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e-Xploration
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#BIGDATA SOCIETY: Age of Reputation or Age of Discrimination? | #controverses #privacy

#BIGDATA SOCIETY: Age of Reputation or Age of Discrimination? | #controverses #privacy | e-Xploration | Scoop.it
luiy's insight:

Like every technology, Big Data has some side effects. Even if you are not concerned about losing your privacy, you should be worried about one thing: discrimination. A typical application of Big Data is to distinguish different kinds of people: terrorists from normal people, good from bad insurance risks, honest tax payers from those who don't declare all income ... You may ask, isn't that a good thing? Maybe on average it is, but what if you are wrongly classified? Have you checked the information collected by the Internet about your name or gone through the list of pictures google stores about you? Even more scary than how much is known about you is the fact that there is quite some information in between which does not fit. So, what if you are stopped by border control, just because you have a similar name as a criminal suspect? If so, you might have been traumatized for quite some time.

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#BigData 's Dangerous New Era of Discrimination | #segmentation

#BigData 's Dangerous New Era of Discrimination | #segmentation | e-Xploration | Scoop.it
Where does value-added segmentation end and harmful discrimination begin?
luiy's insight:

Big Data creates Big Dilemmas. Greater knowledge of customers creates new potential and power to discriminate. Big Data — and its associated analytics — dramatically increase both the dimensionality and degrees of freedom for detailed discrimination. So where, in your corporate culture and strategy, does value-added personalization and segmentation end and harmful discrimination begin?

Let’s say, for example, that your segmentation data tells you the following:

 

Your most profitable customers by far are single women between the ages of 34 and 55 closely followed by “happily married” women with at least one child. Divorced women are slightly more profitable than “never marrieds.” Gay males — single and in relationships — are also disproportionately profitable. The “sweet spot” is urban and 28 to 50. These segments collectively account for roughly two-thirds of your profitability.  (Unexpected factoid: Your most profitable customers are overwhelmingly Amazon Prime subscriber. What might that mean?)

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