## Gender, Technology, and the Future of Work

_Staff Discussion Notes, October 8, 2018_

## Source details

**Canonical URL:** [Gender, Technology, and the Future of Work](https://www.imf.org/en/publications/staff-discussion-notes/issues/2018/10/09/gender-technology-and-the-future-of-work-46236)

## Other formats

- [Markdown version](/en/publications/staff-discussion-notes/issues/2018/10/09/gender-technology-and-the-future-of-work-46236/index.md)
- [Structured JSON version](/en/publications/staff-discussion-notes/issues/2018/10/09/gender-technology-and-the-future-of-work-46236/index.json)
- [Bundle manifest](/en/publications/staff-discussion-notes/issues/2018/10/09/gender-technology-and-the-future-of-work-46236/bundle-manifest.json)

## Bibliographic details
- Authors: Mariya Brussevich, Era Dabla-Norris, Christine Kamunge, Pooja Karnane, Salma Khalid, Kalpana Kochhar
- Published: October 8, 2018
- Series: Staff Discussion Notes
- DOI: https://doi.org/10.5089/9781484379769.006

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### Executive summary and central findings
- New technologies—digitalization, artificial intelligence, and machine learning—are changing the way work gets done at an unprecedented rate.
- 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, the study estimates 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.
- There is significant heterogeneity in automation risk across sectors and countries.
- Extrapolating the results yields around 180 million female jobs at high risk of being displaced globally.

### Distributional patterns and vulnerable groups
- Workers disproportionately exposed to automation:
  - Less well-educated female workers.
  - Older female workers (aged 40 and above).
  - Female workers in low-skill clerical, service, and sales positions.
- Exposure is driven by task composition: higher prevalence of routine tasks among female workers across sectors and occupations increases automation vulnerability.

### Policy implications and recommendations
- Endow women with required skills to adapt to technological change:
  - Invest in training and lifelong learning focused on non-routine cognitive and socioemotional skills.
- Close gender gaps in leadership positions to improve representation in decision-making around technology adoption.
- Bridge the digital gender divide to ensure access to technology and digital skills:
  - Leverage ongoing digital transformation, which could confer greater flexibility in work arrangements, benefiting women.
- Ease transitions for older and low-skilled female workers:
  - Support measures that facilitate re-skilling, job search, and mobility for those at high risk of displacement.

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## Content in this bundle

- **Staff Discussion Note**
  - [Staff Discussion Note (Markdown version)](/-/media/files/publications/sdn/2018/sdn1807.pdf.md){rel="alternate" type="text/markdown"}
  - [Staff Discussion Note (PDF)](/-/media/files/publications/sdn/2018/sdn1807.pdf){rel="external" type="application/pdf"}

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_Source: https://www.imf.org/en/publications/staff-discussion-notes/issues/2018/10/09/gender-technology-and-the-future-of-work-46236_