Bridging Technology and Social Sciences: Applications of AI, Data Analysis, and Policy Evaluation
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Abstract
This review examines the interdisciplinary integration of artificial intelligence, data analytics, and policy evaluation across social sciences, engineering, energy, and urban planning. We highlight applications ranging from personalized recommendation systems and market-oriented strategies to urban mobility optimization, gig economy interventions, digital platform engagement, biomedical prediction, autonomous systems, renewable energy assessment, and socioeconomic policy analysis. By synthesizing evidence from diverse domains, we demonstrate how AI and data-driven methodologies enhance decision-making, optimize operational efficiency, and support sustainable and socially responsible outcomes. The review also identifies future research directions, emphasizing multi-modal data integration, cross-domain methodology transfer, intelligent system deployment, and the collaboration between technological development and social science to address complex socio-technical challenges.
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