Analysis of the domestic and international development and status of AI governance

doi:10.12267/j.issn.2096-5931.2023.01.008

Abstract

Abstract:

To improve artificial intelligence (AI) governance can help to promote the healthy development of AI industry. A series of problems in AI governance of China, such as the imperfect governance system, incomplete laws and regulations, imperfect technical means and governance tools, and difficulties in implementation are discussed. The domestic and international development status of AI governance is analyzed. Further, the AI governance content and means are taken as the focuses for the in-depth analysis. At last, relevant suggestions for China’s AI governance are put forward.

Key words: AI governance, data, algorithm, governance means

CLC Number:

TN929.11

ZHANG Pei, LIU Yuanyuan. Analysis of the domestic and international development and status of AI governance[J]. Information and Communications Technology and Policy, 2023, 49(1): 46-51.

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URL:

http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2023.01.008

http://ictp.caict.ac.cn/EN/Y2023/V49/I1/46

Figures/Tables 1

References 14

[1]	中国信息通信研究院, 京东探索研究院. 可信人工智能白皮书[R], 2021.
[2]	王亦菲, 韩凯峰. 数字经济时代人工智能伦理风险及治理体系研究[J]. 信息通信技术与政策, 2021, 47(2): 32-36.
[3]	李雨霏. 人工智能在数据治理中的应用[J]. 信息通信技术与政策, 2019, 45(5): 23-27.
[4]	中国信息通信研究院, 中国人工智能产业发展联盟. 人工智能治理白皮书[R], 2020.
[5]	朱强. 机器学习中的对抗样本防御和隐私保护[D]. 西安: 西安电子科技大学, 2019.
[6]	魏国富, 石英村. 人工智能数据安全治理与技术发展概述[J]. 信息安全研究, 2021, 7(2): 110-119.
[7]	杨强. AI与数据隐私保护: 联邦学习的破解之道[J]. 信息安全研究, 2019, 5(11): 961-965.
[8]	闫树, 吕艾临. 隐私计算发展综述[J]. 信息通信技术与政策, 2021, 47(6): 1-11.
[9]	令狐曦. 机器学习模型测评技术研究与实现[D]. 北京: 北京邮电大学, 2019.
[10]	GOODFELLOW IJ, SHLENS J, SZEGEDY C, et al. Explaining and harnessing adversarial examples. arXiv:1412.6572, 2014.
[11]	PAPERNOT N, MCDANIEL P, GOODFELLOW I, et al. Practical black-box attacks against machine learning[C]. Computer and Communications Security, 2017: 506-519.
[12]	姜妍, 张立国. 面向深度学习模型的对抗攻击与防御方法综述[J]. 计算机工程, 2021, 47(1): 1-11.
[13]	王科迪, 易平. 人工智能对抗环境下的模型鲁棒性研究综述[J]. 信息安全学报, 2020, 5(3): 13-22.
[14]	腾讯研究院. 可解释AI发展报告2022——打开算法黑箱的理念与实践[R], 2022.

国家/ 组织/ 企业	主要文件名称	数据保护	公平、非歧视	安全可控	合法	以人为本、人的自主权	隐私保护	责任	合作促进	透明、可解释和可溯源	正当使用	数据质量	有益可持续	合乎伦理
欧盟	《可信赖人工智能伦理指南》(2019)		●	●		●				●			●
	《人工智能白皮书》(2020)		●			●						●	●	○
	《人工智能法案》(2021)	●	●	●	○		○	○				●		○
美国	《国家人工智能战略计划》(2019)		○					○	○	○				○
	《人工智能原则》(2019)		●	●	●			●		●
	《人工智能伦理原则》(2019)		●	●				●		●	○			○
	《公司使用AI力求真实、公平和公平》(2021)		●		●			○		●				○
中国	《新一代人工智能治理原则》(2019)		○	○			○	○	○					○
	《新一代人工智能行业自律公约》(2020)		○	○			○	○	○				○	○
	《可信AI操作指引》(2020)			○			○	○		○		●
	《深圳经济特区人工智能产业促进条例》(草案)(2021)		○	○			○	○	○			●	○	○
	《新一代人工智能伦理规范》(2021)		●	●	○	●	●	●		○	○	○		●
日本	《人工智能学会伦理原则》(2017)		●	●		●	●	●	●
日本	《人工智能利用原则草案》(2018)		●	●		●	●	●	●	●	●	●
新加坡	《人工智能治理和伦理的三项倡议》(2018)		○			○				○
新加坡	《人工智能治理模式框架》(2019)		○			●				●
OECD	《负责任地管理可信任的AI原则》(2019)		●	●		●		●		●			●
G20	《G20人工智能原则》(2019)		●	●		●		○	●	●			●	○
GPAI	《全球人工智能合作伙伴关系》(2020)	○				●		●				○	○
NATO	《北约人工智能战略》(2021)		○	●	●			●	●	●
谷歌	《人工智能使用原则》(2018)		●	●			●	●					●

