当“大数据杀熟”遭遇用户“反向驯化”——数字“迷宫”中，如何寻找公平的出口？

Core Viewpoint - The article discusses the phenomenon of "big data price discrimination" where consumers face higher prices based on their purchasing behavior and history, leading to a growing backlash and various strategies from users to combat this issue [1][2][3]. Group 1: Consumer Experiences - Consumers have reported experiencing price discrepancies for the same products based on their shopping frequency, with examples of individuals finding price differences of 10 yuan for the same item when using different accounts [2]. - Common forms of "big data price discrimination" include automatic price increases after multiple views and different prices for the same product at the same time for different users [2][3]. Group 2: Legal and Ethical Considerations - The distinction between "big data price discrimination" and legitimate "differential marketing" is legally ambiguous, requiring clearer guidelines for recognition [3][9]. - Legal frameworks have been established to protect consumers' rights against "big data price discrimination," emphasizing the need for algorithm governance to ensure fair practices [9][10]. Group 3: User Strategies - Users are employing various tactics to counteract "big data price discrimination," such as creating multiple accounts, using different devices, and posting reverse comments to signal financial constraints [4][6]. - The effectiveness of these strategies is debated, with some users reporting temporary success, while others find that such tactics do not consistently yield lower prices [6][7]. Group 4: Industry Response and Governance - Recent initiatives by platforms aim to address "big data price discrimination," with companies like Pinduoduo and Tencent announcing measures to enhance algorithm transparency and consumer protection [9][10]. - The article highlights the need for a collaborative approach among government, businesses, and consumers to establish a fair digital economy and mitigate the impacts of "big data price discrimination" [10].