Silicon Models

There was a time when this was how science was done, wrote Jon Turney:
“Find a plausible theory for how some bits of the world behave, make predictions, test them experimentally.”
But now?
“All the action is in silicon — not in the world, or even the lab.”
‘Silicon’ as in algorithms, data mining and computer simulations.

Kevin Kelly noticed this trend in his 2008 article where he pointed out that Google Translate uses “zillions of datapoints which in aggregate link "this to that" from one language to another”. What does that technique for understanding, he wondered?
“If you can learn how to spell without knowing anything about the rules or grammar of spelling, and if you can learn how to translate languages without having any theory or concepts about grammar of the languages you are translating, then what else can you learn without having a theory?”

George Box famously said, “All models are wrong, but some are useful.” Box’s comment became all the more relevant in the silicon modeled world because, as Turney wrote:
“Computer models are different. They’re often more complex, always more abstract and, crucially, they’re dynamic. It is the dynamics that call for the computation...Just turn your model, whatever it is, into a system of equations, let the computer solve them over a given period, and, voila, you have a simulation.”
Computer models are now rampantly used. Just check out this point:
“The Nobel-anointed discovery of the Higgs boson depends on a constantly accumulating computer analysis of zillions of particle collisions, focusing the probability that the expected signature of the Higgs has actually been observed.”

This abundant use of computer models in today’s world makes it all the more critical that we keep reminding ourselves of the “known unknowns” that lie within those models. Turney lists climate change and economics as two fields that need to be particularly aware of the “known unknowns”, well, because the stakes are so high. And while he feels that climate change experts do seem to be (somewhat) aware of the risks in their models, I feel economists behave more like what John Kay said:
“The stupidity and ignorance lies in the minds of the people who, when they see a world that fails to correspond to the models they use, blame the world rather than their model.”

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