Quick Heuristics and Network Saturation

This presentation, “The Marvels and Flaws of Intuitive Thinking”, is part of a series from Edge.org which looks most interesting,

http://edge.org/conversation/the-marvels-and-flaws-of-intuitive-thinking

We ended up studying something that we call “heuristics and biases”. Those were shortcuts, and each shortcut was identified by the biases with which it came. The biases had two functions in that story. They were interesting in themselves, but they were also the primary evidence for the existence of the heuristics. If you want to characterize how something is done, then one of the most powerful ways of characterizing the way the mind does anything is by looking at the errors that the mind produces while it’s doing it because the errors tell you what it is doing. Correct performance tells you much less about the procedure than the errors do.

If it weren’t for Nature’s “cheap and dirty tricks” of the mind, we would not be alive today.  On the other side of the coin is the science of information saturation in complex adaptive systems, as told by Geoffrey West, also at Edge.org,

http://edge.org/conversation/geoffrey-west

The work I got involved in was to try to understand these scaling laws. And to make it a very short story, what was proposed apart from the thinking was, look, this is universal. It cuts across the design of organisms. Whether you are insects, fish, mammals or birds, you get the same scaling laws. It is independent of design. Therefore, it must be something that is about the structure of the way things are distributed.

You recognize what the problem is. You have ten14 cells. You have this problem. You’ve got to sustain them, roughly speaking, democratically and efficiently. And however natural selection solved it, it solved it by evolving hierarchical networks.

There is a very simple way of doing it. You take something macroscopic, you go through a hierarchy and you deliver them to very microscopic sites, like for example, your capillaries to your cells and so on. And so the idea was, this is true at all scales. It is true of an ecosystem; it is true within the cell. And what these scaling laws are manifesting are the generic, universal, mathematical, topological properties of networks.

Read the whole article, especially the part about network saturation along S-curves, and about singularity/collapse of those networks.  Also note his discovery about the growth curve of companies, which is a semi-vindication of Coasean economics.

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The Brain as an Evolutionary Kluge

Most excellent article, “The Cognitive Science of Rationality”,

http://lesswrong.com/lw/7e5/the_cognitive_science_of_rationality/

I particularly like the discussion of error types.

These modern models of cognitive science are great, but they only explain the mechanisms used to desaturate our neural networks.  What is missing is a good method to differentiate phenomena as a function of whether they are a result of network saturation or desaturation.  At this time, I have no reliable means of differentiating the two.  For instance, is autism a problem of heavy saturation or of excessive desaturation?