Artificial Intelligence and the Economic Gap between Countries
New technologies, such as artificial intelligence, machine learning, robotics, big data, and networks, are expected to revolutionize production processes, but they may also have a major impact on developing economies. For example, there is a big difference between the opportunities and potential sources of growth that the United States and China enjoyed during their early stages of economic development and what Cambodia and Tanzania face in today's world.
Recent research by our experts concludes that new technology brings with it the risks of widening the gap between rich and poor countries by shifting more investments to advanced economies, in which automation has become a stable feature. Consequently, this may have negative consequences for jobs in developing countries, because it threatens to replace their growing workforce rather than complement it, which has traditionally been an advantage in less advanced economies. To prevent this growing divergence, policymakers in developing economies will need to take measures to raise productivity and improve skills among workers.
On typical results derived: Our model considers the case of two countries (one developed and the other developing) that produce goods using three factors of production, labor, capital, and "robots". We interpret "robots" in general as encompassing all the new technologies mentioned above, and we put a basic assumption in the model that robots replace human labor. The artificial intelligence revolution in our framework represents an increase in the productivity of robots.
We conclude that the divergence between developing and developed economies can occur through three different channels: production participation rate, investment flows, and trade exchange rates.
On the percentage of participation in production: Advanced economies offer higher wages because the total productivity of factors of production is higher. These higher wages are prompting companies in advanced economies to use robots more intensively initially, especially when it is easy to replace human labor with robots. Then, when the productivity of robots increases, the advanced economy benefits more in the long term. This divergence increases as robots are used instead of human labor.
And on investment flows: as the productivity of robots increases, the demand for investment in them and in traditional capital (which is supposed to complement robots and work) increases. This demand is even greater in advanced economies because they use robots more intensively (the "production-participation ratio" channel we discussed earlier). As a result, investments are shifting away from developing countries and towards financing this type of capital and for the accumulation of robots in advanced economies, which leads to a transitional decline in the GDP of developing countries.
On the terms of trade exchange: It is likely that the developing economy specializes in sectors more dependent on unskilled labor, which is the most abundant type of employment in these economies compared to advanced economies. And if we assume the use of robots instead of unskilled labor, but with a complementary number of skilled workers, a permanent decrease in the rates of trade might occur in the developing region after the robotics revolution. This is because robots will lay off unskilled workers more than others, causing their relative wages to drop and the price of the commodity they use more intensively to produce. In turn, the decline in the relative price of its primary production becomes another negative shock, which limits the incentive to invest, and may lead to a decline not only in relative GDP but also in absolute GDP.
On the issue of robotics and wages, our findings hinge critically on whether robots will truly replace human labor. While it may be too early to predict the extent of this replacement in the future, the evidence suggests this. Specifically, we find that higher wages are associated with a significant increase in the use of robots, which reinforces the idea that companies will use robots instead of workers due to their higher costs.
And on the repercussions, the improvement in the productivity of robots is a driver of divergence between developed and developing countries if robots easily replace workers. In addition, this improvement often increases income but also increases inequality in its distribution, at least during the transition period and possibly in the long term for some groups of workers, whether in advanced or developing economies.
There is no magic bullet to avoid the spacing. Given the rapid pace of the robotics revolution, developing countries should invest in raising overall productivity and skill levels more urgently than ever before, so that robots supplement their workforce and not replace it. Of course, this is easier said than done. In our model, increasing TFP - which is responsible for many of the institutional and other fundamental differences between developing and developed countries that are not explained by labor and capital inputs - is particularly beneficial, as it stimulates the accumulation of more robots and physical capital. Such improvements are always beneficial, but their gains are getting stronger in the context of the AI revolution.
Our results also confirm the importance of accumulating human capital to avoid divergence and indicate the possibility of a different growth dynamic among developing economies of varying skill levels. The scene is likely to be much more difficult in developing countries that have been hoping to reap high dividends from the demographic transition that they are anticipating with great interest. Policymakers have welcomed the growing young population in developing countries as a great potential opportunity to benefit from the shift in jobs from China as a result of its rise from middle income. Our findings suggest that robots may steal these jobs, which will prompt policymakers to act to mitigate these risks. In the face of these technology-driven pressures, in particular, a massive and rapid shift in productivity gains and investment in education and skills development will benefit from this anticipated demographic shift.
