Tag: ‘technology

USPS Is Turning Mail Trucks Into Rolling Surveillance Cameras

The United States Postal Service is testing forward-facing cameras in roughly 100 delivery vehicles operating in the Washington, D.C., area, according to a labor-relations letter reported by 404 Media. The cameras, supplied by dashcam manufacturer Nextbase, are intended to scan roads, signage, and sidewalks while trucks follow their normal delivery routes.

The pilot was scheduled to begin September 21, 2026. The stated purpose is roadway and infrastructure data collection and what USPS calls “community safety,” though what happens to everything else the cameras capture remains a less-answered question.

What the Cameras Will Actually Do

The cameras begin recording when a truck leaves the postal facility and are designed to collect roadway and infrastructure data without altering driver duties.

Cameras activate when a truck shifts into drive and departs the postal facility. There is no audio recording, and the cameras face forward only, positioned so they do not obstruct the driver’s field of vision. USPS has stated that employees will not need to take any additional action.

Nextbase markets cameras capable of recording in resolutions up to 4K, with product materials noting the ability to capture license-plate details. Those are advertised product capabilities, not confirmed specifications for the units installed in the pilot.

USPS says the pilot does not use automatic license plate reader software. A camera can visually record a plate without running it through ALPR software that converts the image into a searchable database entry; those are meaningfully different functions. Whether USPS retains, processes, or searches incidentally captured plate images is not established in the available reporting.

The logic behind using mail trucks specifically comes directly from USPS Labor Relations, in a letter to National Association of Letter Carriers president Brian Renfroe: “The purpose of this pilot is to leverage the Postal Service’s unique ability to collect this valuable data due to the scale and frequency with which our fleet of postal vehicles travel the streets of every community across the country.”

The arrangement resembles dedicated roadway-mapping fleets, but relies on vehicles already in service rather than purpose-built survey cars.

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The War Department’s Robot Army Is a Moral and Strategic Disaster

By any measure, September 30, 2026, was a dark day for American military ethics.

Standing at Quantico, War Secretary Pete Hegseth announced the creation of AUTOWARCOM – a new four-star command whose entire purpose is to accelerate the deployment of autonomous robots and AI-driven weapons onto the battlefield. He dressed it up in the language of innovation, citing Ukraine, promising speed, invoking “the fastest peacetime shift in modern military history.”

But let’s be clear about what he actually proposed: a military architecture designed to remove human beings from the kill chain. Machines that select targets. Machines that decide who lives and who dies. Machines that answer to no conscience, no court, and no law.

Amnesty International has been warning about this exact future for years. Fully autonomous weapons, the organization argues, are inherently incompatible with international human rights law. They cannot be held accountable. They cannot exercise mercy. They cannot distinguish between a combatant and a child who picks up a rifle out of fear. A machine has no empathy, no reason, no restraint – only code, and code carries the biases of whoever wrote it.

Hegseth’s answer to that concern? “We are putting on the full armor of God. Because while we wage physical war, we all know the real battle is spiritual.” That is not a policy justification. That is a sermon deployed to sanctify a killing machine.

And the timing is obscene. The United States is seven months into a war with Iran with no exit in sight. American troops are burning through missile interceptors defending against Iranian drones. The Strait of Hormuz is a stalemate. The Pentagon is begging for $74 billion for drones and counter-drone systems while contractors admit it will take **at least three years** to replenish basic stockpiles. And in the middle of that, Hegseth wants to stand up a new bureaucracy, hand it a four-star general, and call it strategy.

Worse still, he’s hollowing out the officer corps that would have to run it.

Hegseth confirmed he is doubling his earlier order to cut flag officers — from 10% to 20%.** That’s roughly 160 generals and admirals gone by January 2027. He calls it “accountability.” Senator Mark Kelly, a former Navy combat pilot, calls it what it is: a purge. “He’s purging a generation of great leaders of the military,” Kelly said, “and it’s going to take a generation to recover from it.”

Kelly is right. More than two dozen senior officers have already been fired or forced out – Brown, Franchetti, George among them. Many were women. Many were people of color. Many were simply not ideologically pliant enough for a secretary who seems to view the uniformed military as a personal fiefdom rather than a profession.

So here is the real picture: a secretary who has never commanded troops in combat is dismantling the professional military while building a robot army that no human being will be legally responsible for.

This is not strength. This is not innovation. This is moral cowardice dressed in techno-optimism.

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Florida Deputy Charged After Using Flock License Plate Reader System to Search Woman 300 Times, Another Deputy Arrested After Looking Up 17-Year-Old Girl in Police Database

The misuse of Flock Safety camera systems continues to grow.

