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179 8 Incomplete Knowledge, Uncertainty, and Surprise Scientific knowledge is, inherently and inevitably, incomplete . In this chapter, I explore the role that incompleteness, uncertainty, and surprise play in the evolution of scientific thinking. Tentative hypotheses, initial findings, and problem frames offer a false sense of certainty about what weknow.Thegreatestchallengeofscientificdiscoveryistounlearnwhatwehave learned and to do so systematically and continuously. Sometimes, in decisionmaking , we face a paradox: while attempting to employ the best evidence to make informed, authoritative decisions, we ignore the inherent incompleteness of knowledge. By focusing on the unpredictable dynamics and the uncertainty of coupled human-natural systems, I challenge the myths about stability, optimality , transferability, and adaptability that characterize urban planning. These myths are not necessarily false or true, but are instead simply incomplete . They represent partial explanations of how human-natural systems work. To face current challenges in urbanizing regions, a co-evolving paradigm may be more appropriate: a view that focuses on unpredictable dynamics in urban ecosystems and on strategies as experiments that help us to learn how cities work and evolve. I conclude the chapter by redefining the questions that can lead us in changing the planning paradigm. The Paradox of Knowledge It takes but a simple step beyond the familiar (our home, neighborhood, or city) to experience the incompleteness of our individual knowledge. It 180 Chapter 8 takes a little more imagination, however, to understand incompleteness in science. What we do not know may be both disproportionately greater than what we do know and qualitatively different from what we can expect. We cannot define or quantify what we do not know. Why can this realization be important both in thinking about advances in scientific thinking and in framing the role of science in solving society’s problems? The reason is that what we know influences the way that we think about what to look for and where to look for it. Whether or not we state it explicitly, we all have an idea of what “complete ” or “perfect” knowledge should look like. This idea is often an abstraction, though, and is rarely connected to how the world actually works. At best, it is an expression of the relationship between what we need to know and a set of stated questions that such knowledge would answer. For example, it might provide a framework for compiling evidence about how cities affect ecosystem function. But what if the questions we ask, although good ones, are incomplete? I propose that the questions we ask are strongly shaped by what we already know, and that so, too, is what we define as “unknown.” To tackle such limitations, I propose a distinction between ignorance, defined as what we consider unknown—as Firestein (2012) discussed in his book Ignorance—and what I term incomplete knowledge. In a recent essay, the physicist Igor Teper (2014: n.p.) asked, “If the constitution of nature itself were changing in time, how would you know?” He concluded that we cannot assume that the future will resemble the past, based on past observations, without falling into what the philosopher David Hume (1777 [1748]: 115) called circular logic. Such scientific challenges have enormous implications for planning and decision-making. Strategic decisions about the future—such as whether to invest in urban infrastructure, manage urban growth, and conserve natural resources— are based on our assessment of the past and our expectations for the future. To a certain extent, observations about the past define the “reference ” and “boundary” conditions of the multidimensional space that shapes our predictive tools. How we think about the future has significant implications for the choices we make and the decision-making processes we apply. Traditional approaches to planning and management typically rely on predictions of probable futures extrapolated from trends observed in the past. But such predictions might not be adequate. Uncertainty and Surprise 181 Incompleteness Incomplete knowledge, uncertainty, and surprise all affect our decisions, and they all influence and interact with one another in their effects. Drawing a distinction among them can help us to clarify their roles and to tackle them as we make decisions. What helps us make good decisions is not having perfect knowledge, but acknowledging that we do not have it. In his book Obliquity, the economist John Kay (2010) suggested that in a world that we understand only imperfectly, we achieve better decisions when we approach a problem obliquely or indirectly. He noted that the problems we face are rarely completely specified and that the environment in which we...


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