Automation and the sexes: is job transformation more likely among women?

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Author: Frenette, Marc; Frank, Kristyn


Recent advances in artificial intelligence and machine-learning technologies have fuelled fears of potential job losses among some workers. While the net impact of new technology on total jobs can be negative, positive or neutral, some workers may be more affected than others depending on how easily robots and algorithms can replace them, or how easily their skills complement the new technology. In the case of women and men, it is not clear who is likely to be most affected. While women are more likely to hold a university degree (typically associated with non-routine work that is more...  [+] Show more

Subjects: Technology; Employment; Gender; Skills and knowledge; Qualifications; Demographics

Keywords: Technological change; Educational level; Job requirements; Occupation; Age; Employment status; Redundancy; Skill obsolescence; Comparative analysis

Geographic subjects: Canada; North America

Published: Ottawa, Ontario: Statistics Canada, 2020

Physical description: 21 p.

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ISBN: 9780660360638

ISSN: 1205-9153

Resource type: Paper

Document number: TD/TNC 141.1216

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