Once again, a terrorist attack on American soil proves the massive federal surveillance state doesn’t improve ‘public safety’ and ‘national security’

http://www.freedom.news/2015-12-08-once-again-a-terrorist-attack-on-american-soil-proves-the-massive-federal-surveillance-state-doesnt-improve-public-safety-and-national-security.html~hehe thum sneaky "terror~ain't's" slipped pass "our vaunted" ...Mass surveillance   "state"...    "once" again  ??? we ameri~cans  pay/piss ALL them  billions&billions&billions of OUR $$$ away ON & NOBODY in this dumb~meeed down drugged out... dull.. dim witted... alice in won~dee~land ville   ... 6 rate country  says  WTF  !!!   or maybe the ass pipes in charge are  ... "miss~in" this shit on ..purpose  or maybe ..just fucking maybe there is an "agenda"  go~in ON  & "it's"  ...not 4 "our" ...benny's   ???    i mean cum the fuck ON  ! America ... just how the fuck long can "our" ass pipes ( 'elected' ass facials ) keep rid~in that   'well we R just THAT ...im~cum~pump~tip'  ..."roooo~teen"  ..game  ..before 1 of U.S. boobs says ...wait a minute  ;o  Huh ???  .... Americans have surrendered 100 percent of their privacy for a surveillance state that continues to fail them

http://www.lovethispic.com/image/152692/your-head-is-up-your-ass

December 8th, 2015, by Jon E. Dougherty

(Freedom.news) What’s that we hear from the “national security hawks” on Capitol Hill: Mass surveillance will keep us safe? That Congress and the president must ignore the Fourth Amendment’s privacy guarantee in this “age of terrorism” so they can improve public safety and prevent terrorist attacks?
Yes, well, tell that to the families of the 14 dead Americans in San Bernardino, Calif., as well as the others who were wounded when two people with emerging terrorist ties waltzed into their holiday party and shot the place up.

In fact, as top security experts will tell you, mass surveillance is not effective and actually puts the nation more at risk.
Consider: As per Zero Hedge, the former chief of the National Security Agency’s global intelligence-gathering operations, Bill Binney, told Washington’s Blog that mass surveillance actually disrupts the government’s ability to locate and interrupt bad guys plotting bad things. The government failed to identify plots that led to the 9/11 attacks, the Boston Marathon bombings, the shootings at Fort Hood, Texas, and, most recently, the terrorist attack in San Bernardino, Calif., because of being overwhelmed with data and having too few analysts and resources to adequately sift through it in a timely manner.
Binney said:
A good deal of the failure is, in my opinion, due to bulk data. So, I am calling all these attacks a result of “Data bulk failure.” Too much data and too many people for the 10-20 thousand analysts to follow. Simple as that. Especially when they make word match pulls (like Google) and get dumps of data selected from close to 4 billion people.
This is the same problem NSA had before 9/11. They had data that could have prevented 9/11 but did not know they had it in their data bases. This back then when the bulk collection was not going on. Now the problem is orders of magnitude greater. Result, it’s harder to succeed.
Expect more of the same from our deluded government that thinks more data improves possibilities of success. All this bulk data collection and storage does give law enforcement a great capability to retroactively analyze anyone they want. But, of course,that data cannot be used in court since it was not acquired with a warrant.
In separate comments to Zero Hedge, Binney added:
I always like to point to the obvious. Look at what is happening in France and Belgium after the attack in Paris. They are going after targeted individuals, who they knew were related to the killers before the attack. And, it’s working!!! So, this is what I have been saying they should do all along.
Do a targeted selection of data from the communications based on known people and their attributes and you can succeed (as now in France and Belgium) instead of the bulk collection on everyone which buries them in data and they fail. After the attack and people die, they do the right thing. This should make it obvious what route to take.
Interestingly, following the San Bernardino attacks, we learned that the suspects were actually under FBI surveillance, and yet were never dealt with in time to prevent the attacks that left 14 dead and nearly 20 wounded.
“The recent massacre at the Inland Regional Center in San Bernardino, Calif., in which a married Muslim couple killed 14 people and wounded 21 others is further proof that the surveillance state does not work. Americans have surrendered 100 percent of their privacy for a surveillance state that continues to fail them,” wrote Julie Wilson for NaturalNews Dec. 4.
But unfortunately, we are getting no shortage of intelligence experts and politicians crying for more mass surveillance. In fact, following the mid-November ISIS-connected terrorist attacks in Paris, which left 130 people dead, the Obama administration called for new powers to access via “back doors” all cell phones and other devices, Cyberwar.news reported.
Richard Clarke, counterterrorism czar under Presidents Bill Clinton and George W. Bush, agrees that mass surveillance is a loser in terms of protecting the country, and that surveillance ought to be more targeted, premised upon specific information, and above all constitutional.
“I am troubled by the precedent of stretching a law on domestic surveillance almost to the breaking point. On issues so fundamental to our civil liberties, elected leaders should not be so needlessly secretive,” he told Washington’s Blog in June 2013.
“The argument that this sweeping search must be kept secret from the terrorists is laughable. Terrorists already assume this sort of thing is being done. Only law-abiding American citizens were blissfully ignorant of what their government was doing,” he added.

