Proceedings of the International Conference on Public Organization (ICONPO 2021)

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A Study on the Optimization Path of Artificial Intelligence Governance in the Public Policy Perspective

Authors
Zhen Zhen Liu1, *, Shi Ling Peng2
1, 2School of Public Administration, University of Electronic Science and Technology of China
*Corresponding author. Email: 956496454@qq.com, 2746364200@qq.com
Corresponding Author
Zhen Zhen Liu
Available Online 1 March 2022.
DOI
10.2991/aebmr.k.220209.014How to use a DOI?
Keywords
Public Policy; Artificial Intelligence; Governance; Optimized path
Abstract

The development and application of artificial intelligence (“AI”) has not only brought fundamental changes in the economic, social and political fields, but also provided technological support for the reconstruction of public policies. The pace of development of artificial intelligence is bound to rise to a whole new level with the corresponding introduction of strategic planning for artificial intelligence in China in recent years. However, with the development of AI technology, many social challenges and potential risks are arising from it. Consequently, the measures to handle those risks and challenges need to be focused on, hence the importance of implementing the optimal path of AI application in the public policy perspective. We aim to explore the multiple governance subjects and governance mechanisms of population intelligence, and break the long-standing concerns about AI. We hope to be able to help the optimization of the development of AI and its use for the government activities. This paper attempts to analyze the logic of AI development in the public policy perspective as well as the risk and challenges of it, and discusses the plausible paths in optimizing the use of AI in governance matters in the future.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Public Organization (ICONPO 2021)
Series
Advances in Economics, Business and Management Research
Publication Date
1 March 2022
ISBN
978-94-6239-544-2
ISSN
2352-5428
DOI
10.2991/aebmr.k.220209.014How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

risenwbib
TY  - CONF
AU  - Zhen Zhen Liu
AU  - Shi Ling Peng
PY  - 2022
DA  - 2022/03/01
TI  - A Study on the Optimization Path of Artificial Intelligence Governance in the Public Policy Perspective
BT  - Proceedings of the International Conference on Public Organization (ICONPO 2021)
PB  - Atlantis Press
SP  - 97
EP  - 103
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220209.014
DO  - 10.2991/aebmr.k.220209.014
ID  - Liu2022
ER  -