The one somewhat decent idea I had during theatre history class many years ago was that Aristotle's Poetics had managed to identify nothing more than a Tragic Mean and that if a writer followed Aristotle's rules perfectly they were more likely to write something average than remarkable.  Around this time I was also taking a lot of writing classes and reading books by people who offered structural advice for writers -- it was all based on Aristotle, though updated.  Aristotle told us what all the memorable Greek tragedies had in common.  Syd Field told us what all of the Hollywood blockbusters had in common.  Art is about knowing when to follow the rules and when to break them. If you break the rules well, that's when you get something truly special.

Timothy Egan writes about this in the Times this morning, as he tries to deal with Big Data in education (Common Core) and media (Nate Silver's new site and mission).  Silver is probably getting a bum rap as in his manifesto for fivethirtyeight he pretty well expresses his desire to use data driven journalism to augment, rather than supplant, a more subjective and humanist approach to reporting and analysis.  That said, he's harsh on wonks and commentators who seem to start with their conclusions, however far-fetched ("Romney will win," is Silver's prime example).

Anyone skeptical of Big Data has to deal with the fact that when the data work, the data really work.  It won't do to maintain that the sun revolves around the Earth just because it fits better with the old stories and poems.  It won't do to insist that the universe is what we want it to be.

The problem is that Big Data has an answer for just about everything and it will work, on average.  Nothing is perfect.  We can know, for example, how to teach most students most things and how to encourage them to follow the disciplines that will be most useful in the economy.  But that won't work for everybody.  There are a lot of extraordinary people who will be stifled by such a system.  If you're the type who responds better to free reading, creative projects and experiential learning, you are going to suffer in a binary, test-driven environment.

Big Data can tell philanthropists what causes to support.  But there might be worthy causes with less bang for buck than the data suggest.  If everybody supports the soup kitchen, does the opera die?

Big Data might tell us what medical procedures have the best chance of working, based on a wide sample of other people with illnesses and injuries.  But every person is unique.  If you are the rare person who responds to a certain treatment it does you no good to be told that your insurance won't cover it because it doesn't work for most other people.  On the other hand, since you don't know in advance that you are one of the outliers, Big Data might save you from fruitless and potentially harmful experimentation.

If you choose to buck the data, you take some risk.  When you're right (with a market call, an election call, your NCAA tourney brackets) the Big Data adherents will dismiss it as luck rather than skill.  When you're wrong, and you will be, you will be tempted to rejoin the herd.  I am pretty sure that there are extraordinary people out there who are better off defying the data and who are ill served by completely data driven institutions.  Calling a decision or conclusion "evidence based" is fast becoming the catch-all justification for everything.  But the world is more complicated than that and our institutions need to accommodate that complexity.