陈智高 and 王明月 discuss the phenomenon of big data pricing discrimination and the ethical standards and transparency of algorithms.

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王明月: Master, recently many people have been complaining about big data discrimination, saying that platforms charge old users higher prices than new users. What do you think of this phenomenon?
陈智高: This is typical price discrimination. Essentially, platforms use users’ consumption habits and data for precise pricing. Since old users are more loyal, platforms exploit that and charge them more.
王明月: It’s definitely unfair. Recently, some people have tried ‘reverse taming’ the algorithm by intentionally flooding social media with complaints to influence price fluctuations.
陈智高: That’s an interesting approach, but it may have limited impact. Algorithm models are highly adaptive and self-learning. It might work in the short term, but in the long run, the algorithms will adjust their strategies and more precisely target users’ behavioral patterns.
王明月: How can we regulate this phenomenon? The complexity of algorithms makes regulation more difficult. Professor 陈兵 suggested making algorithms more transparent, but isn’t that technically challenging?
陈智高: It’s indeed difficult, but not impossible. Companies need to have a sense of social responsibility and regularly adjust their algorithms to ensure they align with values of fairness and justice. Regulatory agencies should set standards and promote transparency so consumers understand the pricing logic.
王明月: That’s the only way to rebuild users’ trust. Otherwise, platforms appear to be offering personalized services but are actually profiting from information asymmetry.
陈智高: Exactly. In the information age, while algorithms bring convenience, they also need ethical and moral constraints. This is why we discuss the intersection of technology and humanities.