Everything Is Obvious Once You Know the Answer: How Common Sense Fails Us

EVERYTHING IS OBVIOUS ONCE YOU KNOW THE ANSWER: HOW COMMON SENSE FAILS US by Duncan J. Watts Crown Business, 2011, 342 pp. ISBN: 978-0-307-95179-3Duncan Watts, educated as a physicist and engineer, nevertheless writes about powerful, profound perspectives on the social sciences, in particular sociology. Watts is known for the tremendous contribution he made to social network science with his previous volume entitled, Six Degrees of Separation. This latest book zooms out in scale and looks at the broader scope of the utility and nature of sociology and social science. Watts gives examples of where sociology has, is, or will contribute to solving some of the most challenging and important problems of society, while also explaining some of its limitations. He explains how and why sociology is similar to and different from physics, and compares sociology with biology.Watts' own research is fascinating, and he adds to that by explaining the literature associated with the advancement of sociology as a true and useful science. He starts by explaining how most people, even highly successful CEOs and government officials, often misuse common sense resulting in poor solutions to problems, bad decisions, and disastrous plans. "A quick look at history suggests that when common sense is used for purposes beyond the everyday, it can fail spectacularly." (p. 19) Watts explains how the recurring calls to "return to common sense" fail in politics and government as often as they fail in the corporate boardroom, and how this misuse of common sense should be a call to use the scientific method rather than flawed intuition to solve complex social problems.The book contains many valuable references to studies and experiments that have either advanced society or created miserable policy failures. Watts explains how the initial research and models from artificial intelligence were the result of the incorrect framing problem, and how adjusting the frame to incorporate machine learning and statistical models has now led to real progress. He also explains how incentives are often misapplied and frequently do not address the issues of human behavior they are seeking to produce. The biggest research mistakes are made when social scientists model only from an incomplete and flawed view of history and then use circular reasoning that says, for example, that "X happened because that is what people wanted; and now we know that X is what they wanted because X is what happened" or "X succeeded because it had the right attributes, but the only attributes we know about are the attributes X possesses; thus we conclude that these attributes must have been responsible for X's success. …