◆ After registering as a group purchase member, not only the takeaway full discount is reduced, but the delivery fee is not reduced but also increased
◆ "The more you brush your face, the greater the risk of 'losing face.'"
◆ "Some enterprises have the confidence to abuse data, which lies in the monopoly of big data, and it is difficult to find, prove and identify the opaque algorithm."
Accurate killing, algorithm change calculation; accurate brushing of the face, breeding "shameful" hidden dangers; accurate "weight reduction", plagiarism cloaked in invisibility... As big data applications penetrate into all aspects of modern life, people's food, clothing, housing, eating, drinking and having fun are mostly bundled with software or sets of smart devices.
Seemingly fragmented massive amounts of data are mined, integrated, and analyzed, constantly generating new value. On the one hand, it makes people's work and life more and more convenient and efficient, on the other hand, it also brings new troubles to people's production and life.
"Kill cooked" Xu Jun figure
"Calculated" by big data
The reporter recently visited many places to investigate and learned that under the drive of interests, behind big data analysis, all kinds of chaos occur from time to time.
"Big data kills" occurs frequently, and algorithms become calculated. The same delivery time, place, order, takeaway platform, but members pay more than non-members - not long ago, some netizens found that after registering as a member of a group purchase platform, compared with non-members, not only the takeaway full discount has been reduced, but the delivery fee has not decreased but increased.
The incident quickly caused discussion on the Internet, and netizens complained that it was not an accidental incident. At the same time, the same type of car in the same place to the same destination, a taxi platform has been found by users to be more expensive.
According to the Beijing Municipal Consumer Coordination Survey, more than 80% of the respondents believe that the phenomenon of "big data killing" is quite common now, and more than 50% of the respondents said that they have been "killed by big data". Correspondingly, a number of large Internet companies have been exposed to using big data analysis to differentiate pricing of different groups and implement "price discrimination".
Face recognition is rampant, and there is a hidden danger of "shame". Some time ago, a video of "wearing a helmet to see the house" on a video platform on the Internet triggered public opinion. The video publisher said that this funny move was to counter the helplessness of the "unspoken rules" of the sales office. Originally, the sales office increased data analysis through face recognition to determine the type of customer, and different types of customers such as real estate "old with new", commercial intermediaries, and natural house buyers could get different degrees of house purchase discounts.
Going to work, going home, traveling, traveling... Face recognition has fully entered life. "The community has installed a face recognition system with security and intelligent management requirements, and many owners have raised objections due to concerns about information leakage." A community owner told reporters that after several protests, the property compromised to implement the "dual-track system", and the owner could choose to swipe his card or brush his face.
"The more you brush your face, the greater the risk of 'losing face.'" Yang Fengyu, associate professor of the School of Software of Nanchang Hangkong University, believes that according to relevant laws and regulations, the collection of face data in many scenes is not necessary. "Beware of personal facial information being used by unscrupulous businesses."
"One-click weight reduction" puts an invisibility cloak on academic plagiarism. In order to pass the paper smoothly, re-checking has become a necessary homework for many students. Some platforms "accurately" position the market, in addition to checking the weight, but also launched value-added services - "one-click weight reduction". "The use of big data in the thesis library plus artificial intelligence algorithms can achieve one-click substitution and automatic weight reduction, so that papers can easily pass the repetition rate review." Industry insiders told reporters.
"The purpose of checking papers is to eliminate academic misconduct. Big data weight reduction may encourage the unhealthy trend of academic fraud. Hu Pingbo, a professor at the School of Statistics of Jiangxi University of Finance and Economics, thinks.
Big data is plagued by opacity
When used properly, big data can empower many industry sectors and become a good solution to tough problems. But once used improperly, the problems caused by its unique power are difficult to resolve.
Taking "big data killing" as an example, Chen Yuling, associate professor of the State Key Laboratory of Public Big Data, believes that the implementation of price discrimination needs to meet three conditions: information inequality, differentiated users, and certain monopolies. With the development of Internet information technology, consumer data is collected in large quantities, and the ability of merchants to process and use data has taken a leap forward, and differentiated pricing is no longer difficult.