CONCERNING CERN: ARTIFICIAL INTELLIGENCE TO UNPLUG DATA FLOOD AT CERN? ...

Posted on December 8, 2015 by Joseph P. Farrell •http://gizadeathstar.com/2015/12/concerning-cern-artificial-intelligence-to-unplug-data-flood-at-cern/

THis is one of the articles that so many of you shared that I simply have to comment about it. There seems to be an expanded role for AI envisioned at CERN, which the the world's largest single-entity generator of "data", according to this article from Scientific American:
Artificial Intelligence Called In to Tackle LHC Data Deluge
Now, before I venture into my high octane speculation of the day, I want the reader to focus on the following paragraphs, which summarize the data filtration and collection system in use at CERN's Large Hadron Collider currently, and which I reviewed in my most recent book, The Third Way:

Driven by an eagerness to make discoveries and the knowledge that they will be hit with unmanageable volumes of data in ten years’ time, physicists who work on the Large Hadron Collider (LHC), near Geneva, Switzerland, are enlisting the help of AI experts.
On November 9-13, leading lights from both communities attended a workshop—the first of its kind—at which they discussed how advanced AI techniques could speed discoveries at the LHC. Particle physicists have “realized that they cannot do it alone”, says Cécile Germain, a computer scientist at the University of Paris South in Orsay, who spoke at the workshop at CERN, the particle-physics lab that hosts the LHC.
Computer scientists are responding in droves. Last year, Germain helped to organize a competition to write programs that could ‘discover’ traces of the Higgs boson in a set of simulated data; it attracted submissions from more than 1,700 teams.
Particle physics is already no stranger to AI. In particular, when ATLAS and CMS, the LHC’s two largest experiments, discovered the Higgs boson in 2012, they did so in part using machine learning—a form of AI that ‘trains’ algorithms to recognize patterns in data. The algorithms were primed using simulations of the debris from particle collisions, and learned to spot the patterns produced by the decay of rare Higgs particles among millions of more mundane events. They were then set to work on the real thing.
But in the near future, the experiments will need to get smarter at collecting their data, not just processing it. CMS and ATLAS each currently produces hundreds of millions of collisions per second, and uses quick and dirty criteria to ignore all but 1 in 1,000 events. Upgrades scheduled for 2025 mean that the number of collisions will grow 20-fold, and that the detectors will have to use more sophisticated methods to choose what they keep, says CMS physicist María Spiropulu of the California Institute of Technology in Pasadena, who helped to organize the CERN workshop. “We’re going into the unknown,” she says.
Inspiration could come from another LHC experiment, LHCb, which is dedicated to studying subtle asymmetries between particles and their antimatter counterparts. In preparation for the second, higher-energy run of the LHC, which began in April, the LHCb team programmed its detector to use machine learning to decide which data to keep.

In effect, what all this means, is that the enormous mountain of data that CERN's collider generates is first filtered by computer algorithms which are programed to sift through the mountain of data and pull certain events which conform to this programmed filter for human analysis and review.
It was this fact that led me to propose, in The Third Way, the hypothesis that there could be hidden algorithms, in all the millions of lines of code, designed to pull anomalous or other types of events, and shunt them into a covert program consisting of covert analysts that might have  Additionally, I suggested that one such program would not consist so much of the experiments themselves, but rather, "data correlation" experiments, pulling data not only from the collider, but from concurrent events, be they geophysical, or events concurrent with collider runs that occur in the magnetosphere of the earth, solar events, and so on. In other words, I was, and am, proposing the idea that in addition to the public story of "particle physics," there might be hidden experiments, only revealed by means of such data correlation algorithms, dealing with the macro-systemic effects of the collider's operation.
With that in mind, consider the very opening paragraph of the article:

The next generation of particle-collider experiments will feature some of the world’s most advanced thinking machines, if links now being forged between particle physicists and artificial intelligence (AI) researchers take off. Such machines could make discoveries with little human input—a prospect that makes some physicists queasy. (Emphasis added)

Such a statement seems to imply the possibility for a hidden program, but more importantly, throws an interesting and intriguing light on my "correlation" experiment idea, for such an experiment would seem, perforce, to demand such vast computational powers that only an AI could provide, sifting through reams of data not only from particle collisions, but "concurrent" data seemingly unrelated save only their occurrence in time frames when the collider is active, and their absence when it is not, data from human behavior trends (if any), data from alterations in the magnetosphere's shape and behavior(and there is some suggestive stuff out there), to other types of data. This would require enormous computational ability and considerable skill in designing the algorithms.
So in my high octane speculation of the day, I suspect that perhaps we've been given a hint of this, and of these types of possibilities, in this article, for it seems, reading between the lines a bit, these very types of possibilities.