Beware of "AI Replacing Humans" Joining Forces with "Economic Downturn" to Cause Trouble

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(Source: Titanium Media APP)

“People have a fateful fear of the recurrence of depression.”

The robot show at the Spring Festival Gala sparked elderly expectations for robotic elder care, while also stimulating middle-aged and young groups’ anxiety about falling into the “Uncanny Valley.” On one hand, people watch awkward humanoid robots walk, saying “Baby, keep going, Mom will add to your position,” and on the other hand, under FOMO, they rush to raise “lobsters.” AI has allowed “one-person businesses” to repackage old ideas with new technology, creating the allure of earning millions annually, but also plunging the entire industry into unemployment anxiety…

Long-standing Panic

Human anxiety and panic over being replaced by machines have existed for a long time, especially during several industrial revolutions.

Unemployment will never disappear.

Nobel laureate Robert Shiller tells us that narratives influence people’s economic behavior.

At the last Winter Olympics, gold medalist Xu Mengtao praised the power of belief. This is a self-fulfilling prophecy. In economics, some popular narratives are enough to form a “power of belief,” which, like a prophecy, can produce pessimistic economic effects during certain historical periods.

Economic downturns were once believed to be the result of machine replacement of humans.

Quoting Einstein, “In my opinion, there is no doubt that severe economic depression is largely due to internal economic reasons; production equipment improves through technological inventions and systematization, which reduces demand for human labor, excludes some labor from the economic cycle, and gradually decreases consumers’ purchasing power.”

Insufficient consumption is indeed a byproduct of unemployment. However, once the narrative that “machines will replace humans” is widely promoted, even those not yet unemployed will reduce consumption and investment out of fear—buying homes, for example.

This collective reduction in consumption further shrinks total demand, artificially prolonging and deepening the depression. A vicious cycle then forms among insufficient consumption, overproduction, and unemployment.

Around 1955, the term “automation” suddenly became popular, with new narratives focusing on the complete replacement of humans in production. Robert Shiller pointed out that the recessions of 1957–1958 and 1960–1961 may have been caused by public fears of automation leading to reduced spending.

“History doesn’t repeat itself, but it rhymes.”

Whenever a technology that liberates productivity is born, the story of “machines replacing humans” is reborn with new vitality and contagiousness. After all, basic human drives like fear, greed, and the pursuit of security have hardly changed over thousands of years.

The concept of “artificial intelligence” has existed for a long time. Before the end of World War II and the dawn of the 21st century, related narratives peaked twice. Each phase hinted at a major turning point where “machines take over everything.”

This time, anxiety shifts from physical to mental replacement.

Recently, economist Heather Long pointed out that the U.S. is shifting from the well-known “K-shaped economy” since 2020 to an “E-shaped economy.”

The key to this shift lies in the changing polarization of the middle-income group.

During the K-shaped economy, the main drivers of upward differentiation are knowledge workers. The essence of K-shaped divergence is a trajectory of polarization caused by shocks from technology, finance, or external factors. Almost all disruptive technologies, in their early stages, tend to create significant inequality.

But in the wave of AI, this dynamic K-shaped divergence is quickly converging and solidifying into a static E-shaped polarization. As many narratives suggest, the revolution of AI replacing humans is happening, targeting precisely the knowledge-based income of the middle class.

People across industries seem to be seeking certainty—who will be replaced, and who can ride this wave to success?

Thus, under the prophecy that “the fragile middle class will eventually collapse,” the middle-income group, which might have moved upward or downward, shifts to a defensive stance, holding on in the middle.

Their notable consumption behavior is frantic search for value and substitutes, practicing restrained, tense consumption—shopping at discount stores, desperately maintaining credit, and trying to avoid falling downward.

Robert Shiller asserts that narratives about machine learning make us increasingly afraid of becoming irrelevant and worry about becoming a useless class. If such fears spread widely, they will undoubtedly affect economic confidence and, in turn, the economy.

It’s worth noting that the narrative of “machines replacing humans” has historically taken on different meanings through mutations.

The internet boom of the 1990s turned fears of automation into a narrative of business opportunity. The mainstream narrative then focused on the opportunities brought by new inventions in the information age, fueling the expansion of internet stocks.

However, this also serves as a warning. Today’s narratives fuel a craze for AI, driven by fear of missing out on the technological revolution, leading to excessive capital inflow into a few tech giants—classic bubble formation.

“Downward” Amplifies Anxiety

Even during economic upswings, fears of unemployment due to machine replacement run rampant. When “machines replace humans” meets “economic downturn,” this panic and anxiety are magnified infinitely.

After the U.S. Civil War in 1865, the country entered a rapid development phase of capitalism, rising from a backward agricultural nation to the world’s leading industrial power within 25 years. The East experienced a modernization boom with roaring machinery, urbanization, corporate growth, and monopolization. The West, with westward expansion and railroads, transformed from wilderness into industrial farms and large cities.

