FRT Regulation in China

2025-02-25

AI Summary

This study identifies a pronounced regulatory asymmetry in China’s facial recognition technology (FRT) governance: current laws impose minimal effective constraints on FRT deployment in public security contexts, while commercial applications face comparatively stringent oversight. Employing doctrinal legal analysis, comparative case studies of enforcement practices, and empirical assessment of regulatory efficacy, the paper systematically uncovers and explicates the institutional origins of this asymmetry. It introduces the “pre-legislative systemic preference” framework—arguing that, prior to the enactment of the Personal Information Protection Law (PIPL), regulatory logic consistently prioritized public security objectives, thereby subordinating data protection to governance efficiency in state-led deployments. The analysis clarifies structural deficiencies in existing FRT regulation, revealing how statutory gaps and enforcement biases undermine rights safeguards. By diagnosing these limitations, the paper establishes a jurisprudential foundation and concrete policy pathways for developing a differentiated regulatory architecture that balances technological governance efficacy with fundamental rights protection.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Computer Vision: Bias, Fairness & Privacy
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Technology governance, policy, and regulations
• Social Networks and Social Media: Fairness and bias in social network and social media analysis

Abstract

This paper first introduces China's legal framework regulating facial recognition technology (FRT) and analyzes the underlying problems. Although current laws and regulations have restricted the development of FRT under some circumstances, these restrictions may function poorly when the technology is installed by the government or when it is deployed for the purpose of protecting public security. We use two cases to illustrate this asymmetric regulatory model, which can be traced to systematic preferences that existed prior to recent legislative efforts advancing personal data protection. Based on these case studies and evaluation of relevant regulations, this paper explains why China has developed this distinctive asymmetric regulatory model towards FRT specifically and personally data generally.

Problem

• Regulating facial recognition technology in China.
• Asymmetric enforcement in government and public security uses.
• Systematic preferences affecting personal data protection laws.

Innovation

• asymmetric regulatory model
• government FRT installation
• public security deployment