 [Free Beacon] Face it: Human beings are pretty stupid sometimes. We fall for astrology, vote for morons, buy into conspiracy theories, and send our money to obvious scammers. Today, all this seems to be getting worse as "fake news" and "disinformation" take root and the country fragments along partisan lines—not just when it comes to political beliefs but even when it comes to basic facts.
Oddly enough, though, we’re also stunningly brilliant. Not only have the brightest among us produced stunning feats of science and technology, but even normal people, working without modern tools, can use reason to improve their lives. The hunting-and-gathering that humans did long ago required extensive knowledge and careful thought about plants, seasons, animal behavior, and how humans might get what they want from the world around them.
That’s the tension animating Steven Pinker’s new book Rationality: What It Is, Why It Seems Scarce, Why It Matters. The tome celebrates reason, and it provides a digestible primer on the basics of logic, statistics, and other building blocks of rationality, illustrated with clever brain teasers and the occasional comic. Yet it also explains how the human mind can go wrong and asks why rationality seems to be in short supply these days.
This book does an excellent job explaining the basics of good thinking, though Pinker’s final musings about what ails the modern world are a bit unsatisfying.
Pinker’s thinking toolkit is laid out in a series of lucid chapters in the middle of the book. They explain the basics of formal logic: "If it rained, then the streets are wet" doesn’t imply "if the streets are wet, then it rained," for example, because something else might have made the streets wet. Pinker also goes through the core concepts of probability, explaining, for instance, why a 50 percent chance of rain on Saturday and a 50 percent chance of rain on Sunday don’t add up to a 100 percent chance of rain over the weekend.
He further introduces readers to "signal detection theory," the study of all the weird stuff that happens when we’re forced to grapple with false positives and false negatives. For instance, if a test for a disease is 95 percent accurate, but only 1 percent of people have the disease, a positive test will still suggest you probably don’t have the disease: In every 100 people tested, about one will correctly receive a positive result, but about five will receive false positives. Unless, that is, there are other reasons to think your risk might be higher than a random person’s—in which case we might use "Bayesian" reasoning to integrate the results of the test into everything else we know. Then it’s on to game theory, such as the famous Prisoner’s Dilemma, and social science’s never-ending quest to distinguish causation from mere correlation. In the latter, I was especially impressed by Pinker’s explanation of how regression analysis works, which manages to be simple and easy to follow while capturing some of the more technical details. 
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