Text | summer
Edit | Yang Xuran
Time is now in 2022, and big data is still a problem.
Big data can be seen as more efficient price discrimination under new technical conditions and means. Price discrimination itself has a long history and tradition, and can even be regarded as an inevitable problem in the process of economic and commercial operation.
The British economist Pigou proposed a three-tier definition of price discrimination as early as 1920. In the era of the Internet and big data, the price discrimination of big data is more in line with its third level of discrimination. According to the information included in Baidu Encyclopedia:
The third level of price discrimination refers to the monopoly manufacturers imposing different prices on different consumers in different markets, and obtaining excess profits in markets with high prices... Sometimes businesses have information about their customers, especially about the price they are willing to pay. If the buyer's characteristics are observable, then the seller can set different prices.
The maturity of the means of obtaining and applying big data has provided a new impetus to this ancient method of price discrimination. For example, some people will find that the same flight ticket to a certain place on the same day costs 1000+ to buy it, while others only spend a few hundred at the same time. The reason is simply because, according to big data calculations, you often buy this flight, or because you use Apple's latest mobile phone.
The flip side of price discrimination is that there will always be people who find out and complain. What companies are betting on is that few or only a small percentage of people will find this different pricing. For enterprises, the neglect and tolerance of this part of the people is enough to form excess profits.
Although regulatory policies attach great importance to this, especially in 2021, the state has introduced relevant policies, but considering the long history of price discrimination itself, and the importance of killing for Internet companies - higher profits at your fingertips, it is not easy to solve the problem of big data killing completely by law.
Regulations are like light, there are always shadows where they shine, and shadows are the soil where big data is ripe. In the era of big data, no one is immune to the fate of being monitored and extracted, and protecting their rights and interests is a time-consuming and labor-intensive and difficult thing. Internet companies not only need to be monitored by laws and regulations, but more importantly, they actually form a kind of self-discipline in business ethics.
01 From birth, it is immoral
Algorithms have become the logical support for people's mobile Internet life, and they are inadvertently completed by most people.
For most people, the algorithm is a "black box", and people have no way of knowing how the algorithm works — not clear or interested.
But one thing is certain, the basis for the operation of the algorithm is that the Internet company has enough data from users, and it is not necessarily true whether the source of data on consumer behavior is so "bright and upright".
As the underlying support in a certain sense, algorithm recommendation brings people a more convenient experience on the network, especially through the judgment of user preferences to promote the corresponding content and products. In short videos, graphics and some consumer markets, this has spawned a huge market.
But at the same time, algorithms are also used to classify consumers, and then discriminate and kill. These problems have existed for a long time, not as much news, but they still have an impact on the lives and interests of consumers today.
The earliest well-known case related to "big data killing" is the Amazon DVD incident in 2000: Amazon prices these discs differently based on the demographic data of potential users, shopping history, Internet behavior, etc.
A DVD disc called Titus was quoted at $22.74 for new users and $26.24 for older users. However, this secret was soon discovered by Amazon customers, who found out that they were expensive when they exchanged price information on the forum. In the end, Amazon CEO Bezos had to stand up and apologize.
Since then, the academic community has begun to discuss what is really "big data killing", but it is worth noting that Bezos apologized for this, which means that it is contrary to business ethics from the day of its birth to set differentiated pricing.
Amazon's small moves have been passed down in China's Internet market. According to incomplete statistics, in China, Sohu Video, Baidu, Meituan-Dianping, Youku, iQiyi, Qunar, Tmall, Maoyan Movies, Taobao, Dangdang and many other platforms have been exposed to the phenomenon of big data killing of consumers.
02 To this day, there is still chaos
Although it has long been clearly defined as immoral in business ethics, when it comes to each business, there are still some platforms that are obsessed with interests.
In essence, the technical principle of big data killing is the collection and special purpose of big data, that is, the massive user information and data collected by the platform, which includes user registration and personal information, geographical location, consumption records, search habits, etc. Each person probably has multiple keywords to generate a unique user portrait.
The aggregation of these information data can be called clear "personal property rights". Some Internet companies use user profiles (and for free) and use this information as a basis for targeted push and pricing. So far, the scale of big data killing is still very large.
