算法时代警察权的隐性扩张及其应对
The Implicit Expansion of Police Power in the Age of Algorithm and Its Response
蒋勇1
作者信息
摘要
以算法预测和算法侦查为主要形态的算法警务日渐勃兴,在算法驱动下,警察权的作用节点从传统的危害防止阶段前移到风险预防阶段,警察决策的个别化机制加入了自动化方式,警察的数据分析职权亦脱离了数据收集职权.由于警察法上数据型权利的确权停滞、维稳体系中算法配置的路径依赖以及警务算法监管的体制性障碍,算法对警察权的强化效应并未被我国法治体系所感知,渐呈隐性扩张之势.应对算法时代警察权的扩张,应当以权力显性化为规制目标,在法规范上以数据型权利形塑警察算法型强制措施,以场景类型匹配算法决策的效力,以预防性行政诉讼来加强算法决策的外显,以"剩余风险"控制警察预防任务的过度前移.在配套制度上,则以"技术监管衔接规范授权"为主要路径,包括以算法清单制度收缩警察任务的扩张边界,以算法技术的全过程监管机制加强算法警务的可溯源性,以警务算法专责监督机构来确保算法技术监管的落地.
Abstract
With algorithmic prediction and algorithmic investigation as the main forms,algorithmic policing is booming day by day.Under the veil of algorithms,the role of police power is shifting from the traditional hazard prevention to the risk prevention stage,the automation method has been added to the individualized mech-anism of police decision-making,and the data analysis authority of the police has also been separated from the data collection authority.However,the strengthening effect of police power in the era of algorithms has not been perceived by China's rule of law system,and it has gradually shown a trend of implicit expansion,which is mani-fested that the lack of data analysis authority leads to the failure of power capture,the broadness of police task structure induces the loss of the sense of power boundary of the algorithm,and the blurring of police decision-making supervision aggravates the weakness of the algorithm explicit mechanism.In response to the expansion of police power in the era of algorithms,the goal of regulation should be to make power explicit.The core issue in legal norms is the regulation of police preventive functions,algorithmic police authority,and algorithmic decision-making authority.In terms of supporting systems,the main path is to"connect technical supervision with legal authorization",with the core being to construct the technical supervision mechanism that adapts to algorith-mic policing.
关键词
算法警务/风险预防/警察权/算法决策/算法监管Key words
Alogorithmic Policing/Risk Prevention/Police Power/Algorithm Decision/Algorithm Supervision引用本文复制引用
出版年
2024
NETL
NSTL
万方数据