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Google Flu Trends Gets It Wrong Three Years Running 64

wabrandsma writes with this story from NewScientist: "Google may be a master at data wrangling, but one of its products has been making bogus data-driven predictions. A study of Google's much-hyped flu tracker has consistently overestimated flu cases in the US for years. It's a failure that highlights the danger of relying on big data technologies.

Evan Selinger, a technology ethicist at Rochester Institute of Technology in New York, says Google Flu's failures hint at a larger problem with the algorithmic approach taken by technology companies to deliver services we all want to use. The problem is with the assumption that either the data that is gathered about us, or the algorithms used to process it, are neutral. Google Flu Trends has been discussed at slashdot before: When Google Got Flu Wrong."
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Google Flu Trends Gets It Wrong Three Years Running

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  • Big Data Fail (Score:2, Insightful)

    by Anonymous Coward on Thursday March 13, 2014 @06:19PM (#46478045)

    Not siprising, most analysis on huge data sets is incorrect, that's why the NSA thing is scary! They get it wrong and you end up with a missile through your window! Oops...

  • by rmdingler ( 1955220 ) on Thursday March 13, 2014 @06:47PM (#46478289) Journal

    You can see a trend and make a forecast.

    Agreed. Very similar to a weather forecast, but without the hundred odd years of daily data to study and manufacture predictive models on.

    It is, however, necessary and noble research... they'll just need more flu seasons under their belt to tweak the variables.

  • by khchung ( 462899 ) on Friday March 14, 2014 @12:52AM (#46480083) Journal

    Exactly, the correct comparison should be "technical analysis" in stock markets, which can be applied to any stock you like with the same level of (un)success.

    Without an underlying theory of how things work, which also needs to be somewhat correct, trying to predict future trends simply by using past data is just dumb curve fitting - with a curve of enough degrees of freedom, you can fit any data, but that doesn't mean its prediction would be any better than random guess.

1 + 1 = 3, for large values of 1.

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