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Google Flu Trends Gets It Wrong Three Years Running
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."
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."
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...
Learn from nature! Google needs a genetic algorithm that modifies itself every flu season.
The fittest algorithm will survive to infect thousands.
With big data, when you actively look for patterns you always find them; this is how hedge funds have been operating for years. The purpose of the technology is not to make predictions, but rather to confirm existing trends and possibly identify new ones.
Proper way to utilize big data in this case would be:
1) to assist the CDC in confirming or refuting trends observed in the field
2) to offer additional correlations (such as: are people living closer to highways more sensitive fo specific strains of flu)
3) to provide long-term indicators facilitating the assessment of medication and other flu containment factors
Big data is not a magic eight ball but it's not a piece of shit either.
lucm, indeed.
Yes it has warmed of the last 15 years, you moron.
You statement has been shown false many many times. Please stop.
The Kruger Dunning explains most post on
Well, except for the warming climate https://www2.ucar.edu/climate/...
It's turtles all the way down.
He's not a moron, he's probably a republican; they have figured out that if you constantly state lies as facts then many people will believe them. It is the second best thing in politics after money, which is why republicans are currently having so much success at ruining America.
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.
Happiness in intelligent people is the rarest thing I know.
Ernest Hemingway
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.
Bogus? Are you sure they weren't just... wrong?
It's a prediction.
systemd is Roko's Basilisk.
In addition to "all of the above", the other contribution is that of the philosophical equivalent of Heisenberg: the predictions of outbreaks may have increased vaccination usage in the areas involved, which of course will have an effect of downplaying the outbreaks in those areas.
Not saying I have any evidence for that, (and I will wager it unlikely, considering the #s who vaccinate is still far lower than it should be), but a correlation study may be interesting to see.
If the point of knowledge of a possible outcome is to act to deter it, then shouldn't the actions that attempt to deter it be taken into account?
"But remember, most lynch mobs aren't this nice." (H.Simpson)
-- Joe
Weather forcasts are NOT based on trends found in any data set, they are based on the laws of physics and chemistry, they use the same "finite element analysis" techniques found in numerical wind tunnels and other engineering models that are used to build everything from bridges to aircraft. Archival data is used to test the "skill" of the model by making "hindcasts" and comparing them to the instrumental record.
Climate is basically the long term statistics of weather - meaning a hundered year trend in temprature is a climate statistic, not a weather trend. Climate models and weather models are more or less the same thing using different spacial and temporal parameters, climate statistics such as temprature trends are a completely seperate line of evidence to climate modelling.
And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
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.
Oliver.
You don't really get the scientific model do you? You know, the one where you don't pick an outlier as a base, and then try to "prove" that a trend is occurring by picking another outlier point. The technical term for that kind of "research" would be nit-picking, and is generally frowned upon by real researcher. You know, the kind of people who actually knows up from down, contrary to you.
Or maybe you just can't wrap your head around this whole thing called climate. I'll help you, climate is not weather. If you take your malformed little graph and zoom out, you would have one heck of a difficult time trying to make your model fit. That's why the real researchers can pick any range of years and get the same results as any other range, while you can only pick this one set. Isn't that just disheartening? You're trying so hard, and yet failing so badly.
But yeah I get it. You've drunk the cool aid an committed to the lie, there is no going back. Facts be damned, the world will just have to conform to your belief eh? And who gives a shit, the real consequences of your kind of ignorance will only surface when you're long gone.
... whatever
"The technical term for that kind of "research" would be nit-picking, and is generally frowned upon by real researcher. You know, the kind of people who actually knows up from down, contrary to you."
Actually the term is cherry-picking. Nit-picking is focusing on trivial details.