Economists have long worried that many of the cutting-edge technologies created in advanced economies will not necessarily benefit developing and emerging economies, owing to vast differences in capital intensity and labor-market conditions. This disconnect could grow even more pronounced in the age of artificial intelligence.
CAMBRIDGE – Although experts disagree about whether artificial intelligence will reach human-like levels anytime soon, few doubt that the field will make major advances in the coming years. In the West, how AI will affect workers is already fueling growing concern, with some warning that millions of jobs will be automated. Yet even if such predictions turn out to be alarmist (or industry hype), increased awareness of AI and its implications suggests that advanced economies will be better prepared for whatever is coming.
But what about the billions of workers in the developing world? Even though the threats and opportunities associated with AI are equally significant in these economies, much less has been written about them.
Just a few companies in advanced economies are shaping the current direction of AI development, with the American tech giants, together with Alibaba and Baidu in China, accounting for the bulk of investment in research and development. Owing to these firms’ business models, much of the research into AI is geared toward automating tasks and services based on pattern and image recognition, prediction, and natural language processing. Where these companies lead, others will follow.
The tendency toward labor-replacing AI is problematic enough for workers in advanced economies, especially because it comes at the expense of other AI applications that could make workers more productive. But the implications for the developing world are even more ominous. Even in this age of rapid technological progress, most developing countries’ comparative advantage is still abundant, relatively cheap labor (all the more so now that the rich world is aging).
AI, then, is a classic example of what economists in the 1970s and 1980s called “inappropriate technology.” Capital-intensive innovations developed in advanced economies might not be particularly useful in poor economies where labor is abundant and capital is scarce. For countries like India or Brazil, which face higher relative costs of capital, the appropriate technology is one that actually prioritizes labor-intensive production methods. But, because advanced economies have no reason to invest in such labor-intensive technologies, the trajectory of technological change will increasingly disfavor poor countries.
Capital-intensive sectors are not the only areas where technological inappropriateness can become a problem. The types of seeds and chemicals needed for agriculture differ widely between richer countries in more temperate climates and poorer economies in tropical or semi-tropical areas across the Global South. Thus, R&D conducted in advanced economies will not necessarily lead to seed varieties and complementary technologies that benefit developing countries. Once again, the result is a widening gap between the rich and the poor globally.
At a time of escalating global turmoil, there is an urgent need for incisive, informed analysis of the issues and questions driving the news – just what PS has always provided.
Subscribe to Digital or Digital Plus now to secure your discount.
Subscribe Now
In this way, seeds are no different than AI. The tech giants in advanced economies are pouring billions into AI technologies designed to automate routine physical and cognitive tasks. But that is the last thing the developing world needs.
But an AI-driven divergence between the rich and developing worlds is not inevitable. AI could be used to improve education and health delivery, two areas where developing countries have an expanding need, as well as significant room for growth. AI could also be a powerful tool for providing information and training to farmers and small-scale producers and manufacturers. And the best part is that all these non-automation paths would benefit US and European workers as well.
But to realize this vision, we will need to adopt a two-pronged approach. First, we must redirect the development and deployment of AI technologies in the US and Western Europe toward functions that complement rather than replace human labor. That will require forward-looking leadership on the part of policymakers. In the past, particularly during the post-war era, government demand has been critical in driving the invention and development of cutting-edge technologies; yet today, public policymakers have relinquished their leadership role to Silicon Valley.
Change is also needed on the part of AI scientists and researchers, who should recognize the social consequences of their industry’s singular focus on automation. Some tech-sector workers have already signaled that they will not develop military or surveillance technologies. This attitude should now be extended further: researchers and developers on the front lines should be looking for more ways to complement rather than replace humans.
But this first prong won’t take us very far if tech corporations fund all the research and set the agenda. To ensure an inclusive AI revolution, we should learn from the Green Revolution of the 1950s and 1960s, when high-yield, climate-appropriate varieties of cereals, rice, and wheat were introduced across the developing world. These new crops, along with improved fertilizers and irrigation methods, enabled massive increases in agricultural yields in many developing economies, including Mexico, India, and Brazil.
The Green Revolution was not the brainchild of Western companies. Yes, philanthropic organizations such as the Rockefeller and Ford Foundations provided funding, and Western researchers such as Norman Borlaug (who was awarded the Nobel Peace Prize for his efforts) made critical contributions. But most of the intellectual leadership came from developing countries, where public- and private-sector leaders took it upon themselves to develop the technologies appropriate for their needs.
For example, IR8 (and later IR72), a high-yielding seed created by crossing Indonesian and Taiwanese dwarf rice varieties, produced spectacular increases in Asian rice farmers’ output. This “miracle rice” was developed by the Indian agronomists Surajit Kumar de Dutta and Gurdev Singh Khush at the International Rice Research Institute in the Philippines, in coordination with Western researchers such as Henry Beachell.
We now need a Green Revolution for AI. Even if developing countries cannot match the resources available to American and Chinese tech companies, they should articulate their own vision for an AI-driven future, and then start building toward that homegrown narrative, with coordination and funding assistance from international organizations such as the United Nations. Such efforts, one hopes, would lead to a shift in public opinion globally, at which point the AI development community will have no choice but to listen.
This is a tall order, given that so many developing countries are led by demagogues and autocrats, and are dealing with more pressing concerns. But there is no excuse for complacency. One way or another, the future of the developing world will depend on the future of AI.
