍,然后争取看懂老爷爷的其他书
评分这本书很不错哦 提供了另外一个思考 causal 的角度也还蛮科普的
评分学统计教统计十几年,好多核心的概念第一次看人讲得这么清楚,豁然开朗豁然开朗!
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