Long before ChatGPT or Siri, a woman sat at the centre of the information world, connecting nearly every long-distance call made across America.
She was the telephone switch operator, once the single largest occupation for white, US-born women under the age of 20, and today that job no longer exists.
As artificial intelligence spreads rapidly through the global economy, researchers and economists warn that women are likely to bear a disproportionate share of the employment disruption ahead.
“AI is focused on routine tasks and numbers and finding patterns, and those types of jobs are the clerical, administrative jobs that a lot of women hold,” said Ariane Hegewisch, a senior research fellow at the Institute for Women’s Policy Research.
Hegewisch added that “it’s still 90% of secretaries and clerical workers who are women,” underscoring just how concentrated the risk remains within female-dominated occupations.
The International Labour Organization concluded in research published earlier this year that nearly one in ten women in high-income countries work in occupations facing the highest risk from AI.
The story of the telephone operator offers one of history’s most instructive parallels to the disruption now unfolding across offices and industries worldwide.
In the 1940s, nearly 95% of America’s telephone operators were female, holding relatively well-paying roles that required months of training to master the demands of peak-hour call volumes.
When AT&T introduced the automated telephone switch, an investment considered one of the largest automation projects in history, an estimated 75,000 operator jobs vanished over the following decades.
Economists James Feigenbaum at Boston University and Daniel P. Gross at Duke University’s Fuqua School of Business studied census and payroll data from that period and found that “the effect of this shock on incumbent operators was to dispossess many of their jobs and careers.”
Many switchboard operators ended up in lower-paying roles or dropped out of the workforce entirely, a pattern that economist David Autor says reflects a wider truth about how workers respond to technological disruption.
“Most people are not changing careers very often,” Autor said. “They make their career decisions early, and they stick with those careers.”
Autor added that when the value of that work “suddenly goes out of fashion, becomes technologically obsolete, they’re going to, in general, do something not as good.”
However, Feigenbaum and Gross also found reason for cautious optimism, noting that “future workers found work in other fields, often taking up similar-quality jobs,” with younger workers proving “more adaptive to an evolving labour market.”
Their research concluded that “anxiety over the opportunities available to future generations proved to be somewhat misplaced,” suggesting that displacement at one moment in history does not foreclose opportunity permanently.
A similar dynamic played out in the 1950s, when washing machines, dubbed “engines of liberation” in a seminal paper by University of Pennsylvania economist Jeremy Greenwood and others, freed millions of women from unpaid domestic labour.
Between 1950 and 1980, the number of employed women in the United States grew by more than 25 million, with the female labour force participation rate rising to 52% from 34%, as new economic opportunities opened across the service sector.
The arrival of the personal computer in the 1980s brought another wave of disruption, with more than 4.7 million Americans recorded as secretaries, stenographers and typists in the 1980 census, of whom over 98% were women.
When IBM introduced the personal computer in 1981, followed by Microsoft Word just two years later, many clerical roles were restructured or eliminated as executives gained the ability to handle tasks once delegated to support staff.
A 2022 paper by Marcus Dillender and Eliza Forsythe found that when companies adopted software for office and administrative work, it resulted in a 1% decline in employment in the sector but a 3% increase in wages for college graduates.
Today, more women than ever hold college and advanced degrees and managerial positions, offering some potential insulation from automation, though Hegewisch strikes a note of warning, observing that “AI can learn.”