Optimizing Regulatory Pathways for Generative Artificial Intelligence in China: A Policy-Analytic Study
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Abstract
This paper takes China's regulatory policies for generative artificial intelligence (AI) as the research subject and develops a three-dimensional analytical framework titled "Policy Instrument–Policy Objective–Policy Effectiveness" by employing the policy instrument approach and content analysis methodology. Against the challenges prevailing in China’s current generative AI regula-tion—including the uneven distribution of regulatory resources, the complexity of horizontal and vertical regulatory coordination, the regulatory system’s over-reliance on coercive mechanisms, and the fragmentation tendency of regulatory policies—the study proposes four optimized pathways: first, establish a closed-loop mechanism of "piloting–evaluation–scaling"; second, build a gov-ernment-led multi-center collaborative governance framework that integrates enterprise internal control, third-party evaluation, and industry self-regulation; third, advance model-based regulation for the "model–version–scenario" unit; fourth, implement controllable pilots via regulatory sandboxes to accumulate empirical experience.
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