Boundary reconfiguration: new challenges posed by GenAI to open government data

doi:10.12267/j.issn.2096-5931.2025.12.005

Abstract

Abstract:

Against the backdrop of global competition and rapid advancement in artificial intelligence (AI) technologies and applications, generative AI (GenAI) is becoming increasingly dependent on high-quality government data, while simultaneously disrupting the established boundaries of traditional open government data (OGD) practices. Drawing on literature review and logical induction, this paper systematically examines the interactions between GenAI and OGD across the stages of data acquisition, model training, and application. It reveals how GenAI drives a reconfiguration of boundaries in three key dimensions of OGD: the scope of data subjects, data quality governance, and platform infrastructure. By unpacking these dynamics, the study elucidates the profound challenges GenAI poses to OGD initiatives and offers theoretical insights and policy implications for navigating the evolving landscape of government data openness in the age of generative AI.

Key words: open government data, GenAI, AI-Ready

CLC Number:

G203

LYU Wenzeng, YANG Zhengjun. Boundary reconfiguration: new challenges posed by GenAI to open government data[J]. Information and Communications Technology and Policy, 2025, 51(12): 33-39.

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URL:

http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2025.12.005

http://ictp.caict.ac.cn/EN/Y2025/V51/I12/33

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