大数据赋能隐性腐败治理的机理与路径

Mechanism and Path of Combating Hidden Corruptionwith Big Data

隐性腐败具有伪善性、间接性、复杂性和多源性等特点,较之普通腐败更具欺骗性和隐蔽性,治理难度更大。通过大数据的精准预测、腐败指数测量、全面比对和深度分析功能,能够在预防、发现、调查和惩处环节改善信息不对称现象以赋能隐性腐败治理。在运用大数据治理隐性腐败的同时,要警惕其运行过程中存在的问题和风险,处理好大数据的真实足量与必要收集、共享交换与安全防范,有效利用与依赖限制之间的关系。应从“硬制度+大数据”双轮驱动、完善反腐大数据收集处理机制、有序推进数据开放、加强大数据反腐的顶层设计等方面采取有效举措,实现大数据对隐性腐败的有效治理,助力国家治理体系和治理能力的现代化。

Hidden corruption,characterized by hypocrisy,indirectness,complexity,and multi-source,is more deceptive and covert than ordinary corruption,which makes it quite difficult to combat.Big data can correct the disadvantage of information asymmetry in corruption prevention,detection,investigation,and punishment through precise prediction,corruption index,comprehensive comparison,and profound analysis to empower hidden corruption control.While highlighting the hidden corruption prevention function of big data governance,we should also be alert to the problems and risks of hidden corruption in big data governance,and carefully handle the relationship between data volume and collection necessity,exchange and security,effective use and application restriction.We should fight against hidden corruption by applying“rigid institution plus big data”model,improving big data collection and processing system,gradually promoting data sharing,enhancing top-level construction in this area so that we can realize effective treatment of hidden corruption to help improve the modernization in state governance.