隐私计算赋能公共数据开放的逻辑进路与风险规制

Risk regulation and logical approach of public data opening empowered by privacy-preserving computation

公共数据开放的核心要旨是在保障数据安全前提下,充分释放公共数据潜在价值和效益。通过隐私计算赋能,实现数据协同利用、控制数据用法用量以及打造数据安全流通新模式,有助于消弭公共数据开放中数据安全与数据利用的根本性矛盾。但隐私计算赋能公共数据开放是价值与风险并存的过程,可能导致公共数据开放的信任维系机制失效和引发新型数据安全风险。对此,最优的解决方案是科技治理与法律规制的协同共治,将隐私计算改造成为遵循科技逻辑和法治原理的数据治理科技,包括隐私计算的法律归化以及通过设计的公共数据开放的双重进路,实现公共数据开放中法律规范与代码规则的有机融合,法律和科技的相互增益。

The core essence of open public data is to fully unleash the potential value and benefits of public data while ensuring data security.By empowering privacy computing,it enables collaborative data utilization,control over data usage and quantity,and the creation of new models for secure data circulation.This helps to eliminate the fundamental contradiction between data security and data utilization in open public data initiatives.However,enabling privacy computing for open public data involves a process that entails both value and risks,which could lead to the breakdown of trust mechanisms and give rise to new data security risks.In response,the optimal solution lies in the collaborative governance of technological measures and legal regulations,transforming privacy computing into data governance technology that adheres to both technological logic and the principles of the rule of law.This includes legal normalization of privacy computing and the organic integration of legal norms and code rules through a dual approach to open public data,achieving mutual benefits between law and technology.