国家/ 组织/ 企业	主要文件名称	数据保护	公平、非歧视	安全可控	合法	以人为本、人的自主权	隐私保护	责任	合作促进	透明、可解释和可溯源	正当使用	数据质量	有益可持续	合乎伦理
欧盟	《可信赖人工智能伦理指南》(2019)		●	●		●				●			●
	《人工智能白皮书》(2020)		●			●						●	●	○
	《人工智能法案》(2021)	●	●	●	○		○	○				●		○
美国	《国家人工智能战略计划》(2019)		○					○	○	○				○
	《人工智能原则》(2019)		●	●	●			●		●
	《人工智能伦理原则》(2019)		●	●				●		●	○			○
	《公司使用AI力求真实、公平和公平》(2021)		●		●			○		●				○
中国	《新一代人工智能治理原则》(2019)		○	○			○	○	○					○
	《新一代人工智能行业自律公约》(2020)		○	○			○	○	○				○	○
	《可信AI操作指引》(2020)			○			○	○		○		●
	《深圳经济特区人工智能产业促进条例》(草案)(2021)		○	○			○	○	○			●	○	○
	《新一代人工智能伦理规范》(2021)		●	●	○	●	●	●		○	○	○		●
日本	《人工智能学会伦理原则》(2017)		●	●		●	●	●	●
日本	《人工智能利用原则草案》(2018)		●	●		●	●	●	●	●	●	●
新加坡	《人工智能治理和伦理的三项倡议》(2018)		○			○				○
新加坡	《人工智能治理模式框架》(2019)		○			●				●
OECD	《负责任地管理可信任的AI原则》(2019)		●	●		●		●		●			●
G20	《G20人工智能原则》(2019)		●	●		●		○	●	●			●	○
GPAI	《全球人工智能合作伙伴关系》(2020)	○				●		●				○	○
NATO	《北约人工智能战略》(2021)		○	●	●			●	●	●
谷歌	《人工智能使用原则》(2018)		●	●			●	●					●

[1]	SI Zhiliang. Analysis on the development path of digital economy empowered by digital government construction [J]. Information and Communications Technology and Policy, 2023, 49(1): 17-21.
[2]	LI Shuaizheng, FENG Yesu. Thinking on the path of collaborative construction of digital government and smart city [J]. Information and Communications Technology and Policy, 2023, 49(1): 58-64.
[3]	ZHANG Bin, WEN Nuan, QIU Qin, ZHOU Ying, LI Wenqi. Research and practice of data security management in information and communication enterprises [J]. Information and Communications Technology and Policy, 2022, 48(8): 19-23.
[4]	LIU Xin, CAO Jing, SHAO Zhijie, ZHOU Yuefeng. Anti-ransomware research based on data storage technologies [J]. Information and Communications Technology and Policy, 2022, 48(8): 36-42.
[5]	WANG Wei, CAO Jing, CHENG Geng, LI Xueying. Research on reducing the impact of automated decision on personal information security [J]. Information and Communications Technology and Policy, 2022, 48(8): 52-58.
[6]	WEI Kai, YAN Shu, LYU Ailin. An overview on the market-based allocation of data factor [J]. Information and Communications Technology and Policy, 2022, 48(8): 59-64.
[7]	ZONG Shanshan. Characteristics, challenges and prospects of local legislation on data [J]. Information and Communications Technology and Policy, 2022, 48(8): 65-69.
[8]	LI Meng, SUN Xiaoming. Research progress on quantum walk related algorithms [J]. Information and Communications Technology and Policy, 2022, 48(7): 28-36.
[9]	ZHOU Bohui, YU Le, MA Yusheng, PAN Jiali. Patent situation analysis of data security technology [J]. Information and Communications Technology and Policy, 2022, 48(7): 87-91.
[10]	SU Zhifu. The path selection and rule construction of commercial data protection in the era of data elements [J]. Information and Communications Technology and Policy, 2022, 48(6): 14-26.
[11]	YAO Huanqing, ZHOU Xun. From regulatory data acquisition to regulatory data use [J]. Information and Communications Technology and Policy, 2022, 48(6): 2-7.
[12]	QIN Le, LI Hongyang. Research on key trends of intellectual property governance of the digital economy in US and EU [J]. Information and Communications Technology and Policy, 2022, 48(6): 36-40.
[13]	GUO Zhen, LI Shuaizheng. Thinking on the path of accelerating the development of digital economy based on artificial intelligence [J]. Information and Communications Technology and Policy, 2022, 48(6): 69-74.
[14]	WANG Shanshan, YAN Wenjun, XIAO Youdan. Research on the rules of utilization of enterprise data [J]. Information and Communications Technology and Policy, 2022, 48(6): 8-13.
[15]	LYU Ailin, YAN Shu. Some thoughts on cross-platform interconnection of privacy preserving computing [J]. Information and Communications Technology and Policy, 2022, 48(5): 2-6.