Carnegie Mellon University (CMU) researchers are studying how facial-recognition tools can be detrimental to privacy. In a recent test, the researchers were able to identify about 33% of the people they tested, only using a snapshot and facial-recognition technology from Google.
In addition, CMU professor Alessandro Acquisti found that he could use information available on Facebook to correctly predict the first five digits of a person's Social Security number about 27% of the time, demonstrating the potentially intrusive potential of facial-recognition technology when used with publicly available personal data. Acquisti says the study shows how Facebook is becoming a de facto identity-verification service.
As part of the CMU study, 93 students volunteered to be photographed with a Webcam. The pictures were uploaded to a cloud computer and put into a database of 261,262 publicly available photos taken from CMU students' Facebook profiles. The researchers were able to find 10 possible matching photos in the Facebook database with more than 30% accuracy. The research "suggests that the identity of about one-third of subjects walking by the campus building may be inferred in a few seconds combining social network data, cloud computing, and an inexpensive Webcam," Acquisti says.
From The Wall Street Journal
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