Until 1873–1879, the U.S. faced a severe depression.

At that time, the widespread belief was that “high unemployment was partly due to labor-saving inventions.”

Labor-saving machines were increasingly used in agriculture, and workers, worried about job prospects, began destroying machinery.

At the 1876 World’s Fair, modern industrial inventions from 20 countries amazed visitors, but simultaneously, these large-scale agricultural machines sounded an alarm for employment. As the Philadelphia Inquirer reported, “Today, one person’s work is equivalent to that of 50 years ago, 100 people.”

The 1890s saw another major depression in the U.S. The Los Angeles Times in 1894 stated, “The introduction of labor-saving machines and the resulting increase in output are closely related to the current business depression… Indeed, in recent years, countless labor-saving inventions have been introduced and used, and society has almost been unable to keep pace with their development.”

Recently, Ray Dalio’s article “2026 Looks Like 1936” became a hit, resembling a possible historical parallel.

In 1936, during the global depression of the 1930s.

This period is associated with the concept of “technological unemployment,” describing the impact of labor-saving inventions. The term first appeared in 1917, gained popularity in 1928, and surged during the Great Depression, peaking in 1933. The emergence of this term revived the old narrative of labor-saving machines.

Notably, in 1928, during the pre-Depression boom, unemployment was 7.4%, and fears of “technological unemployment” ran high.

Economist Sumner H. Slichter pointed out that the most serious cause of unemployment was technological unemployment, as labor-saving measures eliminated jobs faster than new ones were created.

During this period, economist and social theorist Stuart Chase introduced the concept of “Madhouse Economy,” which included four major wastes: human waste, ineffective production, distribution waste, and resource destruction. Human waste referred to the large number of workers unemployed or semi-unemployed even during economic prosperity.

Chase emphasized that humanity had entered the machine age, where technology could drastically shorten working hours. Yet, the old economic system could not adapt, and technological progress should have brought widespread leisure, but in the “Madhouse Economy,” it turned into “technological unemployment,” forcing some to overwork and others to lose jobs altogether, instead of rationally redistributing work.

Before the stock market crash showed any signs, the narrative that unemployment was out of control had already gone viral.

In 1930, the U.S. entered a decade-long Great Depression. During this period, unemployment remained above 8%, reaching an estimated 25% in 1933. An article in the Los Angeles Times in early 1931 stated that labor-saving inventions (robots) in the U.S. were equivalent to 80 million workers, while the male labor force was only 40 million.

The idea that robots took jobs became a primary explanation for the Great Depression and was viewed as a main cause.

Moreover, a prevalent belief then was that “the world would belong to technicians who designed and operated machines.” This caused fear among those who saw themselves as incapable of becoming scientists—most people—and led to reluctance to spend, invest, or hire, which worsened and prolonged the depression.

After this global depression, World War II broke out.

“Downward” Greater Trap

In recent years, the topic of “economic downturn” has been frequently discussed. Related are the ways ordinary people seek to break through and survive. Opposing this is the nostalgia for economic vitality and growth.

Whether “depression,” “recession,” or “downturn,” these narratives themselves significantly influence economic events.

Robert Shiller warns that beyond GDP, interest rates, inflation, and data like gold discoveries, crop failures, and stock market events, we should also consider narratives when analyzing depressions and recessions.

He points out that these narratives “may have contributed to or worsened depressions and recessions. We cannot definitively prove causality because these events are complex and involve multiple narratives. However, during the brewing and fermenting of these severe economic events, the cumulative impact of narratives is far from a simple indirect influence.”

Another prevalent narrative accompanying “economic downturn” is related to the story of “Japan’s Lost Three Decades.”

The reason is that major economic events often evolve into grand narratives, becoming scripts for future economic crises.

Undeniably, when facing challenges, people instinctively look for historical references. “Japanification” then becomes a powerful, transmissible historical narrative.

“Japan’s Lost Three Decades” is like a ready-made script, often used by media to interpret current complex realities. Once this script is widely accepted, more and more people unconsciously project current policies and market fluctuations into it, even comparing the prosperity of live broadcasts and concerts.

Shiller explicitly states, “Japan is just an example, a single phenomenon, so it’s not statistically significant, but its global influence is strong enough to reignite the narrative of the Great Depression and trigger serious concerns about long-term economic stagnation.”

The core of the “Japan’s Lost Three Decades” narrative is asset devaluation and debt minimization. Once companies and households believe in this narrative, they shift their financial goals from profit maximization to debt minimization. Even with ample liquidity from central banks, people are reluctant to borrow.

This extreme risk aversion is a psychological root of long-term economic stagnation. The most tricky part is that once this grand narrative takes root in collective memory, reversing it with conventional monetary or fiscal policies becomes extremely difficult, as people have developed immunity and skepticism toward policy stimuli.

It reminds me of the lines from the Book of Songs, “How dare I love it, fearing the many words of others. Zhong can be trusted, but the many words of people are also to be feared.”