The Privacy Crunch and Data Mining

I recently came across a nice article on data mining (if you wanted to get a rapid overview) that I thought I’d share with all of us. Michael Seringhaus’ and Mark Gerstein’ ‘The Privacy Crunch‘ reads as follows;

Some questions shouldn’t be asked. Employers, for instance, generally are not allowed to discriminate based on marital status, sexual orientation and so on. But our growing digital footprint is threatening our ability to dodge inappropriate inquiries. Through data mining, employers, insurers, advertisers and others can infer the answers to private questions without even asking.

They need two things: a heap of personal data, and the techniques to crunch it. Both are readily available.

The rest of their article continues to give a quick and cutting description of what data mining is, and how it’s used. This speaks to some of our worries/discussions about the complexities of the present information-trading economy; no longer is a truly unique piece of personal information needed to generate detailed digital portfolios about individuals (though the accuracy of such portfolios is never guaranteed). If you’re interested in data mining, Daniel Solove’s The Digital Person (Cato book review here) does a great job of detailing both how ‘traditional’ privacy archetypes are unsuitable for the contemporary databank era, as well as showing just how massive the datamining economy is in the US.