The real American factory killer? It wasn’t automation



Dylan Matthews at Vox wants you to believe that robots — not China — killed American manufacturing. Even if tariffs reshore production, he argues, they won’t bring back jobs because machines have already taken them.

This is not just wrong. It’s an ideological defense of a decades-long policy failure.

The jobs lost to offshoring aren't just the five million factory jobs that disappeared — the number is likely more than double that. The real toll could exceed 10 million jobs.

Yes, American manufacturing has grown more productive over time. But increased productivity alone does not explain the loss of millions of jobs. The real culprit isn’t automation. It’s the collapse of output growth — a collapse driven by offshoring, trade deficits, and elite dogma dressed up as economic inevitability.

Ford’s logic

To understand what actually happened, start with Henry Ford.

In 1908, Ford launched the Model T. What set it apart wasn’t just its engineering. It was the price tag: $850, or about $21,000 in today’s dollars.

For the first time, middle-class Americans could afford a personal vehicle. Ford spent the next few years obsessing over how to cut costs even further, determined to put a car in every driveway.

In December 1913, he revolutionized manufacturing. Ford Motor Company opened the world’s first moving assembly line, slashing production time for the Model T from 12 hours to just 93 minutes.

Efficiency drove output. In 1914, Ford built 308,162 Model Ts — more than all other carmakers combined. Prices plummeted. By 1924, a new Model T cost just $260, or roughly $3,500 today — an 83% drop from the original price and far cheaper than any “affordable” car sold now.

This wasn’t just a business success. It was the dawn of the automobile age — and a triumph of American productivity.

Ford’s moving assembly line supercharged productivity — and yet, he didn’t lay off workers. He hired more. That seems like a paradox. It isn’t.

Dylan Matthews misses the point. Employment depends on the balance between productivity and output. Productivity is how much value a worker produces per hour. Output is the total value produced.

If productivity rises while output stays flat, you need fewer workers. But if output rises alongside productivity — or faster — you need more workers.

Picture a worker with a shovel versus one with an earthmover. The earthmover is more productive. But if the project doubles in size, you still need more hands, earthmovers or not.

This was Henry Ford’s insight. His assembly line made workers more productive, but it also let him build far more cars. The result? More jobs, not fewer.

That’s why America’s manufacturing employment didn’t peak in 1914, when people first warned that machines would kill jobs. It peaked in 1979 — because Ford’s logic worked for decades.

The vanishing act

Matthews says manufacturing jobs vanished because productivity rose. That’s half true.

The full story? America lost manufacturing jobs when the long-standing balance between output and productivity broke.

From 1950 to 1979, manufacturing employment rose because output grew faster than productivity. Factories produced more, and they needed more workers to do it.

But after 1980, that balance began to shift. Between 1989 and 2000, U.S. manufacturing output rose by 3.7% annually. Productivity rose even faster — 4.1%.

Result: flat employment. Factories became more efficient, but they didn’t produce enough extra goods to justify more hires.

In other words, jobs didn’t disappear because of robots. They disappeared because output stopped keeping pace.

The real collapse began in 2001, when China joined the World Trade Organization. Over the next decade, U.S. manufacturing output crawled forward at just 0.4% a year. Meanwhile, productivity kept rising at 3.7%.

That gap — between how much we produced and how efficiently we produced it — wiped out roughly five million manufacturing jobs.

Matthews, like many of the economists he parrots, blames job loss on rising productivity. But that’s only half the story.

Productivity gains don’t kill jobs. Stagnant output does. From 1913 to 1979, American manufacturing employment grew steadily — even as productivity surged. Why? Because output kept up.

So what changed?

Output growth collapsed. And the trade deficit is the reason why.

Feeding the dragon

Since 1974 — and especially after 2001 — America’s domestic output growth slowed to a crawl, even as workers kept getting more productive. Why? Because we shipped thousands of factories overseas. Market distortions, foreign subsidies, and lopsided trade agreements made it profitable to offshore jobs to China and other developing nations.

The result: America now consumes far more than it produces. That gap shows up in our trade deficit.

In 2024, America ran a $918 billion net trade deficit — including services. That figure represents all the goods and services we bought but didn’t make. Someone else did — mostly China, Mexico, Canada, and the European Union.

The trade deficit is a dollar-for-dollar reflection of offshore production. Instead of building it here, we import it.

How many jobs does that deficit cost us? The U.S. Census Bureau estimates that every billion dollars of GDP supports 5,000 to 5,500 jobs. At $918 billion, the deficit displaces between 4.6 and five million jobs — mainly in manufacturing.

That’s no coincidence. That’s the hollowing-out of the American economy.

We can’t forget that factories aren’t just job sites — they’re economic anchors. Like mines and farms, manufacturing plants support entire ecosystems of businesses around them. Economists call this the multiplier effect.

