The Google Way of Science - The Growing Importance of Data

This whole idea strikes me as extremely confused. Data mining is just observation. Any extrapolation from data is a theory. Anderson and this author seem to be surprised that you can get so far with an incomplete theory that doesn't explain everything. That seems obvious to me -- remember classical mechanics?

Here's a particularly bad example:

"When you misspell a word when googling, Google suggests the proper spelling. How does it know this? How does it predict the correctly spelled word? It is not because it has a theory of good spelling, or has mastered spelling rules. In fact Google knows nothing about spelling rules at all."

"Spelling rules" are a heuristic extrapolation just like the one Google is making, but are probably less accurate! Why is a set of rules designed to be memorable and useful to a human more of a theory than rules that you have to write down, and need a computer to use?

I also doubt that there will have to be no theory. While you can analyze huge datasets and look for correlations, you probably need a theory to give you an idea of what data you should collect. Imagine if you tried to build the Large Hadron Collider without any particle physics theory to guide you in the design? How do you decide how to build it and what you should look for? If you build it on a hunch, you might stumble onto some really interesting things, but in most cases it will probably be an expensive collection of nothing special...

"There was no theory of Chinese, no understanding. Just data. (If anyone ever wanted a disproof of Searle's riddle of the Chinese Room, here it is.)

Shouldn't this be a 'proof' instead of 'disproof'?

The author should have applied the "Google's spell checker" to his own article: "this emerging method... will compliment established theory-driven science".