Despite the minimal news coverage, sexual harassment and gender inequality against women are no less prevalent in science than they are in pop culture and corporate America.

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.

蚂蚁在组成群体时为何会表现出如此的精密性和具有目的性?数以亿计的神经元是如何产生出像意识这样极度复杂的事物?是什么在引导免疫系统、互联网、全球经济和人类基因组等自组织结构?这些都是复杂系统科学尝试回答的迷人而令人费解的问题的一部分。 理解复杂系统需要有全新的方法.需要超越传统的科学还原论，并重新划定学科的疆域。借助于圣塔菲研究所的工作经历和交叉学科方法，复杂系统的前沿科学家米歇尔以清晰的思路介绍了复杂系统的研究，横跨生物、技术和社会学等领域，并探寻复杂系统的普遍规律，与此同时，她还探讨了复杂性与进化、人工智能、计算、遗传、信息处理等领域的关系。

Series showing how new camera technology is revealing the inner workings of the Earth's most spectacular natural wonders.