摘要
伴随智能社会的兴起,算法公平已跃升为人工智能治理最为核心和紧迫的议题。基于主体和技术生命周期,算法公平可被归类为个体算法公平和群体算法公平;起点算法公平、过程算法公平和结果算法公平。以此类型框架为据审视我国算法公平规范现状,可见其呈现出体系化不足、可操作性欠佳、规范维度失衡、治理工具缺失以及对具备通用目的的人工智能与特定人工智能存在治理盲区等问题。为破解算法公平治理之困,应依循算法公平的技术机理和伦理关切,凝练法律、伦理和科技之间的内在共识,将算法非歧视原则作为算法公平治理底线,实现跨领域共识的有机融合。在此基础上,我国应立足反歧视法理,通过动态构建差异化的受保护特征清单、打造具有一致性和可预测性的算法歧视审查框架,建立合法性与必要性并重的算法影响评估机制,探寻算法公平的融贯理路与法治化实现路径。
With the rise of artificial intelligence in society,algorithmic fairness has emerged as the most crucial issue in AI governance.Based on the subject and technical life cycle,algorithmic fairness can be classified into individual and group algorithmic fairness,as well as fairness at the starting point,in the process,and in the outcome.Examining China's current norms using this typological framework reveals problems such as lack of systematization,weak operability,imbalanced regulatory dimensions,lack of governance tools,and regulatory blind spots for general and specific AI.To resolve the dilemma,it is necessary to distill the inherent consensus among law,ethics,and technology,and establish the principle of non-discrimination as the foundation of algorithmic fairness governance.Grounded in non-discrimination norms,a dynamic and differentiated list of protected characteristics should be constructed,a consistent and predictable commensurable review framework should be created,and an algorithm impact assessment mechanism that emphasizes both legality and necessity should be established for achieving algorithmic fairness.
出处
《中外法学》
北大核心
2024年第4期866-883,共18页
Peking University Law Journal
基金
北京市教育科学“十四五”规划课题(项目编号:3030—0014)的阶段性研究成果。
关键词
算法公平
算法歧视
数字正义
人工智能治理
通用人工智能
Algorithmic Fairness
Algorithmic Discrimination
Digital Justice
AI Governance
Artificial General Intelligence
