Utilizing AI for Social Good: Tackling Global Issues and Fostering Inclusive Solutions

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Md.Mafiqul Islam

Abstract

This research delves into the intricate influence of Artificial Intelligence (AI) on community development across vital sectors such as healthcare, education, environmental sustainability, and community empowerment. Its core aim is to comprehensively analyze how individuals in underserved communities perceive and experience the use of AI technologies. To achieve this, a mixed-methods approach is adopted, combining quantitative surveys for statistical insights with qualitative narratives for nuanced perspectives. Engaging 120 participants from diverse backgrounds and age groups, the research methodology incorporates Likert scales and regression analysis for data interpretation. The study reveals a prevalent positive outlook on AI's impact across various domains, particularly highlighting its significant effects on healthcare, education, and environmental sustainability. Integration of qualitative narratives enriches the findings, offering depth and context to statistical analyses. Its novelty lies in the comprehensive examination of AI's influence on community development, seamlessly blending quantitative and qualitative dimensions. By providing nuanced insights into AI's multifaceted role in community contexts, the research significantly contributes to the field. Ultimately, the study underscores the importance of responsible AI deployment, aligned with community values, to navigate the evolving technological landscape and foster sustainable community development.

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Islam, M. (2024). Utilizing AI for Social Good: Tackling Global Issues and Fostering Inclusive Solutions . Journal of Artificial Intelligence General Science (JAIGS) ISSN:3006-4023, 3(1), 234-255. https://doi.org/10.60087/jaigs.vol03.issue01.p255
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How to Cite

Islam, M. (2024). Utilizing AI for Social Good: Tackling Global Issues and Fostering Inclusive Solutions . Journal of Artificial Intelligence General Science (JAIGS) ISSN:3006-4023, 3(1), 234-255. https://doi.org/10.60087/jaigs.vol03.issue01.p255

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