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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17930905 |
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Table of Contents:
- <p><span>The rapid advancement of digital technologies has fundamentally transformed the landscape of public governance. In modern governments and digital societies, big data and intelligent systems have emerged as critical instruments for improving the design and evaluation of public policies. This study examines how the integration of large-scale data analytics, artificial intelligence, and intelligent decision-support systems enhances evidence-based policymaking, policy effectiveness, and governmental responsiveness. Big data, derived from diverse sources such as administrative records, social media, sensors, and digital platforms, enables policymakers to better understand complex social dynamics, identify emerging policy problems, and design targeted interventions. Intelligent systems further support this process by applying machine learning and predictive analytics to forecast policy outcomes, optimize resource allocation, and reduce uncertainty in decision-making.</span><em><span dir="RTL"> </span></em><span>The article highlights the role of these technologies across different stages of the public policy cycle, particularly in policy formulation and evaluation. In policy design, data-driven insights facilitate more precise problem definition and scenario analysis, while in policy evaluation, continuous data streams allow for real-time monitoring, performance measurement, and impact assessment. This shift from traditional, retrospective evaluation methods to dynamic and adaptive evaluation frameworks enhances accountability and institutional learning.</span><em><span dir="RTL"> </span></em><span>Moreover, the use of big data and intelligent systems contributes to digital governance by increasing transparency and enabling greater citizen participation through open data initiatives and digital feedback mechanisms. However, the study also emphasizes key challenges, including data privacy risks, algorithmic bias, ethical concerns, and limitations in institutional capacity. Addressing these challenges requires robust data governance frameworks, ethical guidelines, and investment in technical and human capabilities. Overall, the article argues that while big data and intelligent systems hold significant potential to transform public policymaking, their successful adoption depends on balancing technological innovation with democratic values, social equity, and public trust.</span></p>