Around 1200 BC, the Chinese Shang Dynasty had factory systems that produced tens of thousands of bronzes for daily and ritual purposes. In this early large-scale production example, the bronze casting process required intricate planning and coordination among a large number of workers who performed separate tasks in precise order. A thousand years later, similar complex processes were also used to make the famous Terracotta Warriors and Horses, which were “made with an assembly line system that lays the foundation for large production and commercial operationsâ€. Some scholars have speculated that the form of these early prescriptive work (prescripTIve-work) technology has played a very important role in the formation of Chinese society. Together with other factors, they have accepted the social philosophy of the bureaucracy that emphasizes the hierarchy, and also makes people believe that everything has simple and correct methods. When industrialized factories were born in Europe in the nineteenth century, even the firm critics of capitalism such as Engel admitted that regardless of whether the economic system is capitalism or socialism, large-scale production is a necessary condition for centralization. In the twentieth century, theorists such as Langdon Winner extended this idea to technology. He believes that (for example) an atomic bomb should be considered an "inherent political product" because its "fatal attribute requires it to be controlled by a centralized rigid command hierarchy chain." Today, we can extend this idea even further. Consider machine learning algorithms—the most important general-purpose technology used today. A key feature of machine learning algorithms is that their performance improves as data increases. Therefore, the use of these algorithms creates a technical impetus to process information about people into recordable, callable data. Just like large production systems, they are “inherently poliTIcal†because their core functions require certain social behaviors and hinder other social behaviors. In particular, machine learning dissemination is directly opposed to individual privacy aspirations. A system based on public accessibility information about individual members of society seems to fit socialists such as Amitai Etzioni, who believe that restrictions on privacy are enforced by social norms. means. But unlike socialists, algorithms don't care about social norms. They focus only on making better predictions, and this can be achieved by turning more and more areas of human life into diversable data sets. Algorithm evaluation is not new. Scholars such as Oscar H. Gandy warned that we are turning into a society of records and rankings and demanding more accountability to correct the errors caused by technology. But unlike modern machine learning algorithms, the old assessment tools can be understood quite thoroughly. They make decisions based on relevant normative and empirical factors. For example, it is no secret that carrying a lot of credit card debts is detrimental to a person’s reputation. Instead, new machine learning techniques dig deep into large data sets to find correlations between things that are predictable but not fully understood. In the workplace, algorithms can track employee conversations, where they eat lunch, how much time they spend on computers, phones, or meetings. With this data, the algorithm can develop complex productivity models that go far beyond our common sense intuition. In an algorithmic elite system, what the model requires and what becomes an excellent standard. Still, technology is not fatal. We decide technology before technology determines us. Business leaders and decision makers can develop and deploy technology based on their institutional needs. We have the ability to place a privacy network around sensitive areas of human life, protecting people from the harmful uses of data, and requiring algorithms to balance the accuracy of predictions with values ​​such as fairness, accountability and transparency. But before we follow the logic flow of natural algorithms, more elite is inevitable. This change will have a profound impact on our democratic institutions and political structures. If the current business and consumer culture continues, we will soon have more similarities with the sinister politics and socialist traditions than our own individualism and liberal democratic traditions. If we want to change the trend, we must put our own political responsibility before the technology. 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