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Governing Artificial Intelligence in an Age of Inequality

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  • Padmashree Gehl Sampath

Abstract

This article seeks to position both AI‐based activities, and related policy developments, in the global South in light of a technology industry with desires for continuous expansion and self‐governance. The article proceeds along three themes. First, using field interviews and related information (in an anonymised manner), the article classifies expanding AI activities in several core sectors by businesses, governments and other agencies in the global South into three categories. Next, it reviews the current AI policy priorities and positions in developing countries, showing how the introduction of AI has been punctuated by considerations of digital cannibalization by large firms from the North at the expense of a full‐fledged debate on privacy and data protection. By showing how AI exemplifies structural inequality in the global South, the article identifies four critical departure points in developing countries that make the expanding use of AI a matter of concern. While many of challenges posed by AI are somewhat universal, the article argues that their ramifications can be much worse in the global South. Countering these will require policy frameworks that factor in privacy protection in a more accountable manner. It concludes with suggestions for a more nuanced debate on industrialisation, privacy protection and development.

Suggested Citation

  • Padmashree Gehl Sampath, 2021. "Governing Artificial Intelligence in an Age of Inequality," Global Policy, London School of Economics and Political Science, vol. 12(S6), pages 21-31, July.
  • Handle: RePEc:bla:glopol:v:12:y:2021:i:s6:p:21-31
    DOI: 10.1111/1758-5899.12940
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    References listed on IDEAS

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    1. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
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    5. Larsson, Stefan, 2018. "Algorithmic governance and the need for consumer empowerment in data-driven markets," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 7(2), pages 1-13.
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    Cited by:

    1. Xiaojun Li, 2026. "Public Trust in Global AI Governance Across Geopolitical Rivals," Global Policy, London School of Economics and Political Science, vol. 17(1), pages 36-46, February.
    2. Carè, Rosella & Boitan, Iustina Alina & Stoian, Andreea Maria & Fatima, Rabia, 2025. "Exploring the landscape of financial inclusion through the lens of financial technologies: A review," Finance Research Letters, Elsevier, vol. 72(C).
    3. Andrew J. Keith, 2024. "Governance of artificial intelligence in Southeast Asia," Global Policy, London School of Economics and Political Science, vol. 15(5), pages 937-954, November.
    4. Wang, Shangrui & Zhang, Yuanmeng & Xiao, Yiming & Liang, Zheng, 2025. "Artificial intelligence policy frameworks in China, the European Union and the United States: An analysis based on structure topic model," Technological Forecasting and Social Change, Elsevier, vol. 212(C).

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