The Dirty Little Secret About Mass Surveillance: It Doesnít Keep Us Safe
2013-06-14 0:00

From: WashingtonsBlog

NSA Spying Doesnít Work to Prevent Terrorism

William Binney knows as much about spying as anyone alive.

Binney Ė a 32-year National Security Agency veteran Ė is the former head of the NSAís global digital data gathering program, and a very highly-regarded cryptographer.

Binney told Daily Caller yesterday that the spying ďdragnetĒ being carried out by the government is useless:

Daily Caller: Thereís been some talk about the authorities having a recording of a phone call Tamerlan Tsarnaev had with his wife. That would be something before the bombing?

Binney: Before the bombing, yes. [This information comes from former FBI counterrorism agent Tim Clemente.]

Daily Caller: Then how would they have that audio?

Binney: Because the NSA recorded it.

Daily Caller: But apparently the Russians tipped off the FBI, which then did a cursory interview and cleared him. So how were they recording him?

Binney: Because the Russians gave a warning for him as a target. Once youíre on a list, they start recording everything. Thatís what Iím saying.

Daily Caller: So why didnít they prevent the bombing?

Binney: Once youíve recorded something, that doesnít mean they have it transcribed. It depends on what they transcribe and what they do with the transcription.

Daily Caller: So it seems logical to ask: Why do we need all of this new data collection when theyíre not following up obvious leads, such as an intelligence agency calling and saying you need to be aware of this particular terrorist?

Binney: Itís sensible to ask, but thatís exactly what theyíre doing. Theyíre making themselves dysfunctional by collecting all of this data. Theyíve got so much collection capability but they canít do everything.


Daily Caller: So what are they doing with all of this information? If they canít stop the Boston marathon bombing, what are they doing with it?

Binney: Well again, theyíre putting an extra burden on all of their analysts. Itís not something thatís going to help them; itís something thatís burdensome. There are ways to do the analysis properly, but they donít really want the solution because if they got it, they wouldnít be able to keep demanding the money to solve it. I call it their business statement, ďKeep the problems going so the money keeps flowing.Ē Itís all about contracts and money.

Daily Caller: But isnít data collection getting easier and processing speeds getting faster and data collection cheaper? Isnít the falling price one of the reasons they can collect data at this massive level?

Binney: Yes, but thatís not the issue. The issue is, can you figure out whatís important in it? And figure out the intentions and capabilities of the people youíre monitoring? And they are in no way prepared to do that, because that takes analysis. Thatís what the big data initiative was all about out of the White House last year. It was to try to get algorithms and figure out whatís important and tell the people whatís important so that they can find things. The probability of them finding whatís really there is low.

Similarly, Fortune notes that the NSAís ďbig dataĒ strategy is ineffective:

The evidence for big data is scant at best. To date, large fields of data have generated meaningful insights at times, but not on the scale many have promised. This disappointment has been documented in the Wall Street Journal, Information Week, and SmartData Collective.


According to my firmís research, local farmers in India with tiny fields frequently outperform ó in productivity and sustainability ó a predictive global model developed by one of the worldís leading agrochemical companies. Why? Because they develop unique planting, fertilizing, or harvesting practices linked to the uniqueness of their soil, their weather pattern, or the rare utilization of some compost. There is more to learn from a local Indian outlier than from building a giant multivariate yield prediction model of all farms in the world. The same is true for terrorism. Donít look for a needle in a giant haystack. Find one needle in a small clump of hay and see whether similar clumps of hay also contain needles.


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