A Regulatory Placebo? The Systemic Failure of Mandatory GenAI Labeling
Authors: Jingyi Chen, Chaofan Bu, Shibo Yan, Xuesong Li
Organizations: Faculty of Law, University of Macau, MC 999078, Macau · Research Center for Criminal Justice, Renmin University of China, Beijing 100872, China · Faculty of Law, Waseda University, Tokyo 1698050, Japan · Professional Graduate School, Meiji University, Tokyo 101-8301, Japan · Institute of Comparative Law, Meiji University, Tokyo 101-8301, Japan
We examine the worldwide trend of mandatory labeling of generative artificial intelligence(GenAI) as a reactive, symbolic form of legislation triggered by technological panic and institutional responses. From a technical perspective, this study demonstrates that current mandatory labeling not only creates implementation dilemmas but also risks hindering the evolutionary trajectory of AI technology. We then systematically analyze the three dominant theoretical strands of this regime, the value dilution theory, the information authenticity theory, and the proactive regulation theory, and find that they are products of regulators' cognitive limitations in understanding the logic of modern technology. Not only do such formalistic compliance requirements become a regulatory placebo, but they also obscure the genuine legal demands of the technological era. This challenges the current governance paradigm and suggests a shift from identity-label governance to content governance, with an urgent need to address the complex problems associated with GenAI.
Artificial intelligence governance studies how laws, institutions, and technical controls shape AI development, deployment, accountability, and social effects.
Technichal University Berlin XpaliNLP Group · Research Center for Artificial Intelligence (DFKI) Berlin · Center for European Research on Trusted AI (CERTAIN) +1