What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems (...) scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity : A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time. (shrink)

ABSTRACT Nassim Taleb rightly points out that although people may acknowledge in the abstract that the world is uncertain, they still behave as if a large enough sample size is all that is needed to predict, and model, the future. He also rightly notes that ever‐increasing quantities of information are relevant only in simple situations, such as in predicting the range of human height, but are misleading in more random arenas, such as financial markets. However, while Taleb decries the use (...) of narratives for falsely forcing the facts to fit a given story, we need narratives in order to make sense of a complex world. Further, Taleb fails to take sufficient heed of the fact that human narratives themselves become objects that act on subjects in an ever‐increasing web of complexity. (shrink)

There is not, of course, a one-to-one relation between policy conclusions and the conclusions of positive economics; if there were, there would be no ...

The correct solution to complex problems, such as those involved in international relations, can generally be discovered ex post but not predicted ex ante. Economics and game theory attempt to model such complexity, but have difficulty taking into account psychological subtleties, the myriad factors that each agent considers when making a decision, and cultural differences. And understanding that one is dealing with a system—that is, with interacting factors instead of with insulated monads—may not make the questions any more amenable to (...) prediction, particularly because the more unique an event, the less likely it is to be foreseen. Jervis's analysis of complex systems may therefore be more of a contribution to the historical sciences than to predictive social science. (shrink)

ABSTRACT We like to believe that our world is regular, that we can predict it fairly well, and that we can control the risks we run. Nassim Taleb argues that we are fooling ourselves and that the course of history is driven by rare and extreme events, which he calls Black Swans. There is much to this, but scholars—at least in political science—are less oblivious to the problem than he believes. More thought needs to be given to hard issues of (...) whether key events were anticipated, whether there were functional substitutes for events that are seen as turning points, the role of beliefs and expectations in Black Swans, and the dynamics that might explain unpredictability. (shrink)

Based on more than three decades of observation, Robert Jervis concludes in this provocative book that the very foundations of many social science theories--especially those in political science--are faulty. Taking insights from complexity theory as his point of departure, the author observes that we live in a world where things are interconnected, where unintended consequences of our actions are unavoidable and unpredictable, and where the total effect of behavior is not equal to the sum of individual actions. Jervis draws on (...) a wide range of human endeavors to illustrate the nature of these system effects. He shows how increasing airport security might actually cost lives, not save them, and how removing dead trees (ostensibly to give living trees more room) may damage the health of an entire forest. Similarly, he highlights the interconnectedness of the political world as he describes how the Cold War played out and as he narrates the series of events--with their unintended consequences--that escalated into World War I. The ramifications of developing a rigorous understanding of politics are immense, as Jervis demonstrates in his critique of current systemic theories of international politics--especially the influential work done by Kenneth Waltz. Jervis goes on to examine various types of negative and positive feedback, bargaining in different types of relationships, and the polarizing effects of alignments to begin building a foundation for a more realistic, more nuanced, theory of international politics. System Effects concludes by examining what it means to act in a system. It shows how political actors might modify their behavior in anticipation of system effects, and it explores how systemic theories of political behavior might account for the role of anticipation and strategy in political action. This work introduces powerful new concepts that will reward not only international relations theorists, but also all social scientists with interests in comparative politics and political theory. (shrink)

Complexity science has witnessed a number of advances since the publication of Jervis's System Effects. These advances better allow us to untangle the messy elements in a system and predict sets of likely outcomes. However, just because a system is complex doesn't mean that all the ideas relating to complexity—such as agent-based modeling, path dependency, tipping points, between-class versus within-class effects, and networks—are necessarily relevant. One of our tasks is to determine whether they are—and, if so, their implications. As examples, (...) we use China's role in the formation of the United States housing bubble; the federal government's bailout of AIG and Bear Stearns but not Lehman Brothers; and China's failure to experience a regime change such as the Middle East's Arab Spring. (shrink)

