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Author: Mariya Brussevich
Publisher: International Monetary Fund
ISBN: 1498303749
Category : Technology & Engineering
Languages : en
Pages : 37
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Book Description
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.
Author: Mariya Brussevich
Publisher: International Monetary Fund
ISBN: 1498303749
Category : Technology & Engineering
Languages : en
Pages : 37
Get Book Here
Book Description
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.
Author: Mariya Brussevich
Publisher: International Monetary Fund
ISBN: 1498313809
Category : Technology & Engineering
Languages : en
Pages : 37
Get Book Here
Book Description
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.
Author: Mariya Brussevich
Publisher: International Monetary Fund
ISBN: 1484379764
Category : Social Science
Languages : en
Pages : 36
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Book Description
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.
Author:
Publisher: Academic Conferences and publishing limited
ISBN: 1914587294
Category : Social Science
Languages : en
Pages :
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Book Description
Author: Collett, Clementine
Publisher: UNESCO Publishing
ISBN: 9231005138
Category : Political Science
Languages : en
Pages : 81
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Book Description
The development and use of Artificial Intelligence (AI) continue to expand opportunities for the achievement of the 17 United Nations Sustainable Development Goals (SDGs), including gender equality. Taking a closer look at the intersection of gender and technology, this collaboration between UNESCO, the Inter-American Development Bank (IDB) and the Organisation for Economic Co-operation and Development (OECD) examines the effects of AI on the working lives of women. This report describes the challenges and opportunities presented by the use of emerging technology such as AI from a gender perspective. The report highlights the need for more focus and research on the impacts of AI on women and the digital gender gap, in order to ensure that women are not left behind in the future of work.
Author: Luke Munn
Publisher: Stanford University Press
ISBN: 1503631435
Category : Social Science
Languages : en
Pages : 201
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Book Description
For some, automation will usher in a labor-free utopia; for others, it signals a disastrous age-to-come. Yet whether seen as dream or nightmare, automation, argues Munn, is ultimately a fable that rests on a set of triple fictions. There is the myth of full autonomy, claiming that machines will take over production and supplant humans. But far from being self-acting, technical solutions are piecemeal; their support and maintenance reveals the immense human labor behind "autonomous" processes. There is the myth of universal automation, with technologies framed as a desituated force sweeping the globe. But this fiction ignores the social, cultural, and geographical forces that shape technologies at a local level. And, there is the myth of automating everyone, the generic figure of "the human" at the heart of automation claims. But labor is socially stratified and so automation's fallout will be highly uneven, falling heavier on some (immigrants, people of color, women) than others. Munn moves from machine minders in China to warehouse pickers in the United States to explore the ways that new technologies do (and don't) reconfigure labor. Combining this rich array of human stories with insights from media and cultural studies, Munn points to a more nuanced, localized, and racialized understanding of the "future of work."
Author: Norbert F. Schneider
Publisher: Edward Elgar Publishing
ISBN: 1788975545
Category : Social Science
Languages : en
Pages : 479
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Book Description
Exploring how family life has radically changed in recent decades, this comprehensive Research Handbook tracks the latest developments and trends in scholarly work on the family. With a particular focus on the European context, it addresses current debates and offers insights into key topics including: the division of housework, family forms and living arrangements, intergenerational relationships, partner choice, divorce and fertility behaviour.
Author: Fernanda Brollo
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 47
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Book Description
Generative artificial intelligence (gen AI) holds immense potential to boost productivity growth and advance public service delivery, but it also raises profound concerns about massive labor disruptions and rising inequality. This note discusses how fiscal policies can be employed to steer the technology and its deployment in ways that serve humanity best while cushioning the negative labor market and distributional effects to broaden the gains. Given the vast uncertainty about the nature, impact, and speed of developments in gen AI, governments should take an agile approach that prepares them for both business as usual and highly disruptive scenarios.
Author: Ms. Era Dabla-Norris
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 48
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Book Description
Labor markets in the UK have been characterized by markedly widening wage inequality for lowskill (non-college) women, a trend that predates the pandemic. We examine the contribution of job polarization to this trend by estimating age, period, and cohort effects for the likelihood of employment in different occupations and the wages earned therein over 2001-2019. For recent generations of women, cohort effects indicate a higher likelihood of employment in low-paying manual jobs relative to high-paying abstract jobs. However, cohort effects also underpin falling wages for post-1980 cohorts across all occupations. We find that falling returns to labor rather than job polarization has been a key driver of rising inter-age wage inequality among low-skill females. Wage-level cohort effects underpin a nearly 10 percent fall in expected lifetime earnings for low-skill women born in 1990 relative to those born in 1970.
Author: Ata Can Bertay
Publisher: International Monetary Fund
ISBN: 1513546279
Category : Social Science
Languages : en
Pages : 42
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Book Description
We study whether higher gender equality facilitates economic growth by enabling better allocation of a valuable resource: female labor. By allocating female labor to its more productive use, we hypothesize that reducing gender inequality should disproportionately benefit industries with typically higher female share in their employment relative to other industries. Specifically, we exploit within-country variation across industries to test whether those that typically employ more women grow relatively faster in countries with ex-ante lower gender inequality. The test allows us to identify the causal effect of gender inequality on industry growth in value-added and labor productivity. Our findings show that gender inequality affects real economic outcomes.
