Hunch then looks for statistical correlations between the information that all of its users provide, revealing fascinating links between people’s seemingly unrelated preferences. For instance, Hunch has revealed that people who enjoy dancing are more apt to want to buy a Mac, that people who like The Count onSesame Street tend to support legalizing marijuana, that pug owners are often fans of The Shawshank Redemption, and that users who prefer aisle seats on planes “spend more money on other people than themselves.”
Stuff like this is usually overblown a bit (writers always get a case of Gladwell-itis when talking statistics) but it’s also the future as more and more data about us gets logged in ways that allow for association.
On thing that occurs to me reading this is that the shift in statistics consumption is likely to mirror the post-internet shift in traditional publishing — strong associations, like books, used to be hard and expensive to churn out, so a lot of filtering went into the process up front — people would run statistics on things they thought might matter for other reasons.
With the advent of total life-logging via credit card, smartphones, and social media and the with rise of large and extensive cohort databases, associations become cheap — but the significance filter is passed on to the consumer.
In other words, if your publication filter is insufficient for the modern world (as Shirky claims) just imagine how inadequate your statistics filter is for the deluge about to come…