Industry monopoly is one of the deeper reasons behind it.
Xu Weidong, an associate professor at Hangzhou Dianzi University, said that the Internet is naturally prone to monopoly, the platform has more discourse power, and "big data killing" is only one of the points that infringe on the rights and interests of consumers.
Others, such as algorithm-based recommendation ads, always seem to be able to "guess" your preferences, from "psoriasis" on the pole to "accurate delivery" in the circle of friends, always inducing and interfering with consumer behavior.
Another example is that after some violations of the law put on the big data "vest", they turned into glamorous commercial technology. Some time ago, Qiaoda Technology Company, which claimed to use "big data" and "cognitive engine" to master the resumes of 220 million natural persons, was "cool".
"This company obtains a large number of citizens' resumes under the banner of recruitment, and then uses so-called big data means to classify personal information and sell it to third parties." Hu Pingbo said. Compared with the traditional direct trafficking of user information, merchants use self-packaging such as rule-making rights and algorithm technology to confuse the audience, and also make the illegal industrial chain longer and more professional.
"Some Internet companies have the confidence to abuse data, because there are difficulties in discovery, evidence, and identification of big data monopolies and algorithm opaqueness, which have led to many violations of laws and regulations evading punishment." Wang Shifa, a lawyer at Jiangxi Nanfang Law Firm, told reporters.
Proceed to install the safety valve
To curb the "negative energy" of big data empowerment, many experts believe that the key lies in industry self-discipline.
"The one who knows you best is often your opponent. The people who know best about whether an enterprise is using big data to kill are often their peers. Tang Yahui, a doctor of political economy at the Shanghai Academy of Social Sciences, and Xue Anwei, an associate researcher at the Institute of World Economics of the Shanghai Academy of Social Sciences, believe that mutual supervision and collaborative self-discipline of digital platforms and enterprises can be strengthened through scientific system design. At the same time, public opinion and media supervision are encouraged, and social forces are actively used to create a healthy market environment.
Dai Qingfeng, director of the Institute of Social Sciences of nanchang City, Jiangxi Province, also suggested that the self-discipline role of industry associations should be strengthened, the self-restraint mechanism should be improved, the use of big data and safety norms should be established and improved, and the orderly, beneficial and benign competition of enterprises should be promoted. At the same time, strengthen the vocational education of practitioners, especially pay attention to cultivating the awareness of data standard use of college students in related majors, and build the first firewall of big data security.
To combat the abuse of big data, self-discipline is not enough, and supervision is more necessary.
In fact, the abuse of big data has long attracted the attention of regulatory authorities. From the e-commerce law prohibiting "big data killing"; to the Ministry of Culture and Tourism issuing the Interim Regulations on the Administration of Online Tourism Operation Services, which clearly stipulates that online tour operators must not abuse technical means such as big data analysis... In recent years, relevant policies have been continuously improved.
"On the one hand, government supervision needs to adhere to the bottom line thinking, so that enterprises can maintain good innovation vitality and compete freely within the legal range." On the other hand, in view of the problems such as the killing of big data that consumers have strong reactions to, it is necessary to increase the punishment, increase the cost of violating the law, effectively maintain the market order, and guide enterprises to develop in the direction of better meeting the needs of the people. Dai Qingfeng said.
The interviewed experts suggested that we should continue to improve laws and regulations, increase the punishment of relevant violations and violations, and install "safety valves" for big data applications by smoothing judicial rights protection channels.
In the view of Tang Yahui and Xue Anwei, the lack of institutional norms in such links as data ownership, pricing, use, transactions, statistics, privacy protection, and supervision is an important factor in data abuse. They suggested that the relevant laws and regulations of the data element market should be improved as soon as possible, so as to provide an institutional basis for curbing the ripening of big data, and effectively improve the mutual trust mechanism of the digital economy. (Reporters Hu Jinwu, Yao Ziyun, Guo Fengqing)
Source: Lookout WeChat public account