Issue |
SHS Web Conf.
Volume 218, 2025
2025 2nd International Conference on Development of Digital Economy (ICDDE 2025)
|
|
---|---|---|
Article Number | 03011 | |
Number of page(s) | 6 | |
Section | Digital Economic Governance: Policy and Sustainability | |
DOI | https://doi.org/10.1051/shsconf/202521803011 | |
Published online | 03 July 2025 |
Analysis of Artificial Intelligence Monopoly Issue and Related Solutions
College of Art and Science, Boston University, Boston, 02215, United States
* Corresponding author: frank233@bu.edu
The rapidly developed Artificial intelligence (AI) industry relies on data resources and is often controlled by some tech giants. Although the organizational monopoly in the AI industry is more efficient in text and image generation and transmission in a vast and generative digital market, it still has some problems. The monopoly will cause the issues, such as data and computing resources central control, unequal competition, user discrimination, and so on. This paper will conduct research on these monopoly problems, which not only make a pavement for further research on the academic field of AI but also provide more theoretical evidence for the solutions in regulating AI development in the future. The qualitative analysis will be used, and monopoly issues will be explored with the three aspects, including data monopoly, platform monopoly, and user monopoly, which will reflect the negative impacts of the monopoly in the competition of the AI industry and provide more available solutions for the issues. Especially in the new emerging AI industry, this research has practical significance for guiding an anti-monopoly competition market and maximizing the utilization and fair distribution of data and computing resources.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.