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Google Begat the End of the Scientific Method?

TheSauce writes "In a fairly concise one-pager from Chris Anderson, at Wired, the editor posits that all of our current (or now previous) models for collecting data are dead. The content is compelling. It notes that we've entered the Age of the Petabyte — where one can collect immense amounts of data that are paradigm agnostic. It goes on to add a comment from the head of Google's R&D, that we need an update to George Box's maxim: 'All models are wrong, and increasingly you can succeed without them.' Have we reached a time where all of our tool-sets are now made moot by vast clouds of information and strictly applied maths?"

24 of 387 comments (clear)

  1. Ahem by Anonymous Coward · · Score: 5, Insightful

    The content is compelling. It notes that we've entered the Age of the Petabyte â" where one can collect intense amounts of data that is paradigm agnostic. It goes on to add a comment from the head of Google's R&D, that we need an "update to George Box's maxim: "All models are wrong, and increasingly you can succeed without them." Have we reached a time where all of our tool-sets are now made moot by vast clouds of information and strictly applied maths?" I believe I speak for not a few of us when I respond:

    WTF?

    English, ---, do you speak it?

    1. Re:Ahem by smallfries · · Score: 5, Insightful

      I used to think that I could translate most dialects of bullshit into english but this threw me off guard. The most reasonable explanation is that Chris Anderson is a tool and doesn't know what he is talking about.

      For example, data is now "paradigm agnostic". Seriously, wtf? When was data ever not "paradigm agnostic" and when did we develop the need for a term to describe it. Data is data. It is raw, and unanalysed, and as such the notion of a paradigm is completely irrelevant.

      --
      Slashdot: where don knuth is an idiot because he cant grasp the awesome power of php
    2. Re:Ahem by eln · · Score: 5, Interesting

      It's simple really: The article seems to be saying that we have access to such a ludicrously large amount of data that trying to draw any real meaning from it is pointless. So, we employ a "shotgun" approach at reading the data, and voila, we get data that at least appears to be interesting.

      Of course, since we have no particular purpose in mind when we do this, and no particular method other than "random", we end up with mostly useless data (in the example given, we have a bunch of random gene sequences that must belong to previously unknown species, but we know nothing about those species other than that we found some random DNA that probably belongs to them, and have no particularly good way of finding out more).

      The article seems to be saying that since we have so much data, we can now draw correlations between different pieces of data and call it science. No reason is given why this is useful other than that we have so much of it, and Google is somehow involved. Apparently when you have enough data, "correlation does not equal causation" is no longer true. Again, no coherent reason is given for this stance.

      I think the article makes the same mistake a lot of ill-informed people that get excited by big numbers make: It seems to believe that data is in and of itself an end goal, when really vast amounts of data are useless unless it can help us as humans answer questions that we want answered. Yes, knowing that there are lots of species of organisms in the air that we didn't know about before is sort of interesting I guess, but it doesn't really tell us anything useful.

      Above all, the article proves that you can be almost entirely incoherent and still get your article published in Wired if it says something about how Google is changing the world.

    3. Re:Ahem by Anonymous Coward · · Score: 5, Informative

      Each claim the others data is unsound by the paradigm's umbrella it falls under.

      No, each claim the other's theory is wrong.

      Nobody (sane) refutes the existence of ring species, or refutes microevolution, or other observable forms of data. The only thing in dispute in the controversy is "species are species because they were made that way" versus "species are species because after some really big N evolutionary steps they become that way".

    4. Re:Ahem by nine-times · · Score: 5, Interesting

      Yeah, I don't know what "paradigm agnostic" means specifically, but I think it's a mistake to think that "data is data".

      Not all data is created equally. You have to ask how it was collected, according to what rules, and with what purpose. I can collect all sorts of data by stupid means, and have it be unsuitable for proving anything. It's even possible that I could collect a bunch of data in an appropriate way, accounting for the variables which matter for my particular experiment, and have that data be inappropriate for other uses.

      Of course, if what's intended by "paradigm agnostic" is that we no longer pay attention to those things, then I hope we're not becoming paradigm agnostic. I'm just bringing this up because I think some people think numbers don't lie, and that when you analyze data, either your conclusions will be infallible or your analysis is flawed. On the contrary, data can not only be bad, but it can be inappropriate.

