电商平台算法推荐下消费者自主性的困境与治理

Dilemmas and Governance of Consumer Autonomy in the Context of Algorithmic Recommendation

摘要: 随着电子商务平台算法推荐机制的广泛应用，消费者决策过程日益受到数据画像、个性化排序与精准营销的影响。算法推荐在提升信息匹配效率的同时，也可能通过信息过滤、偏好塑造和算法黑箱削弱消费者自主性。通过以消费者自主性为核心概念，从认知自主性、意志自主性和行为自主性三个层面分析算法推荐的影响机制，并借助马克思异化理论与福柯权力理论揭示其背后的资本逻辑和规训机制。算法推荐并非中立技术工具，而是嵌入平台商业逻辑的行为引导机制。为维护消费者主体地位，应从数据节制、算法透明、主体赋权、平台责任、公共监管和数字素养提升等方面完善治理路径。

Abstract: With the widespread application of algorithmic recommendation mechanisms on e-commerce platforms, consumers’ decision-making processes are increasingly influenced by data profiling, personalized ranking, and targeted marketing. While algorithmic recommendation improves the efficiency of information matching, it may also undermine consumer autonomy through information filtering, preference shaping, and algorithmic opacity. Taking consumer autonomy as the core concept, this study analyzes the influence mechanism of algorithmic recommendation from three dimensions: cognitive autonomy, volitional autonomy, and behavioral autonomy. It further draws on Marx’s theory of alienation and Foucault’s theory of power to reveal the capital logic and disciplinary mechanisms embedded behind algorithmic recommendation. Algorithmic recommendation is not a neutral technological tool, but a mechanism of behavioral guidance embedded in the commercial logic of platforms. To safeguard consumers’ subject status, governance pathways should be improved in terms of data minimization, algorithmic transparency, subject empowerment, platform accountability, public regulation, and the enhancement of digital literacy.