Research on dynamic perception and early warning technology and legal regulation of risk management in grass-roots social grid empowered by generative artificial intelligence

DOI

10.2991/978-94-6463-578-2_16How to use a DOI?

Keywords

generative artificial intelligence; Grass-roots grid governance; Dynamic forecasting and early warning; Legal regulation

Abstract

The specific contents of the new era Fengqiao experience mainly include upholding the party’s mass line, correctly handling contradictions among the people, relying on the masses, and resolving issues locally. These aspects not only reflect the core concepts of grassroots social governance but also represent the inheritance and development of the traditional “Fengqiao experience”. Grass-roots social grid governance is the innovative development of “Maple Bridge Experience” in the new era, and it is also the concrete embodiment of the modernization of grass-roots social governance system and national governance capacity. In recent years, Dongcheng District of Beijing, Zhoushan City of Zhejiang Province, Zhuji City, Changning District of Shanghai and other places have successively implemented grid governance of grass-roots society, making “small grid” play a “big role” in grass-roots governance and service, and really get through the last mile of serving the masses. Subsequently, the grass-roots social grid governance model blossomed all over the country, and digital and information technology was continuously introduced in the follow-up practice, showing a trend of “grid+digitalization+refinement”. The introduction of digital technology has greatly improved the quality and efficiency of grid governance in grassroots society. Generally speaking, it is a bottom-up practice-oriented development to use digital technology in grass-roots social grid governance in various places, which has achieved remarkable results, but it is difficult to form a set of replicable and popularized experiences due to the lack of systematic, legal, standardized, refined and practical thinking. Therefore, on the basis of clarifying the technical problems and rationalizing the operation mechanism, it is necessary to raise the practical experience to a theoretical and normative level, build a model of grass-roots social grid governance mechanism, including multi-collaboration, consultation and judgment, and democratic consultation mechanism, and formulate guiding norms for grass-roots social grid governance. Especially, it explores the dynamic early warning, forecasting, monitoring and legal regulation scheme of grass-roots grid governance driven by the generative big model. Through the generative artificial intelligence technology, we can more accurately and quickly perceive various risks and dynamic changes in the grass-roots social grid. Empowering through technology will help managers find problems early and respond in time, thus improving the efficiency and accuracy of governance.

Copyright

© 2024 The Author(s)

Open Access

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TY  - CONF
AU  - Lanping Kang
AU  - Anxiang Gu
PY  - 2024
DA  - 2024/12/01
TI  - Research on dynamic perception and early warning technology and legal regulation of risk management in grass-roots social grid empowered by generative artificial intelligence
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Digital Management (ICAIDM 2024)
PB  - Atlantis Press
SP  - 141
EP  - 153
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-578-2_16
DO  - 10.2991/978-94-6463-578-2_16
ID  - Kang2024
ER  -