Assessing the Role of Artificial Intelligence in Poverty Eradication (SDG1): A SWOT–Fuzzy SIWEC Framework

Ibrahim Badi; Mouhamed Bayane Bouraima

doi:10.31181/msa31202648

Authors

Ibrahim Badi 1) Department of Mechanical Engineering, Libyan Academy-Misrata, Misrata, Libya Author https://orcid.org/0000-0002-1193-1578
Mouhamed Bayane Bouraima 2) Organization of African Academic Doctors (OAAD), Nairobi, Kenya; 3) International School of Technical Education, Sichuan University of Architectural Technology, Sichuan, China Author https://orcid.org/0000-0002-5801-884X

DOI:

https://doi.org/10.31181/msa31202648

Keywords:

Artificial intelligence, Strengths, Weaknesses, Opportunities, and Threats Analysis, Poverty Eradication, Sustainable Development Goal, Fuzzy Simple Weight Calculation

Abstract

This study adopted a fuzzy-based strategic approach to assess the strengths, weaknesses, opportunities, and threats (SWOT) related to the role of artificial intelligence in eradicating poverty under Sustainable Development Goal (SDG 1). First, 17 SWOT factors are identified based on experts’ opinions and a literature review. Then, data were collected from four domain experts, and a fuzzy simple weight calculation (F-SIWEC) was applied to determine the weight of SWOT factors. The findings reveal that the predictive capabilities of machine learning applied to satellite and aerial imagery (S2), along with the integration of passive data collection and AI-driven analytics for reliable poverty estimation (O5), serve as key enablers of poverty eradication. In contrast, the lack of effective data for measuring poverty in developing countries (W1) and the risk of automation exacerbating income inequality and widening the rich–poor gap (T2) constitute major barriers to achieving this goal. The study makes a meaningful contribution to the decision sciences and management literature by offering practical insights for policymakers in eradicating poverty and concludes by outlining clear avenues for future research.

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References

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