The “Queen Bees” Commands the “Worker Bees”: Technological Upgrading and Labor Downgrading of the Central Brain Algorithm Experiment

LIU Zhanwei

Chinese Journal of Journalism & Communication ›› 2024, Vol. 46 ›› Issue (3) : 116-135.

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Chinese Journal of Journalism & Communication ›› 2024, Vol. 46 ›› Issue (3) : 116-135.
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The “Queen Bees” Commands the “Worker Bees”: Technological Upgrading and Labor Downgrading of the Central Brain Algorithm Experiment

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Abstract

Data is a kind of power, and whoever owns the data holds the power. From the perspective of labor technology control, this paper focuses on the algorithmic experiments and central brain system of N enterprises, and studies the human labor process of data collection at the front end of the algorithmic system and instruction execution at the end. In the algorithm experiment, “human worker bees” as ghost labor and “machine worker bees” as IOT sensors carry out large-scale data collection to make up for the “last mile” of artificial intelligence. The central brain system takes over everything. The central brain system takes over everything, controls the employee labor process, evaluates employee performance appraisal, and generates a technology governance technique that is tighter than the Taylor system “shovel experiment”. Technological upgrading did not bring about the liberation of people, but rather the emergence of electronic circular prison-style panoramic monitoring, triggering the paradox of “technological upgrading” and “labor downgrading”. From the “shovel experiment” to the “algorithm experiment”, the algorithm has become the “queen bee” on the throne of control, and people have been reduced to “worker bees” abstracted by the algorithm system. The human being is reduced to a “worker bee” abstracted by the algorithmic system.

Key words

algorithmic experimentation / central brains / technological upgrades / labor downgrades / ghost labor

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LIU Zhanwei. The “Queen Bees” Commands the “Worker Bees”: Technological Upgrading and Labor Downgrading of the Central Brain Algorithm Experiment[J]. Chinese Journal of Journalism & Communication. 2024, 46(3): 116-135

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