Dilemma and resolution of data governance when embedding artificial intelligence into new industrialization

doi:10.12267/j.issn.2096-5931.2024.12.002

Abstract

Abstract:

China’s new industrialization has entered a new historical stage and is heading towards the high-quality development when artificial intelligence serves as an engine. As one of the key elements driving the development of artificial intelligence, data are rapidly integrating into various aspects such as production, distribution, circulation, consumption, and social service management, becoming the cornerstone for achieving intelligence, automation, and optimizing industrial processes. This article analyzes the current dilemma of traditional and emerging risks of artificial intelligence data in the industrial field, such as “insufficient to use”, “afraid to use”, “difficult to use”, and “unwilling to use” from a systematic research perspective. It points out that the basic logic of governance is to balance development and governance, and reveals governance strategies such as following the “guidance” of legal rules and adopting the “technique” of self-discipline.

Key words: new industrialization, artificial intelligence, data governance

CLC Number:

F49
F424

SUN Xiaotong, GUO Sumin. Dilemma and resolution of data governance when embedding artificial intelligence into new industrialization[J]. Information and Communications Technology and Policy, 2024, 50(12): 7-12.

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URL:

http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2024.12.002

http://ictp.caict.ac.cn/EN/Y2024/V50/I12/7

References 11

[1]	MELISSA H. Google is finally taking action to curb non-consensual deepfakes. MIT Technology Review[EB/OL]. (2024-08-06)[2024-10-10]. https://www.technologyreview.com/2024/08/06/1095774/google-is-finally-taking-action-to-curb-non-consensual-deepfakes/.
[2]	北京智源人工智能研究院. AI大模型行业数据全景扫描[EB/OL]. (2024-10-18)[2024-10-20]. https://github.com/FlagOpen/Awesome-Industry-Dataset/blob/main.
[3]	孔祥俊. 商业数据权:数字时代的新型工业产权[J]. 知识产权, 2022(2):127-128.
[4]	国家知识产权局. 国家知识产权局办公室关于确定2024年数据知识产权试点地方的通知[EB/OL]. (2023-12-21)[2024-10-15]. https://www.cnipa.gov.cn/art/2023/12/29/art_543_189393.html?xxgkhide=1.
[5]	辛勇飞. 中国数据治理规则体系构建:现状、挑战与展望[J]. 学术前沿, 2023(6):4-12.
[6]	祝守宇, 蔡春久. 数据治理工业企业数字化转型之道[M]. 北京: 电子工业出版社, 2020.
[7]	黄群慧, 盛方富. 以科技创新和产业创新深度融合助力发展新质生产力.光明日报[N], 2024-07-16( 11).
[8]	周辉, 孙牧原. 我国的数据治理挑战及其应对[J]. 信息安全研究, 2023, 9(7): 612-617.
[9]	约翰·拉德利. 数据治理:如何设计、开展和保持有效的数据治理计划[M]. 刘晨, 车春雷, 宾军志, 等译. 北京: 清华大学出版社, 2021.
[10]	The Encore Team. Overcoming the top 8 obstacles for data governance in manufacturing[EB/OL]. (2024-09-16)[2024-10-13]. https://www.encorebusiness.com/blog/data-governance-in-manufacturing-overcoming-top-challenges/.
[11]	焦豪, 杨季枫, 王培暖, 等. 数据驱动的企业动态能力作用机制研究:基于数据全生命周期管理的数字化转型过程分析[J]. 中国工业经济, 2021(11):174-192.

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