算法推荐中的消费者信息弱势地位及其法律救济

The Vulnerable Position of Consumers in Algorithmic Recommendations and Legal Remedies

摘要: 在数字经济的浪潮下，算法推荐技术已广泛应用于电商平台。平台凭借数据垄断和算法黑箱的优势，使消费者陷入“信息茧房”，消费者面临“大数据杀熟”、知情权与选择权受损等问题。本文通过分析消费者信息弱势的成因，包括技术与资本驱动的数据垄断、算法操纵，以及由此导致的消费者在算法决策中的被动地位。同时，探讨现行法律体系在应对算法推荐挑战时的不足，如规则模糊、救济乏力、技术治理困境等。针对这些问题，提出“赋权 + 共治”的双向救济体系，旨在通过法律赋权和技术治理，平衡平台与消费者之间的信息不对称和权力失衡。具体措施包括细化算法解释权、引入数据可携带权、要求平台备案核心算法、实施动态监测、利用隐私计算技术优化模型，以及开发算法透明度工具等。强调多元共治的重要性，鼓励消费者参与维权、推动平台自律与政策激励相结合。

Abstract: Under the wave of digital economy, algorithmic recommendation technology has been widely used in e-commerce platforms. Relying on the advantages of data monopoly and algorithmic black box, the platform has made consumers fall into an “information cocoon”, and consumers are faced with problems such as “big data killing”, and the right to know and the right to choose are impaired. This paper analyzes the causes of consumer information weakness, including data monopoly driven by technology and capital, algorithmic manipulation, and the resulting passive position of consumers in algorithmic decision-making. At the same time, this paper discusses the shortcomings of the current legal system in coping with the challenges of algorithmic recommendation, such as vague rules, lack of relief, and technical governance dilemmas. In view of these problems, a two-way relief system of “empowerment + co-governance” is proposed, which aims to balance the information asymmetry and power imbalance between platforms and consumers through legal empowerment and technical governance. Specific measures include refining the right to interpret algorithms, introducing the right to data portability, requiring platforms to record core algorithms, implementing dynamic monitoring, using privacy-preserving computing technology to optimize models, and developing algorithm transparency tools. It emphasizes the importance of pluralistic co-governance, encourages consumers to participate in rights protection, and promotes the combination of platform self-discipline and policy incentives.