Friday, June 21, 11.00 am to 12.30 pm
Ms. Era Dabla-Norris, Division Chief, Fiscal Affairs Department, International Monetary Fund
On June 21, the Joint Vienna Institute (JVI) hosted a lecture on “Gender, Technology and the Future of Work.” Ms. Era Dabla-Norris of Fiscal Affairs Department of the International Monetary Fund (IMF) discussed a recent IMF study of the impact on women of new technologies that are changing the nature of the production process and the landscape of work.
Although new technologies could provide opportunities for more flexible work arrangements, there is uncertainty about how technology will affect future work, so that helping people adapt to those changes will be the defining challenge of our time.
The study concluded that digitalization, machine learning and artificial intelligence increase the range of workplace tasks that can be automated. Many jobs involving repetitive low- and middle-skill tasks are already being eliminated. Ms. Dabla-Norris emphasized that routine tasks are at the highest risk of automation because of their substitutability with technology.
Ms. Dabla-Norris reminded the audience that gender gaps still persist in labor markets. The study therefore asked how technological advances will affect the gender differences in employment outcomes, and whether women’s jobs are more vulnerable to being displaced by technology.
She explained that because more routine tasks are more susceptible to the substitution of labor by capital, the workers who perform them are more exposed to automation. To establish how routine a certain job is, the study developed a new index – a routine task intensity (RTI) index - based on data from the OECD Program for the International Assessment of Adult Competencies (PIAAC) survey of worker perceptions of the tasks they perform.
The IMF study found that in the 30 countries studied, the tasks performed by women are more repetitive and less analytical than those done by men—even when both women and men hold similar jobs and are in similar occupations. For example, in health and public administration – sectors where women are relatively overrepresented, and where jobs are at a lower risk of being automated – women tend to perform more routine tasks, and thus face a higher risk of job displacement.
Figure 1. Routinization levels for women
Source: IMF Staff Discussion Note 18/07
Note: Routinization Levels for Women are Highest in Eastern and Southern Europe and Lowest in Scandinavia and Central Europe.
RTI index is calculated at the female level using information on routine, abstract, and manual tasks performed.
The study estimates that about 26 million female workers in the 30 countries covered are at high risk of being displaced by automation—especially less-educated and older women in low-skilled positions. The researchers also established that the degree of routinization is a factor that helps explain gender wage gaps.
Ms. Dabla-Norris concluded that rethinking policies will be necessary to ensure that technological change operates to help narrow gender gaps in labor markets. Governments will need to act in at least four areas: empowering women with skills, closing gender gaps in leadership positions, investing in capital infrastructure to ensure equal access to finance and connectivity, and easing transitions by providing support for workers to acquire new skills and building effective social protection systems.
During the highly interactive Q&A session, among the questions asked was whether the new jobs created would mitigate the impact on women, and what would be the appropriate policy response to the challenges posed by automation for a specific country. Ms. Dabla-Norris emphasized that seizing job opportunities offered by new technologies will require policies that help workers to adapt to the changing environment. For example, women are underrepresented in science, technology, engineering, and mathematics (STEM)—the sectors where countries can expect job growth and where technological change can be complementary to human skills. Prioritizing gender inclusion in STEM fields can therefore help break down gender stereotypes and help empower women. She concluded that specific policy packages would depend on country circumstances: even though it was found that women are universally more vulnerable to losing jobs to automation, the study found significant cross-country heterogeneity in women’s exposure to routine job tasks. This reflects country differences in the structure of production, the technologies adopted, and the flexibility of their labor markets.
Asel Isakova, Senior Economist, JVI