Is the DOJ Essentially Now a Data Laundering Operation?

In a recent interview with Democracy Now, Julian Assange(starting at around the 29:00 mark) made a particularly salient observation regarding the current DOJ surveillance ignominy involving the AP and Fox News: the NSA already had the data. The DOJ “investigation” was not an investigation per se, but rather a “data laundering operation” to “cleanse” the data for possible legal use in court proceedings. Assange prefaced his remarks with “do not be deceived,” and I would spot a high probability that he is correct in this instance with the only qualification being that he will be absolutely right within the very near future.

Interestingly, Assange proceeded to spell out the political economy of data analytics, detailing how the NSA is involved in a massive graphical analysis of node connections(nodes would be you and me) to map out the “social network”(the links or edges that connect all of us). Of course, this very thing was the basis of my earlier critique of his “Call to Cryptographic Arms,” noting that encryption can’t reliably shield the connectedness of your own little(or perhaps not so little) matrix in the well-connected graph1.

In any event, Assange labeled the NSA the “dirty team” and the DOJ the “clean team.” In the totalitarian surveillance world of the well-connected graph, this shifts the DOJ’s role to be that of the State’s data launderer. In the 21st century political economy, the so-called liberal “rule of law” rests on the foundation of a data laundering operation.

Two words: The Firm. And the lines are further blurred between the Ministry of Truth and The Department of Justice.

1 Benjamin Tucker is noted for his four monopolies. The 21st century political economy will introduce a fifth one: data analytics. And this will be the mother of all monopolies. Tucker’s observation regarding money–a free market in banking is one of humanity’s greatest civilizers while a monopoly in the same is one of its greatest enslavers–can be multiplied by orders of magnitude both ways in regards to data analytics.

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