Cristian Alonso, Mr. Andrew Berg, Siddharth Kothari, Mr. Chris Papageorgiou, and Sidra Rehman
This paper considers the implications for developing countries of a new wave of technological change that substitutes pervasively for labor. It makes simple and plausible assumptions: the AI revolution can be modeled as an increase in productivity of a distinct type of capital that substitutes closely with labor; and the only fundamental difference between the advanced and developing country is the level of TFP. This set-up is minimalist, but the resulting conclusions are powerful: improvements in the productivity of “robots” drive divergence, as advanced countries differentially benefit from their initially higher robot intensity, driven by their endogenously higher wages and stock of complementary traditional capital. In addition, capital—if internationally mobile—is pulled “uphill”, resulting in a transitional GDP decline in the developing country. In an extended model where robots substitute only for unskilled labor, the terms of trade, and hence GDP, may decline permanently for the country relatively well-endowed in unskilled labor.
Mr. Arnoud W.A. Boot, Peter Hoffmann, Mr. Luc Laeven, and Mr. Lev Ratnovski
We study the effects of technological change on financial intermediation, distinguishing between innovations in information (data collection and processing) and communication (relationships and distribution). Both follow historic trends towards an increased use of hard information and less in-person interaction, which are accelerating rapidly. We point to more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms. We argue that in particular the rise of new communication channels can lead to the vertical and horizontal disintegration of the traditional bank business model. Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers. We discuss limitations to these challenges, and the resulting policy implications.
Mr. Carlos Mulas-Granados, Richard Varghese, Vizhdan Boranova, Alice deChalendar, and Judith Wallenstein
We exploit a survey data set that contains information on how 11,000 workers across advanced and emerging market economies perceive the main forces shaping the future of work. In general, workers feel more positive than negative about automation, especially in emerging markets. We find that negative perceptions about automation are prevalent among workers who are older, poorer, more exposed to job volatility, and from countries with higher levels of robot penetration. Perceptions over automation are positively viewed by workers with higher levels of job satisfaction, higher educational attainment, and from countries with stronger labor protection. Workers with positive perceptions of automation also tend to respond that re-education and retraining will be needed to adapt to rapidly evolving skill demands. These workers expect governments to have a role in shaping the future of work through protection of labor and new forms of social benefits. The demand for protection and benefits is more significant among women and workers that have suffered job volatility.
The Spring-Summer 2019 issue of the IMF Research Perspectives explores how technology deals with old questions. Articles discuss the ways technological progress and the increased availability of data have helped in some areas, while presenting new challenges for analyzing various matters. The issue also includes an interview with Gita Gopinath, the new director of the IMF Research Department.
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.