City-scale AI Development and Regional AI Divide Assessment Datasets for China’s 283 Cities from 2003 to 2023

Artificial intelligence (AI) has become a key driver of urban development in the digital age. Meanwhile, the uneven development of AI among cities is creating a new “digital divide”. As one of the pioneering countries in AI development, China has seized the opportunities presented by urban AI development while also encountering the challenge of a regional AI divide. This provides a unique context for the trajectory and spatial layout of regional AI development. However, existing city-scale AI development index assessments generally use a single indicator and have limitations such as insufficient indicator relevance, short coverage period, and lack of regional AI divide assessment. This study constructed a Chinese city-scale AI development index assessment dataset containing 283 cities and a province-scale regional AI divide dataset for 26 provinces from 2003 to 2023. hese datasets encompassed a composite indicator system and evaluation method consisting of three metrics: the number of AI enterprises, the number of patent applications, and the industrial robot installation density, and utilized the Dagum-Gini coefficient method to assess the regional AI divide index. These datasets can comprehensively assess the situation and development trends of AI development in Chinese cities and the regional AI divide, providing data support for academic research related to regional AI development and government policy-making.人工智能（Artificial Intelligence）已成为数字时代城市发展的核心驱动力。与此同时，各城市间人工智能发展的不均衡性正催生全新的“数字鸿沟”。作为人工智能发展的先驱国家之一，中国在把握城市人工智能发展机遇的同时，也面临着区域人工智能发展差距的挑战。这为研究区域人工智能发展的演进路径与空间布局提供了独特的研究语境。然而，现有城市级人工智能发展指数评估大多采用单一指标体系，存在指标关联性不足、覆盖周期较短、缺乏区域人工智能差距评估等局限。本研究构建了涵盖2003年至2023年、覆盖283个中国城市的城市级人工智能发展指数评估数据集，以及针对26个省份的省级区域人工智能差距数据集。本数据集采用由人工智能企业数量、专利申请数量以及工业机器人安装密度三项指标构成的复合指标体系与评估方法，并运用达古姆-基尼（Dagum-Gini）系数法测算区域人工智能差距指数。该数据集可全面评估中国城市人工智能发展现状与发展趋势，以及区域人工智能发展差距情况，可为区域人工智能发展相关学术研究及政府决策提供数据支撑。