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Why the cloud cannot obscure the scientific method

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on 2008-06-26 by imrchen

This article is a response to Chris Anerson's article "The End of Theory: The Data Deluge Makes the Scientific Method Obsolete" - http://www.wired.com/science/discoveries/magazine/16-07/pb_theory

Public Sticky notes

Correlations are a way of catching a scientist's attention, but the models and mechanisms that explain them are how we make the predictions that not only advance science, but generate practical applications.

Highlighted by rakerman

Every so often, someone (generally not a practicing scientist) suggests that it's time to replace science with something better.

Highlighted by jrstoltz

Anderson appears to take the position that the new research part of the equation has become superfluous; simply having a good algorithm that recognizes the correlation is enough.

The source of this flight of fancy was apparently a quote by Google's research director, who repurposed a cliché that most scientists are aware of: "All models are wrong, and increasingly you can succeed without them."

Highlighted by jrstoltz

And Google clearly has. It doesn't need to develop a theory as to why a given pattern of links can serve as an indication of valuable information; all it needs to know is that an algorithm that recognizes specific link patterns satisfies its users.

Highlighted by sshein

all it needs to know is that an algorithm that recognizes specific link patterns satisfies its users.

Highlighted by jrstoltz

Anderson appears to take the position that the new research part of the equation has become superfluous; simply having a good algorithm that recognizes the correlation is enough.

Highlighted by imrchen

Highlighted by sshein

Correlations are a way of catching a scientist's attention, but the models and mechanisms that explain them are how we make the predictions that not only advance science, but generate practical applications.

Highlighted by jrstoltz

Correlations are a way of catching a scientist's attention, but the models and mechanisms that explain them are how we make the predictions that not only advance science, but generate practical applications.

Highlighted by sshein

Correlations are a way of catching a scientist's attention, but the models and mechanisms that explain them are how we make the predictions that not only advance science, but generate practical applications.

Highlighted by imrchen

he neglects to mention two key things: without the testable predictions made by the theory, we'll never be able to tell how precisely it is wrong and, in those decades where we've failed to find a replacement, the predictions of quantum mechanics have been used to create

Highlighted by jrstoltz

the data cloud is changing science, and leaving us in many cases with a Google-level understanding of the connections between things. Where Anderson stumbles is in his conclusions about what this means for science. The fact is that we couldn't have even reached this Google-level understanding without the models and mechanisms that he suggests are doomed to irrelevance. But, more importantly, nobody, including Anderson himself if he had thought about it, should be happy with stopping at this level of understanding of the natural world.

Highlighted by jrstoltz

without the testable predictions made by the theory, we'll never be able to tell how precisely it is wrong

Highlighted by imrchen

Overall, the foundation of the argument for a replacement for science is correct: the data cloud is changing science, and leaving us in many cases with a Google-level understanding of the connections between things. Where Anderson stumbles is in his conclusions about what this means for science. The fact is that we couldn't have even reached this Google-level understanding without the models and mechanisms that he suggests are doomed to irrelevance.

Highlighted by imrchen