电子商务平台AI推荐算法歧视的生成机制与治理路径

The Generative Mechanisms and Governance Approaches of Algorithmic Discrimination in AI Recommendations on E-Commerce Platforms

摘要: 在数字经济快速发展的背景下，电子商务平台AI推荐算法已经成为电商平台提升用户体验和转化率的关键因素。然而，基于大规模数据驱动的AI推荐算法在提升效率的同时，也暴露出一系列算法歧视所导致的不公平问题，如差异化定价、推荐结果对特定群体不利等。本文以电商平台AI推荐算法为分析主体，从数据、模型、平台与用户四个维度分析算法歧视的生成机制，揭示其结构性成因与自我强化逻辑。在此基础上，从数据处理、技术设计、评估体系搭建与用户参与等维度提出一套多层次的治理路径，为电商平台实现“效率–公平”双重目标，构建公平、负责的电商智能推荐体系提供支撑与参考。

Abstract: In the context of the rapid development of the digital economy, AI recommendation algorithms on e-commerce platforms have become a key driver for improving user experience and conversion rates. However, while these data-driven algorithms enhance efficiency, they also expose a series of fairness issues arising from algorithmic discrimination—such as differential pricing and systematically unfavorable recommendation outcomes for certain groups. Focusing on AI recommendation algorithms used by e-commerce platforms, this paper analyzes the generative mechanisms of algorithmic discrimination from four dimensions: data, models, platforms, and users, revealing its structural causes and self-reinforcing logic. Building on this analysis, the paper proposes a multi-level governance framework covering data processing, technical design, evaluation system development, and user participation. This framework aims to support e-commerce platforms in achieving the dual goals of efficiency and fairness, and in constructing a fair and responsible intelligent recommendation system.