Luddites, Looms, and Large Language Models:
What 500 Years of Automation Panic Can Teach Us
If you have picked up a newspaper, watched CNBC for more than eleven minutes, or made the mistake of scrolling through a business feed before coffee, you have probably noticed the current theme: the machines are coming for our jobs. Not some jobs. Not repetitive jobs. Apparently all jobs. Software engineers, attorneys, analysts, writers, consultants, portfolio managers, college professors, customer service reps, and presumably the guy who writes inspirational LinkedIn posts about “leaning into uncertainty” are all about to be replaced by Generative AI.
That may happen in pockets. Some jobs will change. Some jobs will disappear. Some jobs probably should disappear, particularly if the job mostly involves forwarding spreadsheets and scheduling meetings about other meetings. But the larger panic—the idea that AI is about to make human labor broadly obsolete—sounds much less like serious economic analysis and much more like a very old human habit: we discover a tool that makes life easier, and then immediately assume it will destroy civilization.
Long before Silicon Valley discovered hoodies and stock options, the original tech disruption happened in Mainz, Germany. In the 1450s, Johann Gutenberg introduced movable type to Europe, and the world of hand-copied manuscripts was never the same. For centuries, the copying of books had been the province of monks, scribes, and a small educated class that controlled the flow of written knowledge. Then along came the printing press, and suddenly the economics of information changed. Books could be reproduced faster, cheaper, and at scale.
Naturally, the people who had built their lives around the old system were not thrilled. One of the great critics of the printing press was Johannes Trithemius, a German abbot who wrote In Praise of Scribes in the late 15th century. He argued that copying books by hand was spiritually and intellectually superior to printing them. Printed books, in his view, were cheap, vulgar, and less reliable. Hand-copying, by contrast, built discipline and character. It was a beautiful argument for preserving the old craft. The problem, of course, was that the world had already moved on. The printing press did not destroy knowledge. It multiplied it. The scribes lost their monopoly, but the broader economy gained publishing, mass education, scientific exchange, journalism, libraries, and the entire modern information economy. That is not a bad trade, unless your business model depends on being the only person in town with a quill.
A few centuries later, the panic moved from books to textiles. The Luddites, who today are usually invoked whenever someone refuses to update their iPhone, were not just grumpy technophobes. They were skilled weavers and textile workers in early 19th-century England who saw machinery threatening their livelihoods, their bargaining power, and their status. They were worried about “deskilling,” though they probably did not say it in a McKinsey deck. Factory owners could use machines and less-skilled labor to produce cloth more cheaply, and the old artisanal model was under siege. So they smashed the machines. Under the mythical banner of “General Ned Ludd,” they destroyed wide-frame knitting machines and looms, trying to stop the industrial tide with sledgehammers. It did not work. It never works.
The machines won, as machines usually do when they are cheaper, faster, and more scalable. But the story did not end with mass unemployment and a permanently broken labor force. Textiles became dramatically cheaper. Clothing became more affordable. Production expanded. Trade expanded. Banking, shipping, insurance, and manufacturing infrastructure expanded with it. The textile industry became one of the great engines of the Industrial Revolution.
Even the economists worried about this. In 1821, David Ricardo, one of the foundational thinkers in classical economics, added a chapter called “On Machinery” to his work. Ricardo understood that machinery could, at least in the short run, hurt laborers by substituting capital for human work. He was not wrong. Technological disruption is not painless. There are always people caught on the wrong side of the transition, and pretending otherwise is both historically ignorant and morally lazy. But Ricardo, like many after him, underestimated the compounding nature of productivity. When companies produce more with less, the savings do not simply vanish. They show up in lower prices, higher margins, new investment, new products, higher consumption, and entirely new industries. Efficiency is not just a cost-cutting story. It is a capital redeployment story. The first-order effect may be fewer workers doing one specific thing. The longer-term effect is often more economic activity in areas that did not previously exist.
The Second Industrial Revolution brought the assembly line and electric power, but fueled anxiety that "Taylorism" (as outlined in Frederick Winslow Taylor’s 1911 work The Principles of Scientific Management) would turn human workers into machines via stopwatch-timed, high-efficiency labor. This era feared that extreme specialization and the reduction of human movement to mechanical efficiency would lead to total replaceability and plummeting wages. This dread was perfectly captured in Karel Čapek’s 1920 play R.U.R., which coined the term "robot" to depict forced, biological laborers built only for output, reflecting a deep societal concern that systems would replace human utility.