On Wednesday, Pinellas County Sheriff Bob Gualtieri announced the arrests of two deputies accused of improperly accessing law enforcement databases, including an automated license plate reader system that uses Flock cameras.

According to Gualtieri, Deputy Karl Gwynn, 57, ran 381 searches on a 35-year-old woman he had arrested years earlier because he reportedly wanted a relationship with her.

Of the 381 searches, 300 queries were made through the Flock ALPR system.

The second deputy arrested was 33-year-old Travis Stanton who allegedly used the police databases to gather information on a 17-year-old girl he was reportedly “romantically interested in.”

Per WTSP:

Two Pinellas County sheriff’s deputies have resigned and face criminal charges after investigators said they improperly accessed sensitive law enforcement databases, including the Flock camera system.

Sheriff Bob Gualtieri announced the arrests Wednesday, describing two unrelated cases involving a former deputy’s interest in a 17-year-old girl and another deputy’s repeated searches of a woman’s information across multiple databases.

The first case involves former Deputy Travis Stanton, 33, who resigned on Sept. 25 after the sheriff’s office began investigating his conduct involving a 17-year-old girl who had filed a complaint with the agency. Gualtieri said Stanton used several databases to gather information about the girl and her vehicle, including running her license plate through Florida’s vehicle registration system using a computer in his patrol car.

In an unrelated case, Deputy Carl Gwynn, 57, allegedly queried a 35-year-old woman’s information 381 times.

Sheriff Gualtieri said Gwynn had arrested the woman years earlier and wanted a relationship with her. Unlike the Stanton case, Gwynn’s alleged misconduct directly involved the sheriff’s office automated license plate reader system (ALPR), commonly associated with Flock Safety cameras.

Gwynn has since resigned and was arrested on four counts of unlawfully accessing secure systems with his bond being set at $25,000.

Stanton was charged with unlawfully accessing secure systems and his bond was set at $10,000.

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Chuck Schumer Orders Democrats to Block Bill That Aims to Force Data Centers to Cover Increased Energy Costs

Senate Democrats are working to short-circuit a bill aimed at protecting consumers from the costs of data centers.

The Ratepayer Protection Act passed the House 417-3 in the 435-member House.

However, Senate Minority Leader Chuck Schumer opposes the bill, which he called “a fraud,” according to The Hill.

“Americans are demanding real guardrails on AI and data centers, but all the Republicans offer is a toothless messaging bill,” he said Tuesday.

The bill requires 60 votes to pass a procedural hurdle. Although Republicans have a majority in the Senate, it would take Democratic votes to move the bill forward.

Democratic Sen. Peter Welch of Vermont, who had been the lone Democrat supporting the bill, said he has changed his mind.

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Who Keeps The Money When AI Rewrites Bank Code?

The code most American banks run on was designed in 1959, the year Alaska and Hawaii became states. A committee of government and industry people wrote COBOL so that business programs could be read by people who were not mathematicians, and a good part of it was modeled on FLOW-MATIC, an earlier language from Grace Hopper, a Navy officer. I doubt anyone on that committee thought it would still be running banks in 2026. In 2017 Reuters estimated that about $3 trillion of daily commerce still ran through COBOL. In April 2020, when unemployment claims in New Jersey overwhelmed the state’s forty-year-old system, Governor Phil Murphy went on television and asked for volunteers who knew COBOL. The state had to go on TV to find programmers for its own unemployment system.

I bring this up because of a clip I posted last night of Bill Ackman talking with Shane Parrish on The Knowledge Project. Ackman said Cognition, the company behind the coding agent Devin, can rewrite a bank’s COBOL “in a matter of days as opposed to many months.” Someone replied asking me what I meant when I said commoditized lenders would compete the savings away. It is a fair question and I could not answer it in a tweet.

I do believe Ackman that the savings are real. Inside a large bank the core ledger still runs in batch. The balance a customer sees on the app at noon is an estimate (bankers call it memo-posted). The actual accounting happens overnight, when a mainframe works through a queue of jobs in a set order, posting transactions, accruing interest, charging fees, and producing files that every other system reads the following morning. The programs share data through copybooks, which are record layouts where a field is known only by its position. Cognition described one client where a single taxpayer ID showed up under dozens of different names across thousands of programs. Most big banks were put together through acquisitions, and each acquired bank came with its own core system that management was usually too nervous to shut off, so the old systems just piled up.

