I have been highlighting some cases of analysts doing a masterful job in taking apart claims made in the media. Here is another example from Bruce Schneier, the national security expert.
In June 2013, a Who’s Who list of telecom and technology companies, such as Verizon, AT&T, Google and Facebook, was busted for passing customer data to the National Security Agency in its domestic surveillance program. This episode invites scrutiny on one of the tenets of Big Data, the business practice of tracking customers. One of the articles I read at the time mentioned TrackMeNot as a way to foil the spies. TrackMeNot is a browser plug-in developed at New York University that sends randomly generated search queries from your browser. This strategy has a scientific basis—those who read Nate Silver’s book, The Signal and The Noise, can appreciate how adding noise can diffuse the signal.
Despite the association with a reputable institution and the scientific principle, one would be mistaken to think that TrackMeNot protects one from snooping!
A search of “TrackMeNot” brought me to a blog post from 2006 (!) by Bruce Schneier (link), whose valuable work on security technology I came across while researching Numbers Rule Your World. In fewer than 1,000 words, he turned what sounded like a promising concept into half-baked pseudoscience. The secret is read the fine print, something you should always do before believing statistical claims.
It turns out that the “random” search queries generated by the tool (circa 2006) consisted of two-word combinations, chosen from a dictionary of 1,673 words, sent to one of four search engines at regular twelve-second intervals. Imagine how easy it is for an analyst to remove such noise from the web logs. It is obvious from reading the comments that Schneier’s audience is well informed about the Achilles’ heel of all terrorist prediction methodologies, the problem of false positives. One reader simply said “WakeMeNot.”
Chapters 6 and 7 of Numbersense, on economic indicators, highlight the importance of learning the formulas behind metrics, and how data are processed. In short, details matter.
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