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Biological evolution is a complex blend of ever changing structural stability, variability and emergence of new phenotypes, niches, ecosystems. We wish to argue that the evolution of life marks the end of a physics world view of law entailed dynamics.
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A simple system is one where at least one actor is sufficiently intelligent, knowledgeable and powerful to unilaterally alter the dynamics of the system based on a predictive model of what the system will do. Perhaps we might more meaningfully say that a system is simple or complex relative to a given actor if that actor has the capacity to unilaterally alter the system based on their understanding thereof. A complex system (a system complex relative to a given actor) is one where no actor can unilaterally alter the system based on their understanding thereof (though they may be able to alter their own place within the system).
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The mere existence of key agents, I argue, transforms the complex system into a simple one (for some players, for some purposes). Not that those key agents can act flawlessly, but rather, that their size and knowledge makes modeling the system impossible without taking into account their ability to alter whatever temporary rules seem to be evident. Investment banks may not have known all of the consequences of their actions in the mid-2000s, but they had a much better sense than the rest of us, and at least some of those actors (e.g. Goldman Sachs) were capable of timing the bubble to maximum advantage (or minimum disadvantage). The Fed responded in turn, guided by its own models (models here being both quantitative, econometric and structural models but also more heuristic or cultural models of how-things-generally-work). The financial collapse of 2007-2009 was at once a story of millions of individual actors slowly changing behaviors (home buyers and individual mortgage brokers) and the story of influential policy decisions by a handful of organizations. The latter part is not characteristic of a complex system but rather a simple one.
While there is an extensive literature on the potential wisdom of human emotion – David Hume was a prescient guy – it’s only in the last few years that researchers have demonstrated that the emotional system (aka Type 1 thinking) might excel at complex decisions, or those involving lots of variables. If true, this would suggest that the unconscious is better suited for difficult cognitive tasks than the conscious brain, that the very thought process we’ve long disregarded as irrational and impulsive might actually be more intelligent, at least in some conditions.
"Bank bosses have played a trick which countless ordinary workers do. The IT support guy who introduces lots of “security features” to his firm’s IT systems, or the secretary who has an incomprehensible filing system, make themselves indispensable by inconveniencing others."
The US financial markets have suffered over 18,000 extreme price changes caused by ultrafast trading, according to a new study of market data between 2006 and 2011
Critical transitions are sudden, often irreversible, changes that can occur in a large variety of complex systems; signals that warn of critical transitions are therefore highly desirable. We propose a new method for early warning signals that integrates multiple sources of information and data about the system through the framework of a generalized model. We demonstrate our proposed approach through several examples, including a previously published fisheries model. We regard our method as complementary to existing early warning signals, taking an approach of intermediate complexity between model-free approaches and fully parameterized simulations. One potential advantage of our approach is that, under appropriate conditions, it may reduce the amount of time series data required for a robust early warning signal.
Under certain market conditions, cartels arise naturally without collusion. This raises important questions over how the behavior should be controlled.
" The initial 2012 conference will be based on an Institute for Advanced Topics in the Digital Humanities (IATDH) sponsored by the National Endowment for the Humanities and the UNC Charlotte Complex Systems Institute this past year that was dedicated to computer modeling in the humanities and social sciences. In keeping with the theme of the IATDH, the topic for our first conference will be: Modeling Complexity in the Humanities and Social Sciences."
"Finance has always been complex. More precisely it has always been opaque, and complexity is a means of rationalizing opacity in societies that pretend to transparency. Opacity is absolutely essential to modern finance. It is a feature not a bug until we radically change the way we mobilize economic risk-bearing. The core purpose of status quo finance is to coax people into accepting risks that they would not, if fully informed, consent to bear."
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Herbert Simon is one of the seminal thinkers in the study of complexity. His 1962 article, "The Architecture of Complexity" (link), put forward several ideas that have become core to the conceptual frameworks of people who now study social complexity.
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First, the complexity of a system derives from the "nonsimple" nature of the interaction of its parts (subsystems). A watch is a simple system, because it has many parts but the behavior of the whole is the simple sum of the direct mechanical interactions of the parts. The watchspring provides an (approximately) constant impulse to the gearwheel, producing a temporally regular motion in the gears.
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"Human interaction cannot be understood as predictive processes but as patterns
A pattern is something that unfolds through the complex interactions between elements in a system. Although there is apparent order, there is never exact repetition if the system is viable. This is why human interaction cannot be understood as processes in the way they were used in manufacturing, but as patterns."
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The American sociologist George Herbert Mead (1863 – 1931) distinguished between two types of objects: physical objects and social objects. While a physical object may be understood in terms of itself, a social object has to be understood as being composed of patterns of interaction.
Mead referred to a market as an example of a social object. The acts of buying and selling define a market. Markets cannot exist without these social activities. When one person offers to buy something, this act involves a range of responses from other people. A person making an offer can only know how to make the offer if she is able to understand the attitude of the other parties to the bargain. The ideas of buying and selling are thus always interconnected. This is why it is called a “social” object.
"Successful animal systems often manage risk through synchronous behavior that spontaneously arises without leadership. In critical human systems facing risk, such as financial markets or military operations, our understanding of the benefits associated to synchronicity is nascent but promising. "
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