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The Socio-Economic Impact of AI on Developing Economies
This paper contributes to the literature by: Exploring AI's Dual Impact: It provides a balanced analysis of both the opportunities and challenges posed by Artificial Intelligence (AI) in developing economies, addressing gaps in existing literature that often emphasize one perspective over the other. Contextualizing AI in Developing Nations: By focusing on the unique socio-economic contexts of developing economies, it bridges the gap between global AI advancements and their localized applications. This contextual approach is essential for crafting policies that resonate with regional realities. Highlighting Sector-Specific Innovations: The paper delves into sector-specific examples such as precision agriculture, healthcare, and financial inclusion, showcasing how AI drives innovation in areas critical to developing nations' growth. Addressing Ethical and Regulatory Dimensions: Unlike many existing studies that focus on technological capabilities, this paper underscores the ethical challenges, such as algorithmic bias and data privacy, providing a comprehensive view of AI's implications. Offering Strategic Recommendations: It proposes actionable strategies for inclusive AI adoption, emphasizing education, local innovation ecosystems, and international cooperation, thus serving as a practical guide for policymakers, researchers, and stakeholders. Incorporating Case Studies: Through examples like Kenya’s M-Pesa and India’s precision agriculture initiatives, the paper enriches the literature with real-world instances that highlight AI’s transformative potential and limitations. Encouraging Interdisciplinary Dialogue: By intersecting technology, economics, and ethics, this paper invites a multidisciplinary discourse on AI's role in fostering sustainable development in underrepresented regions. These contributions make the paper a valuable addition to ongoing discussions on leveraging AI for equitable global development.