Replacing all of that has gone badly more often than well. Commonwealth Bank of Australia spent five years and more than A$1 billion replacing its core, and people in the industry consider that one a success. TSB in the UK moved customers onto a new platform in April 2018 and the platform did not work. Customers were locked out, some could see other people’s accounts, and service was not back to normal until December. TSB ended up paying £32.7 million in redress and £48.65 million in fines. Cognition’s own figure is that roughly two-thirds of COBOL modernization projects fail. With odds like that most banks built layers around the old core and left it alone. JPMorgan expects to spend about $19.8 billion on technology in 2026, and its CFO told investors in February that the priority had moved to “modernizing the underlying application code and data.” I would guess a large share of that budget still goes to keeping the layers standing.

Cognition is fairly careful about what its agents can do today. Devin is good at documentation, refactoring, and batch jobs, which are the parts of a migration where you can give the agent yesterday’s inputs and outputs and let it keep trying until the new code matches the old results. Cognition estimates batch is 30 to 50 percent of a typical migration. The real-time systems (card authorizations, for example) are still out of reach. Banks also have a security reason to hurry. Anthropic’s Mythos model, which can find and exploit software vulnerabilities, had bank regulators in the U.S. and Europe holding urgent calls this spring, and Reuters quoted security experts who named legacy bank systems as especially exposed.

Ackman’s harder point came a little later in the conversation. “The problem with money generally is it’s a commodity,” he said. For loans I agree with him. A company that wants a five-year term loan will collect six or seven term sheets and take the cheapest one, and a bank whose costs just went down will give up some spread to win it. Deposits have never really worked like a commodity, and I think that is where his argument is missing a piece.

The best explanation I have read is from three NYU economists, Itamar Drechsler, Alexi Savov and Philipp Schnabl. Their paper argues that banks have real market power over deposits. When the Fed raises rates, banks raise what they pay depositors slowly and only partway. Keeping that power costs money for branches, bankers and technology, but almost all of the cost is fixed. So deposits end up behaving like long-term fixed-rate funding, which is how a bank can hold thirty-year mortgages without being wiped out every time rates go up. It is also why the industry’s net interest margin has barely moved over several decades of rate cycles. The FDIC has it at 3.32 percent today.

Bankers measure this with the deposit beta (the share of a rate increase that gets passed along to depositors). Checking accounts have low betas. Online banks have high ones because, as the St. Louis Fed put it, their customers are looking for yield. During the 2022 hiking cycle the New York Fed found that super-regional banks passed through more than small banks did, while the very largest banks passed through less than either. After Silicon Valley Bank lost $42 billion in deposits in one day, money moved toward size, and the biggest banks did not have to pay more to get it.

Meta’s Muse goes right at this. It launched September 8, the same day Cognition announced it had raised more than $2 billion at a $48 billion valuation with run-rate revenue near $900 million. Muse is a personal agent that reads accounts at more than 12,000 U.S. banks and financial apps through Plaid. On Tuesday, September 22, Schwab fell 6 percent, LPL fell 7 percent, JPMorgan and Wells Fargo each fell more than 3 percent, and XLF, the largest financials ETF, was down 2 percent. On Sunday Torsten Slok at Apollo put out a note titled “Is an Agentic bank run coming?” He pointed out that the average checking account pays about 0.1 percent while Revolut, SoFi, Wealthfront and others pay between 3.3 and 5 percent, and he warned that banks “could lose a large share of the cheap deposits they rely on to make loans.”

Muse cannot move money yet. The Plaid connection is read-only, and Meta deserves to have that said. I still would not want to be running a bank’s treasury desk this month. Most people leave savings at a tenth of a percent because switching is a hassle. Opening a new account takes an afternoon, and nobody wants to be the person who breaks their own direct deposit. If an agent already sees every balance and can fill out the forms, most of that afternoon goes away.

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The Trump Administration Is Building A Pre Crime Panopticon Unlike Any Authoritarian Regime Before It

As of late American citizens have been more concerned with surveillance and privacy than ever before. Rightfully so, as we see an explosion of surveillance equipment being installed across the country.

For decades, liberty activists have diligently watched and warned of the slowly encroaching mission creep of domestic mass surveillance seeping its way into everyday American life. Opposition to such violations of fundamental liberty have been one of the few causes to transcend the false left / right paradigm, with instances such as leftists opposed to the surveillance of civil rights groups during the days of COINTELPRO and conservative opposition to the surveillance of Second Amendment activists.

Even today, amid rising concerns of the mass implementation of Flock cameras across the nation, these concerns are actively creating a bridge of solidarity among the polarized political chasm.

While surveillance of the American citizenry has existed in some way for more than a century, the persistent punitive pervasiveness of such violations of privacy have been perpetually on the rise since the passage of the Patriot Act following the false flag attack of September 11th, 2001.

