论算法个性化定价的解构与规制——祛魅大数据杀熟

Deconstruction and Regulation of the Algorithm Personalized Pricing:Decrypt the Mist of Big Data Kill

算法个性化定价的监管实践与理论分析未能遵循规制对策与问题相匹配的规制原理。该原理要求注意算法个性化定价与算法合谋定价、欺诈定价、歧视定价、个性化推荐的区别。同时基于危害性差异我们也应将算法个性化定价进一步分为三类:超高价格、超低价格和一般价格。超高价格或超低价格场景下的算法个性化定价危害可借助既有的法律框架得以消减。虽然一般价格场景下的算法个性化定价既没有损害消费者权益,也不会排除或限制竞争,但会从分配不公平和程序不公平两个角度诱发消费者不信任,动摇数字市场经济秩序。政府、经营者和消费者应以信任受损机理为基本遵循,合力共筑消费者信任,以实现创新发展和消费者利益保护的动态平衡。

The regulatory practices and theoretical analysis of algorithm personalized pricing fail to follow the regulatory principle of matching regulation countermeasures with the hazards.According to the principle, we should pay attention to the differences between algorithm personalized pricing and algorithm collusion pricing, fraudulent pricing, discriminatory pricing, personalized recommendation.Meanwhile, the complexity of hazards requires us to deconstruct the algorithm personalized pricing into three subcategories: ultra-high price, ultra-low price and ordinary price.The hazards of ultra-high and ultra-low price scenarios can be resolved under the existing legal framework.In ordinary price scenario, algorithm personalized pricing will not infringe consumers’ rights and interests, nor eliminate and restrict competition.However, it will damage consumers’ trust and disorder the digital market from the perspective of distributive unfairness and procedural unfairness.The government, business operators and consumers should work together to establish consumers’ trust, based on the understanding and use of the damage mechanism of consumers’ trust, so as to achieve a dynamic balance between innovative development and consumer interests protection.