As algorithms increasingly influence user behavior on the internet, a phenomenon known as “reverse domestication” of data is gaining traction among young Chinese internet users. This trend involves actions aimed at disrupting AI algorithms to enhance user experience and reduce costs.
In early December, Ding Ran, an office worker in Beijing, planned a trip abroad with her boyfriend. While using a travel app, she found a round-trip ticket from Beijing to Seoul priced at 4,359 yuan. Expressing her disappointment about the cost on social media, she commented, “Flight tickets are too expensive; I can’t afford to go anymore.” The following day, upon checking the app again, she discovered that the price had decreased to around 3,000 yuan. While she was unsure whether her comments influenced the price change or if it was merely coincidental, Ran’s experience reflects a larger movement among Chinese internet users who engage in practices aimed at “reverse domesticating” algorithms.
Many users have reported experiences of being at a disadvantage due to the practices of big data. For instance, one netizen highlighted that during a business trip, the hotel room price he received was consistently 50 yuan higher than that of a colleague booking the same room for the same dates. Similar discrepancies have been noted in ride-hailing services, where different users receive varying quotes for identical rides. This has sparked debates about how prices on these platforms are tailored not to a universal standard, but rather to individual user profiles based on spending habits, income, and occupation.
Professor Chen Bing from the School of Law at Nankai University noted that the exploitation of big data is evident in the varying prices presented to different customer groups. He referenced a 2021 case in which a plaintiff, Hu Moumou, sued a travel company for price discrepancies perceived as fraudulent. The court determined that the company had misled customers regarding pricing and ordered compensation.
In November, Chinese authorities mandated that platforms adjust their algorithms to prevent the discriminatory use of big data, explicitly prohibiting price variations based on user characteristics such as age or income.
To counteract the influence of big data, Chinese users have begun initiatives aimed at “killing” algorithms. Strategies include frequently downloading and deleting applications to limit data collection and maximize promotional incentives, as new users typically receive better offers. Some users even employ services that allow the use of fake phone numbers for account registration.
However, Professor Bing cautioned that these tactics may only be effective against simpler algorithmic models. He explained that contemporary AI algorithms possess self-learning capabilities that produce unpredictable outcomes, making it challenging to control pricing strategies over time. Although reverse domestication may yield initial price reductions, ongoing algorithmic assessments based on user behavior will likely lead to higher prices in the long run. Enforcement agencies and lawmakers may also struggle to ensure transparency in the algorithmic processes that dictate pricing.
Ultimately, effective long-term regulation of algorithms may require the implementation of anti-competitive laws, ensuring that algorithm operations adhere to fair practices. Professor Bing advocates for continuous updates from internet companies, coupled with regulatory adjustments, to promote transparency and fairness in algorithmic pricing.