Interestingly enough, the provisions of the Patriot Act with all of its violations of constitutional protections had already been cooked up well before the September 11th attacks but was projected not to pass a congressional vote until such attacks took place. Indeed, the Patriot Act simply served as an expansion of surveillance authority circumventing the Constitution implemented in the 1996 Antiterrorism Act, itself only justified following the Oklahoma City false flag attack just a year prior. Simply a coincidence, surely. 

The conversation surrounding concerns about domestic mass surveillance reached mainstream dialog following the explosive revelations of NSA whistleblower Edward Snowden in 2013, when leaked documents provided to journalist Glenn Greenwald revealed a sprawling network of illegal spying against American citizens through the National Security Agency’s PRISM program.

Despite Snowden’s revelations and warnings, and subsequent surveillance scandals in the years since, next to nothing has been done to curtail this campaign of illegal mass spying against the American people. In fact, it has only continued to worsen.

This brings us to today. Oftentimes in discussion of illegal mass surveillance, the cynical statist would posit a straw man argument to the likes of “What does it matter? If you’ve done nothing wrong you should have nothing to hide.” As if an all encompassing surveillance state simply exists in a vacuum. As if history has not demonstrated again and again the kind of atrocities enabled by repressive regimes who track, trace, and database their citizenry.

Mass surveillance does not simply exist to “keep an eye on people”, it serves as a tool of the state to suppress dissent, identify and silence dissidents, and centralize control over the populace.

Here at The Free Thought Project, we have warned for years about the dangers of integrating artificial intelligence with law enforcement. 

Now, it appears the Trump administration is diving head first into a Minority Report style pre crime surveillance system powered by AI to throw a digital dragnet over the entirety of the American people.

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AI: The Ominous Opportunity

“You can see the computer age everywhere but in the productivity statistics.” — Robert Solow, 1987

The economy has been growing steadily since we started to recover from the 2020 pandemic and shutdown; the unemployment rate is and has been near the bottom of the range normally considered to be full employment; and, wages adjusted for inflation are the highest they’ve ever been. Nevertheless, the productivity slowdown observed by Robert Solow forty years ago seems to have returned, and surveys of consumer confidence are at or near their all-time lows. This essay explores possible reasons for the productivity slowdown and widespread economic uncertainty in the midst of our AI boom.

Measurement Problems

Among the possible explanations of the productivity slowdown or what merely appears to be a productivity slowdown is our limited ability to measure productivity in an economy increasingly dominated by services.

It wasn’t so long ago that productivity was measured in the sectors of the economy concerned with physical output such as agriculture and manufacturing. The productivity of office workers was either ignored or simply subsumed into the productivity of goods-producing companies.

There were problems of measuring quality differences in goods, but these could in theory be surmounted. For example, by comparisons of the prices of old and new vintages of similar products. And, the changing composition of production could be represented by slowly-changing weights in indexes of production.

As much effort as was put into measuring production, systematic discrepancies persist in indexes of the prices of services versus the prices of commodities. The CPI, for example, typically registers a 1 or 2 percentage point higher rate of inflation than the PPI. With the digital economy, now augmented by AI, a serious effort must be made to measure the production of information, entertainment and services. For example, an hour of broadcast time prior to the development of the internet might have cost something like $1 million (in today’s dollars). What about the several hundred thousand hours of video uploaded to YouTube nowadays?

Prototypes (as Opposed to Practical Inventions)

In the past, it took a while for breakthroughs such as the steam engine to have a discernible impact on production. It was more or less a century from prototype steam engines to when steam engines were first put to a practical use (in the refreshing of air in coal mines). Then, several more decades until steam engines were used to run industrial machinery. Then, yet several more decades until steam-powered locomotives were used in transportation.

Even when the steam-powered locomotive was developed, horse-drawn trains were more reliable. The story is told of a race in 1830 between a steam-powered locomotive and a horse-drawn train along the Baltimore & Ohio Railroad from Baltimore to Endicott City. The horse won the race since the locomotive broke down. Nevertheless, over the next century, horses lost their jobs in transportation.

Ditto, the steam-powered hammer. According to folklore, John Henry who—through superhuman effort—beat the steam-powered hammer, preserving jobs for the men of railroad work gangs. Nevertheless, over the next century, men lost their jobs to industrial machinery. Warehousemen who relied on their strength to manhandle barrels of pork, flour, and other produce were replaced by forklifts. Dockworkers lost their jobs to electric-powered derricks.

