OPPORTUNITIES, CHALLENGES, AND RESPONSE PATHWAYS FOR URBAN MANAGEMENT IN THE AGE OF ARTIFICIAL INTELLIGENCE

Authors

  • MingKang Yuan (Corresponding Author) School of Public Administration, Xiangtan University, Xiangtan 411105, Hunan, China.

Keywords:

Artificial intelligence, Urban management, Intelligent governance, Algorithmic risk

Abstract

Artificial intelligence is profoundly reshaping the paradigm of urban governance. On one hand, AI brings efficiency gains, resource optimization, and enhanced resilience — automated administration, precise services, and intelligent operations make cities run more efficiently. On the other hand, the accompanying risks cannot be ignored: algorithm optimization, responsible data governance, transparent decision-making, and inclusive digital development. These challenges highlight the importance of balancing technological innovation with public values. To overcome this predicament, a shift toward a people-centered governance paradigm is needed, where human-AI collaboration and inclusive governance establish a dynamic balance between efficiency and equity, innovation and regulation.

References

[1] Zhang X H. ChatGPT-like AI technology embedded in digital government governance: Value, risks, and prevention and control. E-Government, 2023(04): 45-56.

[2] Zhao J W, He A X. Digital government governance theory and model innovation under the "intelligentization tournament": An analysis based on the "DeepSeek + government affairs" practice. E-Government, 2025(06): 16-30.

[3] Dong C Q, Li D Y, Mi J N. Large model embedding in government services: Capability boundaries, collaborative governance, and development pathways: Based on observations of large-scale local government deployment of DeepSeek. E-Government, 2025(08): 13-21.

[4] Zhang S Z, Ma Y Y, Liu H. DeepSeek empowering government services: Scenario reconstruction, operational logic, and advancement pathways. Modern Urban Research, 2025(07): 50-56.

[5] Yigitcanlar T, Desouza K, Mossberger K, et al. Artificial intelligence and the city: An editorial perspective. Journal of Urban Technology, 2025, 32(1): 1-12.

[6] Yigitcanlar T, Senadheera S, Marasinghe Pelige R, et al. Artificial intelligence and the local government: A five-decade scientometric analysis. Cities, 2024, 150: 105017.

[7] Wolniak R, Stecuła K. Artificial intelligence in smart cities—Applications, barriers, and future directions: A review. Smart Cities, 2024, 7(3): 1346-1389.

[8] Wei Y S. Advantages, dilemmas, and response strategies of government governance algorithmization in the intelligent age. Public Administration and Policy Review, 2024, 13(04): 24-38.

[9] Peng Y P. The birth of perceptual politics: Technology governance in the era of human-machine collective intelligence. Journal of Nanjing University (Philosophy, Humanities and Social Sciences), 2025, 62(06): 87-95, 163.

[10] He N, Yao C L. AI large models empowering urban digital governance: Internal logic, practical challenges, and implementation pathways. Dongyue Tribune, 2025, 46(05): 184-190.

[11] Zhang C Y, Cai Q M, Yang L. Smart city construction and residents' happiness: An empirical analysis based on CLDS data. Social Sciences, 2023(01): 128-140.

[12] Huang X H, Wang L C. Algorithmic governance in public administration: Rise, risks, and regulation. Journal of Beijing Administrative College, 2025(01): 64-72.

[13] Zang L Z, Chen H. Generative AI algorithmic risks and social governance challenges. Journal of the Party School of the Central Committee of the C.P.C. (Chinese Academy of Governance), 2025, 29(01): 43-53.

[14] Alon-Barkat S, Busuioc M, Schwoerer K, et al. Algorithmic governance in public service provision: Understanding citizens’ attribution of responsibility for human versus algorithmic decision-making. Journal of Public Administration Research and Theory, 2025, 35(3): 273-289.

[15] Kuang Y L, Meng C Y. The construction of a digitally inclusive aging society from a global perspective: Evolution, issue focus, and pathway exploration. E-Government, 2025(06).

[16] Duan Z Z. Controlling algorithm-enabled governance: Dilemmas and pathways. E-Government, 2021(12): 2-16.

[17] Zhang Z, Guan Z X. Legal regulation of digital governance in mega-cities. Journal of Chongqing University (Social Science Edition), 2025, 31(04): 251-264.

[18] Lü P. Core concepts and practical pathways of intelligent social governance. Journal of Central China Normal University (Humanities and Social Sciences), 2025, 64(05): 177-188.

[19] Yang J, Liu J N. The realization of people-centeredness: Research on human-AI collaborative pathways and public decision-making models in urban social governance. Academic Research, 2025(06): 67-75, 99.

[20] Liu W, Zhao X F. A new approach to generative governance for complex social fields: Exploring governance methods based on generative AI. Journal of Public Administration, 2025, 22(01): 102-114.

[21] Yang L, Meng S F, Li Y. "Power-algorithm" adaptive survival: The human-AI co-governance mechanism in smart governance of urban villages in mega-cities: A case study of T Village in Tianjin. E-Government, 2025.

[22] Keppeler F, Borchert J, Pedersen M J, et al. How ensembling AI and public managers improves decision-making. Journal of Public Administration Research and Theory, 2025, 35(3): 289-307.

[23] Tan X Y. Generative AI large models embedded in social governance: Empowering scenarios, risk patterns, and regulatory pathways. Jinan Journal (Philosophy and Social Sciences), 2024, 46(12): 97-111.

[24] Wang L Z, Xu C M. Cross-departmental collaboration: Operational mechanisms and practical pathways of smart city governance in China. Journal of Beijing Normal University (Social Sciences), 2024(06): 146-156.

[25] Wu P Y, Shen H M, Liang Z. Agile governance of government large models: A multi-case analysis based on "data-scenarios". E-Government, 2025(08): 2-12.

[26] Lee J W, Lee K. Building a consensus: Harmonizing AI ethical guidelines and legal frameworks in Korea for enhanced governance. Government Information Quarterly, 2025, 42(3): 102060.

[27] Bian X, Wang B, Yang A. The trust trifecta: How transparency, ethics, and benefits shape public confidence in government AI. Government Information Quarterly, 2025, 42(4): 102083.

[28] Almeida P G R, Santos Júnior C D. Artificial intelligence governance: Understanding how public organizations implement it. Government Information Quarterly, 2025, 42(1): 102003.

[29] David A, Yigitcanlar T, Desouza K, et al. Understanding local government responsible AI strategy: An international municipal policy analysis. Cities, 2024, 154: 105097.

Downloads

Published

2026-07-30

How to Cite

MingKang Yuan. Opportunities, Challenges, And Response Pathways For Urban Management In The Age Of Artificial Intelligence. Trends in Social Sciences and Humanities Research. 2026, 4(6): 11-17. DOI: https://doi.org/10.61784/tsshr3250.