RansomEXX Gang is Keeping Busy

Israeli Firm Receives $235 million for Facial Recognition Tech

*Clip from Free Thinker Radio (7/14/21): Are The People Ready to Push Back?. Micah and Derrick discuss a new article about the Government Accountability Office reports on use of facial recognition AND an Israeli firm receiving $235 million in funding. https://pinecast.com/listen/63bd1654-2d18-4857-af3a-95769dbf9101.mp3 Sources: As U.S. Government Report Reveals Facial Recognition Tech Widely Used, WEF-Linked Israeli Facial […]

Israeli Firm Receives $235 million for Facial Recognition Tech

From: Big Tech Drone and IoT Surveillance- | Wired: surveillance … “little closer to omniscience”

Wired (Feb 04, 2021) describes in the following a surveillance system that is potentially genocidal, and it exists today, operated by the police in cities like New York.

At least it will finally be “peace” on Earth when this system is fully activated and deployed everywhere in order to quickly catch all criminals and “domestic terrorists”, real and imagined.

Fusion AI surveillance is such a threat to entire humanity that we must have the same attitude as Churchill who was willing to cooperate with anyone, including Stalin, when fighting a common totalitarian enemy.

If you ignore this Wired article you are basically like those in the 1930s who ignored the existence of totalitarian regimes. Yes, the situation is really that serious:

There Are Spying Eyes Everywhere—and Now They Share a Brain

“Security cameras. License plate readers. Smartphone trackers. Drones. We’re being watched 24/7. What happens when all those data streams fuse into one?”

” … I was here to meet Giovanni Gaccione, who runs the public safety division of a security technology company called Genetec. …”

“He led me first to a large monitor running a demo version of Citigraf, his division’s flagship product. The screen displayed a map of the East Side of Chicago. Around the edges were thumbnail-size video streams from neighborhood CCTV cameras. In one feed, a woman appeared to be unloading luggage from a car to the sidewalk. An alert popped up above her head: “ILLEGAL PARKING.” The map itself was scattered with color-coded icons—a house on fire, a gun, a pair of wrestling stick figures—each of which, Gaccione explained, corresponded to an unfolding emergency. He selected the stick figures, which denoted an assault, and a readout appeared onscreen with a few scant details drawn from the 911 dispatch center. At the bottom was a button marked “INVESTIGATE,” just begging to be clicked.” (…)

“Gaccione told me about one counterterrorism unit, which he wouldn’t name, that had used the system to build a detailed profile of “a middle-aged unemployed individual with signs of radicalization,” using “various databases, CCTV, phone records, banking transactions, and other surveillance methods.” If done manually, he estimated, this kind of investigatory grunt work would take a couple of weeks. In this instance, it took “less than a day.”” (…)

“For all these customers, a central appeal of fusion is that it can scale to new sources of data. You can add fuel to your “correlation engine” by, say, hooking up a new network of sensors or acquiring a privately owned library of smartphone location data. (The Pentagon’s Special Operations Command was recently revealed to be a buyer of many such libraries, including those from a Muslim prayer app with tens of millions of users.) Organizations with their own coders can develop capabilities in-house. In New York, for instance, the police department’s analytics division created a custom plug-in for its fusion system. The feature, called Patternizr, draws on more than a decade’s worth of departmental data to match property crimes that could be related to each other. When a new report comes in, all the investigator has to do is click “Patternize,” and the system will return a list of previous incidents, scored and ranked by similarity.”

“Mind-bending new breakthroughs in sensor technology get a lot of buzzy press: A laser that can covertly identify you from two football fields away by measuring your heartbeat. A hack that makes your smartphone spy on anything nearby with a Bluetooth connection, from your Fitbit to your smart refrigerator. A computer vision system that will let the authorities know if you suddenly break into a run within sight of a CCTV camera. But it’s a mistake to focus our dread on each of these tools individually. In many places across the world, they’re all inputs for a system that, with each new plug-in, reaches a little closer to omniscience.” (…)

“Analysts would run the fusion system 24 hours a day, searching for the red teams in radar and lidar sweeps, drone footage, cell phone and internet data, and encyclopedic intelligence records that, as Cutler put it, “no analyst can possibly read.” The system might, for instance, alert its operators whenever a vehicle from an enemy watchlist entered a certain neighborhood. It could also generate a “normalcy model” of the observed areas so that it could alert analysts to anomalies, like a car driving erratically. (The more complex patterns remain secret; many are still used to identify targets in counterterrorism operations today.)”