It is easy, looking back, to see the impact of the Industrial Revolution on productivity, on wages, and on standards of living. But, in real time, it took time for these benefits to accrue. In the meanwhile, workers had to deal with disruptive change.

More recently, in 1996, a super-computer named Deep Blue challenged Gary Kasparov, the world chess champion of the humans. Kasparov won the match 3 games to 1 game to 2 draws. However, the victory was fleeting. A year later, Deep Blue won a rematch; and, nowadays, a decent laptop computer can easily defeat a grandmaster. Today, in the current phase of the Industrial Revolution, computers, robots, and AI are coming after our jobs, not steam-, gasoline- and electric-powered machines.

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UK Police Pilot AI System to Track “Suspicious” Driver Journeys

Police forces across Britain are experimenting with artificial intelligence that can automatically monitor and categorize drivers’ movements using the country’s extensive number plate recognition network.

Internal records obtained by Liberty Investigates and The Telegraph reveal that three of England and Wales’s nine regional organized crime units are piloting a Faculty AI-built program designed to learn from vehicle movement data and detect journeys that algorithms label “suspicious.”

For years, the automatic number plate recognition (ANPR) system has logged more than 100 million vehicle sightings each day, mostly for confirming whether a specific registration has appeared in a certain area.

The new initiative changes that logic entirely. Instead of checking isolated plates, it teaches software to trace entire routes, looking for patterns of behavior that resemble the travel of criminal networks known for “county lines” drug trafficking.

The project, called Operation Ignition, represents a change in scale and ambition.

Unlike traditional alerts that depend on officers manually flagging “vehicles of interest,” the machine learning model learns from past data to generate its own list of potential targets.

Official papers admit that the process could involve “millions of [vehicle registrations],” and that the information gathered may guide future decisions about the ethical and operational use of such technologies.

What began as a Home Office-funded trial in the North West covering Merseyside, Greater Manchester, Cheshire, Cumbria, Lancashire, and North Wales has now expanded into three regional crime units.

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Europol Pinpoints When Skynet-Like Human Resistance To AI Could Emerge

If Goldman’s estimates of a partial or full displacement of up to 300 million jobs across the Western world due to the proliferation of artificial intelligence and automation are even remotely correct, a new report suggests that by 2035, society could face widespread public resentment, protests, and even acts of sabotage directed at robotic systems.

A new report by Europol, the EU’s central intelligence and coordination hub for serious crime and terrorism, identifies around 2035 as a potential inflection point at which a human resistance movement against AI could begin to take shape, in a scenario that echoes the resistance to Skynet in the Terminator film franchise.

Europol warned of “bot-bashing” incidents and acts of sabotage against robotic systems in the middle of the next decade, as the spread of AI and robotics could fuel a populist backlash against technologies that have hollowed out parts of the Western economy and left millions unemployed.

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How Palantir Is Expanding the Surveillance State

When people complain about Big Tech, they tend to mean companies like Meta, Google, and X—entities providing free tools and platforms that we can choose whether to use. Much less attention is directed at the tech companies helping the federal government consolidate and analyze data on all of us. Companies like the data analytics firm Palantir, created by Paypal co-founder and Donald Trump supporter Peter Thiel.

Palantir has long been connected to government surveillance. It was founded in part with CIA money, it has served as an Immigration and Customs Enforcement (ICE) contractor since 2011, and it’s been used for everything from local law enforcement to COVID-19 efforts. But the prominence of Palantir tools in federal agencies seems to be growing under President Trump. “The company has received more than $113 million in federal government spending since Mr. Trump took office, according to public records, including additional funds from existing contracts as well as new contracts with the Department of Homeland Security and the Pentagon,” reports The New York Times, noting that this figure “does not include a $795 million contract that the Department of Defense awarded the company last week, which has not been spent.”

Palantir technology has largely been used by the military, the intelligence agencies, the immigration enforcers, and the police. But its uses could be expanding.

“Representatives of Palantir are also speaking to at least two other agencies—the Social Security Administration and the Internal Revenue Service—about buying its technology, according to six government officials and Palantir employees with knowledge of the discussions,” reports the Times.

Along with the Trump administration’s efforts to share more data across federal agencies, this signals that Palantir’s huge data analysis capabilities could wind up being wielded against all Americans.

This won’t allow the authorities watch us more so much as it helps them make use of all the data it’s already got on us. But that’s unsettling too.

“The ultimate concern is a panopticon of a single federal database with everything that the government knows about every single person in this country,” Cody Venzke, senior policy counsel at the American Civil Liberties Union, told Wired in April. “What we are seeing is likely the first step in creating that centralized dossier on everyone in this country.”

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