Let me first quote from the Amazon,com description of the book:
Managing ambiguity—in our jobs, our relationships, and daily lives—is quickly becoming an essential skill. Yet most of us don’t know where to begin.
As Jamie Holmes shows in Nonsense, being confused is unpleasant, so we tend to shutter our minds as we grasp for meaning and stability, especially in stressful circumstances. We’re hard-wired to resolve contradictions quickly and extinguish anomalies. This can be useful, of course. When a tiger is chasing you, you can’t be indecisive. But as Nonsense reveals, our need for closure has its own dangers. It makes us stick to our first answer, which is not always the best, and it makes us search for meaning in the wrong places. When we latch onto fast and easy truths, we lose a vital opportunity to learn something new, solve a hard problem, or see the world from another perspective.
In other words, confusion—that uncomfortable mental place—has a hidden upside. We just need to know how to use it. This lively and original book points the way.
Over the last few years, new insights from social psychology and cognitive science have deepened our understanding of the role of ambiguity in our lives and Holmes brings this research together for the first time, showing how we can use uncertainty to our advantage. Filled with illuminating stories—from spy games and doomsday cults to Absolut Vodka’s ad campaign and the creation of Mad Libs—Nonsense promises to transform the way we conduct business, educate our children, and make decisions.Now from the review:
In an increasingly unpredictable, complex world, it turns out that what matters most isn’t IQ, willpower, or confidence in what we know. It’s how we deal with what we don’t understand.
Rationality, mind you, is more than pure logic. It employs a heavy dose of meta-cognition: thinking about how your mind works and the errors it tends to make. It’s more psychology than mathematics and thus helps solve interpersonal disputes (what assumptions am I making about this guy?) as astutely as it does scientific conundrums (what other explanations fit these findings?). One key element of rationality is knowing how much you don’t know and how much more you ought to know before drawing a conclusion. A new book focuses on those gaps in our knowledge and the power therein.......
The first type of lesson addresses when to induce uncertainty. For instance, ambiguity is good when seeking creative insight. One method for straying into the wild is what the researcher Tony McCaffrey calls the “generic parts technique.” Looking at a set of ingredients, we tend to fixate on their intended function: A candle is for creating light. Instead, list all components with no assumptions about their purpose, and you might find, say, that the string in a candle can tie two objects together. This technique is how Alexander Graham Bell came to see the telegraph as a tool that could transmit voices.
You might also encourage uncertainty after getting feedback — win or lose. Failure typically does that for us, as it upsets our expectations of what works. But sometimes we don’t win for the reasons we think, so if you want to extend the streak, a debriefing is de rigueur. Query what you think you know. Holmes illustrates this principle with a Ducati motorcycle racing team that rested on its laurels and tumbled off the podium, so to speak. Pixar, on the other hand, makes a habit of deconstructing even its blockbusters.Thinking back on my own experience, here are some examples:
- We worked for a year or more in a pattern recognition project trying to properly classify patterns in data based on a human-classified sample of the patternsprovided to us. We could not get better than 90 percent. It occurred to me facing that failure that we had assumed that the sample of patterns provided to us was correctly classified. We went back and checked, and it turned out the the people who did the original classifications only agreed with each other bout 90 percent of the time. The insight that people make mistakes served me well in several future pattern recognition studies, as well as in the analysis of peer review results.
- In one case, towards the end of a scheduled presentation, I (a lowly graduate student) dared to ask a visiting lecturer at my university to explain the assumption he had started out with because it did not seem to hold up. He looked at it for a time and then got very angry at me. Seemed he didn't think it could be right after reconsidering it, and that the argument that followed therefore could not be defended -- why had I let he go on wasting the time of his distinguished audience?
- In another case, looking at a failed attempt to prove that a proposed solution mechanism to a class of numerical problems was algorithmic (e.g. guaranteed to succeed), I noticed that one feature of the method had not been incorporated in the attempted solution. Again. questioning the author, we agreed that it might be useful to incorporate the feature. I went home and after several days was able to show that the procedure was indeed guaranteed to succeed. I went back to the seminar and presented my logic. Some weeks later, the original presenter published a better proof than mine in a peer reviewed journal.
- In a third case, one day at lunch a friend and colleague showed me that he had developed a computer program to determine the properties of a reverse osmosis screen from some of the characteristics of its manufacture, and that the program went on to predict the costs of using the screen in a practical water purification scheme. I asked him why he had not gone further and embedded the program in a larger program to optimize costs over the set of characteristics that he was using. A few minutes and some notes on the back of an envelop, he went off happy to revise his program. Five publications followed in quick succession, one in the journal Desalinization. My friend extended friendship beyond courtesy to include me as coauthor in all five, although he had done 99.9% of the work.
I could go on, but I suspect that Nonsense is an important book. Often it is useful to create what my friend Julianne calls "a hard problem" -- one which is poorly defined -- from a more straight forward problem in order to rethink framing and assumptions, thus leading to a better solution to the real underlying problem/