This is an article from MIT and basically some high tech hackers went to work with piecing together “mined” data and as you can read below it was not always correct and emphasizes the danger of relying on data mined information. I feel this is an 
important topic as so many are mining data and using data as such for more than just advertising today. It certainly makes room for a ton of doubt and if the data matched and used is this full of holes and errors, well that can easily put holes in companies who are selling this service, like FICO stating they can use your credit rating with other free available information on the web to “score” you and give you a risk assessment on whether or not you will take your prescriptions. As we saw to day credit folks may have some answering to do here soon with their math and formulas.
FICO Analytics Press Release Marketing Credit Scoring Algorithms to Predict Medication Adherence–Update (Opinion)
If you read the link above I have already called this “bunk” and it’s amazing that companies as such can pull the wool over such analytic services and sell the software for a price. Advertising is one thing which is more of an annoyance at times but when you have over stated algorithms convincing people that they are correct and useful to do a risk assessment, we have a problem.
The article also stresses some type of government control of such mining and inflated values as people are using profiles and information for critical decision making at times, which is scary that they can buy into mismatched and erroneous data and judge and rate others at the same time.
We are making strong exploitations about weak data and the article says its not in our nature to fight it so we get fleeced and judged improperly. BD
A complex picture of your personal life can now be pieced together using a variety of public data sources, and increasingly sophisticated data-mining techniques. But just how accurate is that picture?
Last week in Las Vegas, at the computer security conference Black Hat, Alessandro Acquisti, an associate professor of information technology and public policy at the Heinz College at Carnegie Mellon University, showed how a photograph of a person can be used to find his or her date of birth, social security number, and other information by using facial recognition technology to match the image to a profile on Facebook and other websites. Acquisti acknowledges the privacy implications of this work, but he warns that the biggest problem could be the inaccuracy of this and other data-mining techniques.
But Acquisti's research demonstrated the pitfalls of placing too much relevance on social networking data. His team took photos of volunteers and used an off-the-shelf face recognizer called PittPatt (recently acquired by Google) to find each volunteer's Facebook profile—which often revealed that person's real name and much more personal information. Using this information, the team could sometimes figure out part of a person's social security number. They also created a prototype smart-phone app that pulls up personal information about a person after they are snapped with the device's camera.
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