Dr. Gyan Pathak

The Artificial Intelligence revolution could further widen the gap between high and low-income countries, a new joint report from International Labour Organization (ILO) and the UN Office of the Secretary General’s Envoy on Technology has warned, unless cooperative international action is taken to address uneven and low level of investment in technology.

The report titled “Mind the AI Divide: Shaping a Global Perspective on the Future of Work” has also said that AI-driven changes in workplace must also respect worker’s rights.

It notes the rapid advancement of AI which promises widespread transformations for our societies, our economies and the world or work, but also warns that the uneven rates of investment, adoption and use among countries risks exacerbating the already wide disparities in income and quality of life.

Pointing out the emerging “AI divide”, where high income nations disproportionately benefit, while low- and medium-income countries lag behind, the report warns that this divide will grow unless concerted action is taken to foster international cooperation in support of developing countries.

The absence of such policies will not only widen global inequalities, but risks squandering the potential of AI to serve as a catalyst for widespread social and economic progress.

While AI will potentially affect many aspects of our daily lives, its impact is likely to be most acute in the workplace. According to an analysis undertaken by the ILO on the potential exposure of tasks to generative AI technology, clerical support workers are the most exposed occupational group with 24per cent of the tasks in these jobs associated with high level of exposure to automation and another 58 per cent with medium-level exposure.

Other occupational groups are less exposed, with only 1 to 4per cent of tasks considered as having high automation potential, and medium-exposed tasks not exceeding 25 per cent.

With respect to automation, the share of employment that is exposed is highest in Europe and Northern America, reflecting the greater economic and labour market diversification of these regions.

In Latin America, Asia and Africa, the share of employment potential exposed to automation is much smaller, due to the greater share of workers employed in occupations that would not be exposed to generative AI technology such as in agriculture, transport or food vending.

Nevertheless, women’s potential exposure to the automating effects of generative AI technology is much higher, due to their over-representation in clerical occupations. In most regions, the potential exposure of women is more than double that of men’s exposure.

Some of this employment is in business process outsourcing, such as contactor call center work, which is an important part of the economy of several developing countries, including India and the Philippines. The industry is an important source of formal and relatively well-paid employment, particularly for women.

Another finding is that a significantly larger share of total employment is in occupations with high augmentation potential, and this holds across regions, from 10.2 percent in Sub-Saharan Africa to 16.1 percent in Southeastern Asia and the Pacific.

The analysis does not address the potential for new job creation. Thus, while middle-income countries such as India and the Philippines, are more exposed to the automating effects of generative AI technology in their call centre work, their digital infrastructure and skilled workforce can also be an asset for spawning the growth of complementary industries.

Another area of concern is about the impact of AI technology on working conditions and job quality when the technology is integrated into the workplace. While such integration into work tasks can potentially promote more engaging work if routine tasks are automated, it can also be implemented in ways that limits workers’ agency or accelerates work intensity.

Concerns over AI’s integration at the workplace has focused on the growth of algorithmic management, essentially work settings in which “human jobs are assigned, optimized, and evaluated through algorithms and tracked data”.

Algorithmic management is a defining feature of digital labour platforms, but it is also pervasive in offline industries such as the warehousing and logistics sectors.

In warehouses an automated, “voice-picking” system directs warehouse staff to pick certain products in the warehouse, while using data collection to monitor workers and set the pace of work. Besides lacking autonomy to organize their work or set its pace, workers also have little ability to provide feedback or discuss with management about the organization of work.

The integration of generative AI into other fields such as banking, insurance, social services, and customer service more broadly may have a similar effect.

Technological advancements are often felt more immediately at the workplace level and are usually best addressed at the workplace. As a result, whether the effect of technology on working conditions is positive or negative depends in large part on the voice that workers have in the design, implementation and use of technology.

Wealthier countries are more exposed to the potential automating effects of AI in the world of work, but they are also better positioned to realize the productivity gains it offers.

Developing countries, on the other hand, may be temporarily buffered because of a lack of digital infrastructure, but this buffer risks turning into a bottleneck for productivity growth, and more importantly, for the future prosperity of their populations.

Apart from China and India, emerging markets have garnered only a small portion of global investment in advanced technologies. From 2008 to 2017, total venture capital flows to emerging markets, excluding China and India, amounted to just $24 billion, while the United States alone attracted $694 billion during the same period. Annually, more than $300 billion is spent globally on technology to enhance computing capacity.

Ensuring inclusive growth in the future requires proactive measures to empower AI development in countries at the disadvantaged receiving end of the digital divide, fostering digital infrastructure as well as AI skills, and promoting technology transfer and absorption.

Such digital skills can also enable a more positive integration of AI in the workplace, particularly when combined with social dialogue. Social dialogue on the design, implementation and use of technology at the workplace, as well as in the development of regulations essential for ensuring respect of workers’ fundamental rights, is needed.

However, disparities in resources and expertise remain and can hinder AI development in the Global South. By leveraging their advanced AI ecosystems, the Global North can help bridge the gap and empower countries in the Global South to harness AI for sustainable development, while respecting their sovereignty and promoting local innovation ecosystems.