In order to better define the big data ripening event, the legal definition of big data ripening is also gradually improving. On 2 July 2021, the State Administration for Market Regulation (SAMR) issued the Provisions on Administrative Penalties for Price Violations (Revised Draft for Solicitation of Comments) to define big data killing:
"E-commerce platform operators use big data analysis, algorithms and other technical means to set different prices for the same goods or services under the same trading conditions based on the preferences and trading habits of consumers or other business operators, based on factors other than cost or legitimate marketing strategies."
The important features of "big data killing" are also more clearly defined as:
First, business operators use big data technology to collect and analyze non-essential user privacy information;
Second, using customer information asymmetry, the same goods or services are sold to different users at different prices based on the results of analysis, and the price difference does not reflect the cost difference and has no justifiable reason;
Third, the other party that "kills" is mainly an old customer.
The country's regulatory laws will then be rapidly improved in 2021. On November 1, 2021, the Personal Information Protection Law was officially implemented, which is a special law to protect citizens' personal information, and is also affectionately called "killing big data" by netizens. Together with the Civil Code, the Cybersecurity Law, the Data Security Law, the E-Commerce Law, and the Consumer Rights and Interests Protection Law, this law is woven into a "protection net" for consumers' personal information.
Relevant laws and regulatory policies have begun to be implemented smoothly, and more killing incidents have been exposed. For example, in 2021 alone, the Shandong Provincial Court concluded 7471 cases of "web crawlers" and "big data killing"; in 2021, the Beijing Municipal Consumer Association also released the results of the investigation on the "killing" problem of Internet consumption big data, and the data showed that 86.91% of the respondents had the experience of being "killed" by big data, while 82.37% of the respondents believed that the problem of big data "killing" was widespread.
03 Outside the law, conscience is also important
According to the provisions of the Personal Information Protection Law, personal information processors using personal information to make automated decisions shall ensure the transparency of the decision-making and the results of the decisions are fair and just, and must not implement unreasonable differential treatment of individuals in terms of transaction conditions such as transaction prices.
At this year's two sessions, big data has also attracted much attention. A proposal submitted to the conference this year by Han Deyun, a deputy to the National People's Congress and the executive partner of the Chongqing office of Zoomlion Law Firm, is to increase the intensity of market supervision and law enforcement of "big data ripening", strictly prohibit the use of "big data ripening" to arbitrarily harm the interests of consumers, and explore the establishment of an open mechanism for the pricing policy of Internet platform operators.
Although it is not yet very perfect, it can be seen that the mainland has built a system framework for supervision and law enforcement of big data. So the question is, can these frameworks eliminate the misuse of big data?
The answer is basically no – big data, as a technology, has a certain neutrality in itself, like the existence of a kitchen knife, we can't define it as a murder weapon, the key is to see whether it is in the hands of gangsters or chefs. And it is unrealistic to expect that there will never be no gangsters in the world.
Although Bezos himself apologized in 2000, Amazon still can't control its hands in the face of the "gold mine" that really exists in big data. Around 2020, the European Union investigated how Amazon used seller data to sample and analyze 80 million transactions, and after the investigation, the EU accused Amazon of undermining fair competition in the market;
Just earlier this year, there were also Chinese in the United States who shared on social media, as a regular Uber member, he found himself going to the same destination 8.4 miles away, using Uber membership was asked to pay $50, but with another platform Lyft for only $35, and a new Uber member registered with a brand new phone only needed $40 - loyal member users need to spend the most money, behind the algorithm is obviously playing tricks.
In addition, there are also allstates, the third largest insurance company in the United States, which has set up a list of "unjust heads" and squeezed more profits from them.
Cases in Europe and the United States over the years have confirmed that it is almost impossible to completely eliminate the killing of big data. Such as overseas platforms, the moral sentiments of domestic enterprises, how can they give up in the face of excess profits at their fingertips? Facts have proved that in addition to the improvement of various restrictive laws and regulations, avoiding the killing of big data also requires enterprises to "talk about conscience".
In this regard, domestic regulators and enterprises have also played a game and have relevant explorations. Last year, a total of 10 Internet platform companies, including Vipshop, JD.com, Ele.me, Daily Excellent Fresh, Hema Fresh, Ctrip, Qunar.
The law can't solve everything in every detail, and it's equally important to improve the business ethics of the platform, even if it's difficult.
![Algorithms and pricing: The underlying logic of "big data killing" 丨 Wei Yan Yi[fig]](data:image/gif;base64,R0lGODlhAQABAIAAAP///wAAACwAAAAAAQABAAACAkQBADs=)