在大数据时代,随着电子商务的快速发展,算法技术在电子商务中的应用也日渐广泛。然而,一些问题也逐渐浮出水面。其中,算法歧视现象尤为引人关注。文章首先介绍了电子商务领域中算法歧视的概念与特点,然后详细阐述了算法歧视在各阶段的具体表现。接着,文章指出了当前法律规制在应对算法歧视方面的困境,并提出了相应的法律应对方案。最后,文章从法律救济层面进一步探讨如何有效解决算法歧视在电商平台中对消费者的危害性。本文旨在保障消费者权益、促进电商平台健康发展,具有实用性和前瞻性。In the era of big data, with the rapid development of e-commerce, the application of algorithm technology in e-commerce is becoming increasingly extensive. However, some problems have also gradually surfaced. Among them, the phenomenon of algorithm discrimination is particularly noteworthy. This paper first introduces the concept and characteristics of algorithm discrimination in the field of electronic commerce, and then expounds the specific performance of algorithm discrimination in each stage. Then, the paper points out the dilemma of the current legal regulation in dealing with algorithmic discrimination, and puts forward the corresponding legal response plan. Finally, the paper further discusses how to effectively solve the harm of algorithmic discrimination to consumers in the e-commerce platform from the level of legal relief. This paper aims to protect the rights and interests of consumers, promote the healthy development of e-commerce platforms, and is practical and forward-looking.
数字化的电商平台在方便用户购买商品和接受服务的同时,囿于算法黑箱存在的科技壁垒,使算法歧视现象频频出现在电子商务领域。电商平台和用户存在极大的信息不对称且算法黑箱使用户在寻求法律帮助时往往存在诸多障碍。为了更有效地应对这一问题,我们不能仅限于对算法因果关系的复杂探讨,而应将重点转向基于客观事实的不当得利分析,以厘清算法歧视下的责任归属。这一视角的转换不仅有助于揭示算法歧视的核心问题,还能为构建公正合理的法律救济机制提供新的思路和实践路径。Digital e-commerce platforms, while enhancing user convenience in purchasing goods and accessing services, are constrained by technological barriers associated with the “black box” nature of algorithms, leading to frequent occurrences of algorithmic discrimination in the e-commerce sector. The significant information asymmetry between platforms and users, coupled with the opacity of algorithmic decision-making, creates substantial obstacles for users seeking legal remedies. To address this issue more effectively, we should move beyond the intricate discussion of algorithmic causality and instead focus on an unjust enrichment analysis based on objective facts to clarify liability in cases of algorithmic discrimination. This shift in perspective not only helps uncover the core issues of algorithmic discrimination but also provides new insights and practical approaches for establishing a fair and effective legal remedy system.
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