How to find a fair exit in the maze of numbers?
2025-01-20
# Hotels are too expensive, # restaurants are too expensive, if you don't go out to play, you can consider cheaper options. I don't have any money, I don't have a penny. # Milk tea is so expensive, I've never tried it before, do you have a 0.01 down jacket... "This comment with the hashtag" # tag "is a bit confusing, but it has been frequently shared on a certain social media platform. Originally, this was a carefully written reverse review by users to combat the "big data killing" trend. Although its content was slightly exaggerated, it included daily consumption such as clothing, food, housing, and transportation, with the aim of "taming" big data and fighting for corresponding rights. From shopping and travel to daily socializing, from self recording to public expression, big data is deeply embedded in people's lives, bringing unprecedented convenience. But at the same time, "big data killing" has become a chronic disease of the Internet. In recent years, in order to combat the "big data killer", users have come up with various tricks: crying out for poverty, pretending to be new users, uninstalling and reinstalling, and reverse negative reviews... However, these methods are not always effective, and the criticized "big data killer" still occasionally "backstabbes" users, which is difficult to accept. The price of "acquaintances" in big data is approaching the end of the year, and coincidentally, there is a discount on "exchanging old appliances for new ones with national subsidies". Ms. Wang, who lives in Wuhan, Hubei, is preparing to add a few new appliances to her home. She, who is called an "online shopping expert" by her husband, opened the online shopping platform as soon as possible. She first chose a tea bar machine, and as someone experienced in online shopping, she used her husband's phone to search for the same product before placing an order to prevent price differences. As expected, she found a price difference of 10 yuan between two people in the same store for the same product. I then searched for commonly used appliances such as wall breaking machines and microwave ovens, and found price differences. And I can confirm that this price difference is not caused by the new user discount, because my husband is not a new user of the online shopping platform, he just purchases less frequently than me Ms. Wang said. A similar story also happened in Xiaozhuang. During holidays, Xiaozhuang would invite three to five friends to go out and play, and taking a taxi became a necessity for travel. Maybe it's because I take a taxi frequently and enter the same starting and ending points, but the cost of people traveling with me is always lower, "said Xiaozhuang. In traditional business rules, "regular customers" come from the trust of both buyers and sellers, but in the information age, big data has turned "acquaintances" into "targets" and become a tool for "killing acquaintances". The latest data from the China Consumers Association shows that "the frequent occurrence of 'big data killing' in the platform economy" remains one of the top ten consumer rights protection hotspots in the first half of 2024. The reporter searched for "big data kill" on a certain social media platform and found that common forms of "kill" encountered by netizens include "automatic price increase after multiple browsing" and "different users purchasing the same product at different prices at the same time". Although a large number of consumers have expressed their grievances, platforms rarely admit to the existence of "big data killing" behavior and consider it as "differentiated marketing" targeting different users. The essential conditions for normal 'differentiated marketing' are at least the following three: first, consumers are aware of different prices or charging standards; Secondly, operators provide consumers with options that are not tailored to individual characteristics; Thirdly, operators should provide consumers with convenient ways to refuse Liao Huaixue, senior partner of Taihe Tai Law Firm and expert at the China Advertising Association Brand Marketing Ecological Security Service Center think tank, told reporters that although "killing" and "differentiated marketing" cannot be confused, the boundary between "big data killing" and normal "differentiated marketing" is somewhat ambiguous in law, and further recognition rules are needed for guidance. In current judicial cases targeting the rights protection of "killing", there are also different judgment results. 'Big data murder' has secrecy and uncertainty, and even if related illegal activities occur, it faces difficulties in providing evidence and high costs of safeguarding rights Liao Huai's theory. If any app makes me realize it's' kill me ', I'll uninstall it for a while, and the next time I use it, it will be cheaper. Big data is also' honest ' Xiaozhuang said. For most consumers, the cost of time and energy invested in resorting to legal action for "killing" is relatively high. The essence of 'big data killing' is that algorithm systems use user data for speculation, and more users like Xiaozhuang have opened up a new strategy with lower barriers to entry - 'reverse domestication', 'using the way of algorithms to control the body of algorithms', and engaged in intelligent battles with big data. Domestication "is destined to be unsuccessful. The so-called" reverse domestication "refers to users changing their behavior trajectory on online platforms to become" disguisers ", pretending to be new users, infrequently used, or disliked... The core of" disguise "is to prevent the platform from locking in user profiles and interfering with algorithms' speculation of user identity information and consumption preferences. Xiaoqian, who is 25 years old this year, is a "money saving expert" in the mouths of colleagues and often studies the promotional rules of various platforms. If you want to know if you have been 'cooked up' on a food delivery platform, you can try switching platforms. Alternating usage may make food delivery cheaper. "Xiao Qian shared his tips for ordering food delivery with reporters. Yaya, who is the same age as Xiaoqian, also has her own method for "reverse domestication" of big data. Yaya, who