The Data-Driven Life 96
theodp recommends a somewhat long and rambling article by Wired's Gary Wolf, writing in the NY Times Magazine, on recording and mining data about your personal life. "In the cozy confines of personal life, we rarely used the power of numbers. The imposition on oneself of a regime of objective record keeping seemed ridiculous. And until a few years ago, it would have been pointless to seek self-knowledge through numbers. But now, technology can analyze every quotidian thing that happened to you today. 'Four things changed,' explains Wolf. 'First, electronic sensors got smaller and better. Second, people started carrying powerful computing devices, typically disguised as mobile phones. Third, social media made it seem normal to share everything. And fourth, we began to get an inkling of the rise of a global superintelligence known as the cloud.' And the next thing you know, exercise, sex, food, mood, location, alertness, productivity, even spiritual well-being are being tracked and measured, shared and displayed."
Easy (Score:4, Informative)
Re:Article needs a course in experimental design (Score:3, Informative)
> So if you wanted to know the effect of coffee intake on your productivity --
> not the population in general, but you personally; remember that caffeine is
> a drug to which many people react idiosyncratically -- how would you suggest
> designing the experiment?
Buy a can of decaf, a can of regular, and two containers. Label one container "A" and one "B". Have an assistant put the decaf in one and the regular in the other out of your sight and record which is which without letting you see the record. Toss a coin and swap the labels if it comes up heads without letting the assitant see whether you do so or not. Record this, without letting the assistant see. Now no one knows which container has the regular. Drink coffee from "A" for six weeks, recording whatever objective measures you are interested in. Switch to "B" and repeat. Do this three or four times. Analyze your data for systematic differences between "A" and "B". Now compare your assitant's record of which container she put the regular in with your record of whether or not you swapped the labels to determine which data pertains to regular and which to decaf.
Summary is very misleading (Score:4, Informative)
From the quotation given, you might think TFA was about "the cloud" and sharing data in it. It's not, despite the fact that many posts in response seem to think it is.
Basically, the article is about people who collect data about their own lives and then analyze it. Most of the anecdotes given in the article have nothing to do with online communities, media, etc. If you're a person who has tracked your finances, weight, exercise, etc., you know what this is. The anecdotes give some more extreme versions of this tendency to collect data and analyze things about one's own life.
There is some reflection on how more people can do this now with greater ease because technology facilitates it -- both in data collection and in data representation/analysis. But the "sharing," mobile devices, "social media," "cloud," and such stuff mentioned in the summary quote are barely addressed elsewhere in the article... except as vehicles for personal (i.e., primarily private) data collection.