I agree. I think the underlying issue here is that computer models are given way too much credit. A computer model is only as good as the software it runs on and the assumptions about the real world that this software makes.
If as scientist, you want to test assumptions, it is better not to rely on complex computer models that hide all their assumptions under the hood, but to make simpler or as simple as possible theories that can test assumptions one at a time. If you know all your assumptions are reliable then you can cobble them all together in computer models. And of course keep everything open so that others can check your work.
One of the most obvious and disastrous examples of failure of computer models is the economic crash that just happened. A bunch of bankers and rating agencies had a lot of fancy complex computer models that proved that their mortgage backed securities could not possibly lose value. So the securities were rated AAA, and everyone treated them as essentially risk free. Well we all know what happened next.
The economic crash is not a failure of computer models or even complex models. It's a failure based on a single simple assumption: house prices never go down.
If as scientist, you want to test assumptions, it is better not to rely on complex computer models that hide all their assumptions under the hood, but to make simpler or as simple as possible theories that can test assumptions one at a time. If you know all your assumptions are reliable then you can cobble them all together in computer models. And of course keep everything open so that others can check your work.
One of the most obvious and disastrous examples of failure of computer models is the economic crash that just happened. A bunch of bankers and rating agencies had a lot of fancy complex computer models that proved that their mortgage backed securities could not possibly lose value. So the securities were rated AAA, and everyone treated them as essentially risk free. Well we all know what happened next.