topics: |  biology | evolution | brain | neuro-science

One problem in biology is the depth of causal analysis.  For example, a
peacock puts up its feathers in a gorgeous fan by sending neural signals to
move certain muscles in specific ways. This is the proximal cause.  In
another sense, it does so to impress a female.  Another view may be that he
does so becaue his gene "desires" to be propagated, and this behaviour is
just a result of this genetic predilection.  These are distal causes.  The
question is - how far can we go looking for an ultimate cause?

In the notion of "hierarchical reductionism" (p. 13), Dawkins argues that the
explanatory power of a reductionist effort is not useful if extended directly
to the smallest possible parts. For example, if one throws Stephen Jay Gould
out of a window, his fall can be explained by classical mechanics, but
not from such principles as elementary particle physics or superstring theory.
[This analogy appears in an older edit on
wikipedia.  What Dawkins actually says is that his computer can be explained
in terms of hard drives and CPUs and not in terms of nand-gates or from
quantum behaviour of silicon molecules. ]

I am not sure I agree with this particular notion.  The level of explanation
that Dawkins is talking about may be fine for human discourse, where we can
only hold a few things in working memory at a time.  Even for machines, it
may simplify computation if frequently used concepts, composed from deeper
(or more distal) causes are lumped together as symbols.  However, there is
nothing that prevents me from explaining the workings of my computer based on
quantum phenomena directly also, though that explanation would be
incomprehensible to the human mind.  Indeed, very novel theories are
initially hard to grasp (e.g. Goedel's proof, Euclid's V=E+F-2; theory of
relativity) because they lack these middle level of explanation, and they
become much easier as time goes on and these symbols are expanded; but they
are still capable of being proposed!