During the 1970s and 1980s, a major shift occurred in the industrial sector as computer-driven automation began replacing human labor in manufacturing. Computerized machine tools took over roles previously held by assemblers, machinists, and lathe operators, driven by global competition that pressured companies to modernize or risk obsolescence. This transformation led to a structural change in the workforce, moving from manual production jobs toward roles centered on knowledge and technical expertise. Researchers from Case Western, Princeton, and Brandeis Universities suggest that today’s rise of artificial intelligence mirrors this earlier transition, though important differences exist.
According to economist David Clingingsmith of Case Western and his team, today’s knowledge workers may face greater challenges adapting than their industrial counterparts did decades ago. Back then, strong union representation, concentrated job displacement, and accessible retraining pathways helped workers transition. Modern factories now operate with minimal staff, relying on computer numerical control (CNC) systems, automated conveyors, and robotics. Yet, employment did not vanish—instead, it evolved. Demand shifted toward college-educated professionals capable of programming and managing advanced machinery.
Industries exposed to CNC technology saw productivity rise without significant drops in overall employment. The labor market adjusted by favoring higher-skilled individuals, placing CNC-driven automation between the transformative effects of early 20th-century electrification and the more modest impacts of recent industrial robotics.
The study suggests that while today’s AI revolution presents unique hurdles, the past offers valuable insights. Supporting workers through education, reskilling initiatives, and employer-led development programs could help ensure that technological advancement benefits a broad segment of the workforce over time.
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The Economic Shock Of AI; Have We Been Here Before?
There was a time when large-scale computer-driven automation usurped a large array of jobs in the economy. The time was the 1970s into 1980s, when computerized machine tools swept in and took over the jobs of assemblers, parts makers, machinists, lathe operators, and more in industrial settings. This wave of automation was driven by intense global competition that threatened to put many slower-moving manufacturers out of business.
In the process, the economy shifted from manufacturing work to knowledge work. Is there a parallel to the current time, with artificial intelligence threatening the jobs of knowledge workers? A team of researchers from Case Western, Princeton, and Brandeis Universities say there are analogies to the automation wave of the 1980s, but they only go so far.
In this just-published study, economist David Clingingsmith, professor at Case Western University and his colleagues argue that workers might not be able to absorb the shocks of the current AI wave as readily as industrial workers in the 1980s, as they had strong unions, concentrated impacts, and clear retraining paths.
Look at today’s factory floor compared with those four decades ago, the co-authors point out. “The modern factory floor is filled with machines and empty of people.
Computerized machine tools produce complex parts based on instructions encoded in computer programs, conveyors move parts from station to station, and robots assemble the parts into finished products.”
Manufacturing jobs didn’t quite disappear, but rather, they evolved – upward. Rather than rows of low-skilled assembly-line workers, today’s industrial floors are staffed by engineers, developers, and product experts. “Jobs in the factory increasingly require a sophisticated understanding of the programming of machines and often a college degree.” Workers received some union protection to stall an initial shock, but also gravitated en masse toward re-training and educational programs.
Previously, they point out. “machine tools required a semi-skilled machinist to perform operations to specification by hand,” they relate. “Automated machine tools began to
diffuse widely in the 1970s. New computer numerical control (CNC) tools replaced these routine operations with detailed computer programs overseen by skilled workers.”
Along with a more competitive stance in the global economy, the results, at least back then, were positive. “Metal manufacturing industries that were more exposed to CNC tools experienced rising labor productivity with little decline in total employment at either the industry or local labor market level,” the co-authors pointed out. “Labor demand shifted from low- and mid-skill workers toward college graduates.”
This combination of productivity gains, displacement from core tasks, and limited overall dis-employment “place CNC between the large automation gains in the early 20th century though factory electrification and the more minimal gains associated with
industrial robots today.”
In other words, the rise of factory automation in the 1980s can be seen as a long-term success story that’s worth emulating in today’s AI environment, with an emphasis on employers providing training and education, and providing knowledge workers the opportunity to grow their skills sets. While circumstances have changed, the lesson is that moving forward with advanced technologies can be the tide that lifts all boats over the long run.