Let's start with a question: Do you believe someone who says it knows you better than you know yourself?

Whether you believe it or not, in the age of technology, big data knows a lot more about you than you think.

As big as you buy a house to buy a car like which type of model; small as what you eat in the morning, every day to listen to what song, it all know.

A friend said, big data to understand me is not good?

When you open the takeout software, the push is all about what I love to eat; when you click on the taxi software, you don't have to enter the address to know where I'm going.

How convenient is this?

However, there is a saying: The people who know you, hurt you the most.

Those who know you are taking care of an old friend. The same place of departure and arrival, the old customer price is higher; the same hotel, the old customer booking price is more expensive; even if they are all new users of the platform, the new user of the Apple phone than the new user of other cell phones to show the price is higher....

This kind of differentiation, even let the People's Daily have clearly issued an article criticizing: see people under the dish, has constituted price fraud!

However, what makes it more difficult for consumers to prevent is that, in addition to online big data kills, offline store cameras can "face recognition kills" without you even realizing it.

According to this year's 315 Evening Party report, a number of merchants, including Kohler Sanitary Ware, Xi Tea, and BMW 4S stores, have installed face recognition equipment in their offline stores.

So what's the point of these store-installed cameras for facial recognition?

As a consumer, we are of course very resistant and disgusted by this phenomenon, but let's appropriately look at this topic by pulling the angle a little higher.

Back in ancient Greece, Glaucon told a story about a shepherd named Goggles who got a ring that made him invisible, and when he realized that no one could really see him, he used the ring to seduce the queen and murder the king until he eventually stole the throne. After finishing the story, Glaucon asked the crowd: If there are two Goggles' rings, one on the hand of a righteous man and one on the hand of an unrighteous man, will these two people behave differently? Glaucon's conclusion is: No. Because no matter whether a person is a law-abiding, law-abiding person or not, once he has the Goggles' ring, he will definitely do what he wants to do, not what he should do.

So now Big Data has become, in a way, the new "Guggles ring".

In economics, this kind of differentiation based on user profiles is known as "first-degree price discrimination", or "full price discrimination", which is the highest category. In the traditional offline market, it is difficult for operators to understand the purchasing behavior of each consumer, so it is difficult to achieve first-degree price discrimination, but in the era of big data, the user's understanding of themselves may be far less than the algorithm. Benjamin Shiller, an assistant professor in the Department of Economics at Brandeis University in the United States, once launched a study on the online video platform Nefi, and he found that if Nefi uses the personalized pricing method using traditional demographics, it is able to increase its profit by 0.3%, but if Nefi estimates the user's browsing history on the platform through machine learning technology, the profit can be increased by 0.3%, but if Nefi uses machine learning technology based on the user's browsing history on the platform, it can increase the profit by 0.3%. the highest price they are willing to pay, profits can increase by 14.55%. In other words, with user-provided data and machine-contributed algorithms, the platform can differentiate its pricing for different users, resulting in more commercial revenue.

Since they can reap more commercial revenue, these platforms are of course willing to go out of their way to violate consumers' rights in a big way.

Fortunately, our government has recognized and noticed this phenomenon, and has introduced laws and regulations to address it. Only by putting money under the supervision of the law can it grow healthily.

On July 2, the State Administration of Market Supervision drafted the "Provisions on Administrative Penalties for Price Violations (Revised Exposure Draft)", and the relevant penalty provisions on e-commerce platforms for "big data ripening" also appeared in the "Exposure Draft". In terms of penalties, big data to kill familiarization may be imposed at most "on the previous year's total sales of more than 1 per cent of 5 per cent of the following" fine. July 2 Hong Kong stocks closed, the Hong Kong Hang Seng Science and Technology Index fell more than 3%, Alibaba fell 3.64%, the United States group fell 5.12%, Jingdong Group fell 1.51%, Tencent Holdings fell 1.63%.

Gentlemen love money, take the right way, I hope the future of big data can give consumers a better consumer experience, not even "face" do not want.