Duncan J. Watts, Everything Is Obvious (Once You Know the Answer): How Common Sense Fails Us
Consider the last national election, your employer’s last annual report, or your favorite sports team’s last away-game victory. What made the particular outcome happen? Looking backward, conclusions seem foregone; we construct retrospective explanations that justify how what happened had to happen, because, well, it did. But Duncan J. Wells explains that what seems inevitable once it’s already happened, is actually deeply contingent and controversial. Exactly why is both bizarre and revealing.
Trained as an engineer but functioning as a sociologist, Wells has conducted intensive research for America’s largest corporations, including Yahoo and Microsoft. In that capacity, backed with massive corporate capital and utilizing technocratic research techniques that didn’t exist fifteen years ago, he’s investigated questions about how humans make decisions. Not only has this included individual decisions, but how uncountable group decisions form a consensus. That is, he investigates how individuals make a society.
Watts’ answers prove many and various, and deserve careful reading. Their common thread, however, devolves to common sense. A system useful for negotiating everyday interactions, common sense proves more fraught when confronted with the hidden inner dynamics of large groups. Human interactions prove founded on myriad rules, mostly unspoken—as anybody who has ever traveled abroad and unknowingly transgressed serious taboos already knows. These rules are not only unquestioned, but largely unacknowledged.
In this, Watts relies heavily on research avenues first utilized by Stanley Milgram. Though mostly famous for his “Obedience to Authority” experiments, Milgram also pioneered research, like the famous Six Degrees experiment, demonstrating how intensively connected society is. We cannot explain who influences us, and by whom we’re influenced, because we cannot comprehend our cultural links. Watts actually replicates some Milgram experiments digitally, proving reality is more linked than Milgram could’ve realized.
|Duncan J. Watts|
This goes double for situations which, unlike music markets, cannot be segmented and rerun analytically. We cannot, for example, have multiple trial Presidential elections or overseas wars. Explanations for outcomes therefore lack scientific rigor. When Nate Silver gives probabilities for certain electoral outcomes, his numerical assignments mean something very different from Vegas betting pools. The differences are opaque to people who can’t access Silver’s original math. Therefore we construct explanations retrospectively.
This comes across in popular self-help books which examine successful people to unlock their secrets. Authors believe we’ll replicate somebody else’s miracle if we simply find whichever magic choice or simple connection made their success possible. However, Watts asserts, we cannot see every influence that steered so-and-so to seemingly inevitable success. Essentially we assume somebody had to succeed because they did succeed; Watts calls this creeping determinism.
(Watts specifically name-checks Malcolm Gladwell for this tendency, though in fairness, Gladwell did write Outliers, which examines successful individuals’ cultural contexts, to counter this very tendency.)
Essentially, according to Watts, we don’t explain the past, we describe it. Therefore, attempts to construct actually useful predictions prove frustrating. And because most professional soothsayers’ predictions go largely unexamined, we must step over corpses of numberless stupid secular prophecies to reach contemporary reality. Certainly, many people my age lament their missing flying car. But most high-profile attempts to apply past observations to future choices remain equally fruitless, and we often don’t realize it’s happened.
Can we then even make meaningful predictions? Watts says yes, though exactly how defies brief restatement. We must eschew many common prejudices, like expecting meaningful predictions to be particularly precise. We must also limit our horizons: decades-long predictions prove as useless as long-term weather forecasts. And our reliance on either credentialed experts or gifted rookies limits our options. Processes for making actually useful predictions are surprisingly simple, yet because of learned biases, applying them is shockingly difficult.
Watts’ explanation of human reasoning, and its limits, sheds powerful light on how important decisions fail. Watts explicitly describes several implications for business, government, entertainment, and other fields, while constructive readers can imagine other fields which suffer exactly the field blindness Watts describes. If you’ve ever wondered how politicians, CEOs, and media pundits can be so spectacularly wrong, this book’s explanations will chill your blood. As science for the masses, Watts is a master.