Bridging the AI divide calls for global governance and knowledge sharing

Artificial Intelligence (AI) could contribute up to $15.7tn to the global economy by 2030. While all regions of the global economy stand to benefit from AI, North America and China will see the largest GDP gains, according to a World Economic Forum (WEF) report in 2023.

AI could widen the gaps between developed and developing countries, a UN report said last week, calling for policy measures to limit the impact.

Annually, more than $300bn is spent globally on technology to enhance computing capacity, but these investments are focused mainly on higher-income nations, creating a disparity in access to infrastructure and skills development that puts developing countries and their homegrown start-ups at a severe disadvantage.

The report by the United Nations Development Programme (UNDP) warns of a possible "great divergence” emerging between nations in terms of economic performance, people’s skill sets and governing systems.

"We think that AI is heralding a new era of rising inequality between countries, following years of convergence in the last 50 years,” says Philip Schellekens, Chief Economist for UNDP Asia Pacific Regional Bureau.

But the UNDP report also notes that trade, technology and development have helped close gaps between states in recent decades, bringing major income, health and education gains.

The AI revolution could widen the gap between high and low-income countries unless co-operative international action is taken, according to an earlier report from the International Labour Organisation and the UN Office of the Secretary General’s Envoy on Technology.

The report on the AI divide with a global perspective found that the technology is revolutionising industries worldwide, offering tremendous opportunities for innovation and productivity.

However, AI is also exacerbating economic and social inequalities due to uneven rates of investment, adoption, and use.

The emerging "AI divide” means high-income nations disproportionately benefit from AI advancements, while low- and medium-income countries, particularly in Africa, lag behind. The workplace is where AI can lead to productivity gains and improved working conditions.

Unequal access to infrastructure, technology, quality education, and training, however, could lead to uneven adoption of AI, which would, in turn, deepen inequalities globally.

The 2023 WEF report on The ‘AI divide’ between the Global North and the Global South found that the economic and social benefits of AI remain geographically concentrated, primarily in the Global North. Without an enabling operating environment, disparities in AI readiness will feed into global inequality.

One of the root causes of this "AI divide” is found in structural limitations, as there are marked gaps between the Global North and Global South.

Successful adoption of AI on a scaled level requires a demanding infrastructure that has elements of technical infrastructure, models and tools, data, and talent and capacity.

On top of that, policies and guidelines are essential to ensuring trustworthiness in regulating new technologies.

In order to successfully implement and scale AI-driven solutions, sound technical infrastructure is necessary.

This includes high capacity computing resources to handle the workloads, large storage capacity to scale as the data grows, a network infrastructure with high bandwidth and low latency to support network communications, and a mature cybersecurity infrastructure to protect sensitive data and prevent abuse.

The cost of implementing such advanced technologies is one of the biggest barriers for resource-constrained countries in the Global South.

There are, however, green shoots of positive changes emerging in bridging the gap. The 2024 Oxford Insights assessment of 188 countries around the world and their preparedness in using AI in public services highlights that AI strategies are on the rise again, with growing momentum across low- and middle-income countries.

As AI advances, global governance and international collaboration and knowledge-sharing are becoming essential for effective and responsible adoption.

Looking forward, these efforts will be critical in addressing the gaps in technology governance, as more countries formalise AI strategies and strengthen their capacity to adopt AI effectively.