%0 Journal Article
%T 数字政府时代背景下算法行政的风险及其防控
Risk and Prevention of Algorithmic Administration in the Digital Government Era
%A 胡漫琦
%J Open Journal of Legal Science
%P 5804-5810
%@ 2329-7379
%D 2023
%I Hans Publishing
%R 10.12677/OJLS.2023.116830
%X 在大数据、智能化时代,我国政府的数字化转型也正逐步推进,数字技术深度嵌入行政权力的运作过程之中,形成新的行政运作模式,即算法行政。随着数字技术的发展,算法行政的运用场景越来越广泛,对社会生活的介入程度也越来越深,其作为一种崭新的行政模式,相较于传统行政更具精确性、高效性、中立性,对于提高行政效率,减轻行政负担具有积极作用。在算法行政为我国政府治理工作带来红利的同时,其也面对着许多不可避免的风险,例如算法错误、算法歧视、影响公众参与,泄露个人信息等。如何有效规避风险,也成为行政主体不得不面对的问题,本文从加强事前审查、加强事中权力规制和加强事后责任分配三个方面具体给出解决方案,通过风险规制,让算法更好地为行政活动服务,从而推动数字政府建设。期望推动数字政府建设。
In the era of big data and intelligence, the digital transformation of China’s government is also gradually advancing, and digital technology is deeply embedded in the operation process of administrative power, forming a new administrative operation mode, that is, algorithmic administration. With the development of digital technology, the application scenarios of algorithmic administration are more and more extensive, and the degree of intervention in social life is also more and more profound. As a new administrative mode, algorithmic administration is more accurate, efficient and neutral than traditional administration, which plays a positive role in improving administrative efficiency and reducing administrative burden. While algorithmic administration brings dividends to our government’s governance work, it also faces many unavoidable risks, such as algorithmic errors, algorithmic discrimination, affecting public participation, and revealing personal information. How to effectively avoid risks has also become a problem that administrative subjects have to face. This paper gives specific solutions from three aspects: strengthening pre-examination, strengthening power regulation and strengthening post-responsibility distribution. Through risk regulation, algorithms can better serve administrative activities, thus promoting the construction of digital government. It is expected to promote the construction of digital government.
%K 算法行政,数字政府,大数据
Algorithm Administration
%K Digital Government
%K Big Data
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=75670