This link has been bookmarked by 28 people . It was first bookmarked on 26 Jun 2008, by knobas last.
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24 Jan 09
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16 Sep 08
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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.
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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.
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02 Aug 08
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30 Jun 08
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28 Jun 08
The data cloud rebuttal: "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."
ars_technica john_timmer the_battle_of_ideas chris_anderson data_mining flights_of_fantasy science linkingthinking evaluating scientific_method scientific_method_vs_data_cloud via:joeflintham delicious_import
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Brett BoessenHopes to refute Anderson's piece in Wired on overtaking the need for the scientific method.
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27 Jun 08
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26 Jun 08
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Every so often, someone (generally not a practicing scientist) suggests that it's time to replace science with something better.
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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."
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all it needs to know is that an algorithm that recognizes specific link patterns satisfies its users.
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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.
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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
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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.
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ken .John Timmer (in the cloud?) responds to Chris Anderson's Wired article on scientific method - "the argument for a replacement for science is correct: the data cloud is changing science.." where he "stumbles is in his conclusions about what this means
change debate computer data google information meaning science statistics theory thinking
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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.
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