Robert Jervis's System Effects was published just as systems thinking began to decline among political scientists, who were adopting increasingly strict standards of causal identification, privileging experimental and large-N studies. Many politically consequential system effects are not amenable to research designs that meet these standards, yet they must nonetheless be studied if the most important questions of international politics are to be answered. For example, if nuclear weapons are considered in light of their effect on the international system as a (...) whole, it becomes clear that they have obviated the need for a global balance of power by allowing states to counterbalance threats by acquiring nuclear weapons rather than investing in massive conventional balancing efforts. Similarly, systems thinking should inform our understanding of the impact of a “unipolar power” such as the United States, which has enjoyed an overwhelming preponderance of conventional military power since the fall of the Berlin Wall. A unipolar power is likely to become involved in frequent conflicts because it is not restrained by the presence of a peer competitor. (shrink)

Where Taber and Lodge view belief polarization to indicate a “partisan motivation,” Lord et al. (1979) believed it to be consistent with a desire for accuracy: A “weak” study articulating an opposing viewpoint might simply sharpen participants' initial belief of the wisdom of their prior beliefs. This polarization, Taber and Lodge show, correlates with political sophistication: The more partisan a participant, the more time spent reading the opinions of the other side—in order to critically refute them. Taber and Lodge attribute (...) such findings to people's personal identification with their beliefs. However, participants may have spent so much time reading opinions of the other side because the arguments are unfamiliar. Further, Lord et al. (1984) were able to induce people to act with “skepticism” toward their own views by simply suggesting that they “consider the other side.”. (shrink)

System effects often stand in the way of attempts to come up with simple explanations of politics. Systems are often characterized by nonlinearities, where an effect is more than the sum of the effects of the actions taken by multiple actors. Another system effect is feedback, where the effect of actions is to amplify the problem the actions are intended to solve. There may also be indirect effects, where an incidental aspect of an action becomes more important (to other actors) (...) than the primary intention; contingencies, such that an effect is not inevitable but depends on idiosyncratic or even anti-strategic initial actions; interaction effects, where the behavior of an actor changes the environment of action, so that other actors do not respond as anticipated; and unintended consequences, where the long-term or secondary effects of an action differ from the intended effect. Each of these system effects can frustrate scholarly attempts to understand political behavior using simple models of action, and, even more, can frustrate the attempts of political decision makers to predict the effects of their actions. (shrink)

ABSTRACT What constitutes a Black Swan? And under what conditions may a Black Swan be expected to arise? As Nassim Taleb describes it, a Black Swan is an event that displays three key properties, the two most important of which are that: (1) it is not even imagined as a possibility prior to its occurrence; and (2) it is in some way significant in its impact. It follows that whether or not an event counts as a Black Swan depends on (...) the subjective imaginings of contemporaneous observers and their (usually implicit) criteria regarding what counts as a “significant impact.” Since there is nothing in determinism that precludes (1) and (2), Black Swans may occur even in a perfectly deterministic world. Nevertheless, if the world is indeed characterised by randomness, free will, emergence, and the like, then it is arguably more likely to throw forth events that display the above‐mentioned properties. The same goes for various specific features of an increasingly interconnected global economy, which allowed Taleb (paradoxically) to forecast what was, for most of us at least, the great Black Swan of 2008. (shrink)

Historical analysis and policy making often require counterfactual thought experiments that isolate hypothesized causes from a vast array of historical possibilities. However, a core precept of Jervis's “systems thinking” is that causes are so interconnected that the historian can only with great difficulty imagine causation by subtracting all variables but one. Prediction, according to Jervis, is even more problematic: The more sensitive an event is to initial conditions (e.g., butterfly effects), the harder it is to derive accurate forecasts. Nevertheless, if (...) awareness of system effects can help forecasters better calibrate their probability estimates of whether or not certain events will come to pass, systems thinkers who are pessimistic about prediction are diluting their confidence too much. The challenge is a meta-cognitive one: thinking systematically about when to engage in systems thinking; and weighing the costs and benefits of using simple or complex heuristics in policy environments that can shift suddenly from quiescence to turbulence. (shrink)