has just entered the workplace, regards coffee as her "life-saving tool". Previously, I found that the coffee I used to drink was becoming increasingly expensive, so now I have three accounts with my parents and myself. Because they don't drink coffee at all, I use all three accounts, which is much cheaper than before. "Yaya told reporters that besides ordering coffee, she has also tried similar methods on other platforms. In addition to switching platforms and registering multiple accounts, many netizens have also shared their strategies for "reverse domestication" of big data on social media: some set virtual nicknames, some turn on mobile privacy mode, and some regularly clear cache or even change devices. Of course, the most popular way is to post reverse comments to express their financial difficulties to big data, trying to lower the price of goods or services. After performing operations comparable to "brainwashing" on big data, some users have found that the prices of goods have indeed decreased to a certain extent. So, can big data really be "domesticated" by users? Some users have told reporters that 'reverse domestication' is not always effective, and even if it does, it is short-lived. If we could lower the price of airline tickets by just browsing reviews, then we would all go and browse reviews, "said a travel platform in response to the controversy over changes in airline ticket prices. Digital technology has almost reached a state of omnipotence in the analysis of human records, while humans remain unchanged and will be in an increasingly disadvantaged position. With the continuous improvement of data computing power and algorithms, the imbalance between individuals, technology, and platforms will further intensify. Therefore, relying on users' personal 'reverse domestication' to resist 'big data killing' is destined to be unsuccessful Fang Xingdong, Director of the Cyberspace International Governance Research Base at Zhejiang University and Dean of the Wuzhen Digital Civilization Research Institute, said. Users can compete in the short term through their own consciousness and skills, but algorithms are also becoming smarter and better at playing games, making it difficult for users to win in this intelligent battle. Consumers have the right to supervise and criticize goods or services, but if users use malicious means, they may be suspected of violating the law. For example, attempting to mislead platforms into adjusting pricing strategies by publishing a large number of false reviews may violate relevant regulations such as the Cybersecurity Law that prohibit the fabrication and dissemination of false information Liao Huaixue told reporters that there may be certain legal risks associated with users' "reverse domestication" of big data. Promoting algorithm governance requires long-term effort. "It's not just about 10 yuan, which makes me feel unfair. As an old user, why can't I get a discount?" Ms. Wang compared the price difference found between herself and her husband on the same tea bar machine. Fairness "is a keyword emphasized by many users to reporters during interviews. It is neither reasonable nor fair for users' loyalty to the platform to backfire on their legitimate rights and interests. Establishing a balance of rights and a reasonable and just order in the digital age requires a strong socialized self-discipline system. Therefore, the modernization of governance in the digital age is much more demanding, difficult, and challenging than traditional social governance Fang Xingdong said. For the public, in addition to improving personal qualities such as awareness and skills, it is also necessary to empower individuals through laws and regulations, so that the disadvantaged position of users in safeguarding their rights can be corrected. Of course, what is more important is to make the platform unwilling, afraid, and unable to take action against data infringement Fang Xingdong said. Not long ago, the Cyberspace Administration of China and four other departments jointly issued a notice to carry out the "Clear and Clear Network Platform Algorithm Typical Problem Governance" special action, which clearly stated that it is strictly prohibited to use algorithms to implement big data "killing". It is strictly prohibited to use users' age, occupation, consumption level and other characteristics to implement differentiated pricing for the same product. Regarding the 'big data kill', the law has been clarified in multiple dimensions including competition policy, consumer protection, and personal information protection. If operators implement the behavior of 'big data killing', it may infringe on consumers' right to know and fair trade. However, as a comprehensive governance system, algorithm governance should also be a key focus in dealing with 'big data killing' Liao Huai's theory. In January of this year, multiple online platforms released algorithmic governance measures to promote transparency in algorithmic and platform governance. For example, Pinduoduo stated that it will crack down on "big data killing"; If users discover violations such as "big data murder" on the platform, they can file a complaint and the platform will promptly handle and implement it; Tencent has proposed to promote centralized display of algorithm information within products, enhance users' sense of fairness, openness, and transparency in algorithm recommendation services... Enterprise self-discipline will become an important driving force for eradicating "big data killing" and promoting algorithm governance. Faced with the new type of 'intelligent divide' represented by 'big data killing', the government, enterprises, and the public must form systematic, systemic, and global governance capabilities under the new situation and requirements of overall governance modernization. This is the only way Fang Xingdong said. How to eradicate the problem of 'big data killing', how to balance technological innovation and user rights, and how to make algorithms work towards goodness all require long-term efforts. We look forward to all parties working together to find a fair exit in the digital maze. (New Society)
Edit:Rina Responsible editor:Lily
Source:people.net
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