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Innovation

Women will lose more jobs to automation, report finds

The Fourth Industrial Revolution will not affect everyone equally, according to the World Economic Forum.
Written by Greg Nichols, Contributing Writer

A World Economic Forum report presented at Davos suggests there will be a measurable gender disparity when it comes to jobs lost to automation.

The report, titled Toward a Reskilling Revolution: A Future of Jobs for All, reiterates U.S. Bureau of Labor and Statistics findings that 1.4 million jobs in the United States will be disrupted or lost to automation and other factors between now and 2026. Of those, according to the World Economic Forum's research, 57 percent will belong to women.

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"This is a worrying development at a time when the workplace gender gap is already widening and when women are under-represented in the areas of the labour market expected to grow most robustly in the coming years," according to the authors of the report.

The research was published in collaboration with the Boston Consulting Group and data partner Burning Glass Technologies.

Researchers used a novel methodology, culling data from 50 million online job postings, which account for 15,000 unique skills. They identified 958 unique types of jobs from those postings, then indexed the qualifications needed for each, including education, work skills, years of experience, and work activities. Finally, they used U.S. labor statistics to build a picture of who in the workforce is most likely to be affected by automation and to map out job transition opportunities for those most likely to be impacted.

There were some positive takeaways. With adequate reskilling through training and education, 95 percent of workers who are at the highest risk of losing their jobs would find "good-quality, higher-wage work."

Who foots the bill for that training is an open question, but most discussions at Davos have centered around the need for government safety nets aimed at retraining and job matching.

Without reskilling, only 2 percent of workers are likely to transition to new jobs.

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