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Governing Artificial Intelligence to benefit the UN Sustainable Development Goals

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  • Jon Truby

Abstract

Big Tech's unregulated roll‐out out of experimental AI poses risks to the achievement of the UN Sustainable Development Goals (SDGs), with particular vulnerability for developing countries. The goal of financial inclusion is threatened by the imperfect and ungoverned design and implementation of AI decision‐making software making important financial decisions affecting customers. Automated decision‐making algorithms have displayed evidence of bias, lack ethical governance, and limit transparency in the basis for their decisions, causing unfair outcomes and amplify unequal access to finance. Poverty reduction and sustainable development targets are risked by Big Tech's potential exploitation of developing countries by using AI to harvest data and profits. Stakeholder progress toward preventing financial crime and corruption is further threatened by potential misuse of AI. In the light of such risks, Big Tech's unscrupulous history means it cannot be trusted to operate without regulatory oversight. The article proposes effective pre‐emptive regulatory options to minimize scenarios of AI damaging the SDGs. It explores internationally accepted principles of AI governance, and argues for their implementation as regulatory requirements governing AI developers and coders, with compliance verified through algorithmic auditing. Furthermore, it argues that AI governance frameworks must require a benefit to the SDGs. The article argues that proactively predicting such problems can enable continued AI innovation through well‐designed regulations adhering to international principles. It highlights risks of unregulated AI causing harm to human interests, where a public and regulatory backlash may result in over‐regulation that could damage the otherwise beneficial development of AI.

Suggested Citation

  • Jon Truby, 2020. "Governing Artificial Intelligence to benefit the UN Sustainable Development Goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 946-959, July.
  • Handle: RePEc:wly:sustdv:v:28:y:2020:i:4:p:946-959
    DOI: 10.1002/sd.2048
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    References listed on IDEAS

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    Cited by:

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    6. Peter Seele & Mario D. Schultz, 2022. "From Greenwashing to Machinewashing: A Model and Future Directions Derived from Reasoning by Analogy," Journal of Business Ethics, Springer, vol. 178(4), pages 1063-1089, July.
    7. Serena Strazzullo & Sérgio Moro & Livio Cricelli, 2023. "Unveiling the relationship between sustainable development and Industry 4.0: A text mining literature analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(4), pages 2851-2862, August.
    8. Crumbly, Jack & Pal, Raktim & Altay, Nezih, 2025. "A classification framework for generative artificial intelligence for social good," Technovation, Elsevier, vol. 139(C).
    9. Leonie N. Bossert & Thilo Hagendorff, 2023. "The ethics of sustainable AI: Why animals (should) matter for a sustainable use of AI," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(5), pages 3459-3467, October.
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    13. Basilio Ruiz de Apodaca, Oihana & Montes Gan, Vicente J & Moreno-Brieva, Fernando, 2025. "Non-hierarchic leadership collaboration: Exploring the adoption of AI-driven social networking for addressing social challenges in an extra-organizational environment," Technology in Society, Elsevier, vol. 81(C).
    14. Stefano Bianchini & Giacomo Damioli & Claudia Ghisetti, 2023. "The environmental effects of the “twin” green and digital transition in European regions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 877-918, April.
    15. Haochen Guo & Petr Polak, 2023. "Intelligent finance and change management implications," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    16. Akter, Shahriar & Hossain, Md Afnan & Sajib, Shahriar & Sultana, Saida & Rahman, Mahfuzur & Vrontis, Demetris & McCarthy, Grace, 2023. "A framework for AI-powered service innovation capability: Review and agenda for future research," Technovation, Elsevier, vol. 125(C).
    17. Barbieri, Roberta & Coluccia, Benedetta & Natale, Francesco, 2025. "How are smart city policies progressing in Italy? Insights from SDG indicators," Land Use Policy, Elsevier, vol. 148(C).
    18. M. Eshaq Stanikzai & Ella Mittal, 2025. "Leveraging AI-generated and human-generated content for maximized user engagement in contentpreneurs’ innovation and creativity," Journal of Innovation and Entrepreneurship, Springer, vol. 14(1), pages 1-28, December.
    19. Qiang Wang & Fuyu Zhang & Rongrong Li, 2025. "Artificial intelligence and sustainable development during urbanization: Perspectives on AI R&D innovation, AI infrastructure, and AI market advantage," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(1), pages 1136-1156, February.
    20. Grazia Dicuonzo & Francesca Donofrio & Antonio Fusco & Vittorio Dell?Atti, 2021. "Big data and artificial intelligence for health system sustainability: The case of Veneto Region," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 31-52.
    21. Zhang, Cong & Yang, Jianhua, 2024. "Artificial intelligence and corporate ESG performance," International Review of Economics & Finance, Elsevier, vol. 96(PC).
    22. A. Jiran Meitei & Pratibha Rai & S. S. Rajkishan, 2025. "Application of AI/ML techniques in achieving SDGs: a bibliometric study," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(1), pages 281-317, January.

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