As AI and machine learning transform industries by automating much of the work currently done by humans, women’s careers will be disproportionately affected. That’s according to a McKinsey Global Institute report published earlier this year (“The future of women at work: Transitions in the age of automation“), which found that women predominate in occupations that’ll be adversely impacted. About 40% of jobs where men make up the majority in the 10 economies (Canada, France, Germany, Japan, the U.K., the U.S., China, India, Mexico, and South America) contributing over 60% of GDP collectively could be displaced by automation in our 2030, compared with the 52% of women-dominated jobs with high automation potential.

Mekala Krishnan, a senior fellow at McKinsey’s Boston-based business and economics research arm and a member of the board of the Global Fund for Women, spoke about the research (which she coauthored) at MIT Technology Review’s EmTech MIT conference at the MIT Media Lab. Krishnan pointed out that monotonous or repetitive tasks are ripe for automation. She pegs the share of work that can be automated at greater than 90% in about 10% of occupations. Those particularly susceptible to disruption are construction, tech, and manufacturing (which she noted tend to be male-dominated), as well as female-dominated segments like health care and education.

Those sentiments jibe with a March 2019 report from the U.K.’s Office for National Statistics (ONS), which found that 10% of the U.K.’s workforce (about 1.5 million workers) occupy jobs that are at “high risk” of automation. ONS forecasted that service workers — chiefly waiters and waitresses, retail inventory restockers, and entry-level salespeople — would be disproportionately affected, as well as those in agricultural, automotive, and service industries. And the department predicted that women, who in 2017 held 70.2% of high-risk jobs, would bear the brunt of the coming labor market shifts.

“Essentially, the potential for job losses and job gains could be roughly the same for men and women on average,” said Krishnan. “On the other hand, there’s also opportunities for new jobs to be created.”

Krishnan anticipates that in industries like manufacturing, work might transition from shop floor production, say, to engineering and design. But she also expects a global paradigm shift leading to the creation of entirely new occupations that don’t yet exist.

It wouldn’t be unprecedented. Decades ago, roles like “social media manager” and “data scientist” hadn’t been conceived, much less sought after. Krishnan said that typically, roughly 10% of employment at any given time is in these newly emerged groups of occupations, amounting to 160 million jobs globally.

Whether they take up new work or acquire new skills in their current fields, Krishnan anticipates that tens of millions of workers will have to make some sort of occupational transition by 2030. Many of those workers are women — as many as 40 million to 160 million globally.

Encouragingly, in both developed and emerging markets, the new jobs that are expected to come into vogue are likely to be higher-wage, according to Krishnan. Those jobs will furthermore involve less drudgery, which will be traded for tasks ostensibly more socially and intellectually stimulating. In fact, Krishnan believes that this future of work will require more interpersonal know-how of the workers who occupy its roles.

Of course, the challenge for men and women in the workforce is figuring out how to navigate the transition.

It’s all but certain that advanced degrees and higher levels of education will be demanded of workers in mature and emerging markets. They’ll be expected to have strong leadership and managerial skills, and to excel at creative pursuits involving the use of technology. In fact, Krishnan expects that tech skills — competency with computers and a range of basic software — will be the highest growth area of any skills category in the next decade.

But retraining and reskilling are easier said than done, and geographic immobility remains a major barrier. Krishnan said that the percentage of U.S. workers unwilling or unable to relocate is at an all-time high, a fact that’s doubly problematic considering opportunities are expected to emerge in select pockets of the U.S. at the expense of others.

Those in developing countries won’t have it easier. Krishnan expects the bulk of new roles created by automation will be likewise concentrated in urban as opposed to rural regions, disadvantaging those without access to safe and affordable transportation.

“Women may have less time to reskill in many parts of the world, and they might have lower educational attainment,” Krishnan added. “They’re also going to have to learn to work more with technology, and this may be a particular barrier for women.”

If the transition proceeds smoothly, though, the benefits could be enormous. A separate McKinsey study forecasted that AI could contribute an additional 1.2% to gross domestic product growth (GDP) for the next decade, and that it could help to capture an additional 20-25% in net economic benefits (equating to $13 trillion globally) in the next 12 years.

“This is not a systemic challenge that companies are going to have to deal with, and it’s not just a challenge that governments are going to have to deal with. [V]arious stakeholders [are going to] have to work together to solve this issue,” said Krishnan. “Beyond solving the question of reskilling workers, we also need to think about agendas [and policies that] ensure women are not left further behind. If we act now, we can step into a better future, but it’ll require finding ways to solve some of the barriers and challenges.”

As always, if you come across a story that merits coverage, send news tips to Khari Johnson and Kyle Wiggers — and be sure to bookmark our AI Channel and subscribe to the AI Weekly newsletter.

Thanks for reading,

Kyle Wiggers

Senior AI staff writer

P.S. Please enjoy this video of MIT Technology Review’s Gideon Lichfield using deepfake technology provided by Pinscreeen at the EmTech MIT conference.

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