Robots Are Coming For (Men’s) Jobs

Robots are coming for human jobs. It’s no surprise. However, the automation revolution is much more than just an economic problem, argues Laurie Penny in Wired.

“It is a cultural problem, an identity problem, and—critically—a gender problem,” she writes.

Which Jobs Are at Risk

The robots are mostly eliminating jobs in farm and factory labor, construction and haulage—in other words, blue-collar jobs typically performed by men.

Penny backs that up with numbers. She points to an Oxford study that predicted 70 percent of US construction jobs will disappear in the coming decades, and notes that 97 percent of those jobs are held by men. Men also hold 95 percent of the 3.5 million transport and trucking jobs that, in her words, “robots are presently eyeing.”

She also argues that automation is a bigger threat to this kind of work than the things politicians often blame. “Some political rhetoric blames outsourcing and immigration for the decline in ‘men’s work,’ but automation is a greater threat to these kinds of jobs—and technological progress cannot be stopped at any border,” Penny writes.

Why It’s an Identity Problem

“Millions of men around the world are staring into the lacquered teeth of obsolescence, terrified of losing not only their security but also their source of meaning and dignity in a world that tells them that if they’re not rich, they’d better be doing something quintessentially manly for money. Otherwise they’re about as much use as a wooden coach-and-four on the freeway.”

Penny’s point is that the loss isn’t only a paycheck. For many men, the job is tied up with how they see themselves, so losing it hits pride and purpose as well as income. That’s why she sees the response as a question about what it means to be a man, not just a question about retraining.

She argues that many men “have been trained over countless generations to associate their self-worth with the performance of tasks that are, in a very real sense, robotic—predictable, repetitive, and emotionless.” The trouble, she writes, is that machines are far better at that kind of work than people are.

The Pink-Collar Alternative

Men must change their mindset and be willing to take on jobs in the so-called “pink-collar” industry, she says.

Pink-collar work is the label for jobs that have traditionally been done mostly by women, such as childcare, service work and nursing. In Penny’s view, those jobs are relatively safe from automation, and some are growing. She cites a US Bureau of Labor Statistics prediction that nursing would need more than a million more workers in the following decade.

So why aren’t laid-off factory workers retraining as nurses and nannies? Penny’s answer is status. “Women’s work is low paid and low status, and men are conditioned to expect better,” she writes. The barrier isn’t the technology, she argues, but social attitudes, “and those can’t be updated with the tap of a touchscreen.”

Her more hopeful case is that the shift could push society to value care work properly. If more men take these jobs and join the call for better wages, she argues, pink-collar and unpaid work could be paid more fairly, and more women could stay and thrive in fast-growing fields like STEM.

What’s Changed Since 2017

When Penny wrote her piece, the automation story was mostly about physical machines: factory robots, self-driving trucks and bricklaying droids. Since then, a different kind of automation has arrived, and it complicates the picture.

Generative AI tools like ChatGPT handle language and paperwork, not heavy lifting. In August 2023, the International Labour Organization published a global study, Generative AI and Jobs, which found that clerical work had the greatest exposure to the technology. The ILO found that more than twice the share of female employment was potentially affected by automation compared with male employment, because women are over-represented in clerical jobs, especially in high and middle-income countries.

The same study found that most jobs are only partly exposed, and that generative AI is more likely to change jobs than wipe them out. Its authors said the biggest effect was likely to be on the quality of work, such as how intense it is and how much independence workers have.

That doesn’t undo Penny’s argument about blue-collar work, but it shows the gender story of automation depends on which technology you’re talking about. Robots aimed at warehouses and trucks mostly threaten jobs held by men. Software aimed at offices may hit jobs held by women harder.

The Takeaway

Penny’s central idea still holds up: how people react to automation depends a lot on how tightly their sense of worth is tied to a particular kind of job. For workers, that’s an argument for building skills that machines find hard, like caring for people, adapting to new situations and working closely with others.

For employers and policymakers, it’s a reminder that retraining programs can’t just teach new skills. They also have to deal with how people feel about the work on offer, and whether that work pays enough to be worth doing.