Taorui Guan on Personalizing Patent Law with Social Credit Data (JIPEL)

"Personalizing Patent Law with Social Credit Data"
Taorui Guan
NYU Journal of Intellectual Property and Entertainment Law (Vol 13, no. 2, spring 2024)
Published online: July 2024

Abstract: In the era of digitization, data has become a pivotal force driving advancements across various sectors and transforming legal systems worldwide. China, in particular, is exploring new data-driven governance models. A prime example of this is its integration of the patent system with the Social Credit System (SCS). This paper aims to fill the void in theoretical research on this subject, moving beyond the prevalent narrative of the SCS as either a tool of state surveillance or a reputation-based regulatory mechanism. Instead, it introduces the concept of personalized law in the context of China’s patent system.

The paper suggests that the integration of social credit data within China’s patent law system aligns the system’s operations more closely with its objectives. This offers a personalized approach that provides individual market entities with tailored incentives based on their unique characteristics. To analyze this approach, the paper proposes a novel four-part analytical framework: profiling, personalization, communication, and adjustment. The paper then applies this framework to the two core mechanisms that result from the integration of the patent system with the SCS: the Reward and Punishment Mechanism and the Tiered Regulation Mechanism. This analysis reveals that these mechanisms are still in the stage of crude personalization and grapples with challenges such as narrow data scope, lack of transparency, and over-penalization.

The paper discusses two implications of personalized law reform: the redistribution of power toward administrative bodies—which necessitates a rebalancing of powers to avoid abuse and protect individual rights—and the possible expansion of the law’s functions—which might not align with existing normative theories and might have unintended consequences. The process of personalization requires scholars and policymakers to adapt and refine these theories as well as to identify and eliminate unintended consequences.