Electronics Forum / Basics / June 2006

- Because software is a descriptive model, as well as a testable
prediction, you can test your theories straight away, as soon as you've
written them properly.
- You can see the direct relationship between real-world problems and
abstract logic.
- You can do science all day for decent money (eg programming).
- The metaphysical problems of the mind/brain relationship don't
seem that mysterious.
- Everyone knows that they benefit daily, if not every minute of the
day, from the area of science that you have chosen.
- Every other science uses computer modelling and programming to
advance it.

This is because the true science is algorithms, not adding-machines,
and computers have allowed us to explore this field more extensively,
more easily and more economically.

"The Development of Useful Algorithms", or what might be described as
the science of information-systems, is the overlap of theory and
practice. At its core electronics, it is the practical superset of
logic, maths and physics (and indeed it is what these different fields
get used for a lot these days). It is also, one might consider, an
interesting approach to psychology.

We all need to learn about these funny abstract entities - algorithms -
which are the core of all information systems. They might seem magical
when you use a complex computer game, but that is just because you
don't need to think about the core api or chipset when you're writing
or using the high-level scripts and you don't need to think about the
brain when you thinking about your strategies or sensory data. Thoughts
have properties and can be manipulated as informational entities, and
the application of this abstract logic to real world problems is the
core of science. It is this world that computer science gives us
various windows (no pun intended) into.

If human self-awareness and the different mental faculties that it's
aware *of*, are themselves a collection of algorithms developed by
evolution, then it's more important still.

In short, the science of algorithms, whatever you want to call it, is
the core of all science, and possibly technology and philosophy. Let us
all benefit. To contribute is as easy as mentioning an idea that you
have found useful to apply in the real world.

I have found this model I've been describing useful in a lot of cases,
simply by framing any problem in terms of the information coming in,
and what procedures from my mind can be applied profitably to it, from
a strategic/evolutionary context. In fact I can't find a place where it
fails, so far.

It seems that specific, apparently background information is remarkably
well picked to be in your mind at that point, in that situation. The
software that runs the human has been a long time in development, it
does not waste resources and its self-awareness is state of the art.
This is the real reason that algorithm science is important, it
describes living.