Generative AI may increase global inequality

As I noted in a post earlier this month, the general public appears to be worried about the impact of generative artificial intelligence on jobs and inequality. Some economists are clearly worried as well. Consider this post on the Center for Global Development blog, by Philip Schellekens and David Skilling. They note three reasons why generative AI might increase global inequality, because: (1) richer countries are better equipped to harness AI’s benefits; (2) poorer countries may be less prepared to handle AI’s disruptions; and (3) AI is intensifying pressure on traditional development models.

I have a lot of sympathy for these arguments, but it is worth exploring them in a bit more detail. Here's part of what Schellekens and Skilling said on the first reason:

High-income countries, along with wealthier developing nations, hold a distinct advantage in capturing economic value from AI thanks to superior digital infrastructure, abundant AI development resources, and advanced data systems...

When many people may think about economic growth, we think about catch-up growth. Developing countries often have growth rates that exceed those in developed countries. There are vivid examples of catch-up growth, like the way many developing countries were able to bypass copper telephone lines and move straight to mobile telecommunications. Could AI be like that? It's a hopeful vision. However, the problem with that argument is that AI isn't quite the same as the telecommunications example. There is no outdated technology that is being replaced by AI (unless humans count?). So, developing countries can't leapfrog technology and catch up. If a country doesn't have the technology infrastructure and capital necessary to develop their own AI models, they will be forced to use models developed in other countries. That creates problems for developing countries, and Schellekens and Skilling note two particular concerns:

First, AI could reinforce the dominance of wealthier nations in high-value sectors like finance, pharmaceuticals, advance manufacturing, and defense. As richer countries use AI to enhance productivity and innovation, it becomes harder for poorer countries to penetrate these markets.

Second, while AI is poised to primarily disrupt skill-intensive jobs more prevalent in advanced economies, it can also undermine lower-cost labor in developing countries. Automation in manufacturing, logistics, and quality control would enable wealthier nations to produce goods more efficiently, reducing the need for low-wage foreign workers. This shift, supported by AI-driven predictive analytics and customization capabilities, may allow richer countries to outcompete on cost, speed, and product desirability.

Note that second argument says that in spite of any increase in inequality within developed countries (which is what the general public was most concerned about in my previous post), there would be increases in global inequality because of the differential impact on different labour markets. This is a consequence of past labour market polarisation, where different countries have become reliant on employment in different sectors.

On their second point, Schellekens and Skilling note that, while the social safety net in developed countries may insulate their populations from the negative impacts of AI (a point that I'm not sure that many would agree with), the situation in developing countries is quite different:

Limited resources and underdeveloped social protection systems mean they are less equipped to absorb the economic and social shocks caused by AI-driven disruptions. Many lower-income countries already struggle with high rates of informal employment and fragile labor markets, leaving workers highly vulnerable to sudden economic shifts.

The lack of fiscal space also restricts these countries from investing in crucial areas like reskilling programs, infrastructure upgrades, or targeted welfare schemes to support affected communities. Without such mechanisms, the impact of AI-related job losses could exacerbate unemployment and deepen poverty.

It would be interesting to see some research on the expected impact of generative AI on informal sector employment, but I except that Schellekens and Skilling are largely correct about the impacts on formal sector employment in developing countries.

Finally, on their third point, Schellekens and Skilling note that the model of development that many countries have followed in recent decades, moving first from an agrarian economy, into low-technology manufacturing (like garments), and then into higher-technology manufacturing over time, has become less viable for developing countries over time, and that generative AI may impact the obvious alternative, which is export-oriented service industries:

Countries like the Philippines and India have seen success in business process outsourcing, thanks to booming call center industries and IT services. But AI poses a threat to this model as well. AI has the potential to reduce the labor intensity of these activities, eroding the competitive edge in the international marketplace of lower-cost service providers.

If AI were to undermine labor-intensive service industries, developing countries may find it harder to identify viable pathways for growth, posing a significant challenge to long-term development and dampening the prospects of convergence.

The conclusion here is that generative AI may not only increase within-country inequality, but because of the differential impact on developed and developing countries, it may increase between-country inequality as well. This would potentially reverse decades of declining global inequality (see here and here).