Scientists have dealt with very complex systems for decades now without throwing up their hands in despair.

What we do is develop model systems that have containable levels of variability and then study these in great detail to elucidate the fundamental principles of operation. We start with hypotheses, and test these with data until we have generally accepted theories.

When we are done with this, we then extrapolate to the more complex and useful generalized systems, using the knowledge gleaned from the model studies to formulate (usually numerically) simulations of the complex systems.

I am thinking that maybe there is no such thing as radical uncertainty, just limited patience and discipline in the face of serious complexity.

What makes economics so difficult to model, especially in time, is the number of variables that are both hard to measure and define, the large number of higher order effects (events whose outcomes depend on many things) and the amount of stiffly coupled outcomes (feedback loops, if you like).