How Artificial Intelligence Could Widen the Gap Between Rich and Poor Nations
IMF Blog, December 2, 2020
Source details
- Canonical URL
- How Artificial Intelligence Could Widen the Gap Between Rich and Poor Nations
Other formats
Bibliographic details
- Authors: Cristian Alonso, Siddharth Kothari, Sidra Rehman
- Published: December 2, 2020
Overview
- New technologies cited: "artificial intelligence, machine learning, robotics, big data, and networks."
- Core finding: "new technology risks widening the gap between rich and poor countries by shifting more investment to advanced economies where automation is already established."
- Primary policy challenge identified: developing economies must "take actions to raise productivity and improve skills among workers" to prevent divergence.
Model and key channels of divergence
- Model setup:
- Two countries: one advanced, the other developing.
- Production uses three factors: "labor, capital, and robots."
- "Robots" interpreted broadly to encompass the range of new technologies.
- Main assumption: "robots substitute for workers."
- The "artificial intelligence revolution" is modeled as "an increase in the productivity of robots."
- Three distinct channels through which divergence can occur:
- Share-in-production:
- Advanced economies have higher wages because "total factor productivity is higher."
- Higher wages induce firms in advanced economies "to use robots more intensively."
- When robot productivity rises, "the advanced economy will benefit more in the long run."
- Divergence increases "the more robots substitute for workers."
- Investment flows:
- Increased robot productivity "fuels strong demand to invest in robots and traditional capital."
- Demand is larger in advanced economies because robots are used more intensively there.
- Result: "investment gets diverted from developing countries to finance this capital and robot accumulation in advanced economies," causing "a transitional decline in GDP in the developing country."
- Terms-of-trade:
- Developing economies "will likely specialize in sectors that rely more on unskilled labor."
- Assuming "robots replace unskilled labor but complement skilled workers," a "permanent decline in the terms of trade in the developing region may emerge after the robot revolution."
- Mechanism: displacement of unskilled workers reduces their relative wages and "lowering the price of the good that uses unskilled labor more intensively," which "acts as a further negative shock, reducing the incentive to invest and potentially leading to a fall not just in relative but in absolute GDP."
Evidence on robots and wages
- Empirical suggestive finding: "higher wages coincide with significantly higher use of robots," consistent with firms substituting "away from workers and towards robots in response to higher labor costs."
- Key dependency: results "critically depend on whether robots indeed substitute for workers."
Implications and policy recommendations
- Distributional and growth effects:
- Improvements in robot productivity "drive divergence between advanced and developing countries if robots substitute easily for workers."
- Such improvements "will tend to increase incomes but also increase income inequality, at least during the transition and possibly in the long run for some groups of workers, in both advanced and developing economies."
- No silver bullet:
- "There is no silver bullet for averting divergence."
- Urgency: "developing countries need to invest in raising aggregate productivity and skill levels more urgently than ever before, so that their labor force is complemented rather than substituted by robots."
- Specific policy levers highlighted:
- Increase "total factor productivity" to account for institutional and fundamental differences; these increases "are especially beneficial as they incentivize more robots and physical capital accumulation."
- Prioritize "human capital accumulation" to prevent divergence and manage differing growth dynamics across developing economies with different skill levels.
- Rapidly "improve productivity gains and invest in education and skills development" to capitalize on the demographic transition and mitigate the risk that "robots may steal these jobs."
Cristian Alonso, Siddharth Kothari, Sidra Rehman — December 2, 2020