🤖 AI Summary
This study addresses the concern that mandatory labeling for generative AI has devolved into a "regulatory placebo" that impedes technological advancement. By integrating technical feasibility analysis, regulatory theory critique, and comparative paradigm research, this work systematically deconstructs three fundamental theoretical deficiencies in existing frameworks. The findings confirm that mandatory labeling entails significant implementation challenges and technical risks, prompting the proposal of a novel paradigm shift from "identity labeling" to "content governance." This research transcends traditional regulatory cognitive limitations by establishing content governance as the theoretically superior direction for GenAI oversight. Ultimately, it provides essential scholarly support and practical guidance for constructing a substantive governance system tailored to the generative AI era.
📝 Abstract
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.