交通管理非现场执法程序正当性研究

Study on the Legitimacy of Off-Site Law Enforcement Procedures of Traffic Management

摘要: 《新一代人工智能发展规划》提出人工智能在政府治理、社会服务等领域发挥了一定的影响作用。在行政法学领域，自动化方式的引入使得当下行政行为作出的方式产生了深刻的影响。近几年由于受到新冠病毒疫情的影响，无需人工参与就能实现部分行政行为，一定程度上减少了行政相对人的接触，让我们看到了技术浸入到行政领域，掀起了自动化行政的热潮。交通行政非现场执法是一种自动行政的行政手段，尽管行政机关的行政效能得到了提升，但同时也带来了行政相对人陈述、申辩易被压缩；证据认定流于形式；行政机关说明理由面临变动等关涉行政正当程序的挑战。非现场执法使用技术设备来收集、固定违法事实的核心和执行过程的不独立性，说明《行政处罚法》不需要另外增加非现场执行程序，但可以根据现有的诉讼框架进行适当调整，以应付各种挑战，包括：陈述的空间和扩展说明理由的内容。

Abstract: The Plan for the Development of the New Generation of Artificial Intelligence proposes that AI has played a certain influential role in government governance, social services and other fields. In the field of administrative law, the introduction of automation has had a profound impact on the way that administrative actions are made today. In recent years, due to the impact of the novel coronavirus epidemic, some administrative acts can be realized without manual participation, which reduces the contact of administrative counterparts to a certain extent, let us see the technology immersed into the administrative field, and set off the upsurge of automatic administration. The administrative off-site law enforcement of traffic administration is an administrative means of automatic administration. Although the administrative efficiency of administrative organs has been improved, it also brings the challenges of administrative due process, such as the statement of the administrative counterpart, the defense easy to be compressed, the evidence identification becoming a formality, and the administrative organs facing changes in explaining the reasons. Off-site law enforcement uses technical equipment to collect and fix the core of illegal facts and the independence of the execution process, which shows that there is no need to add off-site execution procedures to the Administrative Punishment Law, but it can be appropriately adjusted according to the existing litigation framework to meet various challenges, including: the space for statement and the expansion of the content of reasons.