Flappers, Factories, and the Original "Vibe Shift"
Ironically, the period that has been compared to the present the most, the 1900s–1930s, had the least “tech revolt.” While there was plenty of worry about the assembly line, automation, and the like, this era marked a phenomenon of Massive Industrial Absorption. The economic boom from these very “new” technologies was so immense that it created an avalanche of entirely new industries and professions—such as automotive mechanics, corporate managers, and radio engineers—resulting in far more job opportunities than jobs lost. By the 1930s, however, that love affair had ended as economic forces outside of technology’s control withered under an avalanche of bad debt and bank closures. Once again, technology became the convenient scapegoat for the country’s ills, triggering the Great Depression's "Technocracy" panic. This sudden shift from optimism to dread was documented across the era, beginning with the cultural anxiety of Karel Čapek’s 1920 play R.U.R., moving to John Maynard Keynes officially coining the term "technological unemployment" in 1930, and culminating in Howard Scott’s 1932 Technocracy manifesto. Ultimately, this wave of panic became so severe it prompted a 1933 sociological study by The Federal Council of Churches to address the widespread public terror that machines had permanently rendered human wages obsolete.
By the mid-20th century, the panic had a new name: automation. Mainframe computers, assembly-line robotics, and early cybernetics produced another wave of anxiety. In 1961, Time wrote about “automation anxiety” and the fear that electronic brains were going to throw huge numbers of people out of work. In 1964, a group of prominent scientists, economists, and public intellectuals sent President Lyndon Johnson what became known as “The Triple Revolution” memorandum, warning that cybernation could permanently separate productivity from employment and create a large class of people the economy no longer needed. It was not a ridiculous concern. Computers really did change work. Factories changed. Offices changed. Entire clerical functions were reduced or eliminated. But the jobless society never arrived. Instead, the decades that followed produced enormous economic expansion, rising productivity, new corporate giants, new professions, and a workforce that kept adapting in ways the forecasters could not map in advance. As before, the mistake was assuming that the economy was a fixed pie and that if machines took a bigger slice, humans must be left with crumbs.
The same fear returned in the 1980s and 1990s, this time in the white-collar world. Personal computers arrived in offices, software replaced layers of clerical work, and the corporate cubicle began its long transformation into whatever we are calling work now. Economist Wassily Leontief famously compared workers to horses, arguing that tractors had made horses economically obsolete in agriculture and that computers might eventually do the same to human labor. Jeremy Rifkin’s The End of Work later predicted a future in which technology would drive permanent unemployment and a jobless economy.
Again, the concern was understandable. And again, the outcome was more complicated. Typing pools disappeared. File rooms shrank. Travel agents, switchboard operators, bank tellers, and many administrative roles were reduced or transformed. But the modern org chart is not empty. It is full of jobs that would have sounded absurd to an executive in 1980: software engineers, cloud architects, cybersecurity analysts, digital marketers, UX designers, data scientists, compliance specialists, product managers, e-commerce strategists, and about twelve different people whose job is to explain why the new CRM implementation is behind schedule.
In the 1800s, labor moved from raw muscle toward machine operation and industrial coordination. In the 1900s, it moved from routine calculation and clerical processing toward management, analysis, sales, service, and strategy. In the 2020s, AI will likely absorb a great deal of rote data work, basic drafting, spreadsheet production, generic research, and repetitive customer interaction. That is not nothing. It will be disruptive. But the more valuable work will migrate toward judgment, synthesis, creativity, trust, empathy, relationships, and strategic decision-making. In other words, toward the parts of work that are harder to automate because they involve context, ambiguity, accountability, and human confidence.
The real power of technology is often not just in the invention. It is in the adoption. The printing press mattered, but so did publishers. The loom mattered, but so did textile manufacturers, shippers, merchants, banks, and retailers. The computer mattered, but so did every company that figured out how to use software to do more with less. AI will likely follow the same path. Some companies will build the tools. Others will quietly use the tools to become more profitable.
The future is not scary simply because it is unfamiliar. The scribes were wrong. The Luddites lost. The automation panic of the 1960s did not end with a permanently jobless society. The office computer did not make human beings the new horse. Technology does not simply remove one task and leave a hole in the economy. It lowers costs, increases output, expands markets, and creates second- and third-order effects that are hard to see at the beginning. The people watching the loom arrive could see the weaver being displaced. They could not easily see the global textile trade, the rise of industrial cities, the growth of consumer markets, or the capital formation that followed.
To me the lessons seem clear, every generation thinks its technology shock is uniquely dangerous because every generation can see what is being disrupted more clearly than what is being created. And, when the economy is healthy, technology absorbs and elevates human labor rather than destroying it.
As always, if you would like to talk about how this may affect your portfolio, or how we are thinking about AI, automation, productivity, and the companies likely to benefit from this next wave, please give us a call. Your capital, our experience, a bespoke creation.