Slashdot

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

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.

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.

Just undoing a slip of the mouse moderation.
That's one disadvantage of the current mod system - no chance to fix mistakes

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.

The article is utter nonsense. But it's such a rambling mess it's hard to know where to start picking it apart.

I suppose you could start where he, again, tries to present the argument that correlation really is "good enough" - causation be damned. What he is blattering on about is that you can infer lots of things via statistical analysis - even complex things. That's certainly true. Where he fails (and it's an EPIC fail) is his assertion that this method is a general phenomena, suitable for every day use.

The other major failure of TFA is that I can't find a car analogy anywhere.

Venter can tell you almost nothing about the species he found.

Exactly. The "deluge of data" is a useful tool, no doubt about it. But Google doesn't make the job of collecting and analyzing data irrelevant any more than the advent of the telescope made the skills and knowledge of astronomers obsolete.

I particularly love this line from TFA:

For instance, Google conquered the advertising world with nothing more than applied mathematics. It didn't pretend to know anything about the culture and conventions of advertising -- it just assumed that better data, with better analytical tools, would win the day. And Google was right.

(Applied) science at its best! "The culture and conventions of advertising" are basically folk wisdom, and folk wisdom is often right but more often wrong. Google took a scientific, unbiased view of how to move bits around and make money with them: start with as few preconceptions as possible, analyze the data, see what happens.

Posted by: technophile
20 hours ago1 Point

I think what you have hit on here is the difference between analytical and empirical solutions. Analytical relationships are usually first determined from empirical ones. Once you have the empirical relationships you can determine the missing factors or constants.

(See also http://en.wikipedia.org/wiki/Empirical_method [wikipedia.org] )

They are both necessary and a part of the scientific process. You collect data, generate empirical equations, then try and derive or otherwise model the empirical relationship with an analytical one. Empirical relationships are limited because they are somewhat system dependent. For instance an empirical relationship for the ideal gas law could be generated using methane. This might be accurate for methane, but limited in its use for a gas that deviates from the ideal behavior (i.e. hydrogen fluoride gas). You could generate an empirical relationship for every single molecule in the universe but that would be impractical, which is why analytical relationships can often be more useful. Hopefully the "Petabyte Age" will allow the scientific method to flourish, not replace it.

edit: Rethinking my reply, what the article seems to say is that the Petabyte Age will make determining empirical relationships for everything practical. The scientist who generates loads of empirical relationships and never questions the underlying theory is not a scientist at all, just an observer of scientific processes. I suppose it depends on your goal as to whether this will suit you or not.

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.

And he works at Wired magazine? You don't say.