    5. Re:Ahem by melikamp · · Score: 5, Funny

      I used to think that I could translate most dialects of bullshit into english

      Piping TFA to bs2english yields:

      Google is a great place to work, and an even better place to invest money in. Go Google! P.S.: buy Google stock.

    6. Re:Ahem by LilGuy · · Score: 5, Insightful

      I'm glad slashdot linked it. I read this the other day and had no idea what to make of it. After the first 20 comments I see I'm not completely retarded.

      --

      You're nothing; like me.
    7. Re:Ahem by JeanPaulBob · · Score: 5, Informative

      In the minds of some Creationists, science is itself defective because it only deals with natural phenomena.
      Psst. It doesn't. It deals with phenomena about which (or based on which) we can make measurable, testable predictions.

      If your methodology for evaluating a theory requires classifying it by abstract metaphysical concepts like "natural" and "supernatural", then you're a step away from the scientific method of "experiment".
  2. WTF indeed by GameboyRMH · · Score: 5, Insightful

    I saw the article yesterday, but it was so WTFey I just moved on...definitely not Slashdot submission material (especially being a Wired article).

    --
    "When information is power, privacy is freedom" - Jah-Wren Ryel
    1. Re:WTF indeed by eggoeater · · Score: 5, Funny

      "WTFey"
      I hadn't seen WTF adjective-ised before, but I love it... there's just so much I can use it with. In fact, I gotta go now and tell my boss how my project is going....

    2. Re:WTF indeed by mrchaotica · · Score: 5, Funny

      adjective-ised

      And I hadn't seen adjective verbed!

      --

      "[Regarding the 'cloud,'] ownership was what made America different than Russia." -- Woz

    3. Re:WTF indeed by MightyMartian · · Score: 5, Funny

      It reads like some sort of brain-damaged new-age technohippy tripe. Yeah, we don't need methodologies any more, because, maaaan, we've got tubes! Gimme a break.

      --
      The world's burning. Moped Jesus spotted on I50. Details at 11.
    4. Re:WTF indeed by dmbasso · · Score: 5, Funny

      And I hadn't seen anything, I'm blind you insensitive clod!

      --
      `echo $[0x853204FA81]|tr 0-9 ionbsdeaml`@gmail.com
  3. So... by dunnius · · Score: 5, Insightful

    So everything possible has been researched now and therefore no more research is necessary since it will all be on the internet? Ridiculous!

  4. How bout no by Anonymous Coward · · Score: 5, Insightful

    Um, no. Claims like this demonstrate a lack of understanding of what a model is.

    From the perspective of physics, the universe is just a massive amount of data--more data than any single human can comprehend at once. But thanks to the models of Newton we have a set of relatively simple equations that describe, generally, the way bodies in the universe interact. The model is not perfect, but it is useful.

    Likewise, Google uses a very explicit model to describe the universe of the web: some pages are more relevant to a given search query than others, and these pages will generally be more 'popular' among other important pages. Again, the model is not perfect, but it is useful.

    The fallacy is that somehow what Google is doing is a paradigm shift. It's not. It's just applying the same kind of scientific method to a type of data that hadn't existed before.

    What, I think, the article is really trying to say is that Google's data is so massive and complex that we can't ascribe any explanation to the results it gives us. First of all, that is false, because the PageRank algorithm in its simplest form does give us a very explicit explanation (popular pages generally return better results). But even if it were true, Newton faced the same kind of accusations when people called his model of the universe 'Godless' and claimed, for example, that he decribed how gravity works without actually explaining "why" it works like it does. And that accusation is always with science. There are always more questions raised than answered. This is nothing new.

  5. Don't rule science out it. by russotto · · Score: 5, Insightful

    The article is utter nonsense. But it's such a rambling mess it's hard to know where to start picking it apart. Perhaps the best is when he presents as an example of this new "model-free" approach with a program which includes "simulations of the brain and the nervous system". Uh, hello... a simulation IS a model.

    1. Re:Don't rule science out it. by feed_me_cereal · · Score: 5, Funny

      He didn't bother writing more than one rambling page because he figured someone said it better somewhere else on the internet and that we're all bound to find it.

      --
      "Question with boldness even the existence of a god." - Thomas Jefferson
    2. Re:Don't rule science out it. by JustinOpinion · · Score: 5, Insightful

      it's such a rambling mess it's hard to know where to start picking it apart. Agreed. I want to do a line-by-line rebuttal... but I fear that would be a waste of time.

