Taorui Guan on Personalizing Patent Legislation with Social Credit score Knowledge (JIPEL)

Summary: Within the period of digitization, information has develop into a pivotal drive driving developments throughout numerous sectors and reworking authorized methods worldwide. China, particularly, is exploring new data-driven governance fashions. A first-rate instance of that is its integration of the patent system with the Social Credit score System (SCS). This paper goals to fill the void in theoretical analysis on this topic, shifting past the prevalent narrative of the SCS as both a software of state surveillance or a reputation-based regulatory mechanism. As an alternative, it introduces the idea of personalised regulation within the context of China’s patent system.

The paper means that the mixing of social credit score information inside China’s patent regulation system aligns the system’s operations extra intently with its goals. This affords a personalised method that gives particular person market entities with tailor-made incentives based mostly on their distinctive traits. To investigate this method, the paper proposes a novel four-part analytical framework: profiling, personalization, communication, and adjustment. The paper then applies this framework to the 2 core mechanisms that end result from the mixing of the patent system with the SCS: the Reward and Punishment Mechanism and the Tiered Regulation Mechanism. This evaluation reveals that these mechanisms are nonetheless within the stage of crude personalization and grapples with challenges resembling slender information scope, lack of transparency, and over-penalization.

The paper discusses two implications of personalised regulation reform: the redistribution of energy towards administrative our bodies—which necessitates a rebalancing of powers to keep away from abuse and shield particular person rights—and the doable enlargement of the regulation’s capabilities—which could not align with present normative theories and may need unintended penalties. The method of personalization requires students and policymakers to adapt and refine these theories in addition to to establish and get rid of unintended penalties.