Legal Risks of the Application of Artificial Intelligence Anti-Trafficking System and Its Regulatory Paths

Abstract

The application of artificial intelligence (AI) in the field of anti-trafficking presents both technological empowerment and social risks. Currently, its use is becoming increasingly widespread, but the legal risk it brings including data security, algorithmic bias, and liability attribution, are gradually becoming more prominent, and thus, requires in-depth research and effective regulation. This paper aims to comprehensively analyze the legal risk associated with AI anti-trafficking systems and explore the construction of a scientifically sound regulatory framework to balance technological development with rights protection. This paper, through empirical analysis and normative research, explains the application of artificial intelligence anti-trafficking systems in intelligence assessment of trafficking-related information, intelligent collection of evidence related to trafficking, and intelligent interrogation of suspects involved in trafficking. It reveals new legal risks such as data security, algorithmic discrimination, and liability attribution that arise from these applications. Moreover, based on the framework of technology governance theory, the paper proposes a regulatory system by integrating preventive legislation + dynamic supervision + technical traceability to emphasize the establishment of a tiered evaluation system for algorithmic impact and the introduction of third-party compliance audit mechanisms. By implementing an algorithm correction mechanism to avoid the risk of algorithmic discrimination, the paper innovatively proposes a "scenario-based attribution of responsibility for technology applications" model provides an institutional solution to balance technical efficiency and rights protection. The study also provides strong technical support and legal safeguards to address social issues and offers new perspectives and methods for scholars engaged in related research.