AI for Development Planning Systematic Review

This dataset was curated specifically for the study presented in the paper, Decoding Development: The AI Frontier in Policy Crafting - A Systematic Review. It comprises 208 peer-reviewed publications that examine the integration of artificial intelligence (AI) and machine learning (ML) in policy planning and development. Each dataset entry includes detailed metadata, such as planning context, policy planning stage (e.g., problem diagnosis, resource allocation, outcome projection), specific Sustainable Development Goals (SDGs) addressed, and documented applications of AI/ML models. Systematically constructed, the dataset enables cross-sectional and comparative analyses, capturing the distribution and intensity of AI/ML applications across different stages of the policy planning cycle and economic contexts. By organizing data on each publication’s thematic focus and methodological approaches, this dataset facilitates a nuanced analysis of research trends, identifies existing gaps, and examines the role of smart algorithms in advancing development-oriented policy.

本数据集旨在为论文《解码发展：政策制定中的AI前沿——系统综述》的研究提供支持。该数据集汇集了208篇经过同行评审的出版物，旨在探讨人工智能（AI）与机器学习（ML）在政策规划和制定过程中的融合。每个数据集条目均包含详尽的元数据，例如规划背景、政策规划阶段（例如，问题诊断、资源分配、结果预测）、针对的具体可持续发展目标（SDGs）以及AI/ML模型的记录应用。该数据集的系统性构建使得可以进行横断面和比较分析，捕捉AI/ML在不同政策规划周期和经济环境中的应用分布和强度。通过组织每篇出版物主题关注点和方法论方法的数据，本数据集有助于对研究趋势进行细致分析，识别现有差距，并探讨智能算法在推动以发展为导向的政策中的作用。