Neuroscience basics & some criticism of Eliezer Yudkowsky

I’ve just written a post at LessWrong covering some basics of neuroscience and criticizing a claim by Eliezer Yudkowsky that the brain “just doesn’t really look all that complicated.” If you just want to read the latter part of the post, I’ve put my criticisms below the fold on this one:

First of all, it is not true that the fact that that brain is divided into only 52 major areas is evidence that it is not very complex, because knowing about the complexity of its macroscopic organization tells us nothing about the complexity of its microscopic wiring. The brain consists of tens of billions of neurons, and a single neuron can make hundreds of synapses with other neurons. The details of how synapses are set up vary greatly. The fact is that under a microscope, the brain at least looks very complex.
The argument from the small size of the genome is more plausible, especially if Eliezer is thinking in terms of Kolmogorov complexity, which is based on the size of the smallest computer program needed to build something. However, it does not follow that if the genome is not very complex, the brain must not be very complex, because the brain may be built not just based on the genome, but also based on information from the outside environment. We have good reason to think this is how the brain is actually set up, not just in cases we would normally associate with learning and memory, but with some of the most basic and near-universal features of the brain. For example, in normal mammals, the neurons in the visual cortex are organized into “ocular dominance columns,” but these fail to form if the animal is raised in darkness.
More importantly, there is no reason to think getting a lot of power out of a relatively simple design requires insights into the nature of intelligence itself. To use Eliezer’s own example of Windows Vista: imagine if, for some reason, Microsoft decided that it was very important for the next generation of its operating system to be highly compressible. Microsoft tells this to its programmers, and they set about looking for ways to make an operating system do most of what the current version of Windows does while being more compressible. They end up doing a lot of things that are only applicable to their situation, and couldn’t be used to make a much more powerful operating system. For example, they might look for ways to recycle pieces of code, and make particular pieces of code do as many different things in the program as possible.
In this case, would we say that they had discovered deep insights into how to build powerful operating systems? Well no. And there’s reason to think that life on Earth uses similar tricks to get a lot of apparent complexity out of relatively simple genetic codes. Genes code for protein. In a phenomenon known as “alternative splicing,” there may be several ways to combine the parts of a gene, allowing one gene to code for several proteins. And even a single, specific protein may perform several roles within an organism. A receptor protein, for example, may be plugged into different signaling cascades in different parts of an organism.
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