全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

风险等级下的人工智能法律监管研究
Research on Artificial Intelligence Legal Supervision under Risk Level

DOI: 10.12677/OJLS.2023.113176, PP. 1232-1240

Keywords: 人工智能,风险等级划分,法律监管
Artificial Intelligence
, Risk Classification, Legal Supervision

Full-Text   Cite this paper   Add to My Lib

Abstract:

近十年里,人工智能已成为世界各国科技发展的战略重点,同时监管风险和人工智能技术相伴相生,成为人工智能立法监管的导向。人工智能风险的产生主要是由黑箱模式以及运行中产生的风险共同构成。法律是进行风险防控强有力的工具,针对目前我国人工智能应用广泛、产业规模庞大、监管力量薄弱等现实困境,可以根据风险等级划分不同类型的监管主体,并在明确具体主体的基础上,以政府监管为主体,构建风险评估监管机制。落实人工智能风险等级划分,以期政府、社会和企业在各自的范围内承担起相应的法律责任,共同促进人工智能产业的蓬勃发展。
In the past ten years, artificial intelligence has become the strategic focus of science and technology development in countries around the world. At the same, regulatory risk and artificial intelligence technology are accompanied by each other, which has become the guidance of artificial intelligence legislation and supervision. The risk of artificial intelligence is mainly composed of the black-box and generated in operation. The law is a powerful tool for risk prevention and control. In view of the realistic dilemmas of China’s extensive application of artificial intelligence, huge industrial scale, and weak regulatory force, we can divide different types of regulatory bodies according to the risk level, and on the basis of clarifying the specific subjects, take government supervision as the regulatory body, and build a risk assessment and supervision mechanism. With the implement of the risk classification of artificial intelligence, the government, society and enterprises should assume corresponding legal liabilities within their respective scopes and collectively promote the prosperous development of artificial intelligence.

References

[1]  唐要家, 尹钰峰. 算法合谋的反垄断规制及工具创新研究[J]. 产经评论, 2020(2): 6.
[2]  Daron, A. and Pascual, R. (2017) Robots and Jobs: Evidence from US Labor Markets. NBER Working Paper 23285, 35.
[3]  Hémous, D. and Olsen, M. (2016) The Rise of the Machines: Automation, Horizontal Innovation and Income Inequality, Barcelona: IESE Business School Working Paper No. WP1110-E, 1.
[4]  Aghion, P., Jones, B.F. and Jones, C.I. (2019) Artificial Intel-ligence and Economic Growth. In: Goldfarb, A.G., Eds., The Economics of Artificial Intelligence: An Agenda, National Bureau of Economic Research, Inc., Chicago, 237-290.
https://doi.org/10.7208/chicago/9780226613475.003.0009
[5]  Corinne, C. (2018) Artificial Intelligence and the Good Society. Science and Engineering Ethics, 24, 505-528.
[6]  唐要家, 唐春晖. 基于人工智能监管治理[J]. 社会科学期刊, 2022(1): 116.
[7]  Jenna, B. (2016) How the Machine Thinks: Understanding Opacity in Machine Learning Systems. Big Data and Society, 3, 1-12.
https://doi.org/10.1177/2053951715622512
[8]  贾开, 蒋余浩. 人工智能治理的三个基本问题: 技术逻辑、风险挑战与公共政策选择[J]. 中国行政管理, 2017(10): 40-44.
[9]  吴汉东. 人工智能时代的制度安排与法律规制[J]. 法律科学(西北政法大学学报), 2017(5): 128-136.
[10]  张凌寒. 算法权力的兴起、异化及法律规制[J]. 法商研究, 2019(4): 63-75.
[11]  沈伟伟. 算法透明原则的迷思——算法规制理论的批判[J]. 环球法律评论, 2019(6): 20-39.
[12]  刘友华. 算法偏见及其规制路径研究[J]. 法学杂志, 2019(6): 55-66.
[13]  Becker, G.S. and Stigler, G.J. (1974) Law Enforcement, Malfeasance, and Compensation of Enforcers. Journal of Economics, 98, 371-400.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133