[Luke:] Yet,
prediction is a broad term and I think there’s a slippery slope to
avoid here. By prediction, we
don’t want to imply the scientist is some sort of magical prophet foretelling
the future exactly as it’s going to be (mainly because I’m not so sure
one can). With the (semi-)free
agency of both individual things and systemic realities as a whole, we aren’t
always going to be able to make predictions that are 100% accurate. Much of prediction still comes down to
probabilities, likely scenarios, Chaos Theory, and Complexity. It has far less to do, I believe, with
materialist mechanism in the Newtonian sense as it does with the trend of
fluid dynamics in both the physical world (matter and energy) and the world of
organisms (biology/biochem./organic chemistry). At least that’s my take on the
matter. What’s
yours?
[Mike:] Accurate predictions carry with them the certainities
assigned by the predictor. A scientist who uses celestial
mechanics can predict the exact day of the next eclipse of the
sun. On the other hand, tomorrow's weather can only be expressed in
terms of probabilities. Yet our understanding of both phenomena is
exact. Science knows the precise laws (all of them) that govern
weather. Employing these laws to make predictions is limited both by
practical matters and by the fundamental mathematical properties of the
equations that govern weather.
Thus, even things (like weather) that are 100% understood (at
the fundamental level) might only be predictable in terms of
probabilities. Then there are a whole host of phenomenon that are not
completely understood (like weather 150 years ago). Nevertheless, it was
not true that people back then could say nothing about the
weather. Historical records and the obvious cyclical structure to
weather (the seasonal cycle) permitted broad probabilistic predictions to be
made (e.g. the Farmers Almanac). This is the level at which my stock
market predictions lie.
[Luke:]
Finally, the term “empirical” can be problematic as well. Empirical investigation can be
characterized by both “use tests” as you put it and by actual
experimentation.
[Mike:] Use tests are a type of
experimentation.
[Luke:] And, yet, when we’re speaking
about the orientation of our scientific investigation - when we speak about
‘science being empirical’ for instance - I think we’re
also focusing on the scope and level of what it is we
are studying as our object – (i.e. the specific fluctuations of the Dow
& the Nasdaq from day to day, the specific activities of a Bill going
through Congress, and so on). In
other words, we’re focusing (to some extent) on the formal distinctions
& discrete matter of specific processes/phenomena of those objects or
systems we choose to study.
[Mike:] I'm
not sure what you are getting at here.