“By the time of Insight’s final disclosed test, in September 2015, the Army had pivoted the program to what McBurnett called “1980s-style, full-on, armored-brigades-on-armored-brigades kind of action.” I obtained a short video of one of these later iterations of the software from BAE Systems, the prime contractor for Insight. It shows Fort Irwin in “grand chessboard” mode, with an enemy artillery unit moving across the terrain. Each vehicle, tracked relentlessly through multiple data feeds, is marked with a “likely identity” and a detailed tactical life history. In the video, analysts use the software to figure out whether the red teams will come at their forces head-on from the north or attempt a flanking maneuver from the south. As new intelligence streams in, Insight recalculates the relative likelihood of each eventuality. Soon, an alert appears in the corner of the screen: Insight predicts an 82 percent chance of an attack from the north.” (…)

“Eventually, the Department of Defense hopes to link every plane, satellite, ship, tank, and soldier into a huge, mostly automated Internet of Wartime Things. Cloud-connected sensors and weapons will correlate among themselves while commanders direct the action on a rich, continuously updated digital chessboard that senior leaders hope will look like Waze. As part of the effort, the Air Force and the Army have earmarked billions of dollars for fusion networks from dozens of defense and technology companies, including Amazon, BAE, and Anduril.” (…)

” … A more recent Army experiment condensed what was traditionally a manual, 20-minute process for targeting decisions into a largely automated cycle that took just 20 seconds.” (…)

” … On the edges of a social gathering, an NYPD official pulled me aside, said he had something to show me, and took an iPhone out of his pocket.”

“The phone, he explained, was loaded with a mobile version of the Domain Awareness System, the NYPD’s multi-intelligence fusion network. …”

“The NYPD official showed me how he could pull up any city resident’s rap sheet, lists of their known associates, cases in which they were named as a victim of a crime or as a witness, and, if they had a car, a heatmap of where they tended to drive and a full history of their parking violations. Then he handed me the phone. Go ahead, he said; search a name.”

“A flurry of people came to mind: Friends. Lovers. Enemies. In the end, I chose the victim of a shooting I’d witnessed in Brooklyn a couple of years earlier. He popped right up, along with what felt like more personal information than I, or even perhaps a curious officer, had any right to know without a court order. Feeling a little dizzy, I gave the phone back.” (…)

” … A devout Christian, Schnedler realized that the same technology that had so thoroughly persuaded him in New York could be turned into a sharp instrument of algorithmic authoritarianism, just as useful for rounding up networks of congregants as it was for mapping criminal organizations. …”

” … In a back room, a chain-smoking senior officer asked Schnedler whether he could build software that would identify masked protesters by correlating the tattoos on their forearms—which they’d often expose momentarily when throwing rocks—with a database of such markings that his government had been assembling. Again, Schnedler knew that this was technically feasible. Again, he worried about how it might be used against Turkey’s Christian population. …”

” … He returned to the United States that fall having learned an important lesson: “To the extent that you do not trust your government, you do not want your government to build these systems.””

” … One government, which he [Gaccione] refused to name, issued a solicitation for a tool that would mesh facial recognition cameras and mobile phone networks to track citizens wherever they went. …”

“In the United States, there are no specific national rules governing fusion technology. Absent a legal challenge to test its constitutional integrity, there’s little to say that you can’t blend data sets together, even if doing so might generate information that investigators would otherwise have needed a court order to obtain. …” (…)

” … The fact that intelligence can be difficult and tedious to correlate was perhaps the last natural rampart standing between us and total surveillance. The little privacy we have left exists in the spaces between each data point.

“Fusion technology eviscerates those spaces. With the click of an “INVESTIGATE” button, our digital footprints, once scattered, become a single uninterrupted life history, leaving not only our enemies, but also our friends and our lovers, with nowhere to hide.”