To have unlimited access to our content including in-depth commentaries, book reviews, exclusive interviews, PS OnPoint and PS The Big Picture, please subscribe
CAMBRIDGE – Although experts disagree about whether artificial intelligence will reach human-like levels anytime soon, few doubt that the field will make major advances in the coming years. In the West, how AI will affect workers is already fueling growing concern, with some warning that millions of jobs will be automated. Yet even if such predictions turn out to be alarmist (or industry hype), increased awareness of AI and its implications suggests that advanced economies will be better prepared for whatever is coming.
But what about the billions of workers in the developing world? Even though the threats and opportunities associated with AI are equally significant in these economies, much less has been written about them.
Just a few companies in advanced economies are shaping the current direction of AI development, with the American tech giants, together with Alibaba and Baidu in China, accounting for the bulk of investment in research and development. Owing to these firms’ business models, much of the research into AI is geared toward automating tasks and services based on pattern and image recognition, prediction, and natural language processing. Where these companies lead, others will follow.
The tendency toward labor-replacing AI is problematic enough for workers in advanced economies, especially because it comes at the expense of other AI applications that could make workers more productive. But the implications for the developing world are even more ominous. Even in this age of rapid technological progress, most developing countries’ comparative advantage is still abundant, relatively cheap labor (all the more so now that the rich world is aging).
AI, then, is a classic example of what economists in the 1970s and 1980s called “inappropriate technology.” Capital-intensive innovations developed in advanced economies might not be particularly useful in poor economies where labor is abundant and capital is scarce. For countries like India or Brazil, which face higher relative costs of capital, the appropriate technology is one that actually prioritizes labor-intensive production methods. But, because advanced economies have no reason to invest in such labor-intensive technologies, the trajectory of technological change will increasingly disfavor poor countries.
Capital-intensive sectors are not the only areas where technological inappropriateness can become a problem. The types of seeds and chemicals needed for agriculture differ widely between richer countries in more temperate climates and poorer economies in tropical or semi-tropical areas across the Global South. Thus, R&D conducted in advanced economies will not necessarily lead to seed varieties and complementary technologies that benefit developing countries. Once again, the result is a widening gap between the rich and the poor globally.
Winter Sale: Save 40% on a new PS subscription
At a time of escalating global turmoil, there is an urgent need for incisive, informed analysis of the issues and questions driving the news – just what PS has always provided.
Subscribe to Digital or Digital Plus now to secure your discount.
Subscribe Now
In this way, seeds are no different than AI. The tech giants in advanced economies are pouring billions into AI technologies designed to automate routine physical and cognitive tasks. But that is the last thing the developing world needs.
But an AI-driven divergence between the rich and developing worlds is not inevitable. AI could be used to improve education and health delivery, two areas where developing countries have an expanding need, as well as significant room for growth. AI could also be a powerful tool for providing information and training to farmers and small-scale producers and manufacturers. And the best part is that all these non-automation paths would benefit US and European workers as well.
But to realize this vision, we will need to adopt a two-pronged approach. First, we must redirect the development and deployment of AI technologies in the US and Western Europe toward functions that complement rather than replace human labor. That will require forward-looking leadership on the part of policymakers. In the past, particularly during the post-war era, government demand has been critical in driving the invention and development of cutting-edge technologies; yet today, public policymakers have relinquished their leadership role to Silicon Valley.
Change is also needed on the part of AI scientists and researchers, who should recognize the social consequences of their industry’s singular focus on automation. Some tech-sector workers have already signaled that they will not develop military or surveillance technologies. This attitude should now be extended further: researchers and developers on the front lines should be looking for more ways to complement rather than replace humans.
But this first prong won’t take us very far if tech corporations fund all the research and set the agenda. To ensure an inclusive AI revolution, we should learn from the Green Revolution of the 1950s and 1960s, when high-yield, climate-appropriate varieties of cereals, rice, and wheat were introduced across the developing world. These new crops, along with improved fertilizers and irrigation methods, enabled massive increases in agricultural yields in many developing economies, including Mexico, India, and Brazil.
The Green Revolution was not the brainchild of Western companies. Yes, philanthropic organizations such as the Rockefeller and Ford Foundations provided funding, and Western researchers such as Norman Borlaug (who was awarded the Nobel Peace Prize for his efforts) made critical contributions. But most of the intellectual leadership came from developing countries, where public- and private-sector leaders took it upon themselves to develop the technologies appropriate for their needs.
For example, IR8 (and later IR72), a high-yielding seed created by crossing Indonesian and Taiwanese dwarf rice varieties, produced spectacular increases in Asian rice farmers’ output. This “miracle rice” was developed by the Indian agronomists Surajit Kumar de Dutta and Gurdev Singh Khush at the International Rice Research Institute in the Philippines, in coordination with Western researchers such as Henry Beachell.
We now need a Green Revolution for AI. Even if developing countries cannot match the resources available to American and Chinese tech companies, they should articulate their own vision for an AI-driven future, and then start building toward that homegrown narrative, with coordination and funding assistance from international organizations such as the United Nations. Such efforts, one hopes, would lead to a shift in public opinion globally, at which point the AI development community will have no choice but to listen.
This is a tall order, given that so many developing countries are led by demagogues and autocrats, and are dealing with more pressing concerns. But there is no excuse for complacency. One way or another, the future of the developing world will depend on the future of AI.