摘要
如果说数据是数字经济时代的核心生产要素,那么算法则是推进这一核心生产要素资产化和价值化的运行基础。当数字技术赋能各个领域,催生了新产品、新组织模式、新商业模式和新产业业态的同时,也带来了诸如算法歧视、算法操纵、算法协同、算法黑箱等潜在风险。不同类型的算法经由设计和实施,其带来的算法应用潜在风险不同,并可能导致政府失灵与市场失灵。围绕“治理主体-治理对象-治理工具措施”探索算法治理的体系架构,可以融合多元主体协同、利益均衡和敏捷治理等三种机制,在元规制和全过程管理理念的基础上优化算法治理措施,推动三种机制并行。
If data is the core factor of production in the digital economy era,then algorithms are the operation foundation for making it an asset and capitalizing on its value.By empowering various fields,the digital technology gives birth to new products,new organizational models,new business models and new industrial formats.But at the same time,it also brings potential risks such as algorithmic bias,algorithmic manipulation,algorithmic collaboration,algorithmic black box and so on.Different types of algorithms have different effects on the potential risks of algorithmic application through design and implementation and may lead to government failure and market failure.To explore the architecture of algorithmic governance surrounding"the governing party-the governed-governance tools and measures",this article suggests integrating the three mechanisms of multi-party collaboration,interest balance and agile governance and making use of them by optimizing algorithmic governance measures on the basis of the concepts of meta regulation and whole process management.
出处
《学术前沿》
CSSCI
北大核心
2022年第10期44-53,共10页
Frontiers
关键词
算法风险
算法类型
治理体系
治理措施
algorithmic risks
algorithm types
governance system
governance measures
