Reading, Writing, and Searching

I learned recently that Abraham Lincoln read out loud all of his life.  (So that explains all of those commas….)  One of the essential figures of 19th century American letters, a master of his craft and a person renowned for assimilating anything from political fact to military theory, was a slow reader.

In an age when we can’t keep up with available information, slow reading seems like a handicap.  But Lincoln’s deliberate reading pace also contributed to his mastery of what he read – he memorized, recited, and transformed to aphorism everything from Biblical stories to legal case law.

Now, with more to learn than what confronted Lincoln, we all wind up making a choice.  For most of us, while we might try to learn a little more a slightly less well, first and foremost we’re forced to select what we learn.

Arguably, one reason for a good education is to gain insight into ideal learning selections, if only by example. There is still a moderate number of really great books in any field, and with some guidance and curation, we’ll invest our time wisely.

But after schooling, who curates our information?   We can’t call up our old professors each day to ask about what we should be learning, and we usually don’t have time to do the job ourselves. For most of us we identify a handful of sources and let it go at that – maybe one or two news sites.

Take my example. On weekdays I’ll take the news at breakfast. First I look at the New York Times, then sometimes the Christian Science Monitor – especially when the Times is more-than-usually unctuous, and finally I’ll glance at the local Columbus Dispatch. That’s it – then it’s off to work.

I suppose my news-reading habits are not very different from many people, but what I’ve described is not a robust learning-selection model – for the most part I’m letting the Times select for me.  It isn’t “robust” because it’s untested – I tend to assume that what one news source tells me is what I need to know.  I could easily be absorbing good information, along with a virtual dust cloud of bias and nonsense in addition. Without another source to test against, how can I tell these apart?

Analytics has something to say about crafting robust models.  Analysts craft robust models by testing them on information separate from what was used in their original formulation. It’s a kind of security against bias, and reading too much into the original information.  Robust models reconcile partially-conflicting test and original data, so while they are less exact in their predictions, they also chase less noise and wind up being simpler than a model that tries to fit every crazy feature in the original information.

So the analytically-approved answer to robust searching is:  search for something definitively outside our normal reading.  However, that also requires some curation. interestingly I found a feature in the New York Times that does a very respectable job of selecting well-considered views from across the political spectrum. (Disclaimer: no one was more surprised than I to find this feature in the Times, which admittedly can epitomize the unctuous establishment media outlet.  The hectoring title, proclaiming “Partisan Writing You Shouldn’t Miss” had me skipping the column for weeks.  It’s the Times – ignore the title. While I personally think the Times does a good job, even if you’re not a fan, I say give ‘em a chance on this one.)

The larger point is that when information curation isn’t robust, it isn’t really worth having. If we’re the keepers of our own learning models, our trusted curators should give us a shot at learning what cuts across particular political notions and biases.   When they do not, we owe it to ourselves to move on.

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