Women stand at the center of a growing concern about artificial intelligence and employment, with historical patterns suggesting they face disproportionate risk from automation’s latest wave.
From automated telephone switches to washing machines to personal computers, American women have repeatedly seen their professional prospects reshaped by technological change in profound ways.
“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 how concentrated female employment remains in the occupations most vulnerable to automation.
The International Labour Organization concluded in March that nearly one in ten women in high-income countries works in occupations facing the highest risk from AI disruption.
The telephone switch operator stands as perhaps the most instructive historical example, once representing the single largest occupation for white, U.S.-born women under age 20.
In the 1940s, nearly 95% of America’s telephone operators were female, holding relatively well-paying jobs that required months of training to master the demands of hundreds of calls per hour.
When AT&T introduced the automated telephone switch, one of the largest automation investments in history, an estimated 75,000 operator jobs ultimately disappeared across the following decades.
Economists James Feigenbaum from Boston University and Daniel P. Gross from Duke University’s Fuqua School of Business studied census and paycheck data from the period, tracking local employment trends along AT&T’s investment rollout.
“The effect of this shock on incumbent operators was to dispossess many of their jobs and careers,” they wrote in 2020, finding many switchboard operators wound up in lower-paying roles or left the workforce entirely.
Economist David Autor explained the underlying dynamic clearly, noting that “most people are not changing careers very often” and that when a career becomes “technologically obsolete, they’re going to, in general, do something not as good.”
However, Feigenbaum and Gross also found that younger workers recovered better, writing that “future workers found work in other fields, often taking up similar-quality jobs” and that “anxiety over the opportunities available to future generations proved to be somewhat misplaced.”
The washing machine offered a different kind of technological disruption, with University of Pennsylvania economist Jeremy Greenwood and co-authors famously dubbing household appliances “engines of liberation” in a seminal paper on the subject.
By dramatically reducing time spent on unpaid housework, these appliances freed women to enter the paid labor force, with the number of employed women in the U.S. growing by more than 25 million between 1950 and 1980.
The female labor force participation rate climbed from 34% to 52% during that same period, a historic transformation driven partly by technology and partly by the booming postwar American economy.
“Between 1940 and 1980, there was a ton of new work created in the U.S. economy, and it was in office and clerical work that was accessible to people with a high school education,” Autor said.
The personal computer, introduced by IBM in 1981, posed yet another challenge, with nearly 4.7 million Americans working as secretaries, stenographers, and typists in 1980, more than 98% of them women.
Microsoft Word’s arrival just two years later shifted many clerical tasks directly to executives, yet women who adapted to the new tools often made themselves indispensable by mastering spreadsheets, databases, and computing platforms.
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 hold college degrees and managerial positions than during any previous wave of automation, offering some buffer, though Hegewisch warns the threat remains dynamic because, as she puts it, “AI can learn.”