And manufacturing has one of the highest multipliers in the economy. Each factory job supports between 1.8 and 2.9 other jobs, depending on the industry. That means when a factory closes or moves offshore, the impact doesn’t stop at the plant gates.

The jobs lost to offshoring aren't just the five million factory jobs that disappeared — the number is likely more than double that. The real toll could exceed 10 million jobs.

That number is no coincidence. It matches almost exactly the number of working-age Americans the Bureau of Labor Statistics has written out of the labor force since 2006 — a trend I document in detail in my book, “Reshore: How Tariffs Will Bring Our Jobs Home and Revive the American Dream.”

Bottom line: Dylan Matthews is wrong. Robots didn’t kill American manufacturing jobs. Elites did — with bad trade deals, blind ideology, and decades of surrender to global markets. It’s time to reverse course: not with nostalgia but with strategy, not with slogans but with tariffs.

Tariffs aren’t a silver bullet. But they’re a necessary start. They correct the market distortions created by predatory trade practices abroad and self-destructive ideology at home. They reward domestic investment. They restore the link between productivity, output, and employment.

In short, tariffs work.

Trump’s promised ‘golden age’ collides with a tech revolution



President Donald Trump opened his second inaugural address by declaring, “The golden age of America begins right now.” His new term promises a transformational four years. While foreign policy, economic concerns, and political divisiveness will dominate headlines, a quieter yet far-reaching revolution is underway. Massive technological innovation coincides with Trump’s presidency, setting the stage for societal changes that will shape the coming decades. These advancements offer progress but also demand vigilance as the nation navigates their ethical and societal challenges.

By the time Trump leaves office in January 2029, artificial intelligence, automation, self-driving cars, quantum computing, and other emerging technologies will have reached unprecedented levels. Their evolution and impact on society will likely shape the future more profoundly than the political battles of today.

The next few years will hinge on how society embraces innovation while protecting freedoms, privacy, and stability.

OpenAI, Tesla, and IBM are driving technological advancements, investing billions in research and development to turn science fiction into reality. The AI startup sector alone secured more than $100 billion in global investments last year. Companies pursuing quantum computing, including Google and IBM, are racing toward quantum supremacy, aiming for breakthroughs that could transform entire industries. Tesla and Waymo are investing billions in self-driving cars, positioning themselves to revolutionize transportation.

This surge in investment and innovation highlights the transformative power of these technologies. At the same time, it raises concerns about how society will navigate their rapid evolution. As these breakthroughs accelerate during Trump’s presidency, the stakes remain high — not only for harnessing their potential but also for mitigating their risks

The rise of a new decision-maker

Artificial intelligence has advanced rapidly in recent years, evolving from narrow, task-specific algorithms to sophisticated systems capable of natural language understanding, image recognition, and even creative tasks like generating art and music. OpenAI’s ChatGPT and Google’s DeepMind have become household names, demonstrating AI's expanding role in everyday life and business.

By 2029, industry experts expect AI to grow more advanced and deeply integrated into society, influencing everything from health care to legal systems. Breakthroughs in generative AI could enable machines to produce realistic virtual experiences, transforming education, entertainment, and training. AI-driven research is also poised to accelerate discoveries in medicine and climate science, with algorithms identifying solutions beyond human capabilities.

These advancements promise significant benefits. AI could revolutionize medicine by personalizing treatments, reducing errors, and improving access to care. Businesses may see substantial productivity gains, driving economic growth and innovation. Everyday conveniences, from personal assistants to smart infrastructure, could enhance quality of life, relieving people from mundane tasks and fostering greater creativity and leisure.

The rapid integration of AI raises serious concerns. As AI systems collect and analyze vast amounts of data, issues of surveillance, privacy, and consent demand attention. There are automated decision-making risks that could displace workers, worsen economic inequality, and foster new forms of dependency. Misuse — whether through biased algorithms, manipulative propaganda, or authoritarian control — heightens the need for vigilance. Protecting individual liberty and ensuring AI serves society, rather than undermining it, remains crucial.

Redefining the workforce

Advanced robotics and automation are rapidly transforming traditional industries. Robots already handle complex tasks in manufacturing, agriculture, and logistics, but improvements in dexterity and AI-driven decision-making could make them essential across nearly every sector by the decade’s end.

Several companies are racing to develop increasingly advanced robots. Tesla’s Optimus and Agility Robotics’ Digit are humanoid models designed to perform tasks once exclusive to humans. As Agility Robotics strengthens its partnership with Amazon, Elon Musk predicts robots will outnumber people within 20 years.

While automation boosts efficiency and productivity, it also threatens jobs. Millions of workers risk displacement, creating economic and social challenges that demand thoughtful solutions. The Trump administration will likely face mounting pressure to balance innovation with protecting livelihoods.

