The Dilemma and Path of Legal Regulation on “Big Data Price Discrimination”: A Two Dimensional Perspective on Regulating Platform Operators’ Algorithmic Power and Protecting Consumer Rights

Abstract

The essence of “Big Data Price Discrimination” lies in the abuse of “algorithmic power” by platform operators, resulting in algorithmic discrimination that violates individual rights such as consumers’ rights to fair trade and information. Under the manipulation of data, algorithmic automation decision-making becomes the technical pathway, wherein operators with access to vast amounts of data create precise profiles of consumers and set different prices accordingly. However, legal regulation of this phenomenon faces numerous challenges, including legislative lag, difficulties in consumer evidence provision, high litigation costs, and the complexity of holding platforms accountable. To address these challenges, the paper proposes a two-pronged approach: Firstly, enhancing the path for protecting consumer rights through detailed legislation, implementing public interest litigation, adopting the principle of “reversed burden of proof”, and improving rights remedies mechanisms to effectively safeguard consumer rights. Secondly, constructing governance pathways for platform operators’ algorithmic power, emphasizing a dual-mode of legal and technical governance, improving platform algorithm accountability mechanisms, implementing scenario-based and refined algorithmic supervision, and promoting effective linkage between platform governance and algorithm governance. Through these measures, it is possible to effectively address the “Big Data Price Discrimination” phenomenon and achieve a balance and coordination between consumer rights protection and platform operator responsibilities.