AI and inequality between the Global North and SouthCEFR B1
7 Nov 2025
Adapted from Abdallah Abdallah, Global Voices • CC BY 3.0
Photo by The New York Public Library, Unsplash
Artificial intelligence promises major economic change, but its benefits are not distributed equally between the Global North and the Global South. The article links current attitudes to history, describing two ways nations relate to technology: a “Protestant pedagogy” that allows adaptation to local needs, and a “Catholic pedagogy” that creates dependence. Acemoglu and Robinson discuss related themes in Why Nations Fail (2012).
Today the divide appears in forecasts and infrastructure. The World Economic Forum estimates AI could add USD 15.7 trillion to the global economy by 2030, with high‑income countries gaining most. Africa generates substantial data but only 2 percent of data centers are located there. Delegates at COSAA 2025 expressed strong skepticism about who will gain, and the article highlights that data labourers and gig drivers in Africa face large inequalities compared with workers in the Global North.
Concrete examples underline uneven control. AFRINIC was created to support digital sovereignty in Africa, yet nearly 7 million IPv4 addresses acquired from AFRINIC by Cloud Innovation — founded by Lu Heng and registered in the Seychelles — are mostly operated in Asia and leased to firms in China, the Philippines, and Hong Kong. Policy also affects access: the Biden administration’s January 2025 Interim Final Rule limits advanced chip distribution and creates tiers, with over 90 percent of Tier 1 countries having unrestricted access and many Global South states placed in Tier 2 with limits. The article adds that current US President Donald Trump plans to scrap this system and negotiate directly, a move that may not deliver greater equity.
To address these gaps the article calls for inclusive governance: transparency, fairness, human oversight and regional cooperation, and for the United Nations to work with regional bodies to improve data standards, protection and participation so AI can better support equitable development.
Difficult words
- economic — Related to money and resources.
- inequalities — Differences in social or economic status.
- development — The process of improving or growing.develop
- governance — The act of managing or controlling.
- collaboration — Working together towards a common goal.
- technology — Tools and machines that help people.
- benefits — Advantages or good results from something.
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- How can technology help reduce inequalities?
- What might happen if AI benefits continue to be unequal?
- Why is collaboration important in AI development?
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