Who is in the driver’s seat?

Self-driving vehicle technology has long been anticipated, with Elon Musk initially predicting its emergence by 2019. While that timeline proved optimistic, autonomous vehicle technology has advanced significantly in recent years. What began as experimental prototypes has evolved into semi-autonomous systems operating in commercial fleets. By 2029, fully autonomous vehicles could become widespread, transforming transportation, urban planning, and logistics.

Despite these advancements, controversies remain. Questions about safety, liability, and infrastructure lack clear answers. Additionally, concerns about centralized control over transportation systems raise fears of surveillance and government overreach. The Trump administration will play a crucial role in shaping regulations that safeguard freedom while fostering innovation.

A massive computing breakthrough

Quantum computing, once limited to theoretical physics, is rapidly becoming a practical reality. IBM and Google have led advancements in this technology, with Google recently unveiling Willow, a state-of-the-art quantum computer chip. According to Google, Willow completed a complex computation in minutes — one that would have taken the world’s most advanced supercomputers 10 septillion years. That’s more than 700 quintillion times older than the estimated age of our universe.

With the ability to solve problems at speeds unimaginable for classical computers, quantum computing could transform industries like cryptography, drug development, and economic modeling.

This technology also presents serious risks to privacy and security. Quantum computing’s ability to break traditional encryption methods could expose sensitive data worldwide. As the field advances, policymakers must develop strong regulations to protect privacy and ensure fair access to this powerful technology.

Trump’s most enduring legacy?

These technological advancements could drive extraordinary breakthroughs, including drug discoveries, disease cures, and an era of abundance. But they also pose significant risks. Concerns over data collection, job displacement, surveillance, and coercion are not hypothetical — they are real challenges that will require attention during Trump’s term.

The next few years will hinge on how society embraces innovation while protecting freedoms, privacy, and stability. Trump’s role in this technological revolution may not dominate headlines, but it will likely leave the most lasting impact.

Tesla robot pictured folding laundry just months after technology was revealed



Elon Musk showcased a video of a Tesla robot folding a shirt just a few short months after both the menial task and robot technology was revealed.

The robots, called "Tesla Optimus," are described as "general purpose, bi-pedal," and "humanoid" robots that are capable of performing tasks that are "unsafe, repetitive or boring."

The bots made their first big reveal in May 2023 and were shown walking around and "learning about the real world."

At the same time, a group of scientists and robotics engineers developed a robot that can learn an individual's cleaning habits and techniques to properly organize their living space and throw out waste.

The "Tidybot" included input from Princeton, Stanford, and Columbia University engineers, along with help from Google and the Nueva School.

One of the engineers posted about the technology as early as May 2023 as well.

While it is unclear whether either technology derived from the other, it was only two months later that the Tesla Optimus revealed it was capable of sorting objects on its own.

"Optimus can now sort objects autonomously," the company wrote on X. "Its neural network is trained fully end-to-end: video in, controls out."

Optimus can now sort objects autonomously \xf0\x9f\xa4\x96 \n\nIts neural network is trained fully end-to-end: video in, controls out.\n\nCome join to help develop Optimus (& improve its yoga routine \xf0\x9f\xa7\x98) \n\n\xe2\x86\x92 https://t.co/dBhQqg1qya
— (@)

By the second week of 2024, Musk unveiled a video of the same robot carefully removing a T-shirt from a laundry basket before gently folding it on a table.

"Optimus folds a shirt," Musk wrote.

The robot is seen carefully arranging the shirt on the table before starting its task while almost seeming to possess too much strength for the intricate feat.

— (@)

When the Tidybot was released, engineers revealed how their robot was able to properly organize household items.

The robot worked by having users input (in text) a small number of sample preferences that instructed the robot as to where items should be placed. For example, "yellow shirts go in the drawer, dark purple shirts go in the closet," the product's abstract described.

This allowed the robot to summarize "large language models" and generalize information to apply to other items it may come across. Therefore, it could generally summarize that "light-colored clothes go in the drawer and dark-colored clothes go in the closet."

The robot could identify objects and receptacles through a database of images it had, meaning it recognized what a shirt or a recycling bin looked like. "The robot will then carry out the cleanup task by repeatedly picking up objects, identifying them, and moving them to their target receptacles," the document stated.

The engineering team said that their approach achieved a 91.2% accuracy rating on unseen objects in their scenarios. In real-world applications, the robot reportedly correctly put away 85% of objects.


