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the essence of "big data maturity" is to use user data to achieve differentiated pricing. but the question is, how to determine whether it is differentiated marketing or differentiated pricing? this question, like an ancient puzzle, has troubled industry insiders and consumers.
the “black box” of algorithms: behind the "big data familiarity", there is a mysterious "black box" hidden. the complexity of the algorithm model makes it difficult to interpret, making it difficult for regulatory authorities to accurately determine whether it constitutes an illegal act.
difficulty in proving and defending rights: the combination of regulatory difficulty and the cost of consumer rights protection has further aggravated the spread of this "killing" phenomenon. many users are unable to understand complex algorithms and pricing logic, and lack transparency on the platform, making it difficult for them to prove the true situation of being “killed”.
the voice of the legal community: in order to better cope with the "big data eradication", government departments have also begun to actively explore solutions. for example, du yuwei, deputy director of the regional modernization research institute of the jiangsu academy of social sciences, believes that the key to solving the problem of "big data killing" lies in anti-monopoly and promoting market competition. he pointed out, "only when the merchant has monopoly power or market dominance, the possibility of 'killing familiarity' may exist."
algorithms are open and transparent: song yubo, associate professor at the school of cyberspace security of southeast university, suggested that companies should disclose pricing algorithm models so that regulatory agencies can judge and verify whether companies have implemented price discrimination against different users. this will help establish clearer rules and reduce the risk of “big data overkill”.
reversal of burden of proof: many legal experts believe that in civil lawsuits, consumers need to prove that platforms engage in differential pricing. in order to avoid the difficulties caused by the "algorithm black box", some countries and regions have tried to formulate new inversion schemes for the burden of proof to shift regulatory responsibilities from "consumers" to "platforms".
future outlook: the governance of “big data maturity” is complex and requires the joint efforts of governments, enterprises and consumers. only by complying with laws and regulations and establishing a transparent and credible rule system can the problem of "big data maturity" be truly solved. at the same time, it is also necessary to encourage technological innovation, develop safer and more reliable technical means, and provide consumers with a fairer and more equitable business environment.
