Anti-Monopoly Regulation of Algorithm Collusion in Big Data Era
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DOI: 10.25236/mmmce.2021.027
Corresponding Author
Jiahuan Yan
Abstract
In the era of big data, with the improvement of algorithms and the frequent use of them in the market competition, the monopoly problem of algorithm collusion becomes increasingly prominent. At present, algorithm collusion can be divided into four categories: Messenger algorithm collusion, hub-and-spoke algorithm collusion, predictive algorithm collusion and autonomous learning algorithm collusion. It is difficult to identify algorithm collusion because of its characteristics of intelligence and occult, and it develops beyond the definition of monopoly agreement in the anti-monopoly law. The present anti-monopoly law enforcement tools have certain limitations, and can not well supervise algorithmic collusion. In order to regulate the monopoly behavior of algorithm collusion, the boundary of algorithm collusion should be further clarified, the block chain technology be brought into the category of anti-monopoly law enforcement tools, and the censorship of algorithm collusion monopoly be further improved. From the standpoint of law enforcement under modest and restrained principle, the anti-monopoly regulation of algorithmic collusion will effectively promote the establishment of a unified, open, competitive and orderly modern market system, which is conducive to the creation of a fair and orderly market development environment.
Keywords
Algorithm collusion, Anti-monopoly, Block chain