      The article does not make a compelling point. It keeps saying that we can give up on models (and science), because now we just have lots of data, and "correlation is enough." What utter BS. Establishing a correlation is not enough. Even if it is predictive for the given trend, it doesn't allow us to generalize to new domains the way a well-established scientific model does. If an engineer is designing a totally new device, that goes above and beyond what any established device has done, what data can he draw upon? If there is no mountain of data, he must rely on the tried-and-true techniques of engineering/science: use our best models, and predict how the new device/system will behave.

      The article actually makes this point perfectly clear when it says:

      Venter can tell you almost nothing about the species he found.
      Indeed. Merely having tons of data doesn't actually give you insight into what you have measured. You must distill the data, pull out trends, and construct models. I just don't see how have mountains of data about a species, but still being unable to answer simple questions about it, is superior to conventional science (which can answer questions about the things it has discovered).

      A deluge of data and data-mining techniques is a boon to science. But I don't see the benefit of giving up on the remarkably successful strategy of constructing models to explain the phenomena we've observed. I somehow doubt that having 20 petabytes of data on electron-electron interactions is more useful than having a concise theory of quantum mechanics.
  6. Google =/= scientific method by Rubikon · · Score: 5, Informative

    That an incredible amount of data exists on any given topic does nothing to describe relationships, causality, precision, accuracy, distribution, correlation, or anything else. Data is information, and information must be processed in order to make it meaningful. Additionally, everything that's written, printed, published, etc, is not necessarily true, accurate, precise, etc.

    If anything, the Google phenomenon demands more rigorous examination by accepted methods.

    The preceding message has been brought to you by Captain Obvious and the letters O,R,L,Y.

  7. Wrong by DogDude · · Score: 5, Insightful

    This is typical web 2.0 hype... more is better. Which, as anybody who has used Wikipedia knows, is utter bullshit. The scientific method can't be supplanted by a large amount of questionable data. Tons and tons of bad data is still bad data. It doesn't get any more correct just because there's more of it.

    --
    I don't respond to AC's.
  8. Interesting, ranty, and wrong by xPsi · · Score: 5, Insightful

    A thought-provoking piece written by someone who neither understands the scientific method nor Google. Who doesn't understand the difference between a Theory and a model. Who still doesn't get correlation!=causation. Who probably has never had to actually analyze any substantial amount of data before. And who has clearly been raised on a self-important intellectual diet consisting of too much Buckminster Fuller, Kurtzweil, Frank Tipler, and Derrida. I'm sure there are some kernels of insight buried in there someplace, but I'm just not clear what they are. If his rant is indicative about the future direction of science, we're all doomed.

    --
    i\hbar\dot{\psi}=\hat{H}\psi
  9. Just to clarify by GameboyRMH · · Score: 5, Insightful

    To avoid the same fate as the GP, let me clarify that by WTFey I specifically meant that the article was full of fluff, light on details and generally pointless...which makes me think "WTF." The closest thing to a point I could get from the article was "Nice big blobs of data can be useful, and statistical data based on said blobs could replace the results of scientific research." Mmmkay.

    A sensational headline leading to a rather pointless article consisting mostly of fluff: WTF.

    --
    "When information is power, privacy is freedom" - Jah-Wren Ryel
  10. The Paradigm is the Data Subset by fictionpuss · · Score: 5, Insightful
    The paradigm is embedded in the quantity, or subset, of data you choose to analyse.

    For example, to detect stress you might traditionally measure heartbeat, skin conductivity, pupil dilation.

    In the "petabyte age" you throw in the number of times the subject uses the letter 's'; how frequently they use the 'reload' button on the browser; what colour of pants they wore last tuesday; Pepsi vs. coca cola; the number of times they picked their nose in 1997 and any and every other bit of data you have on the subject.

    In the "petabyte age", most of the data you sift through will show no correlation, but you have a much better chance of finding the unexpected if indeed, there is some unknown factor out there.

    1. Re:The Paradigm is the Data Subset by kurthr · · Score: 5, Insightful

      Don't you run a much higher probability of finding high correlation by chance?

      I can expect to find a result that matches my model to 95% certainty about 5% of the time in random data. You can correct for this, but it's against human nature because people like to see the face of Mary in toast.

      Learning how to look for correlation in huge uncontrolled data sets will require a new paradigm... or it will ultimately be useless and even perhaps, unsuccessful.