Daily RC Article 50

Large interactive systems

Paragraph 1

When catastrophe strikes, analysts typically blame some combination of powerful mechanisms. An earthquake is traced to an immense instability along a fault line; a stock market crash is blamed on the destabilizing effect of computer trading. These explanations may well be correct. But systems as large and complicated as the Earth's crust or the stock market can break down not only under the force of a mighty blow but also at the drop of a pin. In a large interactive system, a minor event can start a chain reaction that leads to a catastrophe

Paragraph 2

Traditionally, investigators have analyzed large interactive systems in the same way they analyze small orderly systems, mainly because the methods developed for small systems have proved so successful. They believed they could predict the behavior of a large interactive system by studying its elements separately and by analyzing its component mechanisms individually. For lack of a better theory, they assumed that in large interactive systems the response to a disturbance is proportional to that disturbance.

Paragraph 3

During the past few decades, however, it has become increasingly apparent that many large complicated systems do not yield to traditional analysis. Consequently, theorists have proposed a “theory of self-organized criticality”: many large interactive systems evolve naturally to a critical state in which a minor event starts a chain reaction that can affect any number of elements in the system. Although such systems produce more minor events than catastrophes, the mechanism that leads to minor events is the same one that leads to major events

Paragraph 4

A deceptively simple system serves as a paradigm for self-organized criticality: a pile of sand. As sand is poured one grain at a time onto a flat disk, the grains at first stay close to the position where they land. Soon they rest on top of one another, creating a pile that has a gentle slope. Now and then, when the slope becomes too steep, the grains slide down, causing a small avalanche. The system reaches its critical state when the amount of sand added is balanced, on average, by the amount falling off the edge of the disk

Paragraph 5

Now when a grain of sand is added, it can start an avalanche of any size, including a “catastrophic” event. Most of the time the grain will fall so that no avalanche occurs. By studying a specific area of the pile, one can even predict whether avalanches will occur there in the near future. To such a local observer, however, large avalanches would remain unpredictable because they are a consequence of the total history of the entire pile. No matter what the local dynamics are, catastrophic avalanches would persist at a relative frequency that cannot be altered. Criticality is a global property of the sandpile.

Topic and Scope:

Large interactive systems; specifically, why these systems suffer catastrophes.

Purpose and Main Idea:

The author’s purpose is to argue that traditional thinking about why large interactive systems suffer catastrophes has been superseded by new thinking; specifically, he argues that large interactive systems can suffer catastrophes as a consequence of small (as well as large) events

Paragraph Structure:

Paragraphs 1 and 2 mainly describe traditional thinking about why large interactive systems suffer catastrophes. But they also reveal the author’s main idea: he explicitly states that, “In a large interactive system, a minor event can start a chain reaction that leads to catastrophe.”

Paragraph3 describes new thinking about why large interactive systems suffer catastrophes, what the author terms the “theory of self-organized criticality.” Basically, it boils down to the idea that a small change in a large system that has evolved to a critical point can have catastrophic consequences for that system. The author illustrates this new thinking with the extended sandpile example in Paragraphs 4 and 5.

The Big Picture:

  • When a science passage describes a process (as this one does), a good way to get a handle on what’s going on in the text is to visualize that process in your mind.
  • Science passages are often rather straightforward (as this one is). On test day, don’t automatically leave the science passage for last on the assumption that it’s going to be the most difficult one in the RC section.

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