If I wanted to make specific predictions about them, I'd have to have
some way to test whether my actual results matched my descriptions;
that is, I'd have to discover some /definable, observable, difference/
between what is and what might be, and some way to recognize which of
those matches my prediction. Such definable, observable differences
are called "measurements". They don't all have to superficially look
like numbers with units, like "9.8 m/s^2", although those are very
good ones; sometimes they are simply records of distinct observation.
"Yes/No" is your basic one-bit number, and a very good measurement of
things like "the rat found the cheese/the rat didn't find the cheese".
What makes it specifically quantitative is that I can rigorously
define what the measurement is, and I can repeat the experiment
enough times to calculate a t-test or other measure of the probability
that the measurements are chance or that they correlate to some cause.
99% of the measurements you make are subconscious, so you're right
that I don't have to count every step or label every room to get to
where I'm going. But to make predictions, or to explain things to
someone else, I'd better make them more explicit: if I want to tell
someone that there is an alien corpse in a certain room, I'd better
specify exactly which room of which building at what point on the
planet at which point in time, and define what distinguishes my
claim of "alien corpse" from something else, or else my claim isn't
independently verifiable. And how did you get to your office the
first time? By looking for distinguishing measurements of the
building among others--it's order in the street, its height, its
color, its shape, or some other set of measurements.
I'm not discounting the value of human pattern-matching machinery.
That's what gives us conjectures to test, and it is a very valuable
skill. But until they are defined, measured, and tested, it is a
very dangerous game to make predictions on pattern alone.
-- Lee Daniel Crocker <lee@piclab.com> <http://www.piclab.com/lcrocker.html>