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Mariya Brussevich, Ms. Era Dabla-Norris, and Salma Khalid

perform fewer tasks requiring analytical input or abstract thinking (e.g., information-processing skills), where technological change can be complementary to human skills and improve labor productivity. Self-selection by women into specific occupations explains most of these differences, but women’s exposure to routine job tasks varies significantly across countries. Within Europe, women in Eastern and Southern Europe perform more routine tasks than men, while the gender routineness gap (the difference in the routineness index values for women and men) is lowest in

Mariya Brussevich, Ms. Era Dabla-Norris, and Salma Khalid
Using individual level data on task composition at work for 30 advanced and emerging economies, we find that women, on average, perform more routine tasks than men?tasks that are more prone to automation. To quantify the impact on jobs, we relate data on task composition at work to occupation level estimates of probability of automation, controlling for a rich set of individual characteristics (e.g., education, age, literacy and numeracy skills). Our results indicate that female workers are at a significantly higher risk for displacement by automation than male workers, with 11 percent of the female workforce at high risk of being automated given the current state of technology, albeit with significant cross-country heterogeneity. The probability of automation is lower for younger cohorts of women, and for those in managerial positions.
Mariya Brussevich, Ms. Era Dabla-Norris, Christine Kamunge, Pooja Karnane, Salma Khalid, and Ms. Kalpana Kochhar
New technologies?digitalization, artificial intelligence, and machine learning?are changing the way work gets done at an unprecedented rate. Helping people adapt to a fast-changing world of work and ameliorating its deleterious impacts will be the defining challenge of our time. What are the gender implications of this changing nature of work? How vulnerable are women’s jobs to risk of displacement by technology? What policies are needed to ensure that technological change supports a closing, and not a widening, of gender gaps? This SDN finds that women, on average, perform more routine tasks than men across all sectors and occupations?tasks that are most prone to automation. Given the current state of technology, we estimate that 26 million female jobs in 30 countries (28 OECD member countries, Cyprus, and Singapore) are at a high risk of being displaced by technology (i.e., facing higher than 70 percent likelihood of being automated) within the next two decades. Female workers face a higher risk of automation compared to male workers (11 percent of the female workforce, relative to 9 percent of the male workforce), albeit with significant heterogeneity across sectors and countries. Less well-educated and older female workers (aged 40 and above), as well as those in low-skill clerical, service, and sales positions are disproportionately exposed to automation. Extrapolating our results, we find that around 180 million female jobs are at high risk of being displaced globally. Policies are needed to endow women with required skills; close gender gaps in leadership positions; bridge digital gender divide (as ongoing digital transformation could confer greater flexibility in work, benefiting women); ease transitions for older and low-skilled female workers.
Mariya Brussevich, Ms. Era Dabla-Norris, and Salma Khalid
International Monetary Fund. Asia and Pacific Dept

that automation substitutes, or threatens to substitute, for some low- or middle-skilled workers with routine job tasks ( Autor and Dorn 2013 ; Goos, Manning, and Salomons 2014 ), it could weaken the power of such workers to bid up their wages. It could also weaken their unionization. Workers’ bargaining power can also be influenced by exposure to international competition. This may arise through trade and through firms’ participation in global supply chains. The threat of production facilities’ relocating to economies where labor costs are lower would weaken the

Mariya Brussevich, Ms. Era Dabla-Norris, Christine Kamunge, Pooja Karnane, Salma Khalid, and Ms. Kalpana Kochhar

describes analytical and interpersonal tasks; manual index describes long hours of physical work (non-routine); routine index describes lack of job flexibility, little learning on the job, and repetitive tasks. *** indicates that gender differences in RTI indices and their components are statistically significant at 1 percent level. 11. Significant cross-country heterogeneity . Women’s exposure to routine job tasks varies significantly across countries ( Figure 2 ). The exposure is highest in eastern and southern European countries and lowest in Scandinavian and