Recent research by our experts concludes that new technology brings with it the risks of widening the gap between rich and poor countries by shifting more investments to advanced economies, in which automation has become a stable feature. Consequently, this may have negative consequences for jobs in developing countries, because it threatens to replace their growing workforce rather than complement it, which has traditionally been an advantage in less advanced economies. To prevent this growing divergence, policymakers in developing economies will need to take measures to raise productivity and improve skills among workers.
On typical results derived: Our model considers the case of two countries (one developed and the other developing) that produce goods using three factors of production, labor, capital, and "robots". We interpret "robots" in general as encompassing all the new technologies mentioned above, and we put a basic assumption in the model that robots replace human labor. The artificial intelligence revolution in our framework represents an increase in the productivity of robots.
We conclude that the divergence between developing and developed economies can occur through three different channels: production participation rate, investment flows, and trade exchange rates.
On the percentage of participation in production: Advanced economies offer higher wages because the total productivity of factors of production is higher. These higher wages are prompting companies in advanced economies to use robots more intensively initially, especially when it is easy to replace human labor with robots. Then, when the productivity of robots increases, the advanced economy benefits more in the long term. This divergence increases as robots are used instead of human labor.
And on investment flows: as the productivity of robots increases, the demand for investment in them and in traditional capital (which is supposed to complement robots and work) increases. This demand is even greater in advanced economies because they use robots more intensively (the "production-participation ratio" channel we discussed earlier). As a result, investments are shifting away from developing countries and towards financing this type of capital and for the accumulation of robots in advanced economies, which leads to a transitional decline in the GDP of developing countries.
On the terms of trade exchange: It is likely that the developing economy specializes in sectors more dependent on unskilled labor, which is the most abundant type of employment in these economies compared to advanced economies. And if we assume the use of robots instead of unskilled labor, but with a complementary number of skilled workers, a permanent decrease in the rates of trade might occur in the developing region after the robotics revolution. This is because robots will lay off unskilled workers more than others, causing their relative wages to drop and the price of the commodity they use more intensively to produce. In turn, the decline in the relative price of its primary production becomes another negative shock, which limits the incentive to invest, and may lead to a decline not only in relative GDP but also in absolute GDP.
On the issue of robotics and wages, our findings hinge critically on whether robots will truly replace human labor. While it may be too early to predict the extent of this replacement in the future, the evidence suggests this. Specifically, we find that higher wages are associated with a significant increase in the use of robots, which reinforces the idea that companies will use robots instead of workers due to their higher costs.
And on the repercussions, the improvement in the productivity of robots is a driver of divergence between developed and developing countries if robots easily replace workers. In addition, this improvement often increases income but also increases inequality in its distribution, at least during the transition period and possibly in the long term for some groups of workers, whether in advanced or developing economies.
There is no magic bullet to avoid the spacing. Given the rapid pace of the robotics revolution, developing countries should invest in raising overall productivity and skill levels more urgently than ever before, so that robots supplement their workforce and not replace it. Of course, this is easier said than done. In our model, increasing TFP - which is responsible for many of the institutional and other fundamental differences between developing and developed countries that are not explained by labor and capital inputs - is particularly beneficial, as it stimulates the accumulation of more robots and physical capital. Such improvements are always beneficial, but their gains are getting stronger in the context of the AI revolution.
Our results also confirm the importance of accumulating human capital to avoid divergence and indicate the possibility of a different growth dynamic among developing economies of varying skill levels. The scene is likely to be much more difficult in developing countries that have been hoping to reap high dividends from the demographic transition that they are anticipating with great interest. Policymakers have welcomed the growing young population in developing countries as a great potential opportunity to benefit from the shift in jobs from China as a result of its rise from middle income. Our findings suggest that robots may steal these jobs, which will prompt policymakers to act to mitigate these risks. In the face of these technology-driven pressures, in particular, a massive and rapid shift in productivity gains and investment in education and skills development will benefit from this anticipated demographic shift.