When organizing a home, everyone has unique preferences for where things go. How can household robots learn your preferences from just a few examples?\n\nIntroducing \xf0\x9d\x97\xa7\xf0\x9d\x97\xb6\xf0\x9d\x97\xb1\xf0\x9d\x98\x86\xf0\x9d\x97\x95\xf0\x9d\x97\xbc\xf0\x9d\x98\x81: Personalized Robot Assistance with Large Language Models\n\nProject page: https://t.co/LbVGq01QMT
— (@)

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Kuwait inaugurates era of realistic AI-generated news presenters in Arabia with debut of 'Fedha'



A Kuwaiti news outfit debuted the newest member of its team over the weekend. Unlike others at the station, this talking head, named "Fedha," is neither a dues-paying member of a union nor deserving of a parking spot. In fact, Fedha is not even a human being.

Kuwait News, an affiliate of the Kuwait Times, posted a video to Twitter Saturday depicting a modestly dressed white woman with blonde hair that introduced itself as "Fedha ... the first presenter in Kuwait who works with artificial intelligence."

The humanistic simulacrum then said in Arabic, "What kind of news do you prefer? Let's hear your opinions."

Abdullah Boftain, deputy editor in chief for Kuwait News, told AFP that Fedha is a test of AI's potential to both offer "new and innovative content" and present news bulletins to the outlet's 1.2 million Twitter followers in an appropriate Kuwaiti accent.

\u201c\u0623\u0648\u0644 \u0645\u0630\u064a\u0639\u0629 \u0641\u064a #\u0627\u0644\u0643\u0648\u064a\u062a \u062a\u0639\u0645\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\n\n\u2022 #\u0641\u0636\u0629.. \u0645\u0630\u064a\u0639\u0629 #\u0643\u0648\u064a\u062a_\u0646\u064a\u0648\u0632 \u0627\u0644\u0627\u0641\u062a\u0631\u0627\u0636\u064a\u0629\n\n\u2022 \u0645\u0627 \u0647\u064a \u0646\u0648\u0639\u064a\u0629 \u0627\u0644\u0623\u062e\u0628\u0627\u0631 \u0627\u0644\u062a\u064a \u062a\u0641\u0636\u0644\u0648\u0646\u0647\u0627 \u0628\u062a\u0642\u062f\u064a\u0645 #\u0641\u0636\u0629 \u0632\u0645\u064a\u0644\u062a\u0646\u0627 \u0627\u0644\u062c\u062f\u064a\u062f\u0629\u061f .. \u0634\u0627\u0631\u0643\u0648\u0646\u0627 \u0622\u0631\u0627\u0621\u0643\u0645\u201d
— \u0643\u0648\u064a\u062a \u0646\u064a\u0648\u0632 (@\u0643\u0648\u064a\u062a \u0646\u064a\u0648\u0632) 1680984130

"Fedha is a popular, old Kuwaiti name that refers to silver, the metal. We always imagine robots to be silver and metallic in colour, so we combined the two," explained Boftain.

Boftain suggested that Fedha's appearance was intended to reflect the Near Eastern nation's "diverse" population of natives and expatriates, stressing, "Fedha represents everyone."

Fedha also represents an opportunity to help realize Goldman Sachs' prediction that AI will soon replace around 300 million jobs.

A recent report by investment bank Goldman Sachs indicated that a quarter of work tasks in the U.S. and Europe could be replaced by AI, in part because generative AI is now capable of generating new content "that is indistinguishable from human-created output."

This great replacement will impact various sectors, but not all equally. For instance, 46% of tasks in administrative and 44% in legal professions could reportedly be automated, but only 6% in construction can be taken over by AI.

Carl Benedikt Frey, future of work director at the Oxford Martin School, Oxford University, told British state media, "The only thing I am sure of is that there is no way of knowing how many jobs will be replaced by generative AI."

"What ChatGPT does, for example, is allow more people with average writing skills to produce essays and articles," said Frey. "Journalists will therefore face more competition, which would drive down wages, unless we see a very significant increase in the demand for such work."

The Goldman Sachs report indicated that 26% of the arts, design, entertainment, sports, and media industry could possibly be automated by AI.

At Kuwait News, for instance, an AI-generated simulation scripted by ChatGPT could potentially serve as a full0time replacement for a flesh-and-bone script-reader.

The New York Post noted that Fedha, while possibly among the more lifelike, is not the first AI-generated news presenter.

Chinese state news agency Xinhua News revealed a virtual newsreader called Qiu Hao in 2018, dressed in a suit and tie. The humanistic simulacrum said, "I will work tirelessly to keep you informed as texts will be typed into my system uninterrupted."

Xinhua's first English AI anchor makes debut youtu.be

Months later, Xinhua introduced what it claimed was the world's first female AI news anchor, known as Xin Xiaomeng.

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In ‘Human Forever,’ James Poulos Declares War On The Digital Age

James Poulos' book, 'Human Forever: The Digital Politics of Spiritual War,' warns that we are already becoming cyborgs and we will pay for our digital dependence with our souls.