Next, they say the complexity of the global warming problem makes forecasting a fool’s errand. “There’s been no case in history where we’ve had a complex thing with lots of variables and lots of uncertainty, where people have been able to make econometric models or any complex models work,” Armstrong told me. “The more complex you make the model the worse the forecast gets.”
Counterexample: integrated circuits. Trying to simulate an Intel microprocessor is damn hard, but they work anyway. In general, engineers sometimes have to deal with the kinds of problems that this implies are impossible, and they frequently get the job done anyway.
Counterexample: Simulation of interactions within cells. Despite the huge complexity of living cells there were some good simulations created based on known pathways in the cell. They created a finite state machine to model the cell.
the stable states discovered were later found to correspond extremely well with various tissues of the organism and predicted states that would cause apoptosis quite well.
complex thing with lots of variables and lots of uncertainty
The whole point of digital circuitry is that this form of uncertainty is (near)eliminated and does not compound. Arbitrary complexity is manageable given this constraint.
Counterexample: integrated circuits. Trying to simulate an Intel microprocessor is damn hard, but they work anyway. In general, engineers sometimes have to deal with the kinds of problems that this implies are impossible, and they frequently get the job done anyway.
Intel’s main advantage is that they designed the thing they are trying to simulate. No one designed the economy.
I think the main advantage is being able to perform controlled experiments, instead of simply observational measurements.
This only works because of rapid feedback. Long-range scientific forecasting is much too slow to work this way.
I agree. I made somewhat related points in http://lesswrong.com/lw/k6j/paradigm_shifts_in_forecasting/
Counterexample: Simulation of interactions within cells. Despite the huge complexity of living cells there were some good simulations created based on known pathways in the cell. They created a finite state machine to model the cell.
the stable states discovered were later found to correspond extremely well with various tissues of the organism and predicted states that would cause apoptosis quite well.
I’ll dig out my old notes and give a cite later.
The whole point of digital circuitry is that this form of uncertainty is (near)eliminated and does not compound. Arbitrary complexity is manageable given this constraint.