算法偏见与机会公平：电商平台人力资源管理中的算法伦理研究

Algorithmic Bias and Equality of Opportunity: Algorithmic Ethics in E-Commerce Platform Human Resource Management

摘要: 随着人工智能技术在电商平台人力资源管理中的广泛应用，算法偏见已成为威胁机会公平的核心伦理挑战。本文基于技术伦理学与组织公平理论，系统剖析电商平台算法人力资源管理中的偏见来源、表现形式及其对机会公平的侵蚀机制。研究发现，算法偏见主要源于历史数据偏见、特征选择偏见、模型设计偏见与反馈循环偏见四个维度；在招聘筛选、任务分配、绩效评估、薪酬定价等环节呈现出歧视性分配效应；并通过“黑箱”不透明性、计算不对称性与权力失衡等机制侵蚀劳动者的机会公平。本文提出“算法向善”的伦理治理框架，从数据治理、算法审计、透明解释、人机协同、制度保障五个维度构建机会公平的保障机制，为电商平台实现技术效率与伦理价值的平衡提供理论支撑与实践路径。

Abstract: With the widespread application of artificial intelligence technology in e-commerce platform human resource management, algorithmic bias has become a core ethical challenge threatening equality of opportunity. Based on technology ethics and organizational justice theory, this paper systematically analyzes the sources of bias, manifestations, and erosion mechanisms of equality of opportunity in algorithmic HR management of e-commerce platforms. The study finds that algorithmic bias mainly stems from four dimensions: historical data bias, feature selection bias, model design bias, and feedback loop bias; presents discriminatory distribution effects in recruitment screening, task allocation, performance evaluation, and compensation pricing; and erodes workers’ equality of opportunity through mechanisms such as “black box” opacity, calculative asymmetry, and power imbalance. This paper proposes an “Algorithm for Good” ethical governance framework, constructing a safeguard mechanism for equality of opportunity from five dimensions: data governance, algorithmic auditing, transparent explanation, human-machine collaboration, and institutional guarantee, providing theoretical support and practical pathways for e-commerce platforms to achieve a balance between technical efficiency and ethical values.