Algorithm, ie exploitation
Algorithm, ie exploitation
After Ford invented the first assembly line in 1913, the workforce was reversed. The Taylor system uses the theory of division of labor to study the “movement” of workers, while the assembly line implements the Taylor system mechanically. On the assembly line, the body, movement, time and energy of workers are kidnapped by repetitive machines. Smith first worried in “The Wealth of Nations” that the division of labor might lead to the degradation of knowledge. In the age of assembly lines, workers have been “mechanized.”
No one can deny the industrial efficiency revolution brought about by the Taylor system and the assembly line based on division of labor. However, behind this industrial efficiency is another kind of “exploitation”, that is, the management deprives the labor force of the “trade surplus”. Workers can only use large trade unions to play games with capitalists and form a relative balance of power in terms of information and power.
We know that Markov created the theory of surplus value to criticize the exploitation of capitalists. Economists such as Bastiat and Mises, who face Mars and defend liberalism, are regarded as spokesmen for capitalists. However, these two factions failed to reveal the source of the problem.
When he was young, Drucker, a master of management, experienced a totalitarian struggle caused by labor-management contradictions (The End of Economic Man, 1937). In his later “corporate concept”, he criticized the “deprivation” of labor by the Taylor system and assembly line. He believes that this method violates human characteristics and obliterates people’s motivation, interest, feelings, and the advantages of integration, balance, control, and judgment.
However, no matter whether it is Markov, Mie, or German, it is impossible to reveal that the “trading surplus” of labor has been deprived of management. People ignore Smith’s other worry in The Wealth of Nations: knowledge accumulation leads to scale growth, and scale growth leads to market concentration . Whether it is assembly lines or system algorithms, they are precisely using the monopoly advantage of technology to help capitalists establish information and bargaining advantages.
On the assembly line, any worker must complete a process within a certain time (for example, 1 second), and eliminate the “grinding worker”. Time on the assembly line is equivalent to setting mandatory prices for all workers. Regardless of whether the workers are willing or not, this price deprives workers of their “trade surplus.” If the management finds that the skills of the workers are getting higher and higher, and there is still time to reduce the remaining part of the transaction, then the speed of the assembly line will increase.
Today, riders have become workers on assembly lines dominated by algorithms. The working hours of the rider are completely controlled by the system. When the algorithm finds that the time can be compressed after deep learning, the rider’s “trading surplus” will be reduced again.
In theory, the algorithm can also achieve “big data control” for each rider. Determining different delivery times for each rider’s data is equivalent to imposing a different “differential price” for each discrimination, thereby completely depriving all riders of the “trading surplus” (not sure whether it exists). This constitutes first-degree price discrimination.
Capital is on the information superior side, and the rider is on the information-poor side, and there is no bargaining power in front of the algorithm.
From an economic point of view, both parties to a transaction use their own information to play a price game between each other, which is a normal and reasonable competitive behavior. It is this competitive behavior that promotes technological progress and efficiency. However, in the free market, one party has already gained the advantage of information monopoly. For example, the platform controls private data, discriminates against the other party, and minimizes the “trading surplus”. In this way, prices will be distorted and economic efficiency will fall. Part of the rider’s income is captured by the platform, and wealth has long been inclined to the platform, which undermines the distribution mechanism of the free market.
Someone might say that free competition will solve this problem. If you don’t want to be a rider, you can work in the factory. It is precisely because the factory’s wages are too low that more people become riders.
The real logic is that the assembly line “squeezed” the workers’ “trading surplus”. Workers ran to deliver food, and then the algorithm squeezed the “trading surplus”. The depressed income of workers and riders will also drive the wages of the entire labor market. It may even constitute unfair competition in other industries. Small, the platform squeezed the “trading surplus” of the rider, reduced the cost of takeaway delivery, and improved the efficiency of delivery. However, instant noodle companies suffered as a result.
Algorithms can control the rider, or each of us.
In the era of big data, the platform can theoretically control the information of each buyer, and squeeze all the “consumer surplus” of each buyer; it can also control the information of each rider, and squeeze all the information of each rider. Both sides of the platform can absorb excess monopoly profits, leading to the concentration of wealth in Internet giants.
Comparing the Internet ecology of China and the United States, we will find a clear difference. , Housing, media, tourism, business services, logistics.
Because the US antitrust law is a high-voltage line, companies such as Facebook, Google, Microsoft, Amazon, etc. dare not expand horizontally and can only develop in deep areas, such as operating systems, artificial intelligence, big data, cloud computing, unmanned driving, and general purpose. Chips, navigation systems, programming languages, robotics, basic sciences, etc.
Chinese Internet companies rarely enter these areas, and these in-depth areas are where the core technology lies. In the expansion of the terminal field, Chinese Internet giants have obtained huge capital dividends, and a large number of terminal consumer companies with the concept of big data and cloud computing are listed for cash.
The horizontally expanding Internet ecology of terminals has caused at least three major problems: First, capital, talents cannot enter the depth field, and core technology innovation is insufficient; second, our lives are dominated, surrounded and locked by a powerful algorithm; third, the platform algorithm takes everything from top to bottom. , Grabbing the “trading surplus” of the whole society, creating wealth concentration and polarization between the rich and the poor, and even insufficient effective demand.
The theory of price discrimination reveals the exploitation of algorithms “disguised” by big data and cloud computing.
At the same time, the “Interim Provisions on the Management of Online Tourism Management Services” to be implemented on October 1 prohibits big data acquaintances: online tour operators must not abuse technical means such as big data analysis, based on tourist consumption records, travel preferences and other settings Unfair trading conditions violate the legitimate rights and interests of tourists.
The European Parliament passed the General Data Protection Regulation in 2016. The regulations stipulate that any organization that collects, transmits, retains or processes personal information related to all totals in the European Union is bound. This regulation clarifies that the right to personal data is a basic right of citizens and should be respected and protected.
On July 8, 2019, the UK Information Regulatory Authority issued a statement stating that the UK government was fined £183.39 million (approximately RMB 1.58 billion) for violating the General Data Protection Regulation.
In 1942, in the United States v. Roller Tuo Company, Judge Hande creatively proposed a formula to judge the case. The Hande formula means that the party with the lower cost of preventing future accidents should be restricted. .
To prevent the killing of big data, the problem of personal data proprietary must be solved. Various believers try to implant decentralized databases through peer-to-peer technology and encryption algorithms. Facing the challenge of power as Olsen said.
The anti-tech “madman” Hildo Kaczynski warned in the article “Industrial Society and Its Future”: “In the industrialized era, human beings, if they are not directly controlled by highly intelligent machines, or by the few elites behind the machines. Controlled.”
If the data is not privatized or effective control of the algorithm is not established (pay